Abstract
Background
Diabetes mellitus, a metabolic disorder characterised by hyperglycaemia and associated with a heavy burden of microvascular and macrovascular complications, frequently remains undiagnosed. Screening of apparently healthy individuals may lead to early detection and treatment of type 2 diabetes mellitus and may prevent or delay the development of related complications.
Objectives
To assess the effects of screening for type 2 diabetes mellitus.
Search methods
We searched CENTRAL, MEDLINE, LILACS, the WHO ICTRP, and ClinicalTrials.gov from inception. The date of the last search was May 2019 for all databases. We applied no language restrictions.
Selection criteria
We included randomised controlled trials involving adults and children without known diabetes mellitus, conducted over at least three months, that assessed the effect of diabetes screening (mass, targeted, or opportunistic) compared to no diabetes screening.
Data collection and analysis
Two review authors independently screened titles and abstracts for potential relevance and reviewed the full‐texts of potentially relevant studies, extracted data, and carried out 'Risk of bias' assessment using the Cochrane 'Risk of bias' tool. We assessed the overall certainty of the evidence using the GRADE approach.
Main results
We screened 4651 titles and abstracts identified by the search and assessed 92 full‐texts/records for inclusion. We included one cluster‐randomised trial, the ADDITION‐Cambridge study, which involved 20,184 participants from 33 general practices in Eastern England and assessed the effects of inviting versus not inviting high‐risk individuals to screening for diabetes. The diabetes risk score was used to identify high‐risk individuals; it comprised variables relating to age, sex, body mass index, and the use of prescribed steroid and anti‐hypertensive medication. Twenty‐seven practices were randomised to the screening group (11,737 participants actually attending screening) and 5 practices to the no‐screening group (4137 participants). In both groups, 36% of participants were women; the average age of participants was 58.2 years in the screening group and 57.9 years in the no‐screening group. Almost half of participants in both groups were on antihypertensive medication. The findings from the first phase of this study indicate that screening compared to no screening for type 2 diabetes did not show a clear difference in all‐cause mortality (hazard ratio (HR) 1.06, 95% confidence interval (CI) 0.90 to 1.25, low‐certainty evidence). Screening compared to no screening for type 2 diabetes mellitus showed an HR of 1.26, 95% CI 0.75 to 2.12 (low‐certainty evidence) for diabetes‐related mortality (based on whether diabetes was reported as a cause of death on the death certificate). Diabetes‐related morbidity and health‐related quality of life were only reported in a subsample and did not show a substantial difference between the screening intervention and control. The included study did not report on adverse events, incidence of type 2 diabetes, glycosylated haemoglobin A1c (HbA1c), and socioeconomic effects.
Authors' conclusions
We are uncertain about the effects of screening for type 2 diabetes on all‐cause mortality and diabetes‐related mortality. Evidence was available from one study only. We are therefore unable to draw any firm conclusions relating to the health outcomes of early type 2 diabetes mellitus screening. Furthermore, the included study did not assess all of the outcomes prespecified in the review (diabetes‐related morbidity, incidence of type 2 diabetes, health‐related quality of life, adverse events, socioeconomic effects).
Plain language summary
Screening for type 2 diabetes mellitus
Review question
What are the health effects of screening compared to not screening for type 2 diabetes mellitus?
Background
Type 2 diabetes mellitus is a metabolic disorder characterised by high blood sugar which can lead to complications like kidney and eye disease. It can develop at any age but usually peaks in adults 65 years of age and above and may be treated in the beginning through diet and exercise. Type 2 diabetes mellitus may have no or few symptoms at the start and thus may go undiagnosed. Screening of apparently healthy people could lead to early detection and treatment of type 2 diabetes mellitus as well as prevent or delay the development of related complications.
Study characteristics
We found one randomised controlled trial (a clinical study in which participants are assigned to one of two or more treatment groups using a random method) where 20,184 high‐risk individuals from 33 general practices in Eastern England were either invited or not invited to screening for type 2 diabetes (the ADDITION‐Cambridge study). Eligible participants had to have an elevated diabetes risk score but no known diabetes. The diabetes risk score to identify high‐risk individuals comprised variables relating to age, sex, body mass index, and the use of prescribed steroids and anti‐hypertensive medication. Practices were eligible to participate if they could provide data for calculation of the risk score for at least 70% of their patients. A total of 11,737 participants attended screening in actuality, and 4137 participants represented the no‐screening group. In both groups, 36% of participants were women; the average age of participants was 58.2 years in the screening group and 57.9 years in the no‐screening group. Almost half of participants in both groups were on medication for high blood pressure.
This evidence is up‐to‐date as of May 2019.
Key results
We are uncertain about the effects on screening for type 2 diabetes mellitus on death from any cause and death from diabetes‐related causes (the only outcomes of importance for our review for which study authors provided reliable data). The included study did not report on side effects of screening, new cases of type 2 diabetes, health‐related quality of life, glycosylated haemoglobin A1c (HbA1c) as a long‐term measurement of glucose control, and socioeconomic effects (such as costs of screening, use of medication, number of consultations).
Certainty of the evidence
We based the certainty of the evidence on only one study. The overall certainty of the results from this study is low, because the results are not precise, that is they could change in any direction if new studies are published.
Summary of findings
Summary of findings 1. Screening for type 2 diabetes mellitus.
| Screening for type 2 diabetes mellitus | ||||||
|
Population: individuals without known diabetes mellitus but at high risk for the condition Settings: primary healthcare clinics in Eastern England Intervention: invitation to screening followed by intensive treatment or routine care of participants with screen‐detected diabetes Comparison: no invitation to screening for type 2 diabetes mellitus | ||||||
| Outcomes | No screening | Screening | Relative effect (95% CI) | No. of participants (studies) | Certainty of the evidence (GRADE) | Comments |
|
All‐cause mortality Median follow‐up: 9.6 years |
91 per 1000 | 96 per 1000 (82 to 113) | HR 1.06 (0.90 to 1.25) | 20,184 (1) | ⊕⊕⊝⊝ lowa | |
|
Diabetes‐related mortality Assessed according to whether diabetes was included anywhere on the death certificate Follow‐up: 10 years |
4 per 1000 | 5 per 1000 (3 to 8) | HR 1.26 (0.75 to 2.12) | 20,184 (1) | ⊕⊕⊝⊝ lowb |
|
| Diabetes‐related morbidity | See comment | No substantial difference on self‐reported cardiovascular events in a subsample (15% of participants in the screening group and 40% of participants in the control group) | ||||
| Incidence of type 2 diabetes | Not reported | |||||
| Health‐related quality of life | See comment | No substantial difference on self‐reported health‐related quality of life in a subsample (the response rate was 62% in the screening group and 53% in the control group) | ||||
| Adverse events | Not reported | |||||
| Socioeconomic effects | Not reported | |||||
| CI: confidence interval; HR: hazard ratio. | ||||||
| GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate; the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect. | ||||||
aDowngraded by two levels due to serious imprecision (CI includes both benefit and harm; one study only). bDowngraded by two levels due to serious imprecision (CI includes both benefit and harm; one study only; not a common event).
Background
Description of the condition
Diabetes mellitus is a metabolic disorder resulting from a defect in insulin secretion, insulin action, or both. It is characterised by chronic hyperglycaemia and is associated with a heavy health burden of microvascular (retinopathy, nephropathy, and neuropathy) and macrovascular complications (cardiovascular, peripheral vascular, and cerebrovascular disease) (WHO 1999). Notwithstanding, approximately one‐third to one‐half of all people with type 2 diabetes mellitus (now referred to as diabetes), the most common form of the disease, remain undiagnosed (IDF 2019). This is due to the long pre‐clinical period (Harris 1992), as well as inadequate access to care, particularly in low‐ and middle‐income country settings (Peer 2014). Early detection and treatment of diabetes may prevent or delay the development of related complications, as demonstrated in the United Kingdom Prospective Diabetes Study (Colagiuri 2002).
Description of the intervention
Screening programmes
Screening is defined as the possible identification of unrecognised disease amongst apparently healthy individuals by means of tests or examinations conducted to identify those at an increased risk for the condition (Standing committee on screening 2018). The aim is to reduce the burden of the disease in the population including disease incidence, morbidity, or mortality. This is achieved through early intervention to reduce the individual risk of the disease, for example a hysterectomy in the pre‐cancerous phase to prevent cervical cancer or to improve disease outcomes (i.e. early detection of cancers in general to prevent their spread). Screening is therefore only relevant if detecting the disease early has a significant impact on outcomes and if it leads to marked reductions in advanced disease (Carroll 2015).
Screening programmes may be implemented in different ways, for example population‐wide screening for all individuals irrespective of their age or gender, targeted screening for those known to be at higher risk for certain conditions, or opportunistic screening at the point‐of‐care for other conditions (Durão 2015). The choice of, as well as the need for, a screening programme will depend on various factors. These include aspects related to: 1) disease (severity, prevalence, possible detection in the pre‐clinical phase, long latency period, improved outcomes with early detection), 2) screening test (validity, reliability, ease of use, ability for pre‐clinical detection of disease), and 3) screening programme (ADA 2002; Grimes 2002).
Key criteria for a screening programme are that it should respond to a recognised need, have clear objectives, and target a defined population (Andermann 2008). Importantly, there must be scientific evidence that demonstrates the effectiveness of the screening programme. Furthermore, case‐finding, including diagnosis and treatment, should be economically cost‐effective.
Screening for diabetes
Diabetes has a long pre‐clinical phase during which raised blood glucose levels contribute to the development of complications. It is therefore a disease that may be suitable for early detection through a screening programme, and many clinical guidelines now recommend early identification of diabetes through screening for the condition (ADA 2003; Borch‐Johnsen 2003; Canadian Task Force 2012; IDF 2012). The aim is to identify asymptomatic individuals with diabetes so as to implement therapy early and thus impact favourably on the disease course (Grimes 2002).
Universal, that is population‐wide, screening for undiagnosed diabetes is not recommended because it may be poorly targeted and fail to reach the groups most at risk. Individuals at low risk and even those already diagnosed with diabetes may be inappropriately tested (ADA 2002). Screening should be undertaken in high‐risk individuals to increase the likelihood of diabetes detection as well as to increase the cost‐effectiveness of testing (ADA 2003). In fact, the International Diabetes Federation (IDF) recommends that diabetes screening programmes be opportunistic and limited to high‐risk individuals in specific settings (IDF 2012). High‐risk individuals may be identified on screening questions with an increased risk for diabetes associated with older age, a family history of diabetes, or the presence of cardiovascular risk factors such as obesity and hypertension, amongst other variables.
The tests that may be used for diabetes screening are the same as those used to make a diagnosis. These include the oral glucose tolerance test, which is perhaps the optimal, but also the most cumbersome, of the test instruments. It is time consuming, requiring two hours for completion, and involves pre‐planning for an overnight fast, and is thus not an ideal screening tool. Other tests used to screen or diagnose diabetes include fasting or random (casual) glucose levels (IDF 2012; WHO 1999). Glycated haemoglobin A1c (HbA1c) levels is an additional test that has been recently used (IDF 2012). Screening tools to identify individuals at high risk for diabetes usually entail point‐of‐care tests using capillary blood.
Adverse effects of screening
Screening for a medical condition can have psychological, physical, and financial adverse consequences. This is particularly relevant with a false‐positive result, where overdiagnosis, and subsequent overtreatment, may have detrimental consequences (Carroll 2015). However, the literature on the adverse effects associated with screen‐detected diabetes is limited (Selph 2015). Whilst two randomised controlled trials (RCTs) found diabetes screening to be associated with higher levels of short‐term anxiety and worry, the overall impact was minimal with no clear long‐term negative effects on psychological outcomes (Selph 2015; Sherifali 2013).
How the intervention might work
Screening asymptomatic individuals for diabetes may identify the disease earlier (Selph 2015). The duration of the hyperglycaemic period prior to diagnosis and treatment is expected to be shortened in screen‐detected compared with routinely detected diabetes, which may contribute to fewer macro‐ and microvascular complications. Also, earlier diagnosis of diabetes may lead to earlier or more intensive management as well as timely management of complications as they develop. The US Preventive Services Task Force recommended diabetes screening in asymptomatic adults with raised blood pressures because more intensive blood pressure control in those with diabetes and hypertension has been associated with a reduced risk for cardiovascular events, including cardiovascular mortality (Selph 2015).
However, a recent systematic review of meta‐analyses and randomised trials demonstrated little reductions in disease‐specific and all‐cause mortality for diseases with available screening tests and where death is a common outcome (Saquib 2015). Nevertheless, a comparison of the outcomes in people with screen‐detected versus routinely detected diabetes who undergo similar management may provide evidence to support or dispute the above rationale.
Why it is important to do this review
Sherifali 2013 reported that modelling studies have shown that population‐based screening for high‐risk individuals with age and hypertension as risk factors may increase the quality‐adjusted life years, and that screening was cost‐effective if conducted from the age of 45 years and repeated every three to five years thereafter. A review of previous economic models concluded that screening for diabetes appeared to be cost‐effective for those aged 40 to 70 years, especially in the hypertensive and obese subgroups (Waugh 2007). However, a limitation of this study was that instead of using empirical data, it required assumptions relating to glucose control and treatment effectiveness in screened individuals.
Despite the benefits of improved glucose, blood pressure, and lipid control in individuals with diabetes, the benefits on outcomes of early diabetes detection through screening remain unclear (IDF 2012). There is insufficient evidence on the direct benefits of routine screening in the general population (ADA 2008; Diabetes UK 2020; Rutten 2006; WHO 2003). Recently, the efficacy of screening for diabetes followed by intensive treatment or routine care versus no screening (control group) was assessed in the ADDITION study (The Anglo‐Danish‐Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care). Notably, the United Kingdom arm of the study reported no effect of this approach on 10‐year mortality (all‐cause, cardiovascular, cancer or other causes) (Simmons 2012). An absence of a significant reduction in 10‐year mortality with screening compared to no screening for diabetes was also found in the Ely cohort (Simmons 2011). The systematic review on diabetes screening by the US Preventive Services Task Force in 2015 reported that only Simmons 2012 and Simmons 2011 had evaluated the effects of diabetes screening versus no screening on mortality (Selph 2015). More evidence is thus required to ascertain the health impact of diabetes screening.
Furthermore, a recent overview of systematic reviews that examined diabetes and hypertension screening programmes identified the need for a systematic review to assess the effectiveness and impact of such screening strategies (Durão 2015). This review aimed to address this gap in the literature, as a review of the current evidence should help determine which of these recommendations is evidence‐based and worth following (Inzucchi 2012). This will provide useful guidance for professional associations who despite the unclear link to the evidence base, have issued recommendations about screening for diabetes (ADA 2004; IDF 2012).
Objectives
To assess the effects of screening for type 2 diabetes mellitus.
Methods
Criteria for considering studies for this review
Types of studies
We included RCTs.
Types of participants
Participants were adults and children without known diabetes mellitus.
Diagnostic criteria for type 2 diabetes mellitus
The World Health Organization (WHO) criteria for the diagnosis of diabetes requires the administration of an oral glucose tolerance test (OGTT) (WHO 1999). The test is performed after an overnight fast of 8 to 14 hours. Initially, a fasting blood specimen is drawn followed by the administration of a glucose load. This consists of 75 g anhydrous glucose dissolved in about 250 mL of water. Two hours later a blood specimen is drawn to determine the 2‐hour plasma glucose level.
Using this method, the WHO cut‐off values for the diagnosis of diabetes in 1985 were ≥ 7.8 mmol/L for fasting plasma glucose and ≥ 11.1 mmol/L for the 2‐hour plasma glucose (WHO 1985) (Appendix 1). In 1997, the American Diabetes Association (ADA) proposed that a diagnosis of diabetes be based only on fasting plasma glucose, using a lower threshold of 7.0 mmol/L (Expert Committee 1997).
In 1998, the WHO accepted the ADA proposal to lower the fasting blood glucose threshold to 7.0 mmol/L but retained the use of the OGTT for the diagnosis of diabetes (WHO 1999). In 2003, the ADA aligned their diagnostic criteria for diabetes with that of the WHO (ADA 2003).
Both organisations include a diagnosis of diabetes based on random plasma glucose ≥ 11.1 mmol/L providing that the individual is symptomatic (ADA 2003; WHO 1999). A random blood sample is defined as one that is drawn without reference to the time since the last meal. The typical symptoms of hyperglycaemia include polyuria, polydipsia, nocturia, and unexplained weight loss.
Recently, HbA1c has been recommended as an alternative test to diagnose diabetes. HbA1c is a marker of chronic glycaemia and reflects the average blood glucose level over the previous two to three months. It is usually used in diabetes management to determine glucose control, but advances in instrumentation and standardisation have led to marked improvements in the accuracy and precision of HbA1c assays and its use as a diagnostic tool (ADA 2014; International Expert Committee 2009).
Studies that use the following biochemical screening tests, individually or in combination, to determine diabetes were eligible for this review: capillary, plasma or venous whole blood samples for glucose (random, fasting or after a glucose load) or HbA1c, or urine glucose. This includes studies that used stepwise screening procedures, for example risk assessment questionnaires or database selection, followed by a biochemical test.
Types of interventions
We investigated the following comparison of intervention versus control/comparator.
Intervention
Diabetes screening (mass, targeted, or opportunistic).
Comparator
No diabetes screening.
Concomitant interventions had to be the same in both the intervention and comparator groups to establish a fair comparison. For studies with multiple arms, we would include any arm that met the review inclusion criteria.
Minimum follow‐up of intervention
Studies with a minimum follow‐up of three months were eligible for inclusion.
Summary of specific exclusion criteria
Gestational diabetes.
Diabetes insipidus.
Types of outcome measures
We did not exclude any studies on the basis that one or several of our primary or secondary outcome measures were not reported in the publication.
We investigated the following outcomes using the methods and time points specified below.
Primary outcomes
All‐cause mortality
Diabetes‐related mortality
Diabetes‐related morbidity
Secondary outcomes
Incidence of type 2 diabetes
HbA1c
Adverse events
Health‐related quality of life
Socioeconomic effects
Method of outcome measurement
All‐cause mortality: defined as death due to any cause.
Diabetes‐related mortality: defined as death from ischaemic heart disease (IHD) or stroke.
Diabetes‐related morbidity: defined as development of IHD, stroke, diabetic retinopathy, diabetic nephropathy, diabetic neuropathy.
Incidence of type 2 diabetes: defined as newly diagnosed diabetes.
HbA1c: measured in % or mmol/mol.
Health‐related quality of life: evaluated by a validated instrument such as the Diabetes Quality of Life (DQOL) questionnaire.
Adverse events: e.g. psychological effects such as anxiety, effects of false‐positive test results, effects of labelling.
Socioeconomic effects: defined as healthcare consumption (e.g. use of medication, number of consultations), cost of screening per newly detected individual.
Timing of outcome measurement
All‐cause mortality, diabetes‐related mortality, diabetes‐related morbidity, incidence of type 2 diabetes mellitus: measured at any time after randomisation.
HbA1c: measured at any time after randomisation for a diagnosis of diabetes or at least three months postbaseline evaluation for glycaemic control.
Health‐related quality of life, adverse events: measured postbaseline.
Socioeconomic effects: measured at completion of the study.
Specification of key prognostic variables (with associated magnitude of an important difference)
Age
Gender
Ethnicity
Family history of diabetes
Obesity
Presence of other cardio‐metabolic conditions, e.g. hypertension, dyslipidaemia
Search methods for identification of studies
Electronic searches
We searched the following sources from inception of each database to the specified date, with no restrictions on language of publication.
Cochrane Central Register of Controlled Trials (CENTRAL) via Cochrane Register of Studies Online (CRSO) (searched 23 May 2019).
Ovid MEDLINE(R) and Epub Ahead of Print, In‐Process & Other Non‐Indexed Citations and Daily (1946 to 17 April 2019) (searched 23 May 2019).
LILACS (searched 23 May 2019).
US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (clinicaltrials.gov) (searched 23 May 2019).
World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (www.who.int/trialsearch/) (searched 23 May 2019).
We continuously applied an email alert service for MEDLINE via OvidSP to identify newly published studies using the search strategy detailed in Appendix 1. After we submitted the final update review draft for editorial approval, the Cochrane Metabolic and Endocrine Disorders (CMED) Group performed a complete search update on all databases available at the editorial office and sent the results to the review authors.
Searching other resources
We attempted to identify other potentially eligible studies or ancillary publications by searching the reference lists of included studies, systematic reviews, meta‐analyses, and health technology assessment reports. We also contacted authors of the included studies to identify any additional information on the retrieved studies and to determine if further studies existed that we may have missed.
Data collection and analysis
Selection of studies
Two review authors (NP, SD) independently screened the abstract or title or both of each record retrieved by the literature searches to determine which studies should be assessed further. We obtained the full‐text of all potentially relevant records and evaluated these for inclusion in the review. Any disagreements were resolved through consensus or by recourse to the review's advisory group. If we could not resolve a disagreement, we categorised the study as awaiting classification and contacted the study authors for clarification. We have presented an adapted PRISMA flow diagram illustrating the process of study selection (Liberati 2009). We described all articles excluded after full‐text assessment and the reasons for their exclusion in a 'Characteristics of excluded studies' table.
Data extraction and management
For studies that fulfilled the inclusion criteria, two review authors (NP and SD/YB) independently extracted key information on participants, interventions, and comparators. We reported data on efficacy outcomes and adverse events using standardised data extraction sheets from the CMED Group. Any disagreements were resolved by discussion or by consulting with a member of the review's advisory group if required (for details see Characteristics of included studies; Table 2; Appendix 2; Appendix 3; Appendix 4; Appendix 5; Appendix 6; Appendix 7; Appendix 8; Appendix 9; Appendix 10; Appendix 11; Appendix 12; Appendix 13; Appendix 14; Appendix 15; Appendix 16).
1. Overview of study populations.
| Study ID (study design) | Intervention(s) and comparator(s) | Description of power and sample size calculation | Screened/eligible (N) | Randomised (N) | Analysed (primary outcome) (N) | Finishing trial (N) | Randomised finishing trial (%) | Follow‐up |
|
Simmons 2012 (cluster‐RCT) |
I: individuals at high risk for diabetes invited for screening | "The study sample size was originally estimated to quantify the effectiveness of intensive treatment in screen‐detected patients via detection of a 20% relative difference in the UK Prospective Diabetes Study (UKPDS) modelled 10‐year risk of cardiovascular disease between participants with screen‐detected diabetes in the IT and RC groups" | 138 practices/63 practices | 27 practices
(14 to IT, 13 to RC) 16,047 eligible participants (mean 594 (SD 340) per practice) 15,089 participants invited for screening 11,737 participants attended screening |
16,047a | — | — | Median duration of intervention: 9.6 years (IQR 8.9 to 9.9) |
| C: individuals at high risk for diabetes not invited for screening | 5 practices 4137 eligible participants (mean 827 (SD 228) per practice) |
4137 | — | — | ||||
| Total: | 20,184 | |||||||
| Grand total | All interventions | 11,737a | — | |||||
| All comparators | 4137 | — | ||||||
| All interventions and comparators | 15,874a | — | ||||||
— denotes not reported
aNumbers analysed by study authors ("Analyses were done on an intention‐to‐screen basis at the population level. All eligible high‐risk individuals were considered in analyses irrespective of their participation in the screening programme (this population included non‐attenders and high‐risk patients deemed unfit for screening by their general practitioner")
C: comparator; I: intervention; IQR: interquartile range; IT: screening followed by intensive treatment of participants with screen‐detected diabetes; RC: screening followed by routine care according to national guidelines of participants with screen‐detected diabetes; RCT: randomised controlled trial; SD: standard deviation.
We provided information about potentially relevant ongoing trials, including the trial identifiers, in the 'Characteristics of ongoing studies' table and in Appendix 9 'Matrix of study endpoint (publications and trial documents)'. We identified the protocol for each included study and reported primary, secondary, and other outcomes in comparison with the data in the publications in the Appendix 9.
We emailed the author of the ongoing trial to enquire as to whether they would be willing to answer questions regarding their trials. The results of this survey are presented in Appendix 14.
Dealing with duplicate and companion publications
In the case of duplicate publications, companion documents, or multiple reports of a primary study, we maximised the information yield by collating all available data and used the most complete data set aggregated across all known publications. We listed duplicate publications, companion documents, multiple reports of a primary study, and trial documents of included trials (such as trial registry information) as secondary references under the study identifier (ID) of the included study. Furthermore, we also listed duplicate publications, companion documents, multiple reports of a study, and trial documents of excluded trials (such as trial registry information) as secondary references under the study ID of the excluded study.
Data from clinical trials registers
If data from included studies were available as study results in clinical trials registers, such as ClinicalTrials.gov or similar sources, we made full use of this information and extracted the data. If there was also a full publication of the study, we collated and critically appraised all available data. If an included study was marked as completed in a clinical trial register but no additional information (study results, publication, or both) was available, we added this study to the 'Characteristics of studies awaiting classification' table.
Assessment of risk of bias in included studies
Two review authors (NP, SD/YB) independently assessed the risk of bias for each included study. Any disagreements were resolved by consensus or by consulting a member of the review's advisory group to achieve consensus. If there was inadequate information in the publication, trial protocols, or other sources, we contacted the study authors for more detail and to request missing data on 'Risk of bias' domains.
We used the Cochrane 'Risk of bias' assessment tool (Higgins 2019b), assessing each domain as low, high, or unclear risk of bias (for details, see Appendix 3). We evaluated individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions according to the criteria and associated categorisations contained therein (Higgins 2019b).
Summary assessment of risk of bias
We presented a 'Risk of bias' graph and a 'Risk of bias' summary figure. We distinguished between self‐reported, investigator‐assessed, and adjudicated outcome measures.
We defined the following endpoints as self‐reported or subjective outcomes.
Adverse events, depending on measurement
Health‐related quality of life
We defined the following endpoints as investigator‐assessed or objective outcomes.
All‐cause mortality
Diabetes‐related mortality
Diabetes‐related morbidity
Incidence of type 2 diabetes
HbA1c
Adverse events, depending on measurement
Socioeconomic effects
Risk of bias for a study across outcomes
Some 'Risk of bias' domains, such as selection bias (sequence generation and allocation sequence concealment), affect the risk of bias across all outcome measures in a study. In the case of high risk of selection bias, we marked all endpoints investigated in the associated study as high risk. Otherwise, we would not perform a summary assessment of the risk of bias across all outcomes for a study.
Risk of bias for an outcome within a study and across domains
We assessed the risk of bias for an outcome measure by including all entries relevant to that outcome (i.e. both study‐level entries and outcome‐specific entries). We considered low risk of bias to denote a low risk of bias for all key domains; unclear risk to denote an unclear risk of bias for one or more key domains; and high risk to denote a high risk of bias for one or more key domains.
Risk of bias for an outcome across studies and across domains
To facilitate our assessment of the certainty of evidence for key outcomes, we assessed risk of bias across studies and domains for outcomes included in the 'Summary of findings' table. We assessed the evidence as being at low risk of bias when most information came from studies at low risk of bias; unclear risk of bias when most information came from studies at low or unclear risk of bias; and high risk of bias when a sufficient proportion of information came from studies at high risk of bias.
Measures of treatment effect
When at least two included studies were available for a comparison and a given outcome, dichotomous data were described as a risk ratio (RR) or odds ratio (OR) with 95% confidence interval (CI). For continuous outcomes measured on the same scale (e.g. weight loss in kg), we estimated the intervention effect using the mean difference (MD) with 95% CI. For continuous outcomes that measured the same underlying concept (e.g. health‐related quality of life) but used different measurement scales, we calculated the standardised mean difference (SMD). We expressed time‐to‐event data as a hazard ratio (HR) with 95% CI.
Unit of analysis issues
We took into account the level at which randomisation occurred, such as cross‐over studies, cluster‐randomised trials, and multiple observations for the same outcome. If more than one comparison from the same study was eligible for inclusion in the same meta‐analysis, we either combined groups to create a single pair‐wise comparison or appropriately reduce the sample size so that the same participants did not contribute multiply (splitting the 'shared' group into two or more groups). Whilst the latter approach offers some solution to adjusting the precision of the comparison, it does not account for correlation arising from the same set of participants being in multiple comparisons (Higgins 2019a).
We had planned to attempt to re‐analyse cluster‐RCTs that had not appropriately adjusted for clustering in their analyses. The variance of the intervention effects would have been inflated by a design effect. Calculation of a design effect involves estimation of an intracluster correlation coefficient (ICC). We would have obtained estimates of ICCs through contact with the study authors, or imputed them using estimates from other included studies that reported ICCs, or using external estimates from empirical research (e.g. Bell 2013). We had planned to examine the impact of clustering using sensitivity analyses and the approach described above. However, the included study adjusted for clustering adequately, and it was not necessary to re‐analyse it.
Dealing with missing data
If possible, we obtained missing data from the authors of the included studies. We carefully evaluated important numerical data such as screened, randomly assigned participants as well as intention‐to‐treat (ITT) and as‐treated and per‐protocol populations. We investigated attrition rates (e.g. dropouts, losses to follow‐up and withdrawals), and we critically appraised issues concerning missing data and use of imputation methods (e.g. last observation carried forward).
In studies where the standard deviation (SD) of the outcome was not available at follow‐up or could not be re‐created, we standardised by the average of the pooled baseline SD from those studies that reported this information. Where included studies did not report means and SDs for outcomes and the necessary information was unobtainable from the study authors, we imputed these values by estimating the mean and variance from the median, range, and size of the sample (Hozo 2005). We investigated the impact of imputation on meta‐analyses by performing sensitivity analyses, and we reported for every outcome which studies had imputed SDs.
Assessment of heterogeneity
In the event of substantial clinical, methodological, or statistical heterogeneity, we would not report study results as the pooled effect estimate in a meta‐analysis.
We would identify heterogeneity (inconsistency) by visually inspecting the forest plots and by using a standard Chi² test with a significance level of α = 0.1. In view of the low power of this test, we would also consider the I² statistic, which quantifies inconsistency across studies, to assess the impact of heterogeneity on the meta‐analysis (Higgins 2002; Higgins 2003). An I² statistic value of ≥ 75% indicates a considerable level of heterogeneity (Deeks 2019). Had we found heterogeneity, we would have attempted to determine the possible reasons for it by examining individual study and subgroup characteristics. However, given that only one study was included, heterogeneity was not assessed.
Assessment of reporting biases
We did not find enough studies to carry out an assessment of reporting biases. Had we included 10 or more studies that investigated a particular outcome, we would have used funnel plots to assess small‐study effects. Several explanations may account for funnel plot asymmetry, including true heterogeneity of effect with respect to study size, poor methodological design (and hence bias of small studies), and publication bias (Sterne 2017).
Data synthesis
We planned to undertake (or display) a meta‐analysis only if the participants, interventions, comparisons, and outcomes were sufficiently similar to ensure an answer that was clinically meaningful. Unless good evidence showed homogeneous effects across studies, we would primarily summarise data at low risk of bias using a random‐effects model (Wood 2008). We would interpret random‐effects meta‐analyses with due consideration to the whole distribution of effects, ideally by presenting a prediction interval (Borenstein 2017a; Borenstein 2017b; Higgins 2009). A prediction interval needs at least three studies to be calculated and specifies a predicted range for the true treatment effect in an individual study (Riley 2011). For rare events such as event rates below 1%, we used the Peto's odds ratio method, provided that there was no substantial imbalance between intervention and comparator group sizes and intervention effects were not exceptionally large. We also performed statistical analyses according to the statistical guidelines presented in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2019).
Subgroup analysis and investigation of heterogeneity
We did not conduct any subgroup analysis as only one study was included in the review. We expected the following characteristics to introduce clinical heterogeneity and planned to carry out subgroup analyses for these, including investigation of interactions (Altman 2003).
Sex
Ethnicity
Diagnostic criteria for diabetes
Use of different screening methods
Age
Presence of cardiovascular disease risk factors such as hypertension
Sensitivity analysis
We did not include enough studies to carry out sensitivity analysis. We planned to perform sensitivity analyses to explore the influence of the following factors (when applicable) on effect sizes by restricting analysis to the following.
Published studies
Effect of risk of bias, as specified in the Assessment of risk of bias in included studies section
Very long or large studies to establish the extent to which they dominated the results
We used of the following filters, if applicable: diagnostic criteria, imputation used, language of publication (English versus other languages), source of funding (industry versus other), or country (depending on data).
We also planned to test the robustness of results by repeating the analyses using different measures of effect size (RR, OR, etc.) and different statistical models (fixed‐effect and random‐effects models).
Certainty of the evidence
We presented the overall certainty for each outcome specified below according to the GRADE approach, which takes into account issues related to internal validity (risk of bias, inconsistency, imprecision, publication bias) as well as external validity, such as directness of results. Two review authors (NP, SD) independently rated the certainty of the evidence for each outcome. Any differences in assessment were resolved by discussion or by consultation with a third review author (YB).
We included Appendix 15 'Checklist to aid consistency and reproducibility of GRADE assessments' to help with standardisation of the 'Summary of findings' tables (Meader 2014). Alternatively, we used the GRADEpro Guideline Development Tool (GDT) software and presented evidence profile tables as an appendix (GRADEpro GDT 2015). We presented results for outcomes as described in the Types of outcome measures section. When meta‐analysis was not possible, we presented the results in a narrative format in the 'Summary of findings' table. We justified all decisions to downgrade the certainty of trials by using footnotes, and made comments to aid the reader's understanding of the Cochrane Review where necessary.
'Summary of findings' table
We presented a summary of the evidence in the Table 1. This provides key information about the best estimate of the magnitude of effect, in relative terms and as absolute differences for each relevant comparison of alternative management strategies, numbers of participants and trials addressing each important outcome, and a rating of overall confidence in effect estimates for each outcome. We created the 'Summary of findings' table using the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2019), employing along with Review Manager 5 software (RevMan 2014).
The intervention presented in the 'Summary of findings' table was invitation to screening for type 2 diabetes mellitus. The comparator was regular care (no invitation to screening for type 2 diabetes mellitus).
We reported the following outcomes, listed according to priority.
All‐cause mortality
Diabetes‐related mortality
Diabetes‐related morbidity
Incidence of type 2 diabetes
Health‐related quality of life
Adverse events
Socioeconomic effects
Results
Description of studies
For a detailed description of studies, see Table 2; Characteristics of included studies; Characteristics of excluded studies; Characteristics of ongoing studies.
Results of the search
Two review authors screened the titles and abstracts of 4651 unique records identified through electronic database searching, of which 83 full‐texts were assessed against the eligibility criteria. We excluded 71 studies (82 publications/records) with reasons: 29 studies did not include an eligible intervention, 36 were not RCTs, and six assessed the wrong patient population. We included seven records pertaining to one RCT. An additional 20 full‐texts linked to this included study were identified in ClinicalTrials.gov; however, they did not address our review question. We assessed three records pertaining to one study as awaiting classification. Figure 1 outlines the study selection process.
1.
Study flow diagram.
Included studies
For a detailed description of the characteristics of the included study, see Characteristics of included studies and Appendix 3; Appendix 4; Appendix 5; Appendix 6; Appendix 7; Appendix 8; Appendix 9; Appendix 10; Appendix 11; Appendix 12; Appendix 13. The following is a succinct overview.
Source of data
We included one study, the ADDITION‐Cambridge study, in the review (with six linked publications) (Simmons 2012). This trial was part of the larger multicentre ADDITION (Anglo‐Danish‐Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care) trial. The ADDITION trial included 334 general practices in the United Kingdom, the Netherlands, and Denmark (Lauritzen 2000). The general practices were randomised to a screening intervention for diabetes followed by routine care according to national guidelines for the control participants or multifactorial treatment for the intervention group. Men and women aged 40 to 69 years were eligible for inclusion. Individuals with known diabetes at the time of screening, women who were pregnant or lactating, those who were housebound or in poor health and unlikely to survive a year were excluded. In Denmark, participating primary care physicians forwarded diabetes‐related information to all eligible individuals enrolled in their practices. An accompanying letter and questionnaire encouraged individuals at high risk for diabetes to undergo a blood glucose screening test. In England, a previously validated risk score using routine general practice data identified individuals at high risk for diabetes. In the Netherlands, all eligible participants were offered a screening test (Lauritzen 2000). In all three countries, random capillary blood glucose levels identified individuals with levels ≥ 5.5 mmol/L, who were then invited to undergo a fasting capillary blood glucose, and if needed, an OGTT. People newly diagnosed with diabetes were invited to participate in the study. The intensive therapy comprised a group of actions according to strict targets, as well as further randomisation where some participants were allocated to country‐specific interventions. These included motivating adherence to lifestyle changes and medication. A trained facilitator delivered these interventions in England and the Netherlands, whilst trained practitioners did so in Denmark. The choice of medication was determined by the individual doctor and patient based on treatment effect, side‐effects, and costs, with the aim of achieving treatment targets (Lauritzen 2000).
Whilst the ADDITION study was a multicentre study conducted in these three countries, data relevant data to this review were only available for the ADDITION‐Cambridge centre. The ADDITION‐Cambridge study was a pragmatic parallel group, cluster‐randomised trial that involved 33 general practices in Eastern England. The study comprised two phases, of which the first phase that related to diabetes screening was relevant to this review. The second phase compared the effects of intensive multifactorial therapy with routine care in individuals who were diagnosed with screen‐detected type 2 diabetes. The second phase was not relevant to this review, for which the focus was to evaluate screening as the intervention and not different treatment strategies to manage diabetes.
Results from database searches and in ClinicalTrials.gov registry record indicated many publications linked to the ADDITION‐Cambridge study. Of these, some assessed results of the screening phase and others assessed results of phase 2. We excluded all publications linked to phase 2 (N = 33), which were not relevant to this review. Amongst publications linked to phase 1, which were relevant to this review and met the study design criteria, we included seven publications. For example, of those excluded, one paper assessed anxiety and depression as adverse effects of screening outcomes in a convenient subgroup of screening practices and control practices part of the ADDITION trial (Eborall 2007; Echouffo‐Tcheugui 2015). Another paper simply described the baseline cross‐sectional data with no follow‐up data presented (Sandbaek 2008), whilst Griffin 2012 described the impact of early intensive therapy on five‐year outcomes in participants with screen‐detected diabetes from all centres. Another study evaluated the impact of training general practitioners for intensive management of patients with screen‐detected diabetes (Simmons 2017).
All data presented in this review were obtained from published literature.
Comparisons
Simmons 2012 compared inviting versus not inviting high‐risk individuals to screening for diabetes.
Overview of study populations
The ADDITION‐Cambridge study included 20,184 participants from 33 general practices in Eastern England (Simmons 2012). Of these, 27 practices were randomised to the intervention (screening) group, with 11,737 participants actually being screened, and 5 practices were randomised to the control (no screening) group, with 4137 participants. The numbers of participants finishing the study in both groups were not reported.
Study design
The ADDITION‐Cambridge study was a pragmatic parallel‐group, unbalanced cluster‐randomised trial of screening, where 27 practices were randomised to the intervention (screening) arm and 5 practices were randomised to the comparison (no screening) group (Simmons 2012). The investigators assessing outcomes and analysing data were blinded to group assignment. The study started in November 2001 and continued until November 2011, with median follow‐up of 9.6 years (interquartile range 8.9 to 9.9 years).
Settings
The ADDITION‐Cambridge study was conducted in general primary care practices in Eastern England (Simmons 2012).
Participants
Participants included in the study were men and women registered with participating practices in Eastern England, who had a diabetes risk score of more than 0.17 before the start of the study but no known diabetes. The ethnic groups of participants were not reported. In both study arms 36% of participants were female. The mean age of participants in the screening group was 58.2 years, compared to 57.9 years in the no‐screening group. Glycated haemoglobin A1c (HbA1c) and fasting capillary blood glucose (FBG) at baseline were not reported. Mean body mass index (BMI) was 30.5 kg/m² (SD 4.6) and 30.6 kg/m² (SD 4.6) in the intervention and control groups, respectively. Participants in the screening and no‐screening groups were receiving antihypertensive medication (45.9% versus 44.8%) and prescribed steroids (5.4% and 3.7%) at baseline. Participants were excluded from the study if they were pregnant or lactating, had an illness with a likely prognosis of less than one year, or a psychiatric illness likely to limit study involvement.
Interventions
Simmons 2012 reported on the findings from the first phase of the ADDITION‐Cambridge study, which assessed invitation to screening versus no invitation to screening for type 2 diabetes mellitus of participants at high‐risk for diabetes. The diabetes risk score to identify high‐risk individuals comprised variables relating to age, sex, body mass index, and the use of prescribed steroid and anti‐hypertensive medication. The screening process involved stepwise screening of individuals at high‐risk for undetected diabetes using random capillary blood glucose (RCBG), FBG, capillary HbA1c, and OGTT to confirm the results. RCBG, FBG, and OGTT were undertaken on different days.
Outcomes
The primary outcome measured in this study was all‐cause mortality (Simmons 2012). Secondary outcomes assessed included mortality from cardiovascular disease, cancers, other causes, and diabetes‐related mortality. Mortality was assessed through mortality surveillance by the England and Wales Office of National Statistics.
Excluded studies
We excluded 73 records after full‐text screening. For further details see Characteristics of excluded studies.
Studies awaiting classification
We assessed one study (three records) as awaiting classification (Klijs 2012). This study is an RCT conducted in residents of two Dutch municipalities. A total of 10,609 individuals aged 40 to 74 years were randomised to either the diabetes screening or the control arm. The outcomes relevant to this review included: 1) evaluating the effectiveness of screening for type 2 diabetes; and 2) determining whether early detection and treatment of type 2 diabetes compared with no screening contributes to reducing and/or preventing related morbidity and mortality. This study is described as completed in the trial registry, but no publication details were available. We contacted the study author but have not received a response. The trial registry includes one available publication on this study; however, this was an analysis of a subset of participants of the main study by Klijs 2012, and the study design did not meet the criteria for inclusion in this review.
Risk of bias in included studies
For details on the risk of bias of the included study see Characteristics of included studies.
For an overview of review authors' judgements about each 'Risk of bias' item for the included study see Figure 2; Figure 3.
2.
Risk of bias graph: review authors' judgements about each risk of bias item presented as percentages across all included studies (blank cells indicate that the particular outcome was not measured in the included study).
3.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study (blank cells indicate that the particular outcome was not measured in the included study).
Allocation
A statistician used the method of minimisation to perform the randomisation, and there were no imbalances at baseline, either at the individual or cluster level. Allocation was concealed as the randomisation was done centrally. However, the included study was a cluster‐RCT and randomised practices, therefore we assessed selection bias as unclear because it is unknown how and which participants were chosen in the practices to participate in the screening or no‐screening intervention.
Blinding
It was not possible to blind participants or personnel in the ADDITION study. Knowing that you were screened may have altered the behaviour of participants; however, all‐cause mortality and diabetes‐related mortality, assessed through mortality surveillance by the England and Wales Office of National Statistics, are objective outcomes and are therefore not expected to be susceptible to lack of blinding. We thus classified these outcomes as being at low risk of performance bias and detection bias. However, as patient‐reported outcomes, diabetes‐related morbidity and health‐related quality of life were judged to be at high risk of performance and detection bias.
Incomplete outcome data
All eligible participants were flagged for mortality surveillance by the England and Wales Office of National Statistics; the proportion of individuals lost to Office of National Statistics tracking was equally distributed between study groups, and there was a very low loss to follow‐up (1%). The study also used ITT analysis. It was thus classified as being at low risk of attrition bias.
However, for self‐reported outcomes of diabetes‐related morbidity and health‐related quality of life, the risk of bias was high because of low response rates in the screening (62%) and control (53%) groups, with responders being different to non‐responders at baseline. Responders were more likely to be older, female, on hypertensive medication, and have lower BMI and higher risk for undiagnosed diabetes compared with non‐responders.
Selective reporting
All outcomes and methods were described as prespecified in the protocol, therefore we assessed the ADDITION‐Cambridge study as being at low risk of reporting bias.
Other potential sources of bias
We assessed the ADDITION‐Cambridge study as at low risk for other bias. Risk of recruitment bias was low as randomisation was done at the cluster level, and individual participants already belonged to the practices. The study accounted for clustering of practices correctly in their analysis. No other sources of bias were identified.
Effects of interventions
See: Table 1
Baseline characteristics
For details of baseline characteristics, see Appendix 6; Appendix 7.
The ADDITION‐Cambridge study included individuals at high risk for diabetes. High risk in this study was determined using a simple previously validated risk score (diabetes risk score > 0.17). This included routine general practice data (age, gender, prescribed medication, and BMI) collected from their computerised medical records to identify people at high risk of having prevalent undiagnosed diabetes. Practices were eligible to take part if they could provide data for calculation of the risk score for at least 70% of their patients.
The percentage of female participants was 36% in both the intervention and control groups. The mean age and BMI in both groups was similar: 58.2 (SD 7.7) and 57.9 (SD 7.8) years old in the screened and control groups; and 30.5 (SD 4.6) and 30.6 (SD 4.6) kg/m² in the screened and control groups. In both groups about 45% of participants were receiving antihypertensive medication, and slightly more participants in the screened group were receiving prescribed steroids (5.4% versus 3.7%).
Screening versus no screening for type 2 diabetes
Primary outcomes
All‐cause mortality
Simmons 2012 reported that screening compared to no screening for type 2 diabetes made no substantial difference to all‐cause mortality at 10‐year follow‐up (hazard ratio (HR) 1.06, 95% confidence interval (CI) 0.90 to 1.25; P = 0.49; 20,184 participants; low‐certainty evidence; Analysis 1.1). The number of deaths was 377 out of 4137 participants in the no‐screening group and 1532 out of 15,089 participants invited for screening (11,737 participants attending screening). The rate per 1000 person‐years was 9.89 (95% CI 8.94 to 10.94) in the no‐screening group and 10.50 (95% CI 9.99 to 11.04) in the screening group.
1.1. Analysis.
Comparison 1: Screening for diabetes versus no screening for diabetes, Outcome 1: All‐cause mortality
Diabetes‐related mortality
Diabetes‐related mortality was described in our protocol as death from IHD or stroke. The ADDITION‐Cambridge study noted whether diabetes was included anywhere on the death certificates (Simmons 2012). Screening compared to no screening for type 2 diabetes resulted in an HR of 1.26, 95% CI 0.75 to 2.12; 20,184 participants; low‐certainty evidence; Analysis 1.2.
1.2. Analysis.
Comparison 1: Screening for diabetes versus no screening for diabetes, Outcome 2: Diabetes‐related mortality
Simmons 2012 also reported that screening compared to no screening had no substantial impact on cardiovascular mortality (HR 1.02, 95% CI 0.75 to 1.39; Analysis 1.3), defined according to the International Classification of Diseases, 10th edition (ICD‐10) code using I00–I99.
1.3. Analysis.
Comparison 1: Screening for diabetes versus no screening for diabetes, Outcome 3: Cardiovascular mortality
Simmons 2012 also reported that screening compared to no screening had no substantial impact on cancer mortality (HR 1.08, 95% CI 0.90 to 1.30; Analysis 1.4)
1.4. Analysis.
Comparison 1: Screening for diabetes versus no screening for diabetes, Outcome 4: Cancer mortality
Diabetes‐related morbidity
Simmons 2012 reported no substantial difference in self‐reported cardiovascular events (stroke, IHD) between screening and no screening for type 2 diabetes at seven‐year follow‐up in a subsample (15% of participants in the screening group and 40% of participants in the control group) of the main ADDITION trial (odds ratio 0.90, 95% CI 0.71 to 1.15; 1945 participants).
Secondary outcomes
Incidence of type 2 diabetes
This outcome was not reported.
HbA1c
This outcome was not reported.
Adverse events
This outcome was not reported.
Health‐related quality of life
Health‐related quality of life was investigated in a subsample only. The response rate was 62% in the screening group and 53% in the control group.
Simmons 2012 reported no substantial difference in self‐reported health‐related quality of life between the intervention and control groups for type 2 diabetes (mean difference (MD) 0.002, 95% CI −0.02 to 0.02; 1945 participants). This was measured using the EuroQol (EQ‐5D) generic health‐related quality of life instrument, which comprises five questions on mobility, self‐care, pain, usual activities, and psychological status with three possible answers for each item (1 = no problem, 2 = moderate problem, 3 = severe problem). The score ranges from −0.3 to 1, with the maximum score of 1 indicating the best health state.
Simmons 2012 reported no substantial difference in self‐reported mental health between the intervention and control groups at seven‐year follow‐up (MD −0.38, 95% CI −1.33 to 0.57; 1945 participants). Mental health was measured using the 8‐item Short Form Health Survey (SF‐8) summary score, which assesses psychological distress and well‐being (Echouffo‐Tcheugui 2015) .
Socioeconomic effects
This outcome was not reported.
Discussion
Summary of main results
The evidence from a single included study demonstrates that there is no substantial difference in all‐cause and diabetes‐related mortality over a 10‐year period between participants at high‐risk for diabetes who were either screened (intervention) once or not screened (control) for diabetes.
Overall completeness and applicability of evidence
Although the evidence shows that screening versus no screening for diabetes does not significantly impact all‐cause and diabetes‐related mortality, conclusions should not be drawn from a single study regarding these specific outcomes. The ADDITION‐Cambridge study presented separate outcomes pertaining to cardiovascular‐ and diabetes‐related mortality, which we have reported as such. However, this differs from our protocol, where we included death from IHD or stroke (i.e. cardiovascular outcomes) as diabetes‐related mortality.
Diabetes‐related morbidity was also a primary outcome in this review, which included IHD and stroke. These were self‐reported in a substudy of the ADDITION‐Cambridge trial (Simmons 2012). No substantial differences in cardiovascular events were noted. Other diabetes‐related morbidity outcomes pertaining to microvascular complications such as diabetic retinopathy, diabetic nephropathy, or diabetic neuropathy were not reported in the screening and control groups.
Other secondary outcomes of interest were not reported in the ADDITION‐Cambridge study, including incidence of type 2 diabetes, adverse events, HbA1c levels, and socioeconomic effects.
The participants in the ADDITION‐Cambridge trial were all from the same setting, that is primary care practices in the United Kingdom. Consequently, this review cannot provide evidence for effects of screening in other settings, such as low‐ and middle‐income countries, for example.
Quality of the evidence
We included one large study with few methodological limitations in the review. We assessed the certainty of evidence for all‐cause mortality and diabetes‐related mortality to be low, downgrading because of serious imprecision, as the benefits ranged from beneficial to harmful.
Potential biases in the review process
Three review authors without financial interest in the outcome independently extracted data. None of these authors was involved in a previous review related to this topic. The review authors believe that an unbiased process was followed for this review. We consulted with the review's advisory group and other methods experts regarding the study selection process. This included a decision to exclude substudies of the included study, which addressed some of the review's outcomes of interest but did not meet the study design criteria for eligibility.
We contacted an author of a study that we assessed as awaiting classification but have received no response; it is therefore possible that a relevant study that could have provided evidence to address the review's objectives was not included in the review.
The original protocol was published in 2005. The current author team revised the protocol with the Review Group when it took over the review conduct from the previous author team. There have been no deviations from the protocol as agreed with the Review Group at that stage.
Agreements and disagreements with other studies or reviews
In a report for the US Preventive Services Task Force, Selph 2015, and in a health‐assessment technology report for the National Screening Committee (Waugh 2013), screening for diabetes made no difference in mortality at 10 years compared to no screening. Both reports included two studies that addressed this question, one of which was included in this review (Simmons 2012), and the other which was excluded, as it did not meet our study design criteria (Simmons 2011). We are unaware of other reviews on this specific topic.
The Danish arm of the ADDITION‐Europe study, which we did not include in our review because it was a non‐randomised controlled study, compared the risk of mortality and cardiovascular events in individuals with incident diabetes in the screening and control groups (Simmons 2017b_ADDITION Denmark). This study reported reduced all‐cause mortality, diabetes‐related mortality, and cardiovascular events in the screening compared to the no‐screening group.
The same study examined the effect of screening for diabetes and cardiovascular risk factors on population‐level mortality rates and cardiovascular events (Simmons 2017a_ADDITION Denmark). There was no significant difference between the screening and no‐screening groups in all‐cause mortality, cardiovascular mortality, diabetes‐related mortality, or first cardiovascular event.
The Inter99 was an RCT conducted in Copenhagen, Denmark to examine the effect of invitation to participate in a screening and lifestyle programme on IHD; diabetes incidence was a secondary outcome (Lau 2016). We excluded this study because the intervention differed from that prespecified in our protocol, which assessed the effect of screening for diabetes only. Lau 2016 reported no significant difference in the incidence of diabetes between groups at 10‐year follow‐up.
The Ely Study, which we did not include in our review because it was not an RCT, compared outcomes in individuals invited and not invited for diabetes screening. Participants who were invited for screening compared with those not invited for screening had a non‐significant 21% reduction in all‐cause mortality after a median 10 years' follow‐up (Simmons 2011). The prevalence of self‐reported heart attack and stroke, and self‐rated health was similar in individuals without diabetes in the screened and unscreened groups of the Ely cohort 13 years after commencement of screening (Simmons 2011).
Authors' conclusions
Implications for practice.
We are uncertain about the effects of screening for diabetes on all‐cause mortality and diabetes‐related mortality. We included evidence from one study only, therefore we could draw no firm conclusions relating to the health outcomes of early type 2 diabetes screening. Furthermore, the included study did not assess all the outcomes we intended to address in the review: diabetes‐related morbidity, incidence of type 2 diabetes, health‐related quality of life, adverse events, and socioeconomic effects.
Implications for research.
This systematic review found only one study that fulfilled the review criteria. Possible reasons for this may be the costs involved in conducting trials on this topic, which would require following a large sample of participants for a prolonged time period. The aim would be to not only determine the incidence of diabetes in the intervention and control groups but also to determine the incidence of diabetes‐related morbidity and mortality, which usually develop over at least 5 to 10 years. Nevertheless, more evidence pertaining to the effects of diabetes screening is required. Outcomes of importance for which more evidence is required include diabetes‐related morbidity, diabetes‐related cardiovascular mortality, diabetes incidence in high‐risk populations, and impact of diabetes screening on well‐being and socioeconomic outcomes, which were not reported in the included study. Some of these outcomes were reported in substudies of the included study, but due to these being substudies of the main study, following different methodology, they were not eligible for inclusion. More study evidence on the effects of screening in other settings, such as in low‐ and middle‐income countries for example, is also required.
What's new
| Date | Event | Description |
|---|---|---|
| 2 June 2020 | Amended | Addition of the statement of Solange Durao to external sources. |
History
Protocol first published: Issue 2, 2005 Review first published: Issue 5, 2020
Notes
Portions of the Background and Methods sections, the Appendices, Additional tables, and Figures 1 to 3 of this review are based on a standard template established by Cochrane Metabolic and Endocrine Disorders.
Acknowledgements
The first protocol for this Cochrane Review was published by Woolthuis EK, de Grau W, van de Laar F, and Akkermans R. We also thank Dagmar Haller, Johanna Sommer, Arabelle Rieder, Catherine Herter‐Clavel, Anca Paschoud, Danilo Janjic, Angel Vilaseca, Cédric Gillabert, Wim JC De Grauw, and Christophe Combescure for their work on the protocol update. We would like to thank the review advisory board for their input in the review: Tamara Kredo, Taryn Young, and Andre Pascal Kengne. We thank Maria‐Inti Metzendorf, Information Specialist for Cochrane Metabolic and Endocrine Disorders (CMED), for the development of the search strategy. The review authors and the CMED editorial base are grateful to the peer reviewer Philippa Middleton, SAHMRI and The University of Adelaide, Australia, for her time and comments.
Appendices
Appendix 1. Diagnostic criteria for diabetes as defined by expert committees
| Expert committees | Criteria | |||
| Fasting plasma glucosea | 2‐hour plasma glucoseb | Random plasma glucose | HbA1c | |
| World Health Organization (WHO) | ||||
| 1985 (WHO 1985) | ≥ 7.8 mmol/L (≥ 140 mg/dL) | ≥ 11.1 mmol/L (≥ 200 mg/dL) | NA | NA |
| 1998 (WHO 1999) | ≥ 7.0 mmol/L (≥ 126 mg/dL) | ≥ 11.1 mmol/L (≥ 200 mg/dL) | NA | NA |
| American Diabetes Association (ADA) | ||||
| 1997 (Expert Committee 1997) | ≥ 7.0 mmol/L (≥ 126 mg/dL) | Not recommended | NA | NA |
| 2003 (ADA 2003) | ≥ 7.0 mmol/L (≥ 126 mg/dL) | ≥ 11.1 mmol/L (≥ 200 mg/dL) | Symptoms of diabetes + ≥ 11.1 mmol/L (≥ 200 mg/dL) | NA |
| 2010 (ADA 2010) | ≥ 7.0 mmol/L (≥ 126 mg/dL | ≥ 11.1 mmol/L (≥ 200 mg/dL) | ≥ 11.1 mmol/L (≥ 200 mg/dL | ≥ 6.5% (≥ 48 mmol/mol) |
|
aFollowing an overnight fast of ≥ 8 hours.
bDuring an oral glucose tolerance test. HbA1c: glycosylated haemoglobin A1c; NA: not applicable. | ||||
Appendix 2. Search strategies
| CENTRAL (CRSO) |
| 1. MESH DESCRIPTOR Mass Screening 2. screening?:TI,AB,KY 3. (screened or detect or detected or detection):TI 4. #1 OR #2 OR #3 5. MESH DESCRIPTOR Diabetes Mellitus, Type 2 EXPLODE ALL TREES 6. (MODY OR NIDDM OR T2DM OR T2D):TI,AB,KY 7. diabet*:TI,AB 8. #5 OR #6 OR #7 9. MESH DESCRIPTOR Diabetes Insipidus EXPLODE ALL TREES 10. ("diabet* insipidus"):TI,AB,KY 11. #9 OR #10 12. #8 NOT #11 13. #4 AND #12 14. NCT*:AU [filters for ClinicalTrials.gov records] 15. trialsearch:SO [filters for WHO ICTRP records] 16. #14 OR #15 17. #13 NOT #16 |
| MEDLINE (Ovid SP) |
| 1. exp Mass Screening/ 2. (screening?).tw. 3. (screened or detect or detected or detection).ti. 4. or/1‐3 5. exp Diabetes Mellitus, Type 2/ 6. (MODY or NIDDM or T2DM or T2D).tw. 7. (non insulin* depend* or noninsulin* depend* or noninsulin?depend* or non insulin?depend*).tw. 8. ((typ? 2 or typ? II or typ?2 or typ?II) adj3 diabet*).tw. 9. (((late or adult* or matur* or slow or stabl*) adj3 onset) and diabet*).tw. 10. or/5‐9 11. exp Diabetes Insipidus/ 12. diabet* insipidus.tw. 13. 11 or 12 14. 10 not 13 15. 4 and 14 [16‐26: Cochrane Handbook 2008 RCT filter ‐ sensitivity maximizing version] 16. randomized controlled trial.pt. 17. controlled clinical trial.pt. 18. randomi?ed.ab. 19. placebo.ab. 20. drug therapy.fs. 21. randomly.ab. 22. trial.ab. 23. groups.ab. 24. or/16‐23 25. exp animals/ not humans/ 26. 24 not 25 27. 15 and 26 |
| LILACS (IAHx) |
| (MH:"Mass Screening" OR screen$ OR cheq$ OR criba$ OR detec$ OR rastr$ OR triag$) AND (MH:"Diabetes Mellitus, Type 2" OR diabet$) + Filter "Controlled Clinical Trial" |
| ICTRP Search Portal (Standard search) |
| screening* AND diabet* |
| ClinicalTrials.gov (Advanced search) |
|
Conditions: diabetes OR diabetic Interventions: screening OR screenings OR screened OR screen OR detection OR detecting OR detected Study type: Interventional Studies |
Appendix 3. 'Risk of bias' assessment
| 'Risk of bias' domains |
|
Random sequence generation (selection bias due to inadequate generation of a randomised sequence) For each included study, we described the method used to generate the allocation sequence in sufficient detail to allow an assessment of whether it should produce comparable groups.
Allocation concealment (selection bias due to inadequate concealment of allocation prior to assignment) We described for each included study the method used to conceal allocation to interventions prior to assignment and assessed whether intervention allocation could have been foreseen in advance of or during recruitment or changed after assignment.
We also evaluated study baseline data to incorporate assessment of baseline imbalance into the 'Risk of bias' judgement for selection bias (Corbett 2014). Chance imbalances may also affect judgements on the risk of attrition bias. In the case of unadjusted analyses, we distinguished between studies judged as being at low risk of bias on the basis of both randomisation methods and baseline similarity, and studies judged as being at low risk of bias on the basis of baseline similarity alone (Corbett 2014). We reclassified judgements of unclear, low, or high risk of selection bias as specified in Appendix 4. Blinding of participants and study personnel (performance bias due to knowledge of the allocated interventions by participants and personnel during the study) We evaluated the risk of detection bias separately for each outcome (Hróbjartsson 2013). We noted whether endpoints were self‐reported, investigator‐assessed, or adjudicated outcome measures (see below).
Blinding of outcome assessment (detection bias due to knowledge of the allocated interventions by outcome assessment) We evaluated the risk of detection bias separately for each outcome (Hróbjartsson 2013). We noted whether endpoints were self‐reported, investigator‐assessed, or adjudicated outcome measures (see below).
Incomplete outcome data (attrition bias due to quantity, nature, or handling of incomplete outcome data) For each included study or each outcome, or both, we described the completeness of data, including attrition and exclusions from the analyses. We stated whether the study reported attrition and exclusions, and reported the number of participants included in the analysis at each stage (compared with the number of randomised participants per intervention/comparator groups). We also noted if the study reported the reasons for attrition or exclusion, and whether missing data were balanced across groups or were related to outcomes. We considered the implications of missing outcome data per outcome such as high dropout rates (e.g. above 15%) or disparate attrition rates (e.g. difference of 10% or more between study arms).
Selective reporting (reporting bias due to selective outcome reporting) We assessed outcome reporting bias by integrating the results of Appendix 9 'Matrix of study endpoints (publications and trial documents)' (Boutron 2014; Jones 2015; Mathieu 2009), with those of Appendix 10 'High risk of outcome reporting bias according to the Outcome Reporting Bias In Trials (ORBIT) classification' (Kirkham 2010). This analysis formed the basis for the judgement of selective reporting.
Other bias
|
Appendix 4. Selection bias decisions
| Selection bias decisions for studies reporting unadjusted analyses ‐ comparison of results obtained using method details alone with results using method details and study baseline informationa | |||
| Reported randomisation and allocation concealment methods | 'Risk of bias' judgement using methods reporting | Information gained from study characteristics data | Risk of bias using baseline information and methods reporting |
| Unclear methods | Unclear risk | Baseline imbalances present for important prognostic variable(s) | High risk |
| Groups appear similar at baseline for all important prognostic variables | Low risk | ||
| Limited or no baseline details | Unclear risk | ||
| Would generate a truly random sample, with robust allocation concealment | Low risk | Baseline imbalances present for important prognostic variable(s) | Unclear riskc |
| Groups appear similar at baseline for all important prognostic variables | Low risk | ||
| Limited baseline details, showing balance in some important prognostic variablesb | Low risk | ||
| No baseline details | Unclear risk | ||
| Sequence is not truly random, or allocation concealment is inadequate | High risk | Baseline imbalances present for important prognostic variable(s) | High risk |
| Groups appear similar at baseline for all important prognostic variables | Low risk | ||
| Limited baseline details, showing balance in some important prognostic variablesb | Unclear risk | ||
| No baseline details | High risk | ||
| aTaken from Corbett 2014; judgements highlighted in bold indicate situations in which the addition of baseline assessments would change the judgement about risk of selection bias, compared with using methods reporting alone. bDetails for the remaining important prognostic variables not reported. cImbalance identified that appears likely to be due to chance. | |||
Appendix 5. Description of interventions and comparators
| Item | Study ID:Simmons 2012 |
| Study author | Simmons 2012 |
| Brief name | ADDITION (Anglo‐Danish‐Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care) trial |
| Recipient | 20,184 participants from 33 general practices in Eastern England, at high risk for diabetes |
| Why | The high proportion of undiagnosed diabetes, the substantial burden of complications at clinical diagnosis, and the long latent phase of the disease are arguments in favour of screening for diabetes. |
| What (materials) |
|
| What (procedures) | Testing of random or fasting capillary blood glucose in high‐risk patients involved a finger prick test. Oral glucose tolerance test (OGTT) involved an overnight fast of about 10 hours followed by drawing a venous blood sample, the administration of 75 g of anhydrous glucose in 250 mL of water, and another blood sample taken 120 minutes later. |
| Who provided | "In the participating practices, a 'set‐up' visit was undertaken to deliver practice study manuals, to provide the software developed to assist with monitoring the progress of the screening programme and recording of blood glucose test results, and to train the staff in logistical and technical aspects of screening. Further visits were arranged for practices allocated to screening followed by intensive treatment to provide the materials and training to enable them to deliver the intervention." (Echouffo‐Tcheugui 2009, linked to Simmons 2012) |
| How (mode of delivery; individual or group) | "In practices in the RC and IT groups, general practitioners wrote to all high‐risk patients, enclosing a study information sheet, and inviting them to attend the practice for random capillary blood glucose (RBG) and capillary glycosylated haemoglobin (HbA1c) tests, after initial consent had been obtained." "Patients were advised to telephone the surgery and arrange an alternative appointment if the original was inconvenient. One reminder letter was sent to non‐attendees." (Echouffo‐Tcheugui 2009, linked to Simmons 2012). Screenings were provided on an individual basis. |
| Where | OGTT was conducted at 1 of 4 outpatient facilities. Random and fasting blood glucose testing were undertaken at the general practitioner practices on different days. |
| When and how much | Each glucose test was done once. The number of tests done per patient depended on the results of each test. Testing was conducted on different days at the patient's convenience. |
| Tailoring | "Participants with an RBG of ≥ 11.1 mmol/L were invited for a standard 75 g oral glucose tolerance test (OGTT) at one of four outpatient facilities. Those with an RBG of 5.5–11.0 mmol/L were invited to return to the practice for a fasting capillary blood glucose (FBG) test. Those with an FBG of ≥ 6.1 mmol/L, or an FBG of 5.5–6.0 mmol/L together with an HbA1c of ≥ 6.1%, were invited for an OGTT. The RBG, FBG and OGTT were conducted on different days. Participants with an FBG of 5.5–6.0 mmol/L and an HbA1c of ≥ 6.1% who had a positive OGTT underwent a second confirmatory OGTT on a different day." (Echouffo‐Tcheugui 2009, linked to Simmons 2012) |
| Modification of intervention throughout the trial | Not applicable for diabetes screening |
| Strategies to improve or maintain intervention fidelity | Not applicable for diabetes screening. "The invitation list for screening was defined at the outset of the study; practices were asked to invite only the patients on the list that we provided." "Practices were eligible to take part if they could provide data for calculation of the risk score for at least 70% of their patients" (Simmons 2012) |
| Extent of intervention fidelity | Not tested |
| EQ‐5D: EuroQol measure of health outcome; HbA1c: glycosylated haemoglobin A1c; IT: intensive treatment; OGTT: oral glucose tolerance test; RBG: random capillary blood glucose; RC: routine care. | |
Appendix 6. Baseline characteristics (I)
| Study ID | Intervention(s) and comparator(s) | Duration of intervention (follow‐up) | Description of participants | Diagnostic criteria for type 2 diabetes | Study period (year to year) | Country | Setting | Ethnic groups (%) |
| Simmons 2012 | I: High‐risk individuals invited for screening for diabetes | Median 9.6 years follow‐up | People registered with 1 of the participating general practices, aged 40 to 69 years, not known to have diabetes, and with a diabetes risk scorea of > 0.17 | 75 g OGTT (1999 WHO criteria) | November 2001 to November 2011 | United Kingdom | General practices in Eastern England | — |
| C: High‐risk individuals not invited for screening for diabetes | — | |||||||
| —: denotes not reported C: comparator; I: intervention; OGTT: oral glucose tolerance test; WHO: World Health Organization. aThe score consisted of age, gender, body mass index, steroid and antihypertensive medication, family and smoking history. | ||||||||
Appendix 7. Baseline characteristics (II)
| Study ID | Intervention(s) and comparator(s) | Sex (female %) | Age (mean years (SD)) | HbA1c (mean % (SD)) | FBG (mean mg/dL (SD)) | BMI (mean kg/m² (SD)) | Co‐medications/Co‐interventions (% of participants) | Comorbidities (% of participants) |
| Simmons 2012 | I: High‐risk individuals invited for screening for diabetes | 36 | 58.2 (7.7) | — | — | 30.5 (4.6) | Antihypertensive medication: 45.9 Prescribed steroids: 5.4 |
— |
| C: High‐risk individuals not invited for screening for diabetes | 36 | 57.9 (7.8) | — | — | 30.6 (4.6) | Antihypertensive medication: 44.8 Prescribed steroids: 3.7 |
— | |
| —: denotes not reported BMI: body mass index; C: comparator; FBG: fasting blood glucose; HbA1c: glycosylated haemoglobin A1c; I: intervention; SD: standard deviation. | ||||||||
Appendix 8. Study endpoints and timing of outcome measurement
| Study ID | Primary and secondary outcomes of this review | Timing of outcome measurement |
| Simmons 2012 | All‐cause mortality | 10 years |
| Diabetes‐related mortality | 10 years | |
| Diabetes‐related morbidity | 7 years | |
| Incidence of type 2 diabetes | — | |
| Health‐related quality of life | 7 years | |
| Adverse events | 7 years | |
| Socioeconomic effects | — | |
| —: denotes not reported | ||
Appendix 9. Matrix of study endpoints (publications and trial documents)
| Study ID | Endpoints |
| Simmons 2012 | Endpoints quoted in trial document(s) (ClinicalTrials.gov, FDA/EMA document, manufacturer's website, published design paper)a,b |
|
Primary outcome measure(s): Source 1:NCT00237549 (ISRCTN86769081) Cardiovascular mortality, myocardial infarction (non‐fatal), stroke (non‐fatal), revascularisation (operating procedures), amputations, non‐traumatic Source 2 (published protocol): Echouffo‐Tcheugui 2009 under Simmons 2012 "At one year follow‐up the principle outcome is modelled 10‐year risk of cardiovascular events derived using the UKPDS risk engine" "At five‐year follow‐up, the primary endpoint is a composite of cardiovascular mortality and morbidity (non‐fatal myocardial infarction, non‐fatal stroke, non‐traumatic amputations and revascularizations)" Secondary outcome measure(s): Source 1:NCT00237549 (ISRCTN86769081) All‐cause mortality, development of renal impairment, progression of retinopathy, health economy, patient and health service costs and gains, perceived health, SF‐36, ADDQol, neuropathy, periphery and autonomy Source 2 (published protocol): Echouffo‐Tcheugui 2009 under Simmons 2012 All‐cause mortality, development or progression of renal impairment, peripheral neuropathy, blindness, reduced visual acuity, macular oedema, retinopathy; health status, health utility, quality of life, anxiety, well‐being, treatment satisfaction, health service costs (number of visits to general practitioners and hospital doctors for outpatient clinics, hospital admissions and prescribed medications) Other outcome measure(s) (intermediate endpoints) Source 1:NCT00237549 (ISRCTN86769081) Source 2 (published protocol): Echouffo‐Tcheugui 2009 under Simmons 2012 Self‐reported smoking status, diet, physical activity behaviour and medication adherence, HbA1c, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, blood pressure, modelled 10‐year cardiovascular risk (at 5‐year follow‐up), self‐reported hypoglycaemic episodes, microalbuminuria, body mass index, and plasma vitamin C Trial results available in trial register: yes | |
| Endpoints quoted in publication(s)b,c | |
|
Primary outcome measure(s): all‐cause mortality Secondary outcome measure(s): death from cardiovascular disease, cancers, and other causes; diabetes‐related death, health‐related quality of life, mental health Other outcome measure(s): other outcomes listed in the ADDITION trial registry entry were published in various ADDITION papers; we excluded these from our review as they did not address the question of screening versus no screening, but rather the question of intensive versus routine care for screen‐detected diabetes | |
| Endpoints quoted in abstract of publication(s)b,c | |
|
Primary outcome measure(s): all‐cause mortality Secondary outcome measure(s): cardiovascular mortality, cancer mortality, diabetes‐related mortality Other outcome measure(s): — | |
| —: denotes not reported
aTrial document(s) refers to all available information from published design papers and sources other than regular publications (e.g. FDA/EMA documents, manufacturer's websites, trial registers).
bPrimary and secondary outcomes refer to verbatim specifications in publication/records. Unspecified outcome measures refer to all outcomes not described as primary or secondary outcome measures. cPublication(s) refers to trial information published in scientific journals (primary reference, duplicate publications, companion documents or multiple reports of a primary trial). ADDITION: Anglo‐Danish‐Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care; ADDQol: Audit of Diabetes‐Dependent Quality of Life; EMA: European Medicines Agency; FDA: US Food and Drug Administration; HbA1c: glycosylated haemoglobin A1c; HDL: high‐density lipoprotein; LDL: low‐density lipoprotein; SF‐36: 36‐item Short Form Health Survey; UKPDS: UK Prospective Diabetes Study. | |
Appendix 10. High risk of outcome reporting bias according to Outcome Reporting Bias In Trials (ORBIT) classification
| Study ID | Outcome | High risk of bias (category A)a | High risk of bias (category D)b | High risk of bias (category E)c | High risk of bias (category G)d |
| Simmons 2012 | ND | ||||
|
aClear that outcome was measured and analysed; trial report states that outcome was analysed but reports only that result was not significant.
(Classification 'A', table 2, Kirkham 2010)
bClear that outcome was measured and analysed; trial report states that outcome was analysed but reports no results.
(Classification 'D', table 2, Kirkham 2010)
cClear that outcome was measured but was not necessarily analysed; judgement says likely to have been analysed but not reported due to non‐significant results.
(Classification 'E', table 2, Kirkham 2010)
dUnclear whether outcome was measured; not mentioned, but clinical judgement says likely to have been measured and analysed but not reported on the basis of non‐significant results.
(Classification 'G', table 2, Kirkham 2010) ND: none detected. | |||||
Appendix 11. Definition of endpoint measurement (I)a
| Study ID | All‐cause mortality | Diabetes‐related mortality | Diabetes‐related morbidity | Incidence of type 2 diabetes | Health‐related quality of life | Adverse events | Socioeconomic effects |
| Simmons 2012 | The England and Wales Office of National Statistics provided death certificate copies of deceased participants. The General Register Office of Scotland and the Central Statistics Office of Ireland provided the vital status of participants who moved to these areas (IO). |
Diabetes stated as cause of death on death certificates (IO). | Diabetes was included anywhere on the death certificate (IO). | NR | EQ‐5D generic quality of life instrument comprises 5 questions on mobility, self‐care, pain, usual activities, and psychological status. The score ranges from −0.3 to 1, with the maximum score of 1 indicating the best health state (SO). Mental health: SF‐8 mental health summary score, which assesses psychological distress and well‐being. The score ranges from 0 to 100, with the maximum score of 100 indicating the best mental health state (SO). |
— | NR |
| —: denotes not reported aIn addition to definition of endpoint measurement, description of who measured the outcome (AO: adjudicated outcome measurement; IO: investigator‐assessed outcome measurement; SO: self‐reported outcome measurement). EQ‐5D: EuroQol measure of health outcome; NR: not reported; SF‐8: 8‐item Short Form Health Survey. | |||||||
Appendix 12. Adverse events (I)
| Study ID | Intervention(s) and comparator(s) | Participants included in analysis (N) | Deaths (N) | Deaths (% of participants) | Participants with at least 1 adverse event (N) | Participants with at least 1 adverse event (%) | Participants with at least 1 severe/serious adverse event (N) | Participants with at least 1 severe/serious adverse event (%) |
| Simmons 2012 | I: Individuals at high risk for diabetes invited for screening | 16,047 | 1532 | 9.6 | — | — | — | — |
| C: Individuals at high risk for diabetes not invited for screening | 4137 | 377 | 9.1 | — | — | — | — | |
| —: denotes not reported C: comparator; I: intervention. | ||||||||
Appendix 13. Adverse events (II)
| Study ID | Intervention(s) and comparator(s) | Participants included in analysis (N) | Participants discontinuing trial due to an adverse event (N) | Participants discontinuing trial due to an adverse event (%) | Participants with at least 1 hospitalisation (N) | Participants with at least 1 hospitalisation (%) | Participants with at least 1 outpatient treatment (N) | Participants with at least 1 outpatient treatment (%) |
| Simmons 2012 | I: individuals at high risk for diabetes invited for screening | 16,047 | — | — | — | — | — | — |
| C: individuals at high risk for diabetes not invited for screening | 4137 | — | — | — | — | — | — | |
| —: denotes not reported C: comparator; I: intervention. | ||||||||
Appendix 14. Survey of study investigators providing information on included studies
| Included studies | Date study author contacted | Date study author replied | Date study author was asked for additional information (short summary) | Date study author provided data (short summary) | |
| Simmons 2012 | 26 March 2020 | No answer | NA | NA | |
| Studies awaiting assessment | Study completion date | Date study author contacted | Date study author replied | Date study author was asked for additional information (short summary) | Date study author provided data (short summary) |
| Scherstén 1966 | PM | Contact details for the author were unavailable; study was published over 50 years ago. | NA | NA | NA |
| Klijs 2012 | RT (ISRCTN75983009) | February 2018; April 2020 | No answer | NA | NA |
| Ongoing trials (with an estimated study completion date more than 1 year in the past) | Study completion date | Date study author contacted | Date study author replied | Date study author was asked for additional information (short summary) | Date study author provided data (short summary) |
| None | NA | NA | NA | NA | NA |
| NA: not applicable; PM: published manuscript; RT: registered trial. | |||||
Appendix 15. Checklist to aid consistency and reproducibility of GRADE assessments
| (1) All‐cause mortality | (2) Diabetes‐related mortality | (3) Diabetes‐related morbidity | (4) Incidence of type 2 diabetes | (5) Health‐related quality of life | (6) Adverse events | (7) Socioeconomic effects | ||
| Study ID limitations (risk of bias)a | Was random sequence generation used (i.e. no potential for selection bias)? | Unclear | Unclear | Subsample only | — | Subsample only (the response rate was 62% in the screening group and 53% in the control group) | — | — |
| Was allocation concealment used (i.e. no potential for selection bias)? | Unclear | Unclear | ||||||
| Was there blinding of participants and personnel (i.e. no potential for performance bias) or outcome was not likely to have been influenced by lack of blinding? | Yes | Yes | ||||||
| Was there blinding of outcome assessment (i.e. no potential for detection bias) or was outcome measurement not likely to have been influenced by lack of blinding? | Yes | Yes | ||||||
| Was an objective outcome used? | Yes | Yes | ||||||
| Were more than 80% of participants enrolled in the trials included in the analysis (i.e. no potential attrition bias)?e | Yes | Yes | ||||||
| Were data reported consistently for the outcome of interest (i.e. no potential selective reporting)? | Yes | Yes | ||||||
| No other biases reported (i.e. no potential of other bias)? | Yes | Yes | ||||||
| Did the trials end up as scheduled (i.e. not stopped early)? | Yes | Yes | ||||||
| Inconsistencyb | Point estimates did not vary widely? | NA | NA | |||||
| To what extent did confidence intervals overlap (substantial: all confidence intervals overlap at least 1 of the included studies point estimate; some: confidence intervals overlap but not all overlap at least 1 point estimate; no: at least 1 outlier: where the confidence intervals of some of the studies do not overlap with those of most included studies)? | NA | NA | ||||||
| Was the direction of effect consistent? | NA | NA | ||||||
| What was the magnitude of statistical heterogeneity (as measured by I²): low (I² < 40%), moderate (I² 40% to 60%), high (I² > 60%)? | NA | NA | ||||||
| Was the test for heterogeneity statistically significant (P < 0.1)? | NA | NA | ||||||
| Indirectness | Were the populations in the included studies applicable to the decision context? | Applicable | Applicable | |||||
| Were the interventions in the included studies applicable to the decision context? | Applicable | Applicable | ||||||
| Was the included outcome not a surrogate outcome? | Yes | Yes | ||||||
| Was the outcome time frame sufficient? | Sufficient | Sufficient | ||||||
| Were the conclusions based on direct comparisons? | Yes | Yes | ||||||
| Imprecisionc | Was the confidence interval for the pooled estimate not consistent with benefit and harm? | No (↓) | No (↓) | |||||
| What is the magnitude of the median sample size (high: 300 participants, intermediate: 100 to 300 participants, low: < 100 participants)?e | NA | NA | ||||||
| What was the magnitude of the number of included studies (large: > 10 studies, moderate: 5 to 10 studies, small: < 5 studies)?e | Small (↓) | Small (↓) | ||||||
| Was the outcome a common event (e.g. occurs more than 1/100)? | Yes | No (↓) | ||||||
| Publication biasd | Was a comprehensive search conducted? | Yes | Yes | |||||
| Was grey literature searched? | Yes | Yes | ||||||
| Were no restrictions applied to study selection on the basis of language? | Yes | Yes | ||||||
| There was no industry influence on the studies included in the review? | Yes | Yes | ||||||
| There was no evidence of funnel plot asymmetry? | NA | NA | ||||||
| There was no discrepancy in findings between published and unpublished trials? | Unclear | Unclear | ||||||
| —: denotes not reported aQuestions on risk of bias are answered in relation to the majority of the aggregated evidence in the meta‐analysis rather than to individual trials. bQuestions on inconsistency are primarily based on visual assessment of forest plots and the statistical quantification of heterogeneity based on I². cWhen judging the width of the confidence interval, it is recommended to use a clinical decision threshold to assess whether the imprecision is clinically meaningful. dQuestions address comprehensiveness of the search strategy, industry influence, funnel plot asymmetry and discrepancies between published and unpublished trials. eDepends on the context of the systematic review area. (↓): key item for potential downgrading the certainty of the evidence (GRADE) as shown in the footnotes of the 'Summary of findings' table(s). | ||||||||
Appendix 16. Health‐related quality of life: instruments
| Instrument | Dimensions (subscales) (no. of items) | Validated instrument | Answer options | Scores |
Minimum score Maximum score |
Weighting of scores | Direction of scales | Minimal important difference |
| EQ‐5D (G) (employed in Simmons 2012)a | Health utility | Yes | 1 = no problem, 2 = moderate problem, 3 = severe problem | Scores for health utility | Minimum score: −0.3 Maximum score: 1 |
No | Higher values indicate best health state. | ‐ |
| SF‐8 (G) (employed in Simmons 2012)a | Mental health | Yes | 5‐to‐6‐point Likert scale | Scores for mental health | Minimum score: 0 Maximum score: 100 | No | Higher values indicate best health state. | "50 points represents the national standard value for health and functioning" |
|
aSubsample only: the response rate was 62% in the screening group and 53% in the control group. EQ‐5D: EuroQol measure of health outcome; SF‐8: 8‐item Short Form Health Survey; G: Generic: not reported. | ||||||||
Data and analyses
Comparison 1. Screening for diabetes versus no screening for diabetes.
| Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
|---|---|---|---|---|
| 1.1 All‐cause mortality | 1 | Hazard Ratio (IV, Fixed, 95% CI) | Totals not selected | |
| 1.2 Diabetes‐related mortality | 1 | Hazard Ratio (IV, Fixed, 95% CI) | Totals not selected | |
| 1.3 Cardiovascular mortality | 1 | Hazard Ratio (IV, Fixed, 95% CI) | Totals not selected | |
| 1.4 Cancer mortality | 1 | Hazard Ratio (IV, Fixed, 95% CI) | Totals not selected |
Characteristics of studies
Characteristics of included studies [ordered by study ID]
Simmons 2012.
| Study characteristics | ||
| Methods | Study design: pragmatic parallel‐group, unbalanced, cluster‐randomised trial; randomisation ratio: 1:6 randomisation of practices | |
| Participants |
Inclusion criteria: individuals eligible for an invitation for screening were men and women registered with 1 of the participating general practices, aged 40 to 69 years, not known to have diabetes and with a diabetes risk score of > 0.17 (corresponding to the top 25% of the population distribution) Exclusion criteria: pregnancy, lactation, an illness with a likely prognosis of less than 1 year, or a psychiatric illness likely to limit study involvement or invalidate informed consent Diagnostic criteria: a stepwise programme was used for the diagnosis of diabetes. This included a random capillary blood glucose and HbA1c tests, a fasting capillary blood glucose test, and confirmation on OGTT |
|
| Interventions | Screening for diabetes compared to not screening for diabetes in high‐risk individuals. Those diagnosed with diabetes after screening (OGTT) received either intensive multifactorial treatment (IT) or routine care (RC) according to which arm the practice they attended had been randomised to. Number of study centres: 32 general practices participated and were randomised to a screening intervention group (N = 27; 13 to screening and RC and 14 to screening and IT) or to a no‐screening control group (N = 5) |
|
| Outcomes | Proportion of people who responded to the invitation for screening diagnosed with diabetes.
|
|
| Study details | Study ID: ISRCTN86769081 | |
| Publication details |
Language of publication: English Funding: the study was supported by the Wellcome Trust, the Medical Research Council, and National Health Service R&D support funding. Some authors were members of the National Institute for Health Research (NIHR) School for Primary Care Research. The General Practice and Primary Care Research Unit is supported by NIHR research funds. SJG receives support from the Department of Health NIHR Programme Grant funding scheme (RP‐PG‐0606‐1259). Publication status: peer‐reviewed journal |
|
| Stated aim of study | Quote: "To evaluate the effectiveness and cost effectiveness of (i) a stepwise screening strategy for type 2 diabetes; and (ii) intensive multifactorial treatment for people with screen‐detected diabetes in primary care" | |
| Notes | ||
| Risk of bias | ||
| Bias | Authors' judgement | Support for judgement |
| Random sequence generation (selection bias) | Unclear risk |
Quote: "Randomisation was undertaken by a statistician using the method of minimisation. In the first stage of randomisation, 33 recruited practices were allocated (1:3:3) to one of three groups: no screening (control; five practices), screening followed by intensive treatment of patients with screen‐detected diabetes (IT; 15 practices), and screening plus routine care of patients with screen‐detected diabetes (RC; 13 practices). These practices are included in the main trial analysis of screening versus control presented here. One of the 28 screening practices dropped out before screening commenced because of logistical difficulties with identification of people at high risk. The need to achieve the required sample size of patients with screen‐detected diabetes for the treatment trial warranted the uneven randomisation ratio with a disproportionate number of screening practices and a second stage of randomisation. 27 practices were subsequently randomly assigned (1:1) to IT (n=14) and RC (n=13). The final group allocation after the two stages of randomisation included 28 practices to IT, 27 to RC, and five to control (no screening). A further six randomised practices (two IT and four RC) dropped out after recruitment, but before screening commenced because of other commitments or unforeseen difficulties in setting up the practice‐based screening programme. Results from all practices included in the final group allocation are also presented in a parallel cohort analysis. This design has the advantage of increasing the sample size for the comparison of screened versus control practices, but increases the possibility of confounding and selection bias" Comment: randomisation was done centrally; however, it is unknown how and which participants were chosen in the practices to participate in the screening or no‐screening intervention |
| Allocation concealment (selection bias) | Unclear risk | Comment: randomisation was done centrally; however, it is unknown how and which participants were chosen in the practices to participate in the screening or no‐screening intervention |
| Blinding of participants and personnel (performance bias) all‐cause mortality | Low risk | Comment: lack of blinding unlikely to have influenced this outcome |
| Blinding of participants and personnel (performance bias) diabetes‐related mortality | Low risk | Comment: lack of blinding unlikely to have influenced this outcome |
| Blinding of participants and personnel (performance bias) diabetes‐related morbidity | High risk |
Quote: "The questionnaire elicited patients’ experience of cardiovascular disease events" Comment: lack of blinding likely to have influenced this outcome |
| Blinding of participants and personnel (performance bias) health‐related quality of life | High risk | Comment: lack of blinding likely to have influenced this outcome |
| Blinding of outcome assessment (detection bias) all‐cause mortality | Low risk |
Quote: "All eligible participants were flagged for mortality surveillance by the England and Wales Office of National Statistics, with unique NHS patient numbers. This classification was independently done by an assessor masked to randomisation group status. 50% of the deaths were classified by a second assessor with 98% agreement. Consensus was reached by discussion." Quote: "The investigators assessing outcomes and analysing data were masked to group assignment" |
| Blinding of outcome assessment (detection bias) diabetes‐related mortality | Low risk |
Quote: "All eligible participants were flagged for mortality surveillance by the England and Wales Office of National Statistics, with unique NHS patient numbers. This classification was independently done by an assessor masked to randomisation group status. 50% of the deaths were classified by a second assessor with 98% agreement. Consensus was reached by discussion." Quote: "The investigators assessing outcomes and analysing data were masked to group assignment" |
| Blinding of outcome assessment (detection bias) diabetes‐related morbidity | High risk |
Quote: "The questionnaire elicited patients’ experience of cardiovascular disease events" Comment: outcomes of heart attack and stroke are self‐reported without clinical confirmation |
| Blinding of outcome assessment (detection bias) health‐related quality of life | High risk | Comment: lack of blinding likely to have influenced this outcome |
| Incomplete outcome data (attrition bias) all‐cause mortality | Low risk | Comment: all eligible participants were flagged for mortality surveillance by the England and Wales Office of National Statistics, with unique NHS patient numbers, and there was only 1% loss to follow‐up. No clusters were lost during the study. |
| Incomplete outcome data (attrition bias) diabetes‐related mortality | Low risk | Comment: all eligible participants were flagged for mortality surveillance by the England and Wales Office of National Statistics, with unique NHS patient numbers, and there was only 1% loss to follow‐up. No clusters were lost during the study. |
| Incomplete outcome data (attrition bias) diabetes‐related morbidity | High risk | Quote: "The response rate was 62% in the screening group and 53% in the control group."; "Responders to the questionnaire were more likely to be older, to be female, to have been prescribed antihypertensive medication to have a low body mass index (BMI), and to have exhibited a higher risk of undiagnosed diabetes at baseline than non‐responder" |
| Incomplete outcome data (attrition bias) health‐related quality of life | High risk | Quote: "The response rate was 62% in the screening group and 53% in the control group."; "Responders to the questionnaire were more likely to be older, to be female, to have been prescribed antihypertensive medication to have a low body mass index (BMI), and to have exhibited a higher risk of undiagnosed diabetes at baseline than non‐responder" |
| Selective reporting (reporting bias) | Low risk | Comment: all outcomes and methods described as prespecified in the protocol |
| Other bias | Low risk | Cluster RCT (recruitment bias): low; study accounted for clustering of practices. Randomisation was done at the practice and not at the level of the individual. Individuals already belonged to specific practices. Cluster RCT (baseline imbalance): low; there were no differences at the cluster and individual levels to clinically impact on outcomes. Cluster RCT (loss of clusters): low; no clusters were lost during the study. Cluster RCT (incorrect analysis): study accounted for clustering of practices in the analysis. |
HbA1c: glycosylated haemoglobin A1c; OGTT: oral glucose tolerance test; RCT: randomised controlled trial.
Note: where the judgement is 'unclear' and the description is blank, the study did not report that particular outcome.
Characteristics of excluded studies [ordered by study ID]
| Study | Reason for exclusion |
|---|---|
| Acosta 2018 | Intervention not eligible: presents baseline characteristics of a lifestyle project for diabetes prevention (DEMOJUAN project) |
| ACTRN12611000518965 | Intervention not eligible ‐ study of intervention to improve screening and management of type 2 diabetes by Aboriginal Community Control Health Organisations (ACCHOs) |
| ACTRN12616001240437 | Study design not eligible ‐ comparison of different screening tools rather than screening vs no screening |
| ADDITION‐Leicester 2015 | Intervention not eligible |
| Black 2014 | Study design not eligible ‐ study of a subset of participants of a randomised trial with complete data at follow‐up |
| Black 2015 | Study design ineligible ‐ prospective cohort study |
| Charles 2011 ADDITION | Intervention not eligible ‐ study of treating patients with screen‐detected diabetes on neuropathy and peripheral arterial disease |
| Charles 2013 ADDITION | Intervention not eligible ‐ study of treating patients with screen‐detected diabetes on cardiac autonomic neuropathy |
| Charles 2017 ADDITION | Intervention not eligible ‐ study of training of general practitioners in intensive treatment of people with screen‐detected diabetes |
| ChiCTR1800015274 | Ineligible study population ‐ pregnant women |
| ChiCTR1800017260 | Ineligible study design ‐ cohort study |
| CTRI/2016/09/007323 | Ineligible study design ‐ cohort study |
| CTRI/2017/10/010199 | Ineligible participants ‐ patients with tuberculosis |
| CTRI/2018/08/015536 | Ineligible study design ‐ cross‐sectional study |
| CTRI/2018/08/015568 | Ineligible study population ‐ individuals with diabetes |
| CTRI/2018/12/016532 | Ineligible study design ‐ uncontrolled cohort study |
| Dalsgaard 2010 ADDITION Denmark | Ineligible intervention ‐ costs associated with different screening approaches |
| Dalsgaard 2014 ADDITION | Intervention not eligible ‐ study of intensive treatment vs routine care in patients with screen‐detected diabetes |
| den Ouden 2015 ADDITION | Ineligible intervention ‐ study of intensive treatment in patients with screen‐detected diabetes |
| DRKS00009837 | Ineligible study design ‐ uncontrolled study |
| Dunkley 2017 | Ineligible study design ‐ cohort study |
| Eborall 2007 ADDITION | Study design not eligible ‐ comparative study embedded in an RCT |
| Griffin 2011 ADDITION | Intervention not eligible ‐ study of intensive treatment vs routine care in patients with screen‐detected diabetes |
| Harris 2003 | Ineligible study design ‐ systematic review |
| Hellgren 2015 | Ineligible study design ‐ prospective epidemiological study |
| Herman 2015 | Study design not eligible ‐ not an RCT |
| ISRCTN21333761 | Ineligible intervention ‐ study about personalised clinical visits |
| ISRCTN57962668 | Ineligible study design ‐ cross‐sectional study |
| Johansen 2012 ADDITION | Intervention not eligible ‐ study of intensive treatment vs routine care in patients with screen‐detected diabetes |
| Juul 2009 ADDITION | Intervention not eligible ‐ study of adherence to treatment guidelines for patients with screen‐detected diabetes |
| Kenealy 2007 | Study design not eligible ‐ not an RCT |
| Kolaczynski 2000 | Study design not eligible ‐ not an RCT |
| Kullgren 2017 | Ineligible patient population |
| Kumar 2015 | Ineligible intervention ‐ study about mobile reminders for people to come in for additional tests |
| Kuznetsov 2015 ADDITION | Intervention not eligible ‐ study comparing perceptions of care amongst those with screen‐detected diabetes in intensive treatment vs routine care |
| Lau 2016 | Ineligible study design ‐ the population with diabetes was discarded at the beginning of the study, thus removing the randomised aspect of the study |
| Lauritzen 2000 ADDITION | Intervention not eligible ‐ study of cost‐effectiveness of intensive multifactorial intervention for people with screen‐detected diabetes |
| Lauritzen 2011 ADDITION | Study design not eligible ‐ cohort analysis embedded in an RCT |
| Law 2018 | Ineligible intervention ‐ all participants were screened, and study assessed immediate vs delayed feedback on screening |
| Maindal 2013 ADDITION | Intervention not eligible ‐ study of health education vs control in patients with screen‐detected diabetes |
| Monti 2012 | Study design not eligible ‐ not an RCT |
| NCT00007696 | Study design not eligible ‐ not an RCT |
| NCT00042042 | Study design not eligible ‐ not an RCT |
| NCT00253240 | Study design not eligible ‐ not an RCT |
| NCT00377117 | Study design not eligible ‐ not an RCT |
| NCT01591525 | Study design not eligible ‐ not an RCT |
| NCT02223793 | Intervention not eligible ‐ study of behavioural intervention after cardiovascular risk screening, not of screening vs no screening |
| NCT02418637 | Study design not eligible ‐ not an RCT |
| NCT02513277 | Study design not eligible ‐ not an RCT |
| NCT02750527 | Study design not eligible ‐ not an RCT |
| NCT03254979 | Patient population not eligible ‐ includes patients with diabetes |
| NCT03395509 | Study design not eligible ‐ not an RCT |
| Park 2008 | Intervention not eligible ‐ follow‐up shorter than 3 months |
| Raikou 2003 | Study design not eligible ‐ not an RCT |
| Rasmussen 2016 | Study design not eligible ‐ not an RCT |
| Reid 1974 | Study design not eligible ‐ not an RCT |
| Rubak 2009 ADDITION | Intervention not eligible ‐ study of training general practitioners in motivational interviewing for people with type 2 diabetes |
| Scherstén 1966 | Ineligible study design ‐ no control group |
| Simmons 2011 | Study design not eligible ‐ not an RCT |
| Simmons 2012b ADDITION | Intervention not eligible ‐ study of intensive multifactorial treatment in people with screen‐detected diabetes |
| Simmons 2014 ADDITION | Intervention not eligible ‐ study of intensive treatment vs routine care in patients with screen‐detected diabetes |
| Simmons 2017 ADDITION | Intervention not eligible ‐ study of training of general practitioners in intensive treatment of people with screen‐detected diabetes |
| Simmons 2017a_ADDITION Denmark | Study design not eligible ‐ not a randomised trial |
| Simmons 2017b_ADDITION Denmark | Study design not eligible ‐ not a randomised trial |
| Skaaby 2018 | Ineligible intervention ‐ no screening for diabetes carried out with the health checks |
| Sortso 2018 | Study design not eligible ‐ not a randomised trial |
| Spijkerman 2003 | Study design not eligible ‐ not an RCT |
| Su 2017 | Ineligible patient population |
| van den Donk 2013 ADDITION | Intervention not eligible ‐ study of intensive treatment vs routine care in patients with screen‐detected diabetes |
| Villarivera 2012 | Study design not eligible ‐ not an RCT |
| Von Karla 2007 | Study design not eligible ‐ not an RCT |
RCT: randomised controlled trial.
Characteristics of studies awaiting classification [ordered by study ID]
Klijs 2012.
| Methods | Type of study: parallel RCT |
| Participants |
Inclusion criteria: inhabitants of 2 Dutch municipalities, males and females aged 40 to 74, absence of pre‐existing diabetes, indication of abdominal obesity, individuals in the control and screening groups were eligible for the current study if they had completed the questions pertaining to general health, smoking behaviour, and symptom risk for diabetes in the 2006 questionnaire and had a negative screening test result in 2006 if in the screening group. The age‐ and sex‐matched control group had no screening test. Exclusion criteria: a diagnosis of diabetes or IFG Diagnostic criteria: fasting plasma glucose (FPG) level ≥ 7.0 mmol/L diagnosed diabetes, and FPG level of 6.1 to 6.9 mmol/L diagnosed IFG. |
| Interventions | A negative screening test for diabetes |
| Outcomes | BMI, waist circumference, diabetes risk perception, personal control, worry, optimistic bias |
| Reason for awaiting classification | Klijs 2012 is a protocol. The study is complete according to the record in the trials registry, but there are no published reports. We contacted the author for information regarding the study's findings but as of yet have received no reply. |
| Stated aim of study | Aim not reported. Study hypothesis: "Systematic screening for type 2 diabetes in high‐risk obese subjects, identified from the general population, can significantly reduce the diabetes‐related cardiovascular morbidity and mortality by at least 25% compared with not offering a screening program." |
| Study details |
Language of publication: English Funding: ZonMW (Zorgonderzoek Nederland ‐ Medische Wetenschappen) Publication status: peer‐reviewed journal Trial identifier:ISRCTN75983009 |
| Notes | Willems 2014 is a substudy of Klijs 2012; it includes some of the population in the main RCT but does not assess a relevant comparison for this review and therefore has not been included. |
— denotes not reported
ADDITION: Anglo‐Danish‐Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care; BMI: body mass index; FPG: fasting plasma glucose; IFG: impaired fasting glucose; RCT: randomised controlled trial.
Differences between protocol and review
The ADDITION‐Cambridge study also reported on cardiovascular and cancer mortality. Although these outcomes were not prespecified in our protocol, we have reported on both outcomes in the review.
Contributions of authors
All review authors read and approved the final review draft.
Nasheeta Peer (NP): design and write‐up of updated protocol, acquisition of study reports, study selection, data extraction, data analysis, data interpretation, review of drafts and future review updates.
Yusentha Balakrishna (YB): study selection, data extraction, data analysis, data interpretation, review of drafts and future review updates.
Solange Durao (SD): design and write‐up of updated protocol, protocol draft, acquisition of study reports, study selection, data extraction, data analysis, data interpretation, review of drafts and future review updates.
Sources of support
Internal sources
South African Medical Research Council, South Africa
External sources
-
NP was supported by a fellowship offered by Cochrane South Africa, South African Medical Research Council, funded by the Effective Health Care Research Consortium. This Consortium is funded by UK aid from the UK Government for the benefit of developing countries. The views expressed in this publication do not necessarily reflect UK government policy., South Africa
Grant Number 5242
-
SD was partly supported by the Research, Evidence and Development Initiative (READ‐It) project. READ‐It is funded by UK aid from the UK Government. The views expressed in this publication do not necessarily reflect UK Governments official policies., South Africa
Project number 300342‐104
Declarations of interest
NP: none known.
YB: none known.
SD: none known.
Edited (no change to conclusions)
References
References to studies included in this review
Simmons 2012 {published data only}
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ChiCTR1800017260 {published data only}
- ChiCTR1800017260. Screening for people at risk for type 2 diabetes. apps.who.int/trialsearch/Trial2.aspx?TrialID=ChiCTR1800017260 (first received 6 July 2018).
CTRI/2016/09/007323 {published data only}
- CTRI/2016/09/007323. Screening and prevention of non communicable diseases (NCDs) through schools and community based approach. www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=12512&EncHid=&modid=&compid=%27,%2712512det%27 (first received 29 September 2016).
CTRI/2017/10/010199 {unpublished data only}
- CTRI/2017/10/010199. Diabetes and tuberculosis - integrated management using the primary healthcare infrastructure in India [Integrated chronic disease management using the primary healthcare infrastructure in India – a feasibility]. ctri.nic.in/Clinicaltrials/pmaindet2.php?trialid=15771&EncHid=&userName=CTRI/2017/10/010199 (first received 25 October 2017).
CTRI/2018/08/015536 {published data only}
- CTRI/2018/08/015536. Global health research for cardiovascular disease and diabetes. ctri.nic.in/Clinicaltrials/pmaindet2.php?trialid=28022&EncHid=&userName=CTRI/2018/08/015536 (first received 30 August 2018).
CTRI/2018/08/015568 {published data only}
- CTRI/2018/08/015568. Research to practice an ideal screening model for complication of diabetes in India. ctri.nic.in/Clinicaltrials/pmaindet2.php?trialid=27990&EncHid=&userName=CTRI/2018/08/015568 (first received 31 August 2018).
CTRI/2018/12/016532 {unpublished data only}
- CTRI/2018/12/016532. e health initiatives for health. ctri.nic.in/Clinicaltrials/pmaindet2.php?trialid=27309&EncHid=&userName=CTRI/2018/12/016532 (first received 5 December 2018).
Dalsgaard 2010 ADDITION Denmark {published data only}
- Dalsgaard EM, Christensen JO, Skriver MV, Borch-Johnsen K, Lauritzen T, Sandbaek A. Comparison of different stepwise screening strategies for type 2 diabetes: finding from Danish general practice, Addition-DK. Primary Care Diabetes 2010;4(4):223-9. [PMID: ] [DOI] [PubMed] [Google Scholar]
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Dunkley 2017 {published data only}
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- ISRCTN57962668. Multi-centre risk-based screening for diabetes and its complications. www.isrctn.com/ISRCTN57962668 (first received 18 August 2018).
Johansen 2012 ADDITION {published data only}
- Johansen NB, Charles M, Vistisen D, Rasmussen SS, Wiinberg N, Borch-Johnsen K, et al. Effect of intensive multifactorial treatment compared with routine care on aortic stiffness and central blood pressure among individuals with screen-detected type 2 diabetes: the ADDITION-Denmark study. Diabetes Care 2012;35(11):2207-14. [PMID: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
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Kumar 2015 {published data only}
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NCT00007696 {published data only}
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NCT00042042 {published data only}
- NCT00042042. Screening adolescents for type 2 diabetes mellitus in a community clinic. clinicaltrials.gov/ct2/show/NCT00042042 (first received 23 July 2002).
NCT00253240 {published data only}
- NCT00253240. Diabetes screening, risk management and disease management in a high-risk mental health population. clinicaltrials.gov/show/NCT00253240 (first received 15 November 2005).
NCT00377117 {published data only}
- NCT00377117. Diabetes screening, risk management and disease management in a high-risk mental health population part II. clinicaltrials.gov/ct2/show/NCT00377117 (first received 15 September 2006).
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