Weight loss intervention through lifestyle modification or pharmacotherapy for obstructive sleep apnoea in adults

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the effectiveness of lifestyle modification or pharmacotherapy for weight loss for obstructive sleep apnoea in adults with overweight or obesity.

Background

Description of the condition

Obstructive sleep apnoea (OSA) is defined by collapse of the upper airway during sleep, resulting in periodic reduction or cessation in ventilation that generates consequent hypoxia, hypercapnia, and arousal from sleep (Dempsey 2010) and provokes symptoms as snoring, unsatisfactory rest and daytime sleepiness. These stereotypical symptoms are more commonly observed in men, while more nonspecific symptoms (e.g. low energy or fatigue, tiredness, initial insomnia, morning headaches) are more frequent in women. The prevalence of this condition varies from 9% to 38% in adult samples across the world, constituting a significant public health concern (Senaratna 2017). In 2015, the cost of diagnosing and treating obstructive sleep apnoea in the USA was approximately USD 12.4 billion (Watson 2016). Recent estimates indicate that nearly one billion adults worldwide between 30 and 69 years of age have OSA, with 45% of these individuals having a moderate to severe disorder requiring treatment (Benjafield 2019).

Untreated OSA is associated with a wide range of adverse health consequences. OSA increases the risk of occupational accidents and motor vehicle crashes (Gottlieb 2018), cognitive dysfunction (Biyukov 2018), and anxiety and depression (Garbarino 2018). In addition, the intermittent hypoxaemia (partial pressure of oxygen (PaO₂) < 60 mmHg) and hypercapnia (i.e. partial pressure of carbon dioxide (PaCO₂) > 45 mmHg), fragmented sleep, and fluctuations in heart rhythm and blood pressure that occur with OSA can lead to long‐term sequelae such as cardiovascular disorders (Yoshihisa 2019) metabolic dysfunction (Qian 2016), cognitive deterioration (Yaffe 2011), and premature death (Young 2008). The evidence supports a causal association of OSA with increased incidence of hypertension, type 2 diabetes, coronary heart disease, arrhythmia, heart failure, and stroke (Javaheri 2017; Reutrakul 2017).

The primary risk factors for OSA include conditions that reduce the size of the pharynx or increase airway collapsibility during rest (Veasey 2019). The most important risk factor is excess weight. It is estimated that over 50% of all adults who are obese have OSA (Resta 2001). With the increasing prevalence of obesity worldwide, the prevalence of OSA is rising at an alarming rate (Senaratna 2017), and it is estimated that 58% of moderate‐to‐severe OSA is attributable to excess weight (Young 2005). Male sex is another important risk factor; however, the reason for this is unclear. In premenopausal women, progesterone acts to stimulate upper airway muscles and ventilation, which could contribute to the lower prevalence of OSA (Lin 2017). Further, androgen levels in men may contribute to increased muscle mass in the tongue, and this may lead to worsening of OSA (Liu 2003).

Polysomnography (PSG) is the gold standard method to diagnose OSA (Kushida 2006). Through objective assessment of sleep and breathing parameters, PSG provides an apnoea‐hypopnoea index (AHI) that represents the number of apneas and hypopnoeas per hour of sleep. AHI thresholds are commonly used to categorise the severity of OSA: an AHI that is 5 to less than 15 is defined as mild, 15 to more than 30 is considered moderate, and 30 or higher is severe (Epstein 2009).

The gold standard treatment for moderate‐to‐severe OSA is the use of continuous positive airway pressure (CPAP), which is applied with a tight seal to the nose, mouth, or both, and serves to pneumatically stent the upper airway open (Veasey 2019). CPAP applies constant pressure throughout the respiratory cycle, preventing apnoea events by keeping the airways open (Patil 2019). Several studies have demonstrated the benefits of CPAP, including improved cardiovascular function (Aslan 2018), decreased sleepiness (Weaver 2007), and improved work quality (Botokeky 2019).

Description of the intervention

Therapies for OSA have been designed to reduce the frequency of sleep‐disordered breathing events. The most effective therapy to reduce OSA is the use of CPAP (Veasey 2019), with oral appliances recommended for those who cannot tolerate CPAP (Ramar 2015). In recent years, coadjuvant treatments that aim to support weight loss, including dietary modification (Thomasouli 2013), physical exercise (Desplan 2014; Torres‐Castro 2019), and pharmacotherapy (Gadde 2017), have been proposed to lower AHI among people with OSA. Current guidelines for the management of OSA identify weight loss as an important adjunctive therapeutic tool (Qaseem 2013; Hudgel 2018). Weight loss is related to significant reductions in AHI and improvements in OSA symptoms (Mitchell 2014). Similarly, regular physical activity is associated with decreased OSA prevalence, lower AHI values, improved sleep, and less daytime sleepiness (Iftikhar 2014; Mendelson 2018).

Pharmacotherapy for weight loss has also been proposed as an alternative treatment option in people with mild‐to‐moderate sleep apnoea, and could be of value in those intolerant of CPAP (Gaisl 2019). In many cases it is used in combination with dietary modification in people with BMI more than 30 kg/m² or overweight people with comorbidities (Gaisl 2019). More than 40 different drugs or combinations of drugs have been studied to assess their effects on AHI (Gaisl 2019), of these, at least five act directly as drugs for weight loss.

Despite the plethora of potential drug targets in this field (Horner 2017), there are currently no approved drugs to reduce OSA severity.

How the intervention might work

Excess weight is the most prominent risk factor for the occurrence of OSA (Romero‐Corral 2019). The most common cause of upper airway narrowing is obesity, with the most important factor being deposition of adipose tissue in the neck. This creates a mass load on the airway, causing it to collapse when dilator muscle tone is reduced during sleep (Kim 2014).

Obesity and OSA interact in a bidirectional manner. The impact of weight gain on the development and worsening of OSA is well established (Peppard 2009; Hudgel 2018). On the other hand, OSA predisposes to weight gain (Shechter 2017). Moreover, obesity is an aggravating factor for many metabolic and cardiovascular comorbidities common to OSA (Rimm 1995; Hudgel 2018).

Dietary‐induced weight loss (e.g. very low calorie diet), results in significant reductions in AHI and improvements in OSA symptoms (Carneiro‐Barrera 2019). Weight loss of more than 10 kg can resolve OSA in more than 50% of people with mild disease, and this magnitude of weight loss significantly improves cardiometabolic health (Hudgel 2018). There are several mechanisms that may underlie these improvements (Kim 2018), including reduced fat deposition in the anatomical structures surrounding the airway and tongue (Wang 2020) and reduced mechanical loading on the chest (Schwartz 2008).

Additionally, physical exercise (e.g. aerobic and/or resistance exercise) may cause significant reductions in abdominal adiposity that is independent of overall weight loss (Irwin 2003). This mechanism is mediated by the liberation of catecholamines (Martin 1996), which have greater lipolytic action in visceral fat than they do in subcutaneous fat (Richelsen 1991). On the other hand, in addition to its effects on lowering AHI, exercise also has beneficial effects on comorbidities associated with sleep apnoea (e.g. blood pressure) (Pedersen 2015).

The proposed mechanisms by which pharmacotherapy could reduce the severity of OSA include a reduction in appetite or modulation of fat digestion (Gaisl 2019). There are various mechanisms of action through which drugs may work. Orlistat is a weight loss drug that inhibits pancreatic lipase and modifies the absorption of fat. Lorcaserin is a selective serotonin receptor agonist at the 2C site, which suppresses appetite. Phentermine suppresses appetite by activating the sympathetic nervous system. The combination of phentermine/topiramate has been well investigated for the treatment of obesity, and it received FDA approval in 2012. Topiramate has several pharmacological actions, but it is not precisely known which mechanism of topiramate contributes to its effects on weight (Gadde 2017). Other drugs, like sibutramine, a serotonin and norepinephrine uptake inhibitor, have demonstrated effects on weight loss but also showed a slightly increased risk of adverse cardiovascular effects (Krentz 2016; Gadde 2017).

Why it is important to do this review

From a public health perspective, OSA is a significant issue that generates a large burden on individuals and healthcare systems by increasing the risk of premature death, hypertension, heart disease, stroke, pulmonary hypertension, and traffic accidents (Veasey 2019). Further, OSA has a substantial economic impact, resulting from the occurrence of cardiovascular events and metabolic disease. People with OSA have higher rates of hospital admission and medical service use (Banno 2009).

The gold standard treatment for OSA is CPAP. When used properly, CPAP significantly reduces AHI. However, low adherence to CPAP reduces the benefits obtained by people receiving this therapy. It is estimated that 29% to 83% of people prescribed CPAP use their CPAP machines for less than four hours per night (Weaver 2008). Consistent CPAP use is essential to realise its benefits (e.g. decreased cardiovascular morbidity).

Although the literature has shown beneficial effects of diet, exercise, and pharmacotherapy in people with OSA, it is necessary to establish the magnitude of the improvement based on randomised clinical trials, especially considering that it may be an option for those people who do not have adequate CPAP adherence.

As a result, there remains a need to establish the effectiveness of these therapies that are based on lifestyle modifications.

Objectives

To assess the effectiveness of lifestyle modification or pharmacotherapy for weight loss for obstructive sleep apnoea in adults with overweight or obesity.

Methods

Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials (RCTs), including those that adopt a cluster design. We will include studies reported in full text, those published as an abstract only, and unpublished data.

Types of participants

We will include adults with a diagnosis of obstructive sleep apnoea (OSA). We will consider the American Academy of Sleep Medicine (AASM) diagnostic criteria to be the gold standard for comparison purposes (Epstein 2009). We will include studies in which the participants have a mean of BMI of 25 or more, indicating overweight or obesity.

We will exclude participants who have received surgical weight loss interventions (e.g. gastric banding) prior to the study.

Types of interventions

We will include studies comparing weight loss interventions through lifestyle modification (diet, exercise or both combined) or pharmacotherapy with no weight loss intervention or placebo, or a combination of some or all of these.

We will only include studies lasting more than four weeks.

We will make the following comparisons:

1. CPAP naïve

   1. Weight loss by 'lifestyle' (diet or exercise, or both) versus no weight loss intervention

   2. Weight loss by 'lifestyle' plus pharmacotherapy versus no weight loss intervention and placebo

   3. Weight loss by pharmacotherapy versus placebo

1. People established on CPAP (for at least four weeks of use)

   1. Weight loss by 'lifestyle' (diet or exercise, or both) versus no weight loss intervention

   2. Weight loss by 'lifestyle' plus pharmacotherapy versus no weight loss intervention and placebo

   3. Weight loss by pharmacotherapy versus placebo

If we find types of intervention that can be grouped, we will perform this analysis (e.g. types of exercise, types of diets, or family of drugs)

Types of outcome measures

Primary outcomes

1. Apnoea/hypopnoea index (AHI)

2. Quality of life (e.g. Quebec Sleep Questionnaire (Lacasse 2004), Short‐form 36 health survey (McHorney 1993))

3. Adverse events

Secondary outcomes

1. Respiratory disturbance index (RDI);

2. Oxygen desaturation index (ODI);

3. Epworth Sleepiness Scale (ESS) (Johns 1991);

4. Body weight (kg);

5. Waist circumference (cm);

6. Body mass index (BMI; kg/m²);

7. Long‐term regain of weight (i.e. at least one year);

8. Cure of OSA (defined as AHI < 5)

9. Morbidity (e.g. traffic accidents and cardiovascular disease)

Reporting one or more of the secondary outcomes listed here in the study is not an inclusion criterion for the review.

Search methods for identification of studies

Electronic searches

We will identify studies from searches of the following databases and trials registries:

1. Cochrane Airways Trials Register (Cochrane Airways 2019), via the Cochrane Register of Studies, all years to date;

2. Cochrane Central Register of Controlled Trials (CENTRAL), via the Cochrane Register of Studies, all years to date;

3. MEDLINE Ovid SP 1946 to date;

4. Embase Ovid SP 1974 to date;

5. US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov);

6. World Health Organization International Clinical Trials Registry Platform (apps.who.int/trialsearch).

The proposed search strategy for CENTRAL is listed in Appendix 1. This will be adapted for use in the other databases and combined with study design search filters as appropriate. The Cochrane Airways Information Specialist developed this search strategy in collaboration with the review authors.

We will search all databases and trials registries from their inception to the present, and there will be no restriction on language or type of publication. We will identify handsearched conference abstracts and grey literature through the Cochrane Airways Trials Register and the CENTRAL database.

Searching other resources

We will check the reference lists of all primary studies and review articles for additional references. We will search relevant manufacturers' websites for study information.

We will search on PubMed for errata or retractions from included studies and report the date this was done within the review.

Data collection and analysis

Selection of studies

Three review authors (RTC, MOY, VR) will screen the titles and abstracts of the search results independently and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. We will retrieve the full‐text study reports of all potentially eligible studies and two review authors (RTC, VR) will independently screen them for inclusion, recording the reasons for exclusion of ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third review author (GF). We will identify and exclude duplicates and collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table (Moher 2009).

Data extraction and management

We will use a data collection form for study characteristics and outcome data, which has been piloted on at least one study in the review. Two review authors (RTC, MOY) will extract the following study characteristics from included studies.

1. Methods: study design, total duration of study, details of any 'run‐in' period, number of study centres and location, study setting, withdrawals and date of study

2. Participants: number, mean age, age range, gender, severity of condition, diagnostic criteria, baseline lung function, smoking history, inclusion criteria and exclusion criteria

3. Interventions: intervention, comparison group(s), concomitant medications and excluded medications

4. Outcomes: primary and secondary outcomes specified and collected, and time points reported

5. Notes: funding for studies and notable conflicts of interest of study authors

Two review authors (RTC, MOY) will independently extract outcome data from included studies. We will note in the 'Characteristics of included studies' table if outcome data were not reported in a usable way. We will resolve disagreements by consensus or by involving a third review author (JV). One review author (RTC) will transfer data into the Review Manager 5 file (Review Manager 2014). We will double‐check that data are entered correctly by comparing the data presented in the systematic review with the study reports. A second review author (MRF) will spot‐check study characteristics for accuracy against the study report.

Assessment of risk of bias in included studies

Two review authors (RTC, MOY) will assess risk of bias independently for each study using the criteria outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2017). We will resolve any disagreements by discussion or by involving another review author (GF). We will assess the risk of bias according to the following domains:

1. random sequence generation;

2. allocation concealment;

3. blinding of participants and personnel;

4. blinding of outcome assessment;

5. incomplete outcome data;

6. selective outcome reporting;

7. other bias.

We will judge each potential source of bias as high, low or unclear and provide a quote from the study report together with a justification for our judgement in the 'Risk of bias' table. We will summarise the risk of bias judgements across different studies for each of the domains listed. We will consider blinding separately for different key outcomes where necessary (e.g. for unblinded outcome assessment, risk of bias for all‐cause mortality may be very different than for a patient‐reported pain scale). Where information on risk of bias relates to unpublished data or correspondence with a study author, we will note this in the 'Risk of bias' table.

When considering treatment effects, we will take into account the risk of bias for the studies that contributed to that outcome.

Assessment of bias in conducting the systematic review

We will conduct the review according to this published protocol and justify any deviations from it in the 'Differences between protocol and review' section of the systematic review.

Measures of treatment effect

We will analyse dichotomous data as odds ratios (OR) and continuous data as the mean difference (MD) or standardised mean difference (SMD). If data from rating scales are combined in a meta‐analysis, we will ensure they are entered with a consistent direction of effect (e.g. lower scores always indicate improvement).

We will undertake meta‐analyses only where this is meaningful; that is, if the treatments, participants and the underlying clinical question are similar enough for pooling to make sense.

We will describe skewed data narratively (e.g. as medians and interquartile ranges for each group).

Where multiple study arms are reported in a single study, we will include only the relevant arms. If we combine two comparisons from the same study (e.g. intervention A versus no intervention and intervention B versus no intervention) in the same meta‐analysis, we will either combine the active arms or halve the control group to avoid double‐counting.

If adjusted analyses are available (e.g. ANOVA (analysis of variance) or ANCOVA (analysis of covariance)), we will use these as a preference in our meta‐analyses. If both change from baseline and endpoint scores are available for continuous data, we will use change from baseline unless there is low correlation between measurements in individuals. If a study reports outcomes at multiple time points, we will use all time points.

We will use intention‐to‐treat (ITT) or 'full analysis set' analyses where they are reported (i.e. those where data have been imputed for participants who were randomly assigned but did not complete the study) instead of completer or per protocol analyses.

Unit of analysis issues

For dichotomous outcomes, we will use participants, rather than events, as the unit of analysis. However, if rate ratios are reported in a study, we will analyse them on this basis. We will only meta‐analyse data from cluster‐RCTs if the available data have been adjusted (or can be adjusted), to account for the clustering.

Dealing with missing data

We will contact study authors or study sponsors in order to verify key study characteristics and obtain missing numerical outcome data where possible (e.g. when an identified study is available only as an abstract). Where this is not possible, and we think that the missing data would introduce serious bias, we will take this into consideration in the GRADE rating for affected outcomes.

Assessment of heterogeneity

We will use the I² statistic (Higgins 2003), to measure heterogeneity among the studies in each analysis. If we identify substantial heterogeneity we will report it and explore the possible causes by prespecified subgroup analysis. We will consider heterogeneity as substantial for values of I² statistic equal to or above 50% (Deeks 2019), although we recognise that uncertainty surrounds the I² statistic measurement when a meta‐analysis includes few studies. We will use a significance level of P < 0.1 to indicate whether we observe a problem with heterogeneity.

Assessment of reporting biases

If we are able to pool more than 10 studies, we will create and examine a funnel plot to explore possible small study and publication biases (Page 2019).

Data synthesis

We will use a random‐effects model and perform a sensitivity analysis with a fixed‐effect model.

Subgroup analysis and investigation of heterogeneity

We will present separately as subsections results by diet, exercise or pharmacotherapy.

We plan to carry out the following subgroup analyses.

1. Severity of OSA (mild, moderate, severe)

2. Different age groups (> 65 years of age versus < 65 years)

3. By gender (male versus female)

4. Duration of intervention (short term, up to three months; medium term, from three months to two years; and long term)

5. By BMI category (obese versus overweight)

We will use the following outcomes in subgroup analyses.

1. Apnoea/hypopnoea index (AHI)

2. Quality of life (e.g. Quebec Sleep Questionnaire (Lacasse 2004), Short‐form 36 health survey (McHorney 1993))

3. Epworth Sleepiness Scale (ESS) (Johns 1991)

4. Body weight (kg)

We will use the formal test for subgroup interactions in Review Manager 5 (Review Manager 2014).

Sensitivity analysis

We plan to carry out the following sensitivity analyses, removing the following from the primary outcome analyses:

1. removing studies at unclear or high risk of performance and detection bias, due to lack of appropriate blinding;

2. comparing the results from inclusion and exclusion of imputed data values.

We will compare the results from a fixed‐effect model with the random‐effects model.

Summary of findings and assessment of the certainty of the evidence

We will create a 'Summary of findings' table using the following outcomes AHI, quality of life, ESS, weight, waist circumference, BMI, respiratory disturbance index, and adverse events. We will use the five GRADE considerations (risk of bias, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies that contribute data for the prespecified outcomes. We will use the methods and recommendations described in chapter 14 (Schünemann 2019a), and chapter 15 (Schünemann 2019b), of the Cochrane Handbook for Systematic Reviews of Intervention, using GRADEpro software (GRADEpro GDT). We will justify all decisions to downgrade the quality of studies using footnotes and we will make comments to aid the reader's understanding of the review where necessary.

Appendices

Appendix 1. Database search strategy

Database: CENTRAL

Platform: Cochrane Register of Studies

	Search term	Results
#1	MeSH DESCRIPTOR Sleep Apnea, Obstructive	1143
#2	sleep near3 (apnoea* or apnoea*)	6318
#3	(hypopnea* or hypopnoea*)	2533
#4	(OSA OR SHS OR OSAHS:TI,AB)	3437
#5	(#1 OR #2 OR #3 OR #4)	7105
#6	(weight*) NEAR (loss* or lose or reduc*)	24133
#7	lifestyle* or life‐style*	19194
#8	physical* NEAR3 (activity* or train*)	30582
#9	exercise*	89883
#10	diet*	83954
#11	anti‐obesity near3 medicat*	35
#12	obesity* near3 medicat*	108
#13	medicat* near3 obes*	131
#14	sibutramine	392
#15	Reductil	6
#16	orlistat	515
#17	Xenical	35
#18	appetite* NEAR3 (depress* or suppress*)	941
#19	MeSH DESCRIPTOR Appetite Depressants	395
#20	MeSH DESCRIPTOR Anti‐Obesity Agents Explode All	1226
#21	MeSH DESCRIPTOR Weight Loss	4440
#22	MeSH DESCRIPTOR Weight Reduction Programs	18
#23	MeSH DESCRIPTOR Diet, Reducing	1895
#24	MESH DESCRIPTOR Exercise EXPLODE ALL	17928
#25	MESH DESCRIPTOR Life Style EXPLODE ALL	4220
#26	MESH DESCRIPTOR Health Behavior	3431
#27	MESH DESCRIPTOR Body Weight	7249
#28	#6 OR #7 OR #8 OR #9 OR #10 OR #11 OR #12 OR #13 OR #14 OR #15 OR #16 OR #17 OR #18 OR #19 OR #20 OR #21 OR #22 OR #23 OR #24 OR #25 OR #26 OR #27	193822
#29	#28 AND #5	943

Contributions of authors

R. Torres‐Castro: developed the protocol (lead); will develop and run the search strategy (along with Liz Stovold, Information Specialist), obtain copies of studies, select which studies to include, extract data from studies, enter data into Review Manager 5 (Review Manager 2014), carry out the analysis, interpret the analysis, draft the final review, update the review

M. Otto‐Yáñez: developed the protocol; will select which studies to include, extract data from studies, draft the final review, update the review

Marta Roqué I Fuguls: developed the protocol; will carry out the analysis, interpret the analysis, draft the final review, update the review

Vanessa Resqueti: developed the protocol; will select which studies to include, extract data from studies, carry out the analysis, interpret the analysis, draft the final review, update the review

Guilherme Fregonezi: developed the protocol; will carry out the analysis, interpret the analysis, draft the final review, update the review

Jordi Vilaró: developed the protocol; will draft the final review, update the review

Christopher Kline: edited the protocol; will interpret the analysis, draft the final review, update the review

Contributions of editorial team

Rebecca Fortescue (Co‐ordinating Editor): edited the protocol; advised on methodology.

Chris Cates (Co‐ordinating Editor) checked the planned methods; approved the protocol prior to publication.

John White (Contact Editor): edited the review; advised on content.

Emma Dennett (Managing Editor): co‐ordinated the editorial process; advised on content; edited the protocol.

Emma Jackson (Assistant Managing Editor): conducted peer review; edited the references

Elizabeth Stovold (Information Specialist): designed the search strategy; arranged for peer review of the search strategy.

Sources of support

Internal sources

• Comisión Nacional de Investigación Científica y Tecnología‐CONICYT, Chile.

  Rodrigo Torres‐Castro is a pre‐doctoral research fellow supported by Comisión Nacional de Investigación en Ciencia y Tecnología ‐ CONICYT

External sources

• The authors declare that no such funding was received for this systematic review, Other.

Declarations of interest

R Torres‐Castro: none known
 M Otto‐Yáñez: none known
 M Roqué I Fuguls: none known
 V Resqueti: none known
 G Fregonezi: none known
 J Vilaró: I received fees from Smiths Medical for giving a scientific conferences.
 C Kline: none known

New