Interventions for atypical haemolytic uraemic syndrome

Abstract

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

This review aims to evaluate the benefits and harms of interventions for aHUS.

Background

Description of the condition

Haemolytic uraemic syndrome (HUS) is a form of thrombotic microangiopathy (TMA) which affects adults and children and is characterised by thrombocytopenia, microangiopathic haemolytic anaemia and acute kidney injury (AKI) (Noris 2009). The term HUS encompasses several different disease processes which can be broadly divided into infection‐induced HUS, HUS secondary to a pre‐existing condition, or atypical HUS (aHUS) (Loirat 2016).

Around 90% of cases of HUS are considered infection‐induced and are most typically associated with either Shiga toxin‐producing Escherichia coli (STEC) or Streptococcus pneumoniae (Ariceta 2009). STEC‐associated cases are often (but not always) preceded by the onset of bloody diarrhoea (Besbas 2006). Pre‐existing conditions leading to the development of HUS include autoimmune diseases, stem cell or solid organ transplantation, and certain malignancies. This category of HUS can also be associated with certain drugs and with pregnancy (Fakhouri 2017).

The remainder of cases fall into the category of aHUS. Classically this term has been used to describe HUS associated with dysregulation of the alternative complement pathway due to either inherited or acquired dysfunction of complement regulatory proteins (Noris 2009). More recently the definition of aHUS has been broadened to include other rare forms of HUS including diacylglycerol kinase E (DGKE) and Cobalamin C (cblC) deficiency, as well as HUS with no clear precipitant (Loirat 2016).

The incidence of aHUS based on this broader classification is 0.23 to 0.42 cases/million population/year, with around 35% to 42% of cases occurring in children under the age of 18 (Fremeaux‐Bacchi 2013; Sheerin 2016).

Diagnosis is based on the presence of thrombocytopenia, microangiopathic haemolysis and kidney injury and the exclusion of other forms of HUS or thrombotic thrombocytopenic purpura (TTP). A genetic or acquired abnormality of complement regulation can be identified in around 50% of cases, however therapeutic interventions are often required before this information is available (Sheerin 2016).

Historically up to 25% of people die during the acute illness (Kaplan 2014). Of those surviving, 50% require acute renal replacement therapy (RRT) of whom a significant proportion never recover native kidney function and require long‐term RRT (Constantinescu 2004; Noris 2009).

Description of the intervention

Plasma exchange and plasma infusion have been the main treatments for aHUS since the early 1990s and work by replacing absent or removing abnormal complement proteins within the body. Although mortality decreased from 50% to 25% with plasma therapies a significant proportion of patients struggle to tolerate regular plasma therapy and relapse following discontinuation of treatment (Lara 1999; Noris 2005). Various other agents including corticosteroids, antiplatelet agents and thrombolytics have been studied with varying results. Liver transplantation has also been used as a treatment for aHUS in a small number of patients with known genetic complement factor deficiencies (Saland 2009). As certain complement factors such as factor H and factor I are produced in the liver successful transplantation, either alone or with combined kidney transplant, has the potential to cure aHUS in this subset of patients (Coppo 2016). However, this intervention is not without significant risk of morbidity and mortality and is not available in all centres (Remuzzi 2005).

Eculizumab, a humanised monoclonal antibody, targets complement component C5 in an attempt to halt the dysregulated activation of the complement pathway, reducing endothelial injury and subsequent organ dysfunction. Eculizumab is now recognised as the treatment of choice for nocturnal paroxysmal haemoglobinuria, a condition which also involves dysregulated terminal complement activation. Several studies have shown it to be effective for this indication with an acceptable safety profile (Hillmen 2013; Kanakura 2011). Eculizumab may therefore be superior to plasma therapy in the treatment of aHUS due to the ability to “switch off” abnormal complement activity.

Why it is important to do this review

A previous Cochrane Review has identified and evaluated interventions for HUS but this was not specific to aHUS (Michael 2009). Importantly, this review was conducted prior to the widespread use of eculizumab for the treatment of aHUS. We therefore think it important to carry out this review in order to identify and evaluate interventions for aHUS given the apparent recent advances in our understanding of disease pathogenesis and directed treatment.

Objectives

This review aims to evaluate the benefits and harms of interventions for aHUS.

Methods

Criteria for considering studies for this review

Types of studies

All randomised controlled trials (RCTs), quasi‐RCTs (RCTs in which allocation to treatment was obtained by alternation, use of alternate medical records, date of birth or other predictable methods) and non‐RCTs which compare an intervention with placebo, an intervention with supportive therapy, or two or more interventions for aHUS will be included. Given the rare nature of the condition in question and the clinical necessity for evidence to guide usage of eculizumab, single‐arm studies of eculizumab treatment in aHUS will also be included.

Types of participants

Inclusion criteria

Studies including patients of all ages with a confirmed diagnosis of aHUS. This diagnosis is defined as all three of:

• Evidence of kidney impairment (raised serum creatinine (SCr) or equivalent biomarker which meets local criteria for AKI)

• Evidence of thrombocytopenia (platelet count < 150 x 10⁹/L)

• Evidence of haemolysis (lactate dehydrogenase (LDH) above upper limit of normal, haptoglobin count below the lower limit of normal, evidence of fragmented red blood cells (RBC) in a peripheral blood smear, or presence of schistocytes)

Exclusion criteria

The following patient groups will be excluded:

• Patients with evidence of Shiga‐toxin producing bacterial infection

• Patients with evidence of Streptococcus pneumoniae infection

• Patients with evidence of ADAMTS‐13 deficiency (level at or below 10% in plasma)

• Patients with evidence of HUS as a consequence of a pre‐existing condition or disease including malignancy, haematopoetic stem cell transplantation, solid organ transplantation, infections, autoimmune conditions, malignant hypertension and drug‐induced HUS

• Patients with pregnancy‐associated HUS

Types of interventions

Any intervention for aHUS will be considered and may include eculizumab, plasma exchange, plasma infusion, anti‐platelet agents, thrombolytics, immunosuppressants, corticosteroids and liver transplantation.

Types of outcome measures

Primary outcomes

• All‐cause mortality

• Requirement for RRT

• Successful remission as defined independently by each study. This may involve normalisation or stabilisation of platelet count, resolution of haemolysis, or resolution of AKI.

Secondary outcomes

• Persistent elevation of creatinine and/or glomerular filtration rate (GFR) < 60 mL/min/1.73 m² (at time of last follow‐up)

• Persistent requirement for, and duration of, RRT

• Persistent requirement for plasma therapy

• Persistent proteinuria (as evidenced by urinalysis, urine protein:creatinine ratio, or 24 hour urine protein measurement)

• Persistent hypertension (as evidenced by the need for, and number of, antihypertensive agents)

• Renal biopsy changes

• Extra‐renal manifestations of disease

• Health‐related quality of life (HRQoL)

• Adverse events

• Meningococcal infection

Search methods for identification of studies

Electronic searches

We will search the Cochrane Kidney and Transplant Specialised Register through contact with the Information Specialist using search terms relevant to this review. The Specialised Register contains studies identified from the following sources.

1. Monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL)

2. Weekly searches of MEDLINE OVID SP

3. Handsearching of kidney‐related journals and the proceedings of major kidney conferences

4. Searching of the current year of EMBASE OVID SP

5. Weekly current awareness alerts for selected kidney and transplant journals

6. Searches of the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

Studies contained in the Specialised Register are identified through search strategies for CENTRAL, MEDLINE, and EMBASE based on the scope of Cochrane Kidney and Transplant. Details of these strategies, as well as a list of handsearched journals, conference proceedings and current awareness alerts, are available in the Specialised Register section of information about Cochrane Kidney and Transplant.

See Appendix 1 for search terms used in strategies for this review.

Searching other resources

1. Reference lists of review articles, relevant studies and clinical practice guidelines.

2. Letters seeking information about unpublished or incomplete studies to investigators known to be involved in previous studies.

Data collection and analysis

Selection of studies

The search strategy described will be used to obtain titles and abstracts of studies that may be relevant to the review. The titles and abstracts will be screened independently by two authors, who will discard studies that are not applicable; however studies and reviews that might include relevant data or information on studies will be retained initially. Two authors will independently assess retrieved abstracts and, if necessary the full text, of these studies to determine which studies satisfy the inclusion criteria.

Data extraction and management

Data extraction will be carried out independently by two authors using standard data extraction forms. Studies reported in non‐English language journals will be translated before assessment. Where more than one publication of one study exists, reports will be grouped together and the publication with the most complete data will be used in the analyses. Where relevant outcomes are only published in earlier versions these data will be used. Any discrepancy between published versions will be highlighted.

Assessment of risk of bias in included studies

The following items will be independently assessed by two authors using the risk of bias assessment tool (Higgins 2011) (see Appendix 2).

• Was there adequate sequence generation (selection bias)?

• Was allocation adequately concealed (selection bias)?

• Was knowledge of the allocated interventions adequately prevented during the study?

  • Participants and personnel (performance bias)

  • Outcome assessors (detection bias)

• Were incomplete outcome data adequately addressed (attrition bias)?

• Are reports of the study free of suggestion of selective outcome reporting (reporting bias)?

• Was the study apparently free of other problems that could put it at a risk of bias?

Measures of treatment effect

For dichotomous outcomes (e.g. death, requirement for RRT, successful remission) results will be expressed as risk ratio (RR) with 95% confidence intervals (CI). Where continuous scales of measurement are used to assess the effects of treatment (e.g. SCr, blood pressure, regularity of plasma therapy, degree of proteinuria), the mean difference (MD) will be used, or the standardised mean difference (SMD) if different scales have been used.

Dealing with missing data

Any further information required from the original author will be requested by written correspondence (e.g. emailing corresponding author) and any relevant information obtained in this manner will be included in the review. Evaluation of important numerical data such as screened, randomised patients as well as intention‐to‐treat, as‐treated and per‐protocol population will be carefully performed. Attrition rates, for example drop‐outs, losses to follow‐up and withdrawals will be investigated. Issues of missing data and imputation methods (for example, last‐observation‐carried‐forward) will be critically appraised (Higgins 2011).

Assessment of heterogeneity

We will first assess the heterogeneity by visual inspection of the forest plot. We will quantify statistical heterogeneity using the I² statistic, which describes the percentage of total variation across studies that is due to heterogeneity rather than sampling error (Higgins 2003). A guide to the interpretation of I² values will be as follows:

• 0% to 40%: might not be important;

• 
30% to 60%: may represent moderate heterogeneity;

• 
50% to 90%: may represent substantial heterogeneity;

• 
75% to 100%: considerable heterogeneity.

The importance of the observed value of I² depends on the magnitude and direction of treatment effects and the strength of evidence for heterogeneity (e.g. P‐value from the Chi² test, or a confidence interval for I²) (Higgins 2011).

Assessment of reporting biases

If possible, funnel plots will be used to assess for the potential existence of small study bias (Higgins 2011).

Data synthesis

Data will be pooled using the random‐effects model but the fixed‐effect model will also be used to ensure robustness of the model chosen and susceptibility to outliers.

Subgroup analysis and investigation of heterogeneity

Subgroup analysis will be used to explore possible sources of heterogeneity (e.g. participants or interventions). Heterogeneity among participants could be related to their age, whether they were being treated for a first presentation or relapse of aHUS, specific complement mutations identified, whether they required acute RRT, or whether or not they had developed aHUS after a kidney transplant. Heterogeneity in interventions could be related to the dosage and duration of therapies used, as well as co‐interventions and previous treatments. Adverse effects will be tabulated and assessed with descriptive techniques, as they are likely to be different for the various agents used. Where possible, the risk difference with 95% CI will be calculated for each adverse effect, either compared to no treatment or to another agent.

Sensitivity analysis

We will perform sensitivity analyses in order to explore the influence of the following factors on effect size:

• Repeating the analysis excluding unpublished studies

• Repeating the analysis taking account of risk of bias, as specified

• Repeating the analysis excluding any very long or large studies to establish how much they dominate the results

• Repeating the analysis excluding studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), and country.

'Summary of findings' tables

We will present the main results of the review in 'Summary of findings' tables. These tables present key information concerning the quality of the evidence, the magnitude of the effects of the interventions examined, and the sum of the available data for the main outcomes (Schunemann 2011a). The 'Summary of findings' tables also include an overall grading of the evidence related to each of the main outcomes using the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach (GRADE 2008). The GRADE approach defines the quality of a body of evidence as the extent to which one can be confident that an estimate of effect or association is close to the true quantity of specific interest. The quality of a body of evidence involves consideration of within‐trial risk of bias (methodological quality), directness of evidence, heterogeneity, precision of effect estimates and risk of publication bias (Schunemann 2011b). We plan to present the following outcomes in the 'Summary of findings' tables:

• All‐cause mortality

• Requirement for RRT

• Disease remission

• Persistent elevation of creatinine and/or GFR of < 60 mL/min/1.73 m²

• Persistent requirement for plasma therapy

• Adverse events due to treatment

Appendices

Appendix 1. Electronic search strategies

Database	Search terms
CENTRAL	MeSH descriptor: [Atypical Hemolytic Uremic Syndrome] this term only "atypical hemolytic uremic syndrome":ti,ab,kw (Word variations have been searched) "atypical haemolytic uraemic syndrome":ti,ab,kw (Word variations have been searched) "atypical hemolytic uraemic syndrome".tw:ti,ab,kw (Word variations have been searched) ahus:ti,ab,kw (Word variations have been searched) {or #1‐#5}
MEDLINE	Atypical Hemolytic Uremic Syndrome/ atypical h?emolytic ur?emic syndrome*.tw. ahus.tw. or/1‐3
EMBASE	hemolytic uremic syndrome/ atypical h?emolytic ur?emic syndrome*.tw. ahus.tw. or/1‐3

Appendix 2. Risk of bias assessment tool

Potential source of bias	Assessment criteria
Random sequence generation Selection bias (biased allocation to interventions) due to inadequate generation of a randomised sequence	Low risk of bias: Random number table; computer random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots; minimisation (minimisation may be implemented without a random element, and this is considered to be equivalent to being random).
	High risk of bias: Sequence generated by odd or even date of birth; date (or day) of admission; sequence generated by hospital or clinic record number; allocation by judgement of the clinician; by preference of the participant; based on the results of a laboratory test or a series of tests; by availability of the intervention.
	Unclear: Insufficient information about the sequence generation process to permit judgement.
Allocation concealment Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment	Low risk of bias: Randomisation method described that would not allow investigator/participant to know or influence intervention group before eligible participant entered in the study (e.g. central allocation, including telephone, web‐based, and pharmacy‐controlled, randomisation; sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes).
	High risk of bias: Using an open random allocation schedule (e.g. a list of random numbers); assignment envelopes were used without appropriate safeguards (e.g. if envelopes were unsealed or non‐opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure.
	Unclear: Randomisation stated but no information on method used is available.
Blinding of participants and personnel Performance bias due to knowledge of the allocated interventions by participants and personnel during the study	Low risk of bias: No blinding or incomplete blinding, but the review authors judge that the outcome is not likely to be influenced by lack of blinding; blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken.
	High risk of bias: No blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding; blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding.
	Unclear: Insufficient information to permit judgement
Blinding of outcome assessment Detection bias due to knowledge of the allocated interventions by outcome assessors.	Low risk of bias: No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding; blinding of outcome assessment ensured, and unlikely that the blinding could have been broken.
	High risk of bias: No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding; blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding.
	Unclear: Insufficient information to permit judgement
Incomplete outcome data Attrition bias due to amount, nature or handling of incomplete outcome data.	Low risk of bias: No missing outcome data; reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias); missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardised difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size; missing data have been imputed using appropriate methods.
	High risk of bias: Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size; ‘as‐treated’ analysis done with substantial departure of the intervention received from that assigned at randomisation; potentially inappropriate application of simple imputation.
	Unclear: Insufficient information to permit judgement
Selective reporting Reporting bias due to selective outcome reporting	Low risk of bias: The study protocol is available and all of the study’s pre‐specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre‐specified way; the study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre‐specified (convincing text of this nature may be uncommon).
	High risk of bias: Not all of the study’s pre‐specified primary outcomes have been reported; one or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. sub‐scales) that were not pre‐specified; one or more reported primary outcomes were not pre‐specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect); one or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta‐analysis; the study report fails to include results for a key outcome that would be expected to have been reported for such a study.
	Unclear: Insufficient information to permit judgement
Other bias Bias due to problems not covered elsewhere in the table	Low risk of bias: The study appears to be free of other sources of bias.
	High risk of bias: Had a potential source of bias related to the specific study design used; stopped early due to some data‐dependent process (including a formal‐stopping rule); had extreme baseline imbalance; has been claimed to have been fraudulent; had some other problem.
	Unclear: Insufficient information to assess whether an important risk of bias exists; insufficient rationale or evidence that an identified problem will introduce bias.

Contributions of authors

1. Draft the protocol: DP, EDS

2. Study selection: DP, EDS

3. Extract data from studies: DP, EDS

4. Enter data into RevMan: DP, EDS

5. Carry out the analysis: EDS, FAID, PM

6. Interpret the analysis: EDS, FAID, PM

7. Draft the final review: DP, EDS, FAID, PM, DK

8. Disagreement resolution: DK, PM

9. Update the review: DP, EDS

Declarations of interest

• D Pugh: none

• ED O'Sullivan: none

• FAI Duthie: none

• P Masson: none

• D Kavanagh: Newcastle University has received funding from Biomarin, Gyroscope Therapeutics and Alexion Pharmaceuticals for consultancy work undertaken by DK. DK is scientific advisor to Gyroscope Therapeutics, London.

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