Scolaris Content Display Scolaris Content Display

Anti‐IL‐12/23p40 antibodies for maintenance of remission in Crohn's disease

Esta versión no es la más reciente

Contraer todo Desplegar todo

Abstract

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

The objectives of this review will be to assess the efficacy and safety of anti‐IL‐12/23p40 antibodies for maintenance of remission in Crohn's disease.

Background

Description of the condition

Crohn's disease is a chronic, relapsing and remitting, inflammatory condition which results in abdominal pain, diarrhea, and weight loss. Despite highly effective therapies, up to one third patients develop fistulas or require surgery for disease complications (Crohn's and Colitis Foundation of Canada 2012). Additionally, many of the current therapies are encumbered by unexpected adverse events (Colombel 2004; Colombel 2007; Ford 2011; Raj 2010; Schreiber 2007; Singh 2011; Yang 2002). Due to the fact that approximately 40% of patients do not respond to conventional agents such as corticosteroids, immunosuppressants and biologics, the development of new therapies is a priority for clinical practice (Danese 2011; Hanauer 2002; Hanauer 2006; Targan 1997).

Monoclonal antibodies against tumour necrosis factor alpha (TNF‐α) are commonly used for maintenance of remission in Crohn's disease. However, estimates indicate that 25 to 40% of patients receiving TNF‐α antagonists who initially benefit from treatment either lose response or are forced to stop treatment due to intolerable adverse events during the maintenance phase (Danese 2011). Although some patients regain response with an increase in dose, a significant proportion of these patients experience relapsing of their Crohn's due to non‐TNF driven inflammatory pathways (Steenholdt 2016). In these cases, continued anti‐TNF‐α treatment would be ineffective and other therapies are needed.

Description of the intervention

Ustekinumab (CNTO 1275) and briakinumab (ABT‐874) are monoclonal antibodies directed against the shared p40 subunit of interleukin‐12 and interleukin‐23 (IL‐12/23p40). Inhibition of these cytokines is beneficial for induction of remission in Crohn's disease (Feagan 2016).

How the intervention might work

Pathogenic immune responses in Crohn’s disease are characterized by dysregulated T‐cell activity stimulated by the release of interleukin‐12 (IL‐12) and IL‐23 by antigen presenting cells (Benson 2011a; Duvallet 2011; Peluso 2006; Watanabe 2004). IL‐12 promotes differentiation of naive T‐cells down the Th1 pathway (Xavier 2007), whereas IL‐23 stimulates proliferation of Th17 lymphocytes. Activation of the Th1 pathway culminates in the release interferon (IFN)‐ɣ and tumor necrosis factor (TNF)‐α (Benson 2011b; Cingoz 2009; Peluso 2006), two cytokines that have been implicated in the pathogenesis of CD. In contrast, Th17 is important in maintaining many chronic inflammatory conditions (Duvallet 2011).

In murine models, inhibition of IL‐12/23p40 results in apoptosis of T cells in the gut mucosa (Fuss 1999), which results in disease improvement (Neurath 1995). Collectively, these data suggest a possible therapeutic role for ustekinumab in the treatment of Crohn’s disease.

Why it is important to do this review

Ustekinumab is widely used for the treatment of psoriasis where it has demonstrated safety and efficacy (Papp 2008). The safety and efficacy of ustekinumab has been established for induction of remission in CD (MacDonald 2016). However the benefits and harms of this therapy for maintenance of remission in CD has not been systematically assessed.

Objectives

The objectives of this review will be to assess the efficacy and safety of anti‐IL‐12/23p40 antibodies for maintenance of remission in Crohn's disease.

Methods

Criteria for considering studies for this review

Types of studies

Randomized controlled trials (RCTs) will be considered for inclusion.

Types of participants

Patients with quiescent CD (as defined by the original study) will be considered for inclusion. No age restrictions will be applied.

Types of interventions

Trials comparing monoclonal antibodies against IL‐12/23p40 to placebo or an active comparator will be considered for inclusion.

Types of outcome measures

Primary outcomes

The primary outcome measure will be the proportion of patients who failed to maintain remission (as defined by the original study).

Secondary outcomes

Secondary outcomes will include the proportion of patients:

1. Who fail to maintain clinical response (as defined by the original study);

2. Who fail to maintain endoscopic response (as defined by the original study);

3. Who fail to maintain endoscopic remission (as defined by the original study);

4.Who fail to maintain histological response (as defined by the original study);

5.Who fail to maintain histological remission (as defined by the original study);

6. Who fail to maintain both clinical and endoscopic response (as defined by the original study);

7. Who fail to maintain both clinical and endoscopic remission (as defined by the original study);

8. With adverse events;

9. With serious adverse events; and

10. Who withdrew from the study due to adverse events.

Search methods for identification of studies

Electronic searches

We will search the following databases for relevant studies:

1. MEDLINE (Ovid, 1946 to present);

2. EMBASE (Ovid, 1984 to present);

3. The Cochrane Central Register of Controlled Trials; and

4. The Cochrane IBD Group Specialized Register.

The search strategies are listed in Appendix 1

Searching other resources

We will also search the references of relevant trials and review articles for additional studies not identified by the search. Furthermore, we will search conference proceedings from major meetings including Digestive Disease Week, the Euroepan Crohn's and Colitis Organization congress, and the United European Gastroenterology Week for the last five years to identify studies published in abstract form only. We will contact leaders in the field and the manufacturers of briakinumab and ustekinumab (Abbott Laboratories, Abbott Park, IL, USA and Centocor, Horsham, PA, USA) to identify any unpublished studies. Lastly, registered trial databases such as clinicaltrials.gov, clinicaltrials.ifpma.org and the meta register of controlled trials at controlled‐trials.com will be searched to identify any ongoing studies.

Data collection and analysis

Selection of studies

Two authors (SD and TN) will independently screen the search results for eligible studies based on the inclusion criteria as described above. Disagreements will be discussed until a consensus is reached. Any disagreements will be brought to a third author (RK) for resolution.

Data extraction and management

Data will be extracted from included studies by two independent authors (SD and TN). Any disagreements over extracted data will first be discussed and then brought to a third author (RK) for resolution. If data are not available, the study authors will be contacted for additional information.

Assessment of risk of bias in included studies

The quality of included studies will be independently assessed by two authors (SD and TN) using the Cochrane risk of bias tool (Higgins 2011). We will assess several factors pertaining to the methodological quality of the studies including sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting and other potential sources of bias. Studies will be judged to be of high, low or unclear risk of bias. Any disagreements regarding risk of bias will be first discussed and then brought to a third author (RK) for resolution as required.

We will use the GRADE approach to assess the overall quality of evidence supporting both the primary outcomes and selected secondary outcomes ( Schünemann 2011). If the evidence extracted is from a RCT, it will be considered high quality evidence. However, the quality of the evidence can be downgraded when considering the following factors:

1. Risk of bias;

2. Indirect evidence;

3. Inconsistency (unexplained heterogeneity);

4. Imprecision and

5. Publication bias.

The overall quality of the evidence will be classified as high quality (the estimate of effect is very unlikely to be changed despite further research); moderate quality (the estimate of effect is unlikely to be changed despite further research); low quality (the estimate of effect may be changed despite further research) or very low quality (the estimate of effect likely will be changed with further research) (Guyatt 2008).

Measures of treatment effect

We will be using Review Manager (RevMan 5.3) to analyse the data on an intention‐to‐treat (ITT) basis. We will calculate the risk ratio (RR) and corresponding 95% confidence interval (95% CI) for dichotomous outcomes. For continuous outcomes, we will calculate the mean difference (MD) and corresponding 95% CI.

Unit of analysis issues

For outcomes that are measured at different time points, we will determine appropriate fixed intervals for follow‐up for each outcome. Cross‐over trials will be included if data are available for the first phase of the trial prior to crossover. Seperate comparisons will be performed for each type of antibody and each antibody in the context of other therapies. To deal with events that may reoccur (e.g. adverse events), we will report on the proportion of subjects who experience at least one event. If we encounter multiple drug dose groups, we will divide the placebo group across the dose groups to avoid a unit of analysis error. We do not anticipate encountering any cluster randomized trials.

Dealing with missing data

If there are any missing data, the authors from the original study will be contacted. Additionally, patients without treatment outcomes will be presumed to be treatment failures. We will perform a sensitivity analysis to assess the impact of this assumption on the effect estimate if deemed appropriate.

Assessment of heterogeneity

We will assess heterogeneity using the Chi2 test (a P value of 0.10 will be considered statistically significant) and the I2 statistic. For the I2 statistic, 75% will indicate high heterogeneity among study data, 50% will indicate moderate heterogeneity and 25% will indicate low heterogeneity (Higgins 2003). We will conduct sensitivity analysis to explore possible explanations for heterogeneity.

Assessment of reporting biases

To assess potential reporting biases, we will initially compare outcomes listed in the study protocol to those outcomes reported in the published manuscript. If we do not have access to the protocol, we will use the outcomes listed in the methods sections of the published manuscript to compare to the outcomes reported in the published manuscript . We will investigate potential publication bias using funnel plots if a sufficient number of studies (> 10) are pooled for meta‐analysis (Egger 1997).

Data synthesis

We will combine data from individual trials for meta‐analysis when the interventions, patient groups and outcomes are similar as deemed by author consensus. We will calculate the pooled RR and 95% CI for dichotomous outcomes. Additionally, the pooled MD and 95% CI will be calculated for any continuous outcomes A fixed‐effect model will be used to pool data unless heterogeneity exists between the studies. A random‐effects model will be used if heterogeneity exits (i.e. I2 50 to 75%). We will not pool data for meta‐analysis if a high degree of heterogeneity (i.e. I2 ≥ 75%) is found.

Subgroup analysis and investigation of heterogeneity

We plan for subgroup analysis by different drug doses.

Sensitivity analysis

We will use sensitivity analysis to determine the impact of random‐effects and fixed‐effect modelling, risk of bias, type of report (full manuscript, abstract or unpublished data) and loss to follow‐up on the pooled effect estimate.