Benefit-risk balance of advanced therapies in inflammatory bowel disease: emulation of clinical trials using multiple sources of real-world data – IBD-RCT-Emulate

Real world evidence derived from real world data (RWD) has been mainly used to assess treatment safety, while it has been used only in limited circumstances to assess treatment effectiveness in real-life setting. Multiple types of data sources are available to achieve this goal, notably nationwide healthcare databases, electronic health records (EHR), and dedicated cohorts, but each type has its unique strengths and limitations, which might impact the validity of related findings. Linking multiple data sources in one research project may allow to overcome limitations and leverage strengths of each data source. Inflammatory bowel diseases (IBD) including Crohn’s disease and ulcerative colitis affect over 200 000 residents in France. New advanced therapies have been recently approved, but in the absence of head-to-head randomized controlled trials (RCTs), data are lacking on comparative effectiveness and safety to clearly define their optimal position in the IBD therapeutic management.
The general objective of this project is to assess the benefit-risk balance of advanced therapies in IBD using three sources of RWD: the French nationwide healthcare database (Système National des Données de Santé [SNDS]), EHR with the Assistance Publique-Hôpitaux de Paris (EDS AP-HP) Clinical Data Repository, and a prospective cohort of patients with IBD followed in AP-HP centers (SUVIMIC).
First, we will assemble a cohort of patients with IBD from each data source separately. Patients included in the SUVIMIC database will be linked to patients in the EDS AP-HP. This process will be based on a direct linkage using a unique hospital patient identifier. The linkage process between SNDS and the two other data sources will be based on a probabilistic matching using hospitalization data. A cohort of all IBD patients from the SNDS will be assembled, with SNDS data linked to SUVIMIC and EDS AP-HP data for patients included in several databases.
Linking clinical and biological data collected in SUVIMIC and EDS AP-HP to the SNDS will allow to develop and assess the performance of identification algorithms for variables not consistently captured in medical claims data, notably IBD disease characteristics, effectiveness outcomes used in phase III RCTs, and safety outcomes. Data from the EDS AP-HP and the SUVIMIC database will be considered as the gold standard for the validation process. Two methods will be applied to develop the algorithms, one expert-based and one derived by machine learning approach.
Secondly, we will emulate one head-to-head RCT for each comparison and each IBD subtype, using effectiveness and safety outcomes previously validated. Risk ratios with 95% confidence intervals will be estimated in propensity score matched cohorts. Analyses stratified on IBD characteristics previously validated will be performed to assess the benefit-risk balance of advanced therapies in relevant subgroups of patients with IBD.
Finally, a personalized benefit-risk assessment web-based digital tool incorporating emulated trials findings will be made available to clinicians and will summarize treatment effectiveness and safety into one measure incorporating patient preferences. The impact of the web-based digital tool on treatment effectiveness and safety will be assessed in clinical practice by a pragmatic cluster RCT nested in the SNDS.
Based on an innovative methodological framework to assess the benefit-risk balance of IBD related treatment, this project will clarify the optimal position of each advanced therapy in the IBD therapeutic management and disseminate findings to patients and clinicians. The methodological framework developed will be also easily applied to future treatments in IBD with a minimal cost and in a short time scale, and may be also replicated in other diseases.