Characteristics of non-randomised studies of drug treatments: cross sectional study - Raphaël Porcher; Philippe Ravaud; Isabelle Boutron; Viet-Thi Tran; Sally Yaacoub; Anna Pellat; Hillary Bonnet (BMJ Medicine)
Objective To examine the characteristics of comparative non-randomised studies that assess the effectiveness or safety, or both, of drug treatments.Design Cross sectional study.Data sources Medline (Ovid), for reports published from 1 June 2022 to 31 August 2022.Eligibility criteria for selecting studies Reports of comparative non-randomised studies that assessed the effectiveness or safety, or both, of drug treatments were included. A randomly ordered sample was screened until 200 eligible reports were found. Data on general characteristics, reporting characteristics, and time point alignment were extracted, and possible related biases, with a piloted form inspired by reporting guidelines and the target trial emulation framework.Results Of 462 reports of non-randomised studies identified, 262 studies were excluded (32% had no comparator and 25% did not account for confounding factors). To assess time point alignment and possible related biases, three study time points were considered: eligibility, treatment assignment, and start of follow-up. Of the 200 included reports, 70% had one possible bias, related to: inclusion of prevalent users in 24%, post-treatment eligibility criteria in 32%, immortal time periods in 42%, and classification of treatment in 23%. Reporting was incomplete, and only 2% reported all six of the key elements considered: eligibility criteria (87%), description of treatment (46%), deviations in treatment (27%), causal contrast (11%), primary outcomes (90%), and confounding factors (88%). Most studies used routinely collected data (67%), but only 7% reported using validation studies of the codes or algorithms applied to select the population. Only 7% of reports mentioned registration on a trial registry and 3% had an available protocol.Conclusions The findings of the study suggest that although access to real world evidence could be valuable, the robustness and transparency of non-randomised studies need to be improved.