EULAR: Observational studies on drug effectiveness must report reasons for discontinuation
Click Here to Manage Email Alerts
Studies using observational data to compare drug effectiveness must report the proportion of patients who stop or alter therapies and the reasons for treatment discontinuation, according to new EULAR “points to consider.”
“There is an unmet need for [points to consider (PtC)] on the analysis of effectiveness in purely observational real-world data, especially registers, addressing three key aspects of real-world effectiveness,” Delphine Sophie Courvoisier, PhD, of the University of Geneva, in Switzerland, and colleagues wrote. “First, baseline of treatment is often hard to ascertain since patients start and stop different treatments over time.
“Thus, the 1-year follow-up of one treatment could happen 3 months after this treatment was stopped at month 9, and correspond to the start of another treatment,” they added. “Second, visits often occur at variable time points. Third, treatment discontinuation is substantial and may be informative on treatment success, for instance when patients stop for ineffectiveness.”
To develop points to consider for analyzing and reporting comparative effectiveness using observational data, Courvoisier and colleagues formed a EULAR multidisciplinary task force. This task force included eight rheumatologists, four epidemiologists/rheumatologists, two statisticians, two patient representatives who were also social sciences researchers, and two health professionals.
Members performed a systematic review of methods currently used in comparative effectiveness studies — resulting in 211 articles included for assessment — which was then used to draft points to consider in two in-person meetings. During the second meeting, which occurred in November 2019, members of the task force also heard expert opinion and results of a simulation study. Feedback from a larger audience was used to refine the resulting draft, with the final manuscript later reviewed and approved by all task force members and the EULAR Council.
According to the researchers, the task force ultimately approved three overarching principles and 10 points to consider. In the overarching principles, the members define “treatment effectiveness” as how well a therapy performs in routine clinical settings, and establish the limitations of observational data. In addition, they state that “robust and transparent epidemiological statistical methods” bolster trustworthiness in results stemming from observational data.
The 10 EULAR points to consider are:
- Observational studies that report comparative effectiveness must follow STROBE guidelines;
- Reporting on effectiveness should include several outcomes across multiple domains;
- Researchers must report the proportion of patients who stop or change therapies and the reasons for treatment discontinuation;
- Analyses must report on participants lost to follow-up by the exposure of interest;
- Researchers should choose covariates based on subject matter knowledge, and justify their model selection;
- Baseline should be set at the start of treatment, and the analysis should include a description of how covariate measurements relate to baseline;
- The analysis should be based on all participants initiating a treatment, not limited to those remaining on treatment at a specific time;
- Researchers should take into account attrition in the event of treatment discontinuation prior to outcome assessment, possibly using multiple imputation techniques and/or causal inference models such as inverse probability weighting;
- Studies should include sensitivity analyses to examine the impact of “assumptions related to missingness,” especially when attrition occurs; and
- Authors should prepare in advance a statistical analysis plan.
“As analyses of observational data become more complex and to accommodate more intricate research questions and data collection, supporting tools should be provided to researchers,” Courvoisier and colleagues wrote. “These PtC are one tool to support correct reporting of comparative effectiveness studies.
“Another available support is the EULAR Virtual Research Centre offering a range of resources including clinical research support,” they added. “Investigators of future studies should be encouraged to implement variables to be able to adhere to these recommendations, for example, providing reasons for treatment discontinuation. R packages, SAS procedures or any other statistical software should be developed to easily implement state of the art analyses, with a detailed documentation clarifying the substantive choices that fall to the investigators.”
Collapse
Read more about
Click Here to Manage Email Alerts