Estimating and reporting treatment effects in clinical trials for weight management: using estimands to interpret effects of intercurrent events and missing data

Abstract

In the approval process for new weight management therapies, regulators typically require estimates of effect size. Usually, as with other drug evaluations, the placebo-adjusted treatment effect (i.e., the difference between weight losses with pharmacotherapy and placebo, when given as an adjunct to lifestyle intervention) is provided from data in randomized clinical trials (RCTs). At first glance, this may seem appropriate and straightforward. However, weight loss is not a simple direct drug effect, but is also mediated by other factors such as changes in diet and physical activity. Interpreting observed differences between treatment arms in weight management RCTs can be challenging; intercurrent events that occur after treatment initiation may affect the interpretation of results at the end of treatment. Utilizing estimands helps to address these uncertainties and improve transparency in clinical trial reporting by better matching the treatment-effect estimates to the scientific and/or clinical questions of interest. Estimands aim to provide an indication of trial outcomes that might be expected in the same patients under different conditions. This article reviews how intercurrent events during weight management trials can influence placebo-adjusted treatment effects, depending on how they are accounted for and how missing data are handled. The most appropriate method for statistical analysis is also discussed, including assessment of the last observation carried forward approach, and more recent methods, such as multiple imputation and mixed models for repeated measures. The use of each of these approaches, and that of estimands, is discussed in the context of the SCALE phase 3a and 3b RCTs evaluating the effect of liraglutide 3.0 mg for the treatment of obesity.

Once-Weekly Semaglutide in Adults with Overweight or Obesity

“…Two estimands -the treatment policy estimand (traditional intention-to-treat analysis, with effects assessed regardless of treatment discontinuation or rescue intervention) and the trial product estimand (effects assessed if the drug or placebo was taken as intended) -were used to assess treatment efficacy from different perspectives and accounted for intercurrent events and missing data differently, as described previously. 16 All analyses in the statistical hierarchy were based on the primary treatment policy estimand (details on analysis methods are provided in the Supplementary Appendix). All reported results are for the treatment policy estimand, unless stated otherwise.…”

Gastrointestinal tolerability of once‐weekly semaglutide 2.4 mg in adults with overweight or obesity, and the relationship between gastrointestinal adverse events and weight loss

“…This analysis aimed to separate the overall effects on body weight into effects mediated by GI AEs (indirect effects) and those unrelated to GI AEs (direct effects), for the STEP 1‐3 trials. Changes in body weight were analysed addressing the effect of treatment (if taken as intended) using a mixed model for repeated measurements 20 GI AE incidence in the STEP 4 trial was analysed with a methodology similar to that used for the STEP 1‐3 pooled analysis, with the exception that no adjustment of AE incidence or event rate was performed.…”

“…Changes in body weight were analysed addressing the effect of treatment (if taken as intended) using a mixed model for repeated measurements. 20 GI AE incidence in the STEP 4 trial was analysed with a methodology similar to that used for the STEP 1‐3 pooled analysis, with the exception that no adjustment of AE incidence or event rate was performed. Data from participants able to tolerate the semaglutide 2.4 mg dose during the 20‐week run‐in period who were subsequently randomized were used to evaluate the effect of continued semaglutide 2.4 mg or cessation of treatment (switch to placebo) on GI AE incidence.…”

“…Changes in body weight were analysed addressing the effect of treatment (if taken as intended) using a mixed model for repeated measurements. 20 …”

Incorporating estimands into clinical trial statistical analysis plans

“…Since the release of E9 (R1), estimands have been discussed in both statistical and clinical literature. [4][5][6][7][8][9][10][11] Clinical trial protocols increasingly include estimands, 12,13 but there is variation in how they are presented.…”