Win ratio approach for analyzing composite time-to-event endpoint with opposite treatment effects in its components.

There is an increasing interest in the use of win ratio with composite time-to-event due to its flexibility in combining component endpoints. Exploring this flexibility further, one interesting question is in assessing the impact when there is a difference in treatment effect in the component endpoints. For example, the active treatment may prolong the time to occurrence of the negative event such as death or ventilation; meanwhile, the treatment effect may also shorten the time to achieving positive events, such as recovery or improvement. Notably, this portrays a situation where the treatment effect on time to recovery is in a different direction of benefit compared to the time to ventilation or death. Under such circumstances, if a single endpoint is used, the benefit gained for other individual outcomes is not counted and is diminished. As consequence, the study may need a larger sample size to detect a significant effect of treatment. Such a scenario can be handled by win ratio in a novel way by ranking component events, which is different from the usual composite endpoint approach such as time-to-first event. To evaluate how the different directions of treatment effect on component endpoints will impact the win ratio analysis, we use a Clayton copula-based bivariate survival simulation to investigate the correlation of component time-to-event. Through simulation, we found that compared to the marginal model using single endpoints, the win ratio analysis on composite endpoint performs better, especially when the correlation between two events is weak. Then, we applied the methodology to an infectious disease progression simulated study motivated by COVID-19. The application demonstrates that the win ratio approach offers advantages in empirical power compared to the traditional Cox proportional hazard approach when there is a difference in treatment effect in the marginal events.

Estimands, Handling of Missing Data and Impact on Assumed Effect Size and Power in Pivotal COVID-19 Treatment Trials.

Estimands play an important role for aligning study objectives, study design and analyses through a precise definition of the quantity of interest. For COVID-19 studies, apart from intercurrent events, high volume of missing data has been observed. We explore their impact on several estimands through a synthetic COVID-19 data generated from a discrete-time multi-state model. We compare estimators of these estimands based on their ability to closely match the true response rates and retain assumed power. The final choice of the estimand then needs to be aligned with clinically meaningful quantities of interest to patients, clinicians, regulators and payers.

Efficacy and Safety of Baricitinib Combined With Topical Corticosteroids for Treatment of Moderate to Severe Atopic Dermatitis: A Randomized Clinical Trial.

Importance: Baricitinib, an oral selective Janus kinase 1 and 2 inhibitor, effectively reduced disease severity in moderate to severe atopic dermatitis (AD) in 2 phase 3 monotherapy studies. Objective: To assess the efficacy and safety of 4 mg and 2 mg of baricitinib in combination with background topical corticosteroid (TCS) therapy in adults with moderate to severe AD who previously had an inadequate response to TCS therapy. Design, Setting, and Participants: This double-blind, placebo-controlled, phase 3 randomized clinical trial, BREEZE-AD7 (Study of Baricitinib [LY3009104] in Combination With Topical Corticosteroids in Adults With Moderate to Severe Atopic Dermatitis) was conducted from November 16, 2018, to August 22, 2019, at 68 centers across 10 countries in Asia, Australia, Europe, and South America. Patients 18 years or older with moderate to severe AD and an inadequate response to TCSs were included. After completing the study, patients were followed up for up to 4 weeks or enrolled in a long-term extension study. Interventions: Patients were randomly assigned (1:1:1) to receive 2 mg of baricitinib once daily (n = 109), 4 mg of baricitinib once daily (n = 111), or placebo (n = 109) for 16 weeks. The use of low-to-moderate potency TCSs was allowed. Main Outcomes and Measures: The primary end point was the proportion of patients achieving a validated Investigator Global Assessment for Atopic Dermatitis (vIGA-AD) score of 0 (clear) or 1 (almost clear), with a 2-point or greater improvement from baseline at week 16. Results: Among 329 patients (mean [SD] age, 33.8 [12.4] years; 216 [66%] male), at week 16, a vIGA-AD score of 0 (clear) or 1 (almost clear) was achieved by 34 patients (31%) receiving 4 mg of baricitinib and 26 (24%) receiving 2 mg of baricitinib compared with 16 (15%) receiving placebo (odds ratio vs placebo, 2.8 [95% CI, 1.4-5.6]; P = .004 for the 4-mg group; 1.9 [95% CI, 0.9-3.9]; P = .08 for the 2-mg group). Treatment-emergent adverse events were reported in 64 of 111 patients (58%) in the 4-mg group, 61 of 109 patients (56%) in the 2-mg group, and 41 of 108 patients (38%) in the placebo group. Serious adverse events were reported in 4 patients (4%) in the 4-mg group, 2 (2%) in the 2-mg group, and 4 (4%) in the placebo group. The most common adverse events were nasopharyngitis, upper respiratory tract infections, and folliculitis. Conclusions and Relevance: A dose of 4 mg of baricitinib in combination with background TCS therapy significantly improved the signs and symptoms of moderate to severe AD, with a safety profile consistent with previous studies of baricitinib in AD. Trial Registration: ClinicalTrials.gov Identifier: NCT03733301.