Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/32925
Title: Net benefit in the presence of correlated prioritized outcomes using generalized pairwise comparisons: A simulation study
Authors: Giai, Joris
Maucort-Boulch, Delphine
Ozenne, Brice
Chiem, Jean-Christophe
BUYSE, Marc 
Peron, Julien
Issue Date: 2020
Publisher: WILEY
Source: STATISTICS IN MEDICINE,
Status: Early view
Abstract: Background The prioritized net benefit (Delta) is a measure of the benefit-risk balance in clinical trials, based on generalized pairwise comparisons (GPC) using several prioritized outcomes. Its estimation requires the classification as Wins or Losses of all possible pairs of patients, one from the experimental treatment (E) group and one from the control treatment (C) group. In this simulation study, we assessed the impact of the correlation between prioritized outcomes on Delta, its estimate, bias, size, and power. Methods The theoretical Delta value was derived for the specific case of two correlated binary outcomes when a normal copula is used. Focusing on one efficacy and one toxicity outcome, two situations frequently met in practice were simulated: binary efficacy outcome with binary toxicity outcome, or time to event efficacy outcome with categorical toxicity outcome. Several scenarios of efficacy and toxicity were generated, with various levels of correlation. Results When E was more effective than C, positive correlations were mainly associated with a decrease in the proportion of Losses, while negative correlations were associated with a decrease in the proportion of Wins on the toxicity outcome. This resulted in an increase of (Delta) over cap with the intensity of the positive correlation without adding any bias. Results were similar whatever the type of outcomes generated but led to power alteration. Conclusion Correlations between outcomes analyzed with GPC led to substantial but predictable modifications of Delta and its estimate. Correlations should be taken into consideration when performing sample size estimations in clinical trials.
Notes: Giai, J (corresponding author), CHU Albert Michallon, CIC Innovat Technol, Pavillon Taillefer,CS 10217, F-38700 La Tronche, France.
joris.giai@chu-lyon.fr
Other: Giai, J (corresponding author), CHU Albert Michallon, CIC Innovat Technol, Pavillon Taillefer,CS 10217, F-38700 La Tronche, France. joris.giai@chu-lyon.fr
Keywords: clinical trial;correlation;generalized pairwise comparisons;multivariate analysis;net benefit
Document URI: http://hdl.handle.net/1942/32925
ISSN: 0277-6715
e-ISSN: 1097-0258
DOI: 10.1002/sim.8788
ISI #: WOS:000583727100001
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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