For a given therapy, patients, health technology assessment agencies and regulatory agencies are interested in evaluating whether the benefit outweighs the associated risks. Existing work [1] uses prioritized composite outcomes to assess benefit and risk; this manuscript extends this work. The assessment of risk is based on a derived score obtained from predefined adverse events of interest. This derived safety score incorporates full aspects of adverse events of interest. After prioritizing the components of the composite outcomes consisting of benefit and risk outcomes, the net benefit or the Wilcoxon-Mann-Whitney statistic is used to assess the composite benefit-risk outcomes. If there is no prioritization, average net benefit (also called the O’Brien method) can be used to assess the treatment differences in the composite outcomes. Via simulation, we evaluate the characteristics of these measures of benefit-risk. An existing sample size derivation is extended to the case where there is no prioritization (average net benefit). Finally, an example motivated by a plaque psoriasis study is presented.
KeywordsBenefit-Risk AssessmentTreatment-and-Disease-BurdenPrioritized Net BenefitNon-Prioritized Net Benefit
Seifu, Y., Mt-Isa, S., Duke, K., Gamalo-Siebers, M., Wang, W., Dong, G., et al . (2022) Design of Paediatric Trials with Benefit-Risk Endpoints Using a Composite Score of Adverse Events of Interest (AEI) and Win-Statistics. Journal of Biopharmaceuti cal Statistics , 33, 696-707. https://doi.org/10.1080/10543406.2022.2153202
Péron, J., Roy, P., Ding, K., Parulekar, W.R., Roche, L. and Buyse, M. (2015) Assessing the Benefit-Risk of New Treatments Using Generalised Pairwise Comparisons: The Case of Erlotinib in Pancreatic Cancer. British Journal of Cancer , 112, 971-976. https://doi.org/10.1038/bjc.2015.55
Péron, J., Giai, J., Maucort-Boulch, D. and Buyse, M. (2019) The Benefit-Risk Balance of Nab-Paclitaxel in Metastatic Pancreatic Adenocarcinoma. Pancreas , 48, 275-280. https://doi.org/10.1097/mpa.0000000000001234
Buyse, M., Saad, E.D., Peron, J., Chiem, J., De Backer, M., Cantagallo, E., et al . (2021) The Net Benefit of a Treatment Should Take the Correlation between Benefits and Harms into Account. Journal of Clinical Epidemiology , 137, 148-158. https://doi.org/10.1016/j.jclinepi.2021.03.018
Backer, M.D., Sengar, M., Mathews, V., Salvaggio, S., Deltuvaite-Thomas, V., Chiêm, J., et al . (2023) Design of a Clinical Trial Using Generalized Pairwise Comparisons to Test a Less Intensive Treatment Regimen. Clinical Trials , 21, 180-188. https://doi.org/10.1177/17407745231206465
Piffoux, M., Ozenne, B., De Backer, M., Buyse, M., Chiem, J. and Péron, J. (2024) Restricted Net Treatment Benefit in Oncology. Journal of Clinical Epidemiology , 170, Article ID: 111340. https://doi.org/10.1016/j.jclinepi.2024.111340
Buyse, M., Verbeeck, J., Saad, E.D., Backer, M.D., Deltuvaite-Thomas, V. and Molenberghs, G. (2025) Handbook of Generalized Pairwise Comparisons: Methods for Patient-Centric Analysis. Chapman and Hall/CRC.
Péron, J., Roy, P., Ozenne, B., Roche, L. and Buyse, M. (2016) The Net Chance of a Longer Survival as a Patient-Oriented Measure of Treatment Benefit in Randomized Clinical Trials. JAMA Oncology , 2, 901-905. https://doi.org/10.1001/jamaoncol.2015.6359
Buyse, M. (2010) Generalized Pairwise Comparisons of Prioritized Outcomes in the Two-Sample Problem. Statistics in Medicine , 29, 3245-3257. https://doi.org/10.1002/sim.3923
Dong, G., Huang, B., Wang, D., Verbeeck, J., Wang, J. and Hoaglin, D.C. (2020) Adjusting Win Statistics for Dependent Censoring. Pharmaceutical Statistics , 20, 440-450. https://doi.org/10.1002/pst.2086
Ramchandani, R., Schoenfeld, D.A. and Finkelstein, D.M. (2016) Global Rank Tests for Multiple, Possibly Censored, Outcomes. Biometrics , 72, 926-935. https://doi.org/10.1111/biom.12475
Verbeeck, J., Spitzer, E., de Vries, T., van Es, G.A., Anderson, W.N., Van Mieghem, N.M., e t al . (2019) Generalized Pairwise Comparison Methods to Analyze (Non)prioritized Composite Endpoints. Statistics in Medicine , 38, 5641-5656. https://doi.org/10.1002/sim.8388
Deltuvaite-Thomas, V. and Burzykowski, T. (2021) Operational Characteristics of Generalized Pairwise Comparisons for Hierarchically Ordered Endpoints. Pharmaceutical Statistics , 21, 122-132. https://doi.org/10.1002/pst.2156
Niebecker, R., Maas, H., Staab, A., Freiwald, M. and Karlsson, M.O. (2019) Modeling Exposure-Driven Adverse Event Time Courses in Oncology Exemplified by Afatinib. CPT : Pharmacometrics & Systems Pharmacology , 8, 230-239. https://doi.org/10.1002/psp4.12384
Evans, S.R., Rubin, D., Follmann, D., Pennello, G., Huskins, W.C., Powers, J.H., et al . (2015) Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR). Clinical Infectious Diseases , 61, 800-806. https://doi.org/10.1093/cid/civ495
Fay, M.P. and Malinovsky, Y. (2018) Confidence Intervals of the Mann-Whitney Parameter That Are Compatible with the Wilcoxon-Mann-Whitney Test. Statistics in Medicine , 37, 3991-4006. https://doi.org/10.1002/sim.7890
Gasparyan, S.B., Kowalewski, E.K., Folkvaljon, F., Bengtsson, O., Buenconsejo, J., Adler, J., e t al . (2021) Power and Sample Size Calculation for the Win Odds Test: Application to an Ordinal Endpoint in COVID-19 Trials. Journal of Biopharmace utical Statistics , 31, 765-787. https://doi.org/10.1080/10543406.2021.1968893
CIOMS Working Group (2023) Benefit-Risk Balance for Medical Products.
Ozenne, B. and Peron, J. (2024) BuyseTest: Implementation of the Generalized Pairwise Comparisons. R Package Version 3.0.2.
Noether, G.E. (1987) Sample Size Determination for Some Common Nonparametric Tests. Journal of the American Statistical Association , 82, 645-647. https://doi.org/10.1080/01621459.1987.10478478
Kornacki, A., Bochniak, A. and Kubik-Komar, A. (2017) Sample Size Determination in the Mann-Whitney Test. Biometrical Letters , 54, 175-186. https://doi.org/10.1515/bile-2017-0010
Zhou, T.J., LaValley, M.P., Nelson, K.P., Cabral, H.J. and Massaro, J.M. (2022) Calculating Power for the Finkelstein and Schoenfeld Test Statistic for a Composite Endpoint with Two Components. Statistics in Medicine , 41, 3321-3335. https://doi.org/10.1002/sim.9419
Gordon, K.B., Strober, B., Lebwohl, M., Augustin, M., Blauvelt, A., Poulin, Y., et al . (2018) Efficacy and Safety of Risankizumab in Moderate-to-Severe Plaque Psoriasis (Ultimma-1 and Ultimma-2): Results from Two Double-Blind, Randomised, Placebo-Controlled and Ustekinumab-Controlled Phase 3 Trials. The Lancet , 392, 650-661. https://doi.org/10.1016/s0140-6736(18)31713-6
Verbeeck, J., Dirani, M., Bauer, J.W., Hilgers, R., Molenberghs, G. and Nabbout, R. (2023) Composite Endpoints, Including Patient Reported Outcomes, in Rare Diseases. Orphanet Journal of Rare Diseases , 18, Article No. 262. https://doi.org/10.1186/s13023-023-02819-x
Deltuvaite-Thomas, V., De Backer, M., Parker, S., Deneux, M., Polgreen, L.E., O’Neill, C., et al . (2023) Generalized Pairwise Comparisons of Prioritized Outcomes Are a Powerful and Patient-Centric Analysis of Multi-Domain Scores. Orphanet Journal of Rare Diseases , 18, Article No. 321. https://doi.org/10.1186/s13023-023-02943-8
Yuan, S.S., Seifu, Y., Wang, W. and Colopy, M. (2021) Estimands in Safety and Benefit-Risk Evaluation. In: Quantitative Drug Safety and Benefit - Risk Evaluation : Practical and Cross - Disciplinary Approaches , Chapman and Hall/CRC, 317-349. https://doi.org/10.1201/9780429488801-18