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Title: | Assessing Long-Term Survival Benefits of Immune Checkpoint Inhibitors Using the Net Survival Benefit | Authors: | Peron, Julien Lambert, Alexandre Munier, Stephane Ozenne, Brice Giai, Joris Roy, Pascal Dalle, Stephane Machingura, Abigirl Maucort-Boulch, Delphine BUYSE, Marc |
Issue Date: | 2019 | Publisher: | OXFORD UNIV PRESS INC | Source: | JNCI-JOURNAL OF THE NATIONAL CANCER INSTITUTE, 111 (11) , p. 1186 -1191 (Art N° djz030) | Abstract: | Background: The treatment effect in survival analysis is commonly quantified as the hazard ratio, and tested statistically using the standard log-rank test. Modern anticancer immunotherapies are successful in a proportion of patients who remain alive even after a long-term follow-up. This new phenomenon induces a nonproportionality of the underlying hazards of death. Methods: The properties of the net survival benefit were illustrated using the dataset from a trial evaluating ipilimumab in metastatic melanoma. The net survival benefit was then investigated through simulated datasets under typical scenarios of proportional hazards, delayed treatment effect, and cure rate. The net survival benefit test was computed according to the value of the minimal survival difference considered clinically relevant. As comparators, the standard and the weighted log-rank tests were also performed. Results: In the illustrative dataset, the net survival benefit favored ipilimumab [Delta(0) = 15.8%, 95% confidence interval = 4.6% to 27.3%, P = .006]. This favorable effect was maintained when the analysis was focused on long-term survival differences (eg, >12 months, Delta(12) = 12.5% (95% confidence interval = 4.4% to 20.6%, P = .002). Under the scenarios of a delayed treatment effect and cure rate, the power of the net survival benefit test compared favorably to the standard log-rank test power and was comparable to the power of the weighted log-rank test for large values of the threshold of clinical relevance. Conclusion: The net long-term survival benefit is a measure of treatment effect that is meaningful whether or not hazards are proportional. The associated statistical test is more powerful than the standard log-rank test when a delayed treatment effect is anticipated. | Notes: | Peron, J (reprint author), Hosp Civils Lyon, Ctr Hosp Lyon Sud, Serv Oncol Med, 165,Chemin Grand Revoyet 69495, F-69310 Pierre Benite, France. julien.peron@chu-lyon.fr |
Other: | Peron, J (reprint author), Hosp Civils Lyon, Ctr Hosp Lyon Sud, Serv Oncol Med, 165,Chemin Grand Revoyet 69495, F-69310 Pierre Benite, France. julien.peron@chu-lyon.fr | Document URI: | http://hdl.handle.net/1942/30792 | ISSN: | 0027-8874 | e-ISSN: | 1460-2105 | DOI: | 10.1093/jnci/djz030 | ISI #: | WOS:000501732600012 | Rights: | © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2020 |
Appears in Collections: | Research publications |
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