Deviation from the Proportional Hazards Assumption in Randomized Phase 3 Clinical Trials in Oncology: Prevalence, Associated Factors, and Implications.


Journal

Clinical cancer research : an official journal of the American Association for Cancer Research
ISSN: 1557-3265
Titre abrégé: Clin Cancer Res
Pays: United States
ID NLM: 9502500

Informations de publication

Date de publication:
01 11 2019
Historique:
received: 07 12 2018
revised: 25 05 2019
accepted: 15 07 2019
pubmed: 28 7 2019
medline: 9 9 2020
entrez: 27 7 2019
Statut: ppublish

Résumé

Deviations from proportional hazards (DPHs), which may be more prevalent in the era of precision medicine and immunotherapy, can lead to underpowered trials or misleading conclusions. We used a meta-analytic approach to estimate DPHs across cancer trials, investigate associated factors, and evaluate data-analysis approaches for future trials. From 152 trials, we obtained IPLD on 129,401 patients. Among 304 Kaplan-Meier figures, 75 (24.7%) exhibited evidence of DPHs, including eight of 14 (57%) KM pairs from immunotherapy trials. Trial type [immunotherapy, odds ratio (OR), 4.29; 95% confidence interval (CI), 1.11-16.6], metastatic patient population (OR, 3.18; 95% CI, 1.26-8.05), and non-OS endpoints (OR, 3.23; 95% CI, 1.79-5.88) were associated with DPHs. In immunotherapy trials, alternative statistical approaches allowed for more efficient clinical trials with fewer patients (up to 74% reduction) relative to log-rank testing. DPHs were found in a notable proportion of time-to-event outcomes in published clinical trials in oncology and was more common for immunotherapy trials and non-OS endpoints. Alternative statistical methods, without proportional hazards assumptions, should be considered in the design and analysis of clinical trials when the likelihood of DPHs is high.

Identifiants

pubmed: 31345838
pii: 1078-0432.CCR-18-3999
doi: 10.1158/1078-0432.CCR-18-3999
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6339-6345

Informations de copyright

©2019 American Association for Cancer Research.

Auteurs

Rifaquat Rahman (R)

Department of Radiation Oncology, Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts.
Program in Regulatory Science Research, Dana-Farber Cancer Institute, Boston, Massachusetts.

Geoffrey Fell (G)

Program in Regulatory Science Research, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.

Steffen Ventz (S)

Program in Regulatory Science Research, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.

Andrea Arfé (A)

Department of Decision Sciences, Bocconi University, Milano, Italy.

Alyssa M Vanderbeek (AM)

Department of Biostatistics, Columbia University Mailman School of Public Health, New York, New York.

Lorenzo Trippa (L)

Program in Regulatory Science Research, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts.
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts.

Brian M Alexander (BM)

Department of Radiation Oncology, Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts. bmalexander@lroc.harvard.edu.
Program in Regulatory Science Research, Dana-Farber Cancer Institute, Boston, Massachusetts.

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