Assessment of Treatment Effects and Long-term Benefits in Immune Checkpoint Inhibitor Trials Using the Flexible Parametric Cure Model: A Systematic Review.


Journal

JAMA network open
ISSN: 2574-3805
Titre abrégé: JAMA Netw Open
Pays: United States
ID NLM: 101729235

Informations de publication

Date de publication:
01 12 2021
Historique:
entrez: 21 12 2021
pubmed: 22 12 2021
medline: 18 1 2022
Statut: epublish

Résumé

Compared with standard cytotoxic therapies, randomized immune checkpoint inhibitor (ICI) phase 3 trials reveal delayed benefits in terms of patient survival and/or long-term response. Such outcomes generally violate the assumption of proportional hazards, and the classical Cox proportional hazards regression model is therefore unsuitable for these types of analyses. To evaluate the ability of the flexible parametric cure model (FPCM) to estimate treatment effects and long-term responder fractions (LRFs) independently of prespecified time points. This systematic review used reconstructed individual patient data from ICI advanced or metastatic melanoma and lung cancer phase 3 trials extracted from the literature. Trials published between January 1, 2010, and October 1, 2019, with long-term follow-up periods (maximum follow-up, ≥36 months in first line and ≥30 months otherwise) were selected to identify LRFs. Individual patient data for progression-free survival were reconstructed from the published randomized ICI phase 3 trial results. The FPCM was applied to estimate treatment effects on the overall population and on the following components of the population: LRF and progression-free survival in non-long-term responders. Results obtained were compared with treatment effects estimated using the Cox proportional hazards regression model. In this systematic review, among the 23 comparisons studied using the FPCM, a statistically significant association between the time-to-event component and experimental treatment was observed in the main analyses and confirmed in the sensitivity analyses of 18 comparisons. Results were discordant for 4 comparisons that were not significant by the Cox proportional hazards regression model. The LRFs varied from 1.5% to 12.7% for the control arms and from 4.6% to 38.8% for the experimental arms. Differences in LRFs varied from 2% to 29% and were significantly increased in the experimental compared with the control arms, except for 4 comparisons. This systematic review of reconstructed individual patient data found that the FPCM was a complementary approach that provided a comprehensive and pertinent evaluation of benefit and risk by assessing whether ICI treatment was associated with an increased probability of patients being long-term responders or with an improved progression-free survival in patients who were not long-term responders.

Identifiants

pubmed: 34932105
pii: 2787282
doi: 10.1001/jamanetworkopen.2021.39573
pmc: PMC8693223
doi:

Substances chimiques

Immune Checkpoint Inhibitors 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2139573

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Auteurs

Thomas Filleron (T)

Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer Toulouse, Toulouse, France.

Marine Bachelier (M)

Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer Toulouse, Toulouse, France.

Julien Mazieres (J)

Department of Pneumology, Centre Hospitalier Universitaire de Toulouse Larrey, Toulouse, France.

Maurice Pérol (M)

Department of Medical Oncology, Léon Bérard Cancer Center, Lyon, France.

Nicolas Meyer (N)

Institut Universitaire du Cancer Toulouse Oncopôle, Toulouse, France.

Elodie Martin (E)

Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer Toulouse, Toulouse, France.

Fanny Mathevet (F)

Department of Biostatistics, Institut Claudius Regaud, Institut Universitaire du Cancer Toulouse, Toulouse, France.

Jean-Yves Dauxois (JY)

Institut de Mathématiques de Toulouse, Université de Toulouse, Centre National de la Recherche Scientifique, Institut National des Sciences Appliquées de Toulouse, Toulouse, France.

Raphael Porcher (R)

Assistance Publique des Hôpitaux de Paris, Hôpital Hôtel Dieu, Centre d'Épidémiologie Clinique, INSERM U1153, Paris, France.

Jean-Pierre Delord (JP)

Department of Medical Oncology, Institut Claudius Regaud, Institut Universitaire du Cancer Toulouse, Toulouse, France.

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Classifications MeSH