Assessing Long-term Treatment Benefits Using Complementary Statistical Approaches: An In Silico Analysis of the Phase III Keynote-045 and Checkmate-214 Immune Checkpoint Inhibitor Trials.

Flexible parametric survival model with cure Immune checkpoint inhibitor Long-term benefit Milestone survival

Journal

European urology
ISSN: 1873-7560
Titre abrégé: Eur Urol
Pays: Switzerland
ID NLM: 7512719

Informations de publication

Date de publication:
25 Feb 2023
Historique:
received: 23 09 2022
revised: 17 01 2023
accepted: 08 02 2023
entrez: 27 2 2023
pubmed: 28 2 2023
medline: 28 2 2023
Statut: aheadofprint

Résumé

The Keynote-045 trial illustrates that the long-term benefit (LTB) of treatment does not always translate to improved progression-free survival (PFS). Milestone survival and flexible parametric survival model with cure (FPCM) have been proposed as complementary statistical approaches to more comprehensively evaluate LTBs of treatments. The current study compares milestone survival and FPCM analyses to evaluate treatment effects of immune checkpoint inhibitor (ICI) phase III trials. Individual patient data, from initial and follow-up analyses of Keynote-045 (urothelial cancer) and Checkmate-214 (advanced renal cell carcinoma), were reconstructed for PFS. Each trial was reanalyzed using the Cox proportional hazard regression and two complementary methods (milestone survival and FPCM) to estimate treatment impact on the LTB. For each trial, there was evidence of nonproportional hazards. For the long-term analysis of the Keynote-045 trial, FPCM identified a time-dependent effect on PFS, but the Cox model found no statistical difference in PFS (hazard ratio, 0.90; 95% confidence interval, 0.75-1.08). Milestone survival and FPCM identified improvements in the LTB fractions. This was consistent with the results from the reanalysis of Keynote-045, based on the shorter follow-up, although the LTB fraction was not retained. The increase in PFS in Checkmate-214 was identified by both Cox model and FPCM. Experimental treatment-dependent improvement in the LTB fraction was demonstrated using milestone survival and FPCM. The LTB fraction estimated with FPCM was consistent with the results from the reanalysis of the shorter follow-up period. Although ICIs show substantial shifts toward LTBs in terms of PFS, based on a conventional Kaplan-Meier or Cox model analysis, our approach provides an alternative assessment of benefit-risk ratios for new therapeutics and facilitates communicating risk to patients. Kidney patients treated with ICIs can be counseled that they are potentially cured, but future work will need to definitively validate this conclusion. Although immune checkpoint inhibitor treatments show substantial shifts toward long-term benefits in terms of progression-free survival, a more rigorous attempt to quantify this shift, rather than simply using a Kaplan-Meier estimate or comparing progression-free survival curves using the classic Cox model, is warranted. Our results suggest that advanced renal cell carcinoma patients who had not received a previous treatment are functionally cured by nivolumab and ipilimumab, which is not the case for second-line urothelial carcinoma.

Sections du résumé

BACKGROUND BACKGROUND
The Keynote-045 trial illustrates that the long-term benefit (LTB) of treatment does not always translate to improved progression-free survival (PFS). Milestone survival and flexible parametric survival model with cure (FPCM) have been proposed as complementary statistical approaches to more comprehensively evaluate LTBs of treatments.
OBJECTIVE OBJECTIVE
The current study compares milestone survival and FPCM analyses to evaluate treatment effects of immune checkpoint inhibitor (ICI) phase III trials.
DESIGN, SETTING, AND PARTICIPANTS METHODS
Individual patient data, from initial and follow-up analyses of Keynote-045 (urothelial cancer) and Checkmate-214 (advanced renal cell carcinoma), were reconstructed for PFS.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS METHODS
Each trial was reanalyzed using the Cox proportional hazard regression and two complementary methods (milestone survival and FPCM) to estimate treatment impact on the LTB.
RESULTS AND LIMITATIONS CONCLUSIONS
For each trial, there was evidence of nonproportional hazards. For the long-term analysis of the Keynote-045 trial, FPCM identified a time-dependent effect on PFS, but the Cox model found no statistical difference in PFS (hazard ratio, 0.90; 95% confidence interval, 0.75-1.08). Milestone survival and FPCM identified improvements in the LTB fractions. This was consistent with the results from the reanalysis of Keynote-045, based on the shorter follow-up, although the LTB fraction was not retained. The increase in PFS in Checkmate-214 was identified by both Cox model and FPCM. Experimental treatment-dependent improvement in the LTB fraction was demonstrated using milestone survival and FPCM. The LTB fraction estimated with FPCM was consistent with the results from the reanalysis of the shorter follow-up period.
CONCLUSIONS CONCLUSIONS
Although ICIs show substantial shifts toward LTBs in terms of PFS, based on a conventional Kaplan-Meier or Cox model analysis, our approach provides an alternative assessment of benefit-risk ratios for new therapeutics and facilitates communicating risk to patients. Kidney patients treated with ICIs can be counseled that they are potentially cured, but future work will need to definitively validate this conclusion.
PATIENT SUMMARY RESULTS
Although immune checkpoint inhibitor treatments show substantial shifts toward long-term benefits in terms of progression-free survival, a more rigorous attempt to quantify this shift, rather than simply using a Kaplan-Meier estimate or comparing progression-free survival curves using the classic Cox model, is warranted. Our results suggest that advanced renal cell carcinoma patients who had not received a previous treatment are functionally cured by nivolumab and ipilimumab, which is not the case for second-line urothelial carcinoma.

Identifiants

pubmed: 36849297
pii: S0302-2838(23)02619-2
doi: 10.1016/j.eururo.2023.02.011
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Commentaires et corrections

Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Ana Cavillon (A)

Biostatistics & Health Data Science Unit, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France.

Damien Pouessel (D)

Department of Medical Oncology, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France.

Nadine Houédé (N)

Institut de Cancérologie du Gard, CHU Nîmes, Nîmes Cedex, France.

Fanny Mathevet (F)

Biostatistics & Health Data Science Unit, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France.

Jean Yves Dauxois (JY)

Institut de Mathématiques de Toulouse, UMR 5219, Université de Toulouse, CNRS, INSA, Toulouse, France.

Christine Chevreau (C)

Department of Medical Oncology, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France.

Stéphane Culine (S)

Department of Medical Oncology, UCOG, AP-HP, Saint-Louis Hospital, Paris, France; Paris Curie University, Paris, France.

Jean-Pierre Delord (JP)

Department of Medical Oncology, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France.

Raphael Porcher (R)

Université Paris Cité, Centre de Recherche Épidémiologie et Statistiques (CRESS-UMR1153), INSERM, INRAE, Paris, France; Centre d'Épidémiologie Clinique, AP-HP, Hôtel-Dieu, Paris, France.

Thomas Filleron (T)

Biostatistics & Health Data Science Unit, Institut Claudius Regaud - IUCT-Oncopole, Toulouse, France. Electronic address: Filleron.thomas@iuct-oncopole.fr.

Classifications MeSH