17 research outputs found
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
No full textInternational audienceBackgroundThe 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.ObjectiveThe current study compares milestone survival and FPCM analyses to evaluate treatment effects of immune checkpoint inhibitor (ICI) phase III trials.Design, setting, and participantsIndividual 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 analysisEach 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 limitationsFor 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.ConclusionsAlthough 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
Assessment of Treatment Effects and Long-term Benefits in Immune Checkpoint Inhibitor Trials Using the Flexible Parametric Cure Model: A Systematic Review
No full textInternational audienceImportanceCompared 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.ObjectiveTo 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.Evidence ReviewThis 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.FindingsIn 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.Conclusions and RelevanceThis 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
