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Correlation between treatment effects on response rate and progression-free survival and overall survival in trials of targeted therapies in molecularly enriched populations

Benjamin Solomon, Herbert H. Loong, Yvonne Summers, Zachary M. Thomas, Pearl Plernjit French, Boris K. Lin, Andreas Sashegyi, Jennifer Moriatis Wolf, James Chih‐Hsin Yang, Alexander Drilon

2022ESMO Open19 citationsDOIOpen Access PDF

Abstract

•Meta-analysis of trials comparing an agent targeting a primary oncogenic driver versus nontargeted therapy.•Correlative analysis showed that ORR effect size and log PFS HR were strongly correlated.•ORR effect size was positively correlated with the log OS HR ratio, but more weakly.•Analysis of the treatment effects between OS and PFS found no correlation.•Results support the use of a high ORR forming the basis of an initial regulatory approval in biomarker-driven studies. BackgroundThe number of randomized trials of agents targeting oncogene-addicted tumors has surged in the past 10 years. Using a meta-analysis, we explored whether improvements in objective response rate (ORR) in comparative trials using targeted agents could serve as a potential surrogate endpoint for improvements in progression-free survival (PFS) or overall survival (OS) in populations with oncogene-addicted cancer.Patients and methodsUsing commercial text mining software I2E, we searched ClinicalTrials.gov and MEDLINE databases for randomized, phase III trials based on prospectively defined criteria, including (i) use of agents targeting EGFR activating mutations, ALK rearrangements, BRAF V600E or V600K mutations, and BCR-ABL fusion protein; (ii) molecularly enriched trial population or subpopulation; (iii) control arm only randomized to chemo/cytotoxic therapy. Correlative analyses were performed using ORR, OS, and PFS data from trials that met these criteria.ResultsA total of 62 trials were identified; 15 met all of the prespecified criteria. The ORR effect size (both the difference in ORR between arms and the log odds ratio) and log PFS hazard ratio were strongly correlated: –0.78 (P = 0.0007) for the ORR difference model; –0.74 (P = 0.0017) for the log odds ratio model. ORR effect size was positively correlated with the log OS hazard ratio, but more weakly: –0.67 (P = 0.013) for the ORR difference model and –0.58 (P = 0.036) for the log odds ratio model. Analysis of the treatment effects between OS and PFS found no correlation.ConclusionsThese analyses identified a strong correlation between treatment effects on ORR and PFS in randomized clinical trials investigating agents targeting oncogene-driven cancers. A weaker correlation was observed between ORR and OS. These meta-analysis results support the use of a high ORR forming the basis of an initial regulatory approval in biomarker-driven studies. The number of randomized trials of agents targeting oncogene-addicted tumors has surged in the past 10 years. Using a meta-analysis, we explored whether improvements in objective response rate (ORR) in comparative trials using targeted agents could serve as a potential surrogate endpoint for improvements in progression-free survival (PFS) or overall survival (OS) in populations with oncogene-addicted cancer. Using commercial text mining software I2E, we searched ClinicalTrials.gov and MEDLINE databases for randomized, phase III trials based on prospectively defined criteria, including (i) use of agents targeting EGFR activating mutations, ALK rearrangements, BRAF V600E or V600K mutations, and BCR-ABL fusion protein; (ii) molecularly enriched trial population or subpopulation; (iii) control arm only randomized to chemo/cytotoxic therapy. Correlative analyses were performed using ORR, OS, and PFS data from trials that met these criteria. A total of 62 trials were identified; 15 met all of the prespecified criteria. The ORR effect size (both the difference in ORR between arms and the log odds ratio) and log PFS hazard ratio were strongly correlated: –0.78 (P = 0.0007) for the ORR difference model; –0.74 (P = 0.0017) for the log odds ratio model. ORR effect size was positively correlated with the log OS hazard ratio, but more weakly: –0.67 (P = 0.013) for the ORR difference model and –0.58 (P = 0.036) for the log odds ratio model. Analysis of the treatment effects between OS and PFS found no correlation. These analyses identified a strong correlation between treatment effects on ORR and PFS in randomized clinical trials investigating agents targeting oncogene-driven cancers. A weaker correlation was observed between ORR and OS. These meta-analysis results support the use of a high ORR forming the basis of an initial regulatory approval in biomarker-driven studies.

Topics & Concepts

Hazard ratioOdds ratioMedicineInternal medicineOncologyRandomized controlled trialProgression-free survivalMeta-analysisPopulationConfidence intervalClinical endpointOverall survivalEnvironmental healthLung Cancer Treatments and MutationsStatistical Methods in Clinical TrialsAdvanced Causal Inference Techniques