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Comparing Survival Outcomes for Advanced Cancer Patients Who Received Complex Genomic Profiling Using a Synthetic Control Arm

Sophie O’Haire, Koen Degeling, Fanny Franchini, Ben Tran, Stephen J. Luen, Clara Gaff, Kortnye Smith, Stephen B. Fox, Jayesh Desai, Maarten J. IJzerman

2022Targeted Oncology16 citationsDOIOpen Access PDF

Abstract

BACKGROUND: Complex genomic profiling (CGP) has transformed cancer treatment decision making, yet there is a lack of robust and quantifiable evidence for how utilisation of CGP improves patient outcomes. OBJECTIVE: This study evaluated cohort level clinical effectiveness of CGP to improve overall survival (OS) in real-world advanced cancer patients using a registry-based matched control population. PATIENTS AND METHODS: Two cohorts of advanced and refractory cancer patients were seen in consecutive series for early phase trial enrolment consideration. The first cohort (CGP group) accessed tumour profiling via a research study; while the second cohort that followed was not profiled. Overall survival between cohorts was compared using Kaplan-Meier curves and Cox proportional hazard models. Potential confounding was analysed and adjusted for using stabilised weights based on propensity scores. RESULTS: Within the CGP group, 25 (17.6%) patients received treatment informed by CGP results and this subgroup had significantly improved survival compared with CGP patients in whom results did not impact their treatment (unadjusted HR = 0.44, (0.22-0.88), p = 0.02). However, when comparing the entire CGP cohort with the No CGP cohort, no significant survival benefit was evident with adjusted median OS for CGP of 13.5 months (9.2-17.0) compared with 11.0 (9.2-17.4) for No CGP (adjusted HR = 0.92, (0.65-1.30), p = 0.63). CONCLUSIONS: This study utilised real-world data to simulate a control arm and quantify the clinical effectiveness of genomic testing. The magnitude of survival benefit for patients who had CGP result-led treatments was insufficient to drive an overall survival gain for the entire tested population. Translation of CGP into clinics requires strategies to ensure higher rates of tested patients obtain clinical benefit to deliver on the value proposition of CGP in an advanced cancer population.

Topics & Concepts

MedicineHazard ratioCohortInternal medicineOncologyProportional hazards modelSurvival analysisConfoundingPropensity score matchingCohort studyClinical trialPopulationConfidence intervalEnvironmental healthCancer Genomics and DiagnosticsBreast Cancer Treatment StudiesBRCA gene mutations in cancer