Surrogate Endpoints in Oncology Clinical Trials: Are We There Yet? From a Practical Perspective Qian Shi, PhD., Professor of Biostatistics and Oncology ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop September 24, 2020 ©2020 MFMER | slide-1 What We Know ©2020 MFMER | slide-2 Surrogate Endpoints Make drug development Un-validated surrogate endpoints can produce erroneous faster, more efficient, safer, conclusions regarding the efficacy or safety of therapies and more feasible Shi and Sargent, Int J Clin Oncol. 2009 ©2020 MFMER | slide-3 Individual- vs. Trial-level Surrogacy Prognostic association Treatment effect correlation R2 = 0.85 Prognostic does NOT guarantee surrogacy Munshi N et al., JAMA Oncol, 2017 ©2020 MFMER | slide-4 Trial-level Surrogacy – Primary Validation Treatment effect correlation R2 = 0.85 Context of Use: A substitute for “true” clinical endpoint in future trials * 2 ** 2 R WLS and R Copula *Sargent et al. JCO, 2005/2007; **Buyse et al. Biostatistics, 2000 ©2020 MFMER | slide-5 What We Have Learned ©2020 MFMER | slide-6 R2 and R2 Critical trial-level factors that impact the WLS Copula estimation accuracy and variability: most commonly used estimates • Number of trials • Range of the treatment effect sizes Variability Bias Shi et al. CSDA, 2011 ©2020 MFMER | slide-7 Subgroups in All • Previously untreated follicular lymphoma Comers Trials • Surrogate endpoint: CR30 • True clinical endpoint: PFS Shi et al, JCO 2017 ©2020 MFMER | slide-8 Treatment Mechanisms • Previously untreated advance colorectal cancer • Surrogate endpoint: PFS • True clinical endpoint: OS Pre-biologics Era Post-biologics Era Buyse et al, JCO 2007 Shi et al, JCO 2014 ©2020 MFMER | slide-9 Changing Standard of • Early stage colon caner after curative resection Care • Surrogate endpoint: DFS • True clinical endpoint: OS Sargent et al, Shi et al, ASCO JCO 2007 2019 Oral •3-year DFS •Stage III •Stage II & III •2-year DFS •Oxa /IRi •Stage III •5FU •Stage II & III •Oxa/IRI +/- •5FU biologics Sargent et al, Sargent, et al, JCO 2005 EJC 2011 5FU+LVProlonged SAR FOLFOX Prolonged SAR, TTR, OS 1978 1995 2007 1998 2004 2009 Shi et al, JCO 2013 Salem et al, ASCO GI poster 2018 ©2020 MFMER | slide-10 Novel Biomarker – New Challenges ©2020 MFMER | slide-11 Surrogate Endpoints in Oncology Trials Endpoint Events Measures Surveillance True clinical Overall Survival Deaths Death certificates Patient contact endpoint Deaths Imaging, blood test, Routine examinations Traditional surrogate Disease-free BM biopsy, etc. endpoint Survival (SOC, standard Disease Status (RECIST, IMWG) processes) Study specific PSA, MRD, ctDNA, Biomarker Biomarker Status Treatment specific cognitive functions Novel Outside of routine examination surrogate endpoint Composite Biomarker status + Disease status Endpoint involving Disease Status MRD requiring CR dependent Biomarker Deaths ©2020 MFMER | slide-12 Surrogate Endpoints in Oncology Trials Endpoint Events Measures Surveillance Source of heterogeneities True clinical Overall Survival• Patient selectionDeaths for testingDeath certificates Patient contact endpoint • Testing methods Deaths Imaging, blood test, Routine examinations Traditional surrogate Disease-free • Testing time points BM biopsy, etc. endpoint Survival (SOC, standard Disease Status (RECIST, IMWG) processes) Study specific PSA, MRD, ctDNA, Biomarker Biomarker Status Treatment specific cognitive functions Novel Outside of routine examination surrogate endpoint Composite Biomarker status + Disease status Endpoint involving Disease Status MRD requiring CR dependent Biomarker Deaths ©2020 MFMER | slide-13 Sensitivity Level – Deeper Responses Defined by Biomarkers Minimal Residual Disease Clinical Utility Lower Higher • More accurately defining Sensitivity Sensitivity cure Non- MRD+ MRD+ responders Statistical Challenges: Conversion rate differ per • Testing • Assay Conversion • Laboratory • Specimen Responders MRD- MRD- • Disease characteristics Response Rate ↓ • Regimen ©2020 MFMER | slide-14 Dynamics of Responses Over Time RECIST Responses Response Reversing? Directing Treatment? MRD Responses Response Lasts? ©2020 MFMER | slide-15 Biomarker Testing – Protocol Planning to Data Collection Number of Testing • Single vs. many • Varying across patients Timing of Testing • Treatment dependence • Response dependence Patient Selection • Response dependence • Randomization ©2020 MFMER | slide-16 Proposals ©2020 MFMER | slide-17 General Criteria and Principles of Developing Candidate Surrogate Endpoints • Clinically meaningful: • Capture the targeted treatment effect • Correlates the treatment effect on true endpoint • Statistically meaningful: • Programmable derivations based on necessary data elements • Consistency across all trials • Consistency from evaluation to future use • Practically useful in further trials: • Provides utility advantages compared to the true endpoints • Data elements needed can be routinely collected in the future trials ©2020 MFMER | slide-18 IPD from RCTs are Critical for Surrogacy Evaluations • Individual patient data (IPD) from RCTs • Unbiased estimates of treatment effects within trials • Consistent derivations across trials • Evaluate (and develop) surrogate endpoints with no published treatment effect data • RCT selections: Inclusive • Prespecified inclusion/exclusion criteria • More is better (specificity) • Population heterogeneities (universality) • Treatment class and treatment sequencing (universality) ©2020 MFMER | slide-19 Call for Long-term and Large Scale of Collaborations • Harmonization of testing methods • Common testing time points • Common data collection •Share Data!! ©2020 MFMER | slide-20 QUESTIONS & ANSWERS ©2020 MFMER | slide-21.