Importance: Approval by the US Food and Drug Administration of immune checkpoint inhibition (ICI) for advanced gastroesophageal cancer (aGEC) irrespective of PD-L1 status has generated controversy. Exploratory analyses from individual trials indicate a lack of meaningful benefit from ICI in patients with absent or low PD-L1 expression; however, analysis of a single variable while ignoring others may not consider the instability inherent in exploratory analyses. Objective: To systematically examine the predictive value of tissue-based PD-L1 status compared with that of other variables for ICI benefit in aGEC to assess its stability. Data Sources: MEDLINE, Embase, Scopus, Web of Science, Cochrane Central Register (2000-2022). Study Selection, Data Extraction, and Synthesis: Randomized clinical trials (RCTs) were included of adults with aGEC (adenocarcinoma [AC] or squamous cell carcinoma [SCC]) randomized to anti-PD-1 or PD-L1-containing treatment vs standard of care (SOC). Study screening, data abstraction, and bias assessment were completed independently by 2 reviewers. Of 5752 records screened, 26 were assessed for eligibility; 17 trials were included in the analysis. Main Outcomes and Measures: The prespecified primary end point was overall survival. The mean hazard ratio (HR) for ICI vs SOC was calculated (random-effects model). Predictive values were quantified by calculating the ratio of mean HRs between 2 levels of each variable. Results: In all, 17 RCTs (9 first line, 8 after first line) at low risk of bias and 14 predictive variables were included, totaling 11 166 participants (5067 with SCC, 6099 with ACC; 77.6% were male and 22.4% were female; 59.5% of patients were younger than 65 years, 40.5% were 65 years or older). Among patients with SCCs, PD-L1 tumor proportion score (TPS) was the strongest predictor of ICI benefit (HR, 0.60 [95% CI, 0.53-0.68] for high TPS; and HR, 0.84 [95% CI, 0.75-0.95] for low TPS), yielding a predictive value of 41.0% favoring high TPS (vs ≤16.0% for other variables). Among patients with AC, PD-L1 combined positive score (CPS) was the strongest predictor (after microsatellite instability high status) of ICI benefit (HR, 0.73 [95% CI, 0.66-0.81] for high CPS; and HR, 0.95 [95% CI, 0.84-1.07] for low CPS), yielding a predictive value of 29.4% favoring CPS-high (vs ≤12.9% for other variables). Head-to-head analyses of trials containing both levels of a variable and/or having similar design generally yielded consistent results. Conclusions and Relevance: Tissue-based PD-L1 expression, more than any variable other than microsatellite instability-high, identified varying degrees of benefit from ICI-containing therapy vs SOC among patients with aGEC in 17 RCTs.
Importance: Approval by the US Food and Drug Administration of immune checkpoint inhibition (ICI) for advanced gastroesophageal cancer (aGEC) irrespective of PD-L1 status has generated controversy. Exploratory analyses from individual trials indicate a lack of meaningful benefit from ICI in patients with absent or low PD-L1 expression; however, analysis of a single variable while ignoring others may not consider the instability inherent in exploratory analyses. Objective: To systematically examine the predictive value of tissue-based PD-L1 status compared with that of other variables for ICI benefit in aGEC to assess its stability. Data Sources: MEDLINE, Embase, Scopus, Web of Science, Cochrane Central Register (2000-2022). Study Selection, Data Extraction, and Synthesis: Randomized clinical trials (RCTs) were included of adults with aGEC (adenocarcinoma [AC] or squamous cell carcinoma [SCC]) randomized to anti-PD-1 or PD-L1-containing treatment vs standard of care (SOC). Study screening, data abstraction, and bias assessment were completed independently by 2 reviewers. Of 5752 records screened, 26 were assessed for eligibility; 17 trials were included in the analysis. Main Outcomes and Measures: The prespecified primary end point was overall survival. The mean hazard ratio (HR) for ICI vs SOC was calculated (random-effects model). Predictive values were quantified by calculating the ratio of mean HRs between 2 levels of each variable. Results: In all, 17 RCTs (9 first line, 8 after first line) at low risk of bias and 14 predictive variables were included, totaling 11 166 participants (5067 with SCC, 6099 with ACC; 77.6% were male and 22.4% were female; 59.5% of patients were younger than 65 years, 40.5% were 65 years or older). Among patients with SCCs, PD-L1 tumor proportion score (TPS) was the strongest predictor of ICI benefit (HR, 0.60 [95% CI, 0.53-0.68] for high TPS; and HR, 0.84 [95% CI, 0.75-0.95] for low TPS), yielding a predictive value of 41.0% favoring high TPS (vs ≤16.0% for other variables). Among patients with AC, PD-L1 combined positive score (CPS) was the strongest predictor (after microsatellite instability high status) of ICI benefit (HR, 0.73 [95% CI, 0.66-0.81] for high CPS; and HR, 0.95 [95% CI, 0.84-1.07] for low CPS), yielding a predictive value of 29.4% favoring CPS-high (vs ≤12.9% for other variables). Head-to-head analyses of trials containing both levels of a variable and/or having similar design generally yielded consistent results. Conclusions and Relevance: Tissue-based PD-L1 expression, more than any variable other than microsatellite instability-high, identified varying degrees of benefit from ICI-containing therapy vs SOC among patients with aGEC in 17 RCTs.
Authors: Alessandro Liberati; Douglas G Altman; Jennifer Tetzlaff; Cynthia Mulrow; Peter C Gøtzsche; John P A Ioannidis; Mike Clarke; P J Devereaux; Jos Kleijnen; David Moher Journal: J Clin Epidemiol Date: 2009-07-23 Impact factor: 6.437
Authors: Edward B Garon; Naiyer A Rizvi; Rina Hui; Natasha Leighl; Ani S Balmanoukian; Joseph Paul Eder; Amita Patnaik; Charu Aggarwal; Matthew Gubens; Leora Horn; Enric Carcereny; Myung-Ju Ahn; Enriqueta Felip; Jong-Seok Lee; Matthew D Hellmann; Omid Hamid; Jonathan W Goldman; Jean-Charles Soria; Marisa Dolled-Filhart; Ruth Z Rutledge; Jin Zhang; Jared K Lunceford; Reshma Rangwala; Gregory M Lubiniecki; Charlotte Roach; Kenneth Emancipator; Leena Gandhi Journal: N Engl J Med Date: 2015-04-19 Impact factor: 91.245
Authors: Roy S Herbst; Jean-Charles Soria; Marcin Kowanetz; Gregg D Fine; Omid Hamid; Michael S Gordon; Jeffery A Sosman; David F McDermott; John D Powderly; Scott N Gettinger; Holbrook E K Kohrt; Leora Horn; Donald P Lawrence; Sandra Rost; Maya Leabman; Yuanyuan Xiao; Ahmad Mokatrin; Hartmut Koeppen; Priti S Hegde; Ira Mellman; Daniel S Chen; F Stephen Hodi Journal: Nature Date: 2014-11-27 Impact factor: 49.962
Authors: Mohamed E Salem; Alberto Puccini; Joanne Xiu; Derek Raghavan; Heinz-Josef Lenz; W Michael Korn; Anthony F Shields; Philip A Philip; John L Marshall; Richard M Goldberg Journal: Oncologist Date: 2018-06-04
Authors: Julian P T Higgins; Douglas G Altman; Peter C Gøtzsche; Peter Jüni; David Moher; Andrew D Oxman; Jelena Savovic; Kenneth F Schulz; Laura Weeks; Jonathan A C Sterne Journal: BMJ Date: 2011-10-18
Authors: Y-J Bang; E Yañez Ruiz; E Van Cutsem; K-W Lee; L Wyrwicz; M Schenker; M Alsina; M-H Ryu; H-C Chung; L Evesque; S-E Al-Batran; S H Park; M Lichinitser; N Boku; M H Moehler; J Hong; H Xiong; R Hallwachs; I Conti; J Taieb Journal: Ann Oncol Date: 2018-10-01 Impact factor: 32.976