{"title":"评估肿瘤临床试验替代终点与总生存期的相关性。","authors":"Guotao Chu, Xiaochen Zhu, Jiaju Wu, Yike Tang, Jonathan Luu, Chunsheng He, Shu-Pang Huang, Liangang Liu, Hsin-Ju Hsieh","doi":"10.1002/cpt.3613","DOIUrl":null,"url":null,"abstract":"<p><p>Surrogate endpoints, such as progression-free survival (PFS) and objective response rate (ORR), are increasingly used in oncology trials to expedite drug development and decision making. This paper evaluates the effectiveness of these surrogate endpoints by analyzing their correlations with overall survival (OS) across different cancer types, treatments, and therapy lines at both the patient and trial levels using an integrated dataset from Bristol Myers Squibb. At the patient level, correlation between OS and PFS was consistently stronger than those between OS and best overall response (BOR), suggesting that PFS may serve as a more reliable surrogate for OS. Melanoma patients exhibited the highest correlation between OS and BOR, and immune-oncology (IO) therapy patients showed stronger correlations than those treated with chemotherapy. First-line therapy patients demonstrated stronger correlations between BOR, PFS, and OS compared with second-line or third-line patients. At the trial level, the correlation between PFS hazard ratio (HR) and difference in ORR (∆ORR) was stronger than that between other endpoints. Melanoma studies exhibited strong correlations with significant P-values. IO therapy studies exhibited more consistent correlations.</p>","PeriodicalId":153,"journal":{"name":"Clinical Pharmacology & Therapeutics","volume":" ","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing Correlation between Surrogate Endpoints and Overall Survival for Oncology Clinical Trials.\",\"authors\":\"Guotao Chu, Xiaochen Zhu, Jiaju Wu, Yike Tang, Jonathan Luu, Chunsheng He, Shu-Pang Huang, Liangang Liu, Hsin-Ju Hsieh\",\"doi\":\"10.1002/cpt.3613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Surrogate endpoints, such as progression-free survival (PFS) and objective response rate (ORR), are increasingly used in oncology trials to expedite drug development and decision making. This paper evaluates the effectiveness of these surrogate endpoints by analyzing their correlations with overall survival (OS) across different cancer types, treatments, and therapy lines at both the patient and trial levels using an integrated dataset from Bristol Myers Squibb. At the patient level, correlation between OS and PFS was consistently stronger than those between OS and best overall response (BOR), suggesting that PFS may serve as a more reliable surrogate for OS. Melanoma patients exhibited the highest correlation between OS and BOR, and immune-oncology (IO) therapy patients showed stronger correlations than those treated with chemotherapy. First-line therapy patients demonstrated stronger correlations between BOR, PFS, and OS compared with second-line or third-line patients. At the trial level, the correlation between PFS hazard ratio (HR) and difference in ORR (∆ORR) was stronger than that between other endpoints. Melanoma studies exhibited strong correlations with significant P-values. IO therapy studies exhibited more consistent correlations.</p>\",\"PeriodicalId\":153,\"journal\":{\"name\":\"Clinical Pharmacology & Therapeutics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Pharmacology & Therapeutics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/cpt.3613\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Pharmacology & Therapeutics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/cpt.3613","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Assessing Correlation between Surrogate Endpoints and Overall Survival for Oncology Clinical Trials.
Surrogate endpoints, such as progression-free survival (PFS) and objective response rate (ORR), are increasingly used in oncology trials to expedite drug development and decision making. This paper evaluates the effectiveness of these surrogate endpoints by analyzing their correlations with overall survival (OS) across different cancer types, treatments, and therapy lines at both the patient and trial levels using an integrated dataset from Bristol Myers Squibb. At the patient level, correlation between OS and PFS was consistently stronger than those between OS and best overall response (BOR), suggesting that PFS may serve as a more reliable surrogate for OS. Melanoma patients exhibited the highest correlation between OS and BOR, and immune-oncology (IO) therapy patients showed stronger correlations than those treated with chemotherapy. First-line therapy patients demonstrated stronger correlations between BOR, PFS, and OS compared with second-line or third-line patients. At the trial level, the correlation between PFS hazard ratio (HR) and difference in ORR (∆ORR) was stronger than that between other endpoints. Melanoma studies exhibited strong correlations with significant P-values. IO therapy studies exhibited more consistent correlations.
期刊介绍:
Clinical Pharmacology & Therapeutics (CPT) is the authoritative cross-disciplinary journal in experimental and clinical medicine devoted to publishing advances in the nature, action, efficacy, and evaluation of therapeutics. CPT welcomes original Articles in the emerging areas of translational, predictive and personalized medicine; new therapeutic modalities including gene and cell therapies; pharmacogenomics, proteomics and metabolomics; bioinformation and applied systems biology complementing areas of pharmacokinetics and pharmacodynamics, human investigation and clinical trials, pharmacovigilence, pharmacoepidemiology, pharmacometrics, and population pharmacology.