Hormuzd A Katki, Philip C Prorok, Philip E Castle, Lori M Minasian, Paul F Pinsky
{"title":"Increasing power in screening trials by testing control-arm specimens: application to multicancer detection screening","authors":"Hormuzd A Katki, Philip C Prorok, Philip E Castle, Lori M Minasian, Paul F Pinsky","doi":"10.1093/jnci/djae218","DOIUrl":null,"url":null,"abstract":"Background Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the “intended effect” (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests. Methods We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial—colorectal component [PLCO-CRC]). Results Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 6-fold (NLST), 33-fold (MINN-FOBT-A), or 260 000-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 25% (NLST), 47% (MINN-FOBT-A), or 63% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives. Conclusions Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.","PeriodicalId":501635,"journal":{"name":"Journal of the National Cancer Institute","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the National Cancer Institute","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jnci/djae218","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background Cancer screening trials have required large sample sizes and long time-horizons to demonstrate cancer mortality reductions, the primary goal of cancer screening. We examine assumptions and potential power gains from exploiting information from testing control-arm specimens, which we call the “intended effect” (IE) analysis that we explain in detail herein. The IE analysis is particularly suited to tests that can be conducted on stored specimens in the control arm, such as stored blood for multicancer detection (MCD) tests. Methods We simulated hypothetical MCD screening trials to compare power and sample size for the standard vs IE analysis. Under two assumptions that we detail herein, we projected the IE analysis for 3 existing screening trials (National Lung Screening Trial [NLST], Minnesota Colon Cancer Control Study [MINN-FOBT-A], and Prostate, Lung, Colorectal, Ovarian Cancer Screening Trial—colorectal component [PLCO-CRC]). Results Compared with the standard analysis for the 3 existing trials, the IE design could have reduced cancer-specific mortality P values 6-fold (NLST), 33-fold (MINN-FOBT-A), or 260 000-fold (PLCO-CRC) or, alternately, reduced sample size (90% power) by 25% (NLST), 47% (MINN-FOBT-A), or 63% (PLCO-CRC). For potential MCD trial designs requiring 100 000 subjects per arm to achieve 90% power for multicancer mortality for the standard analysis, the IE analysis achieves 90% power for only 37 500-50 000 per arm, depending on assumptions concerning control-arm test-positives. Conclusions Testing stored specimens in the control arm of screening trials to conduct the IE analysis could substantially increase power to reduce sample size or accelerate trials and could provide particularly strong power gains for MCD tests.