{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T12:37:22Z","timestamp":1780576642708,"version":"3.54.1"},"reference-count":31,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100000038","name":"U.S. Food and Drug Administration","doi-asserted-by":"publisher","award":["1U01FD007937-01"],"award-info":[{"award-number":["1U01FD007937-01"]}],"id":[{"id":"10.13039\/100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,1,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"j_em-2025-0009_abs_001\">\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>In drug development, there is increasing interest in leveraging real-world data (RWD) to augment trial data and generate evidence about treatment efficacy. However, comparing patient outcomes across trial and routine clinical care settings can be susceptible to bias, namely due to differences in how and when disease assessments occur. This can introduce measurement error in RWD relative to trial standards and lead to bias when comparing endpoints. We develop a novel statistical method, survival regression calibration (SRC), to mitigate measurement error bias in time-to-event RWD outcomes and improve inferences when combining trials with RWD in oncology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_em-2025-0009_abs_002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>SRC extends upon existing regression calibration methods to address measurement error in time-to-event RWD outcomes. The method entails fitting separate Weibull regression models using trial-like (\u2018true\u2019) and real-world-like (\u2018mismeasured\u2019) outcome measures in a validation sample, and then calibrating parameter estimates in the full study according to the estimated bias in Weibull parameters. We evaluate performance of SRC under varying degrees of existing measurement error bias via simulation, and then illustrate how SRC can address measurement error when estimating median progression-free survival (mPFS) in newly diagnosed multiple myeloma RWD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_em-2025-0009_abs_003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>When measurement error exists between trial and real-world mPFS, SRC can effectively account for its resulting bias. SRC yields greater reduction in measurement error bias than standard regression calibration methods, due to its suitability for time-to-event outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"j_em-2025-0009_abs_004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Outcome measurement error is important to address when combining trials and RWD, as it may lead to biased results. Our SRC method helps mitigate such bias, improving comparability between real-world and trial endpoints and strengthening evidence of treatment efficacy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1515\/em-2025-0009","type":"journal-article","created":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T05:55:51Z","timestamp":1758866151000},"source":"Crossref","is-referenced-by-count":2,"title":["Regression calibration for time-to-event outcomes: mitigating bias due to measurement error in real-world endpoints"],"prefix":"10.1515","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2522-6623","authenticated-orcid":false,"given":"Benjamin","family":"Ackerman","sequence":"first","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan W.","family":"Gan","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juned","family":"Siddique","sequence":"additional","affiliation":[{"name":"Preventive Medicine and Psychiatry and Behavioral Science, Feinberg School of Medicine , Northwestern University , Chicago , IL , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Roose","sequence":"additional","affiliation":[{"name":"Flatiron Health , New York , NY , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer L.","family":"Lund","sequence":"additional","affiliation":[{"name":"Department of Epidemiology , University of North Carolina at Chapel Hill , Chapel Hill , NC , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Janick","family":"Weberpals","sequence":"additional","affiliation":[{"name":"Division of Pharmacoepidemiology and Pharmacoeconomics , Brigham and Women\u2019s Hospital, Harvard Medical School , Boston , MA , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jocelyn R.","family":"Wang","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Craig S.","family":"Meyer","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Hayden","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Khaled","family":"Sarsour","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashita S.","family":"Batavia","sequence":"additional","affiliation":[{"name":"426218 Johnson & Johnson , Raritan , NJ , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"2026032509461492847_j_em-2025-0009_ref_001","unstructured":"U.S. Department of Health and Human Services, Food and Drug Administration. 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