{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T03:59:18Z","timestamp":1773287958293,"version":"3.50.1"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1","funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["75N91019D00024"],"award-info":[{"award-number":["75N91019D00024"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,31]]},"abstract":"<jats:title>SUMMARY<\/jats:title>\n                  <jats:p>We introduce a computationally efficient and general approach for utilizing multiple, possibly interval-censored, data streams to study complex biomedical endpoints using multistate semi-Markov models. Our motivating application is the REGEN-2069 trial, which investigated the protective efficacy (PE) of the monoclonal antibody combination REGEN-COV against SARS-CoV-2 when administered prophylactically to individuals in households at high risk of secondary transmission. Using data on symptom onset, episodic RT-qPCR sampling, and serological testing, we estimate the PE of REGEN-COV for asymptomatic infection, its effect on seroconversion following infection, and the duration of viral shedding. We find that REGEN-COV reduced the risk of asymptomatic infection and the duration of viral shedding, and led to lower rates of seroconversion among asymptomatically infected participants. Our algorithm for fitting semi-Markov models to interval-censored data employs a Monte Carlo expectation\u2013maximization algorithm combined with importance sampling to efficiently address the intractability of the marginal likelihood when data are intermittently observed. Our algorithm provides substantial computational improvements over existing methods and allows us to fit semi-parametric models despite complex coarsening of the data.<\/jats:p>","DOI":"10.1093\/biostatistics\/kxaf038","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T17:25:17Z","timestamp":1763573117000},"source":"Crossref","is-referenced-by-count":0,"title":["Assessing treatment efficacy for interval-censored endpoints using multistate semi-Markov models fit to multiple data streams"],"prefix":"10.1093","volume":"26","author":[{"given":"Rapha\u00ebl","family":"Morsomme","sequence":"first","affiliation":[{"name":"Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health , 5601 Fishers Lane , Rockville, Maryland 20852,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"C Jason","family":"Liang","sequence":"additional","affiliation":[{"name":"Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health , 5601 Fishers Lane , Rockville, Maryland 20852,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2810-478X","authenticated-orcid":false,"given":"Allyson","family":"Mateja","sequence":"additional","affiliation":[{"name":"Clinical Monitoring Research Program Directorate, Frederick National Laboratory for Cancer Research , 8560 Progress Drive , Frederick, Maryland 21701,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dean A","family":"Follmann","sequence":"additional","affiliation":[{"name":"Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health , 5601 Fishers Lane , Rockville, Maryland 20852,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Meagan P","family":"O\u2019Brien","sequence":"additional","affiliation":[{"name":"Regeneron Pharmaceuticles , 777 Old Saw Mill River Road , Tarrytown, New York 10591,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenguang","family":"Wang","sequence":"additional","affiliation":[{"name":"Regeneron Pharmaceuticles , 777 Old Saw Mill River Road , Tarrytown, New York 10591,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6361-702X","authenticated-orcid":false,"given":"Jonathan","family":"Fintzi","sequence":"additional","affiliation":[{"name":"Statistical Methodology and Innovation, Bristol Myers Squibb , 3551 Lawrenceville Road , Lawrence Township, New Jersey 08648,","place":["United 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