{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T16:01:29Z","timestamp":1747152089494,"version":"3.40.5"},"reference-count":18,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2023,12,18]],"date-time":"2023-12-18T00:00:00Z","timestamp":1702857600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2024,2,10]]},"abstract":"<jats:p>We focus on Bayesian inference for survival probabilities in a prime\u2010boost vaccination regime in the development of an Ebola vaccine. We are interested in the heterologous prime\u2010boost regimen (unmatched vaccine deliverys using the same antigen) due to its demonstrated durable immunity, well\u2010tolerated safety profile, and suitability as a population vaccination strategy. Our research is motivated by the need to estimate the survival probability given the administered dosage. To do so, we establish two key relationships. Firstly, we model the connection between the designed dose concentration and the induced antibody count using a Bayesian response surface model. Secondly, we model the association between the antibody count and the probability of survival when experimental subjects are exposed to the Ebola virus in a controlled setting using a Bayesian probability of survival model. Finally, we employ a combination of the two models with dose concentration as the predictor of the survival probability for a future vaccinated population. We implement our two\u2010level Bayesian model in Stan, and illustrate its use with simulated and real\u2010world data. Performance of this model is evaluated via simulation. Our work offers a new application of drug synergy models to examine prime\u2010boost vaccine efficacy, and does so using a hierarchical Bayesian framework that allows us to use dose concentration to predict survival probability.<\/jats:p>","DOI":"10.1002\/sim.9972","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:02:06Z","timestamp":1702944126000},"page":"560-577","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bayesian inference for prediction of survival probability in\u00a0prime\u2010boost vaccination regimes"],"prefix":"10.1002","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0701-4929","authenticated-orcid":false,"given":"Yuelin","family":"Lu","sequence":"first","affiliation":[{"name":"Statistical Innovation, Oncology &amp; Vaccines GlaxoSmithKline Plc  Upper Providence Philadelphia USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0684-8753","authenticated-orcid":false,"given":"Bradley P.","family":"Carlin","sequence":"additional","affiliation":[{"name":"Global Statistics &amp; Data Science PharmaLex U.S. Corp.  Burlington Massachusetts USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"suffix":"Jr.","given":"John W.","family":"Seaman","sequence":"additional","affiliation":[{"name":"Department of Statistical Science Baylor University  Waco Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2023,12,18]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1410863"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(15)61117-5"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1080\/21645515.2017.1264755"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.coi.2009.05.016"},{"key":"e_1_2_8_6_1","first-page":"iv","article-title":"The possible effects of the aggregation of the molecules of hemoglobin on its dissociation curves","volume":"40","author":"Hill AV","year":"1910","journal-title":"J Physiol"},{"volume-title":"Analysis of Dose\u2013Response Curves in Molecular Pharmacology by the SAS System","year":"1994","author":"Baiardi P","key":"e_1_2_8_7_1"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1472-8206.2008.00633.x"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-5193(85)80176-4"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1080\/19466315.2012.707087"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3916"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2010.01403.x"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-69416-0_16"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.3204"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-33706-7_9"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1021\/js950067y"},{"volume-title":"Bayesian Methods for Data Analysis","year":"2009","author":"Carlin BP","key":"e_1_2_8_17_1"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1201\/b16018"},{"key":"e_1_2_8_19_1","unstructured":"TeamS.D. 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