{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T02:21:34Z","timestamp":1755224494550,"version":"3.43.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100009210","name":"FDA","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100009210","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,3]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n               <jats:p>For progressive rare diseases like Duchenne muscular dystrophy (DMD), evaluating disease burden by measuring the totality of evidence from outcome data over time per patient can be highly informative, especially regarding how a new treatment impacts disease progression and functional outcomes. This paper focuses on new statistical approaches for analyzing data generated over time in a small sample, sequential, multiple assignment, randomized trial (snSMART), with an application to DMD. In addition, the use of external control data can enhance the statistical and operational efficiency in rare disease drug development by solving participant scarcity issues and ethical challenges. We employ a two-step robust meta-analytic approach to leverage external control data while adjusting for important baseline confounders and potential conflicts between external controls and trial data. Furthermore, our approach integrates important baseline covariates to account for patient heterogeneity and introduces a novel piecewise model to manage stage-wise treatment assignments. By applying this methodology to a case study in DMD research, we not only demonstrate the practical application and benefits of our approach but also highlight its potential to mitigate challenges in rare disease trials. Our findings advocate for a more nuanced and statistically robust analysis of treatment effects, thereby improving the reliability of clinical trial results.<\/jats:p>","DOI":"10.1093\/biomtc\/ujaf103","type":"journal-article","created":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T17:38:19Z","timestamp":1755020299000},"source":"Crossref","is-referenced-by-count":0,"title":["Evaluating longitudinal treatment effects for Duchenne muscular dystrophy using dynamically enriched Bayesian small sample, sequential, multiple assignment randomized trial (snSMART)"],"prefix":"10.1093","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4838-0842","authenticated-orcid":false,"given":"Sidi","family":"Wang","sequence":"first","affiliation":[{"name":"University of Michigan Department of Biostatistics, , Ann Arbor, MI 48109 ,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4001-3036","authenticated-orcid":false,"given":"Satrajit","family":"Roychoudhury","sequence":"additional","affiliation":[{"name":"Pfizer Inc. , New York, NY 10001 ,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kelley M","family":"Kidwell","sequence":"additional","affiliation":[{"name":"University of Michigan Department of Biostatistics, , Ann Arbor, MI 48109 ,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"key":"2025081213381467700_bib1","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1002\/pst.2093","article-title":"Assessing efficacy in important subgroups in confirmatory trials: An example using Bayesian dynamic borrowing","volume":"20","author":"Best","year":"2021","journal-title":"Pharmceutical Statistics"},{"key":"2025081213381467700_bib2","doi-asserted-by":"crossref","first-page":"2301","DOI":"10.1080\/01621459.2023.2231581","article-title":"Bayesian nonparametric common atoms regression for generating synthetic controls in clinical trials","volume":"118","author":"Chandra","year":"2023","journal-title":"Journal of the American Statistical Association"},{"key":"2025081213381467700_bib3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13023-020-01430-8","article-title":"Global epidemiology of Duchenne muscular dystrophy: An updated systematic review and meta-analysis","volume":"15","author":"Crisafulli","year":"2020","journal-title":"Orphanet Journal of Rare Diseases"},{"key":"2025081213381467700_bib4","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1080\/19466315.2022.2118162","article-title":"Comparing dose levels to placebo using a continuous outcome in a small n, sequential, multiple assignment, randomized trial (snSMART)","volume":"15","author":"Fang","year":"2023","journal-title":"Statistics in Biopharmaceutical Research"},{"key":"2025081213381467700_bib5","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1214\/06-BA117A","article-title":"Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)","volume":"1","author":"Gelman","year":"2006","journal-title":"Bayesian Analysis"},{"key":"2025081213381467700_bib6","doi-asserted-by":"crossref","first-page":"928","DOI":"10.1080\/01621459.1995.10476592","article-title":"A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion","volume":"90","author":"Kass","year":"1995","journal-title":"Journal of the American Statistical Association"},{"key":"2025081213381467700_bib7","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s10928-020-09671-7","article-title":"Latent process model of the 6-minute walk test in Duchenne muscular dystrophy","volume":"47","author":"Lennie","year":"2020","journal-title":"Journal of Pharmacokinetics and Pharmacodynamics"},{"key":"2025081213381467700_bib8","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1177\/2168479018778282","article-title":"Minimizing patient burden through the use of historical subject-level data in innovative confirmatory clinical trials: Review of methods and opportunities","volume":"52","author":"Lim","year":"2018","journal-title":"Therapeutic Innovation and Regulatory Science"},{"key":"2025081213381467700_bib9","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.nmd.2022.02.009","article-title":"Real-world and natural history data for drug evaluation in Duchenne muscular dystrophy: Suitability of the North Star Ambulatory Assessment for comparisons with external controls","volume":"32","author":"Muntoni","year":"2022","journal-title":"Neuromuscular Disorders"},{"key":"2025081213381467700_bib10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1037\/met0000219","article-title":"SMART longitudinal analysis: A tutorial for using repeated outcome measures from SMART studies to compare adaptive interventions","volume":"25","author":"Nahum-Shani","year":"2020","journal-title":"Psychological Methods"},{"key":"2025081213381467700_bib11","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1080\/19466315.2016.1174149","article-title":"On the use of co-data in clinical trials","volume":"8","author":"Neuenschwander","year":"2016","journal-title":"Statistics in Biopharmaceutical Research"},{"key":"2025081213381467700_bib12","volume-title":"Kendall\u2019s Advanced Theory of Statistics, volume 2B: Bayesian Inference","author":"O\u2019Hagan","year":"2004","edition":"2nd edn"},{"key":"2025081213381467700_bib13","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/0021-9681(76)90044-8","article-title":"The combination of randomized and historical controls in clinical trials","volume":"29","author":"Pocock","year":"1976","journal-title":"Journal of Chronic Diseases"},{"key":"2025081213381467700_bib14","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1093\/biomet\/70.1.41","article-title":"The central role of the propensity score in observational studies for causal effects","volume":"70","author":"Rosenbaum","year":"1983","journal-title":"Biometrika"},{"key":"2025081213381467700_bib15","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1111\/biom.12242","article-title":"Robust meta-analytic-predictive priors in clinical trials with historical control information","volume":"70","author":"Schmidli","year":"2014","journal-title":"Biometrics"},{"volume-title":"Bayesian Approaches to Clinical Trials and Health-Care Evaluation","year":"2004","author":"Spiegelhalter","key":"2025081213381467700_bib16"},{"key":"2025081213381467700_bib17","doi-asserted-by":"crossref","first-page":"1811","DOI":"10.1212\/WNL.0000000000004570","article-title":"A phase 3 randomized placebo-controlled trial of tadalafil for Duchenne muscular dystrophy","volume":"89","author":"Victor","year":"2017","journal-title":"Neurology"},{"key":"2025081213381467700_bib18","doi-asserted-by":"crossref","first-page":"3612","DOI":"10.1111\/biom.13887","article-title":"Dynamic enrichment of Bayesian small-sample, sequential, multiple assignment randomized trial design using natural history data: A case study from Duchenne muscular dystrophy","volume":"79","author":"Wang","year":"2023","journal-title":"Biometrics"},{"key":"2025081213381467700_bib19","doi-asserted-by":"crossref","first-page":"6421","DOI":"10.1002\/sim.9191","article-title":"Incorporating external data into the analysis of clinical trials via Bayesian additive regression trees","volume":"40","author":"Zhou","year":"2021","journal-title":"Statistics in Medicine"}],"container-title":["Biometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/81\/3\/ujaf103\/63965923\/ujaf103.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/biometrics\/article-pdf\/81\/3\/ujaf103\/63965923\/ujaf103.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T17:38:26Z","timestamp":1755020306000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/biometrics\/article\/doi\/10.1093\/biomtc\/ujaf103\/8223031"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":19,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,7,3]]}},"URL":"https:\/\/doi.org\/10.1093\/biomtc\/ujaf103","relation":{},"ISSN":["0006-341X","1541-0420"],"issn-type":[{"type":"print","value":"0006-341X"},{"type":"electronic","value":"1541-0420"}],"subject":[],"published-other":{"date-parts":[[2025,9]]},"published":{"date-parts":[[2025,7,3]]},"article-number":"ujaf103"}}