{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T07:49:00Z","timestamp":1785743340792,"version":"3.56.0"},"reference-count":32,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"National Institute of Health","award":["1R21AG08405401"],"award-info":[{"award-number":["1R21AG08405401"]}]},{"name":"National Institute of Health","award":["1U01AG059798"],"award-info":[{"award-number":["1U01AG059798"]}]},{"name":"National Institute of Health","award":["R01AG046179"],"award-info":[{"award-number":["R01AG046179"]}]},{"name":"National Institute of Health","award":["R01AG053267"],"award-info":[{"award-number":["R01AG053267"]}]},{"name":"National Institute of Health","award":["R01AG068319"],"award-info":[{"award-number":["R01AG068319"]}]},{"name":"National Institute of Health","award":["U01AG042791"],"award-info":[{"award-number":["U01AG042791"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>In Alzheimer's disease (AD) clinical trials, efficacy inference is traditionally based on the last visit (e.g., 18 months). However, recent studies suggest that disease-modifying treatment effects may emerge as early as 3 months post-baseline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To explore this further, our study aimed to assess the increased statistical power achieved by incorporating all or multiple post-baseline visits to estimate treatment effect, compared to relying solely on the last visit.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed explicit formulas for the basis functions of the natural cubic spline model, ensuring compatibility with standard SAS procedures. Through simulations using disease progression trajectories from Clarity-AD and TRAILBLAZER-ALZ 2 trials, we comprehensively evaluated various models in terms of power and type I error. Additionally, we offer SAS codes that to facilitate seamless implementation of different modeling approaches.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Simulations based on ClarityAD and TRAILBLAZER-ALZ 2 disease trajectories demonstrated that models incorporating multiple or all post-baseline visits yield greater power than those using only the last visit, while maintaining Type I error control. Furthermore, when three post-baseline visits were included, adding more visits resulted in minimal power gains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Our findings support prioritizing statistical models that incorporate multiple or all post-baseline visits for treatment efficacy inference, as they offer greater efficiency than models relying solely on the last visit.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13872877251352189","type":"journal-article","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T05:15:02Z","timestamp":1751260502000},"page":"1272-1287","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Harnessing greater statistical power: Comprehensive evaluation of disease modifying treatment effects across all or multiple post-baseline visits compared to the last visit for Alzheimer's disease clinical trials"],"prefix":"10.1177","volume":"106","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6808-8737","authenticated-orcid":false,"given":"Guoqiao","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Neurology, Washington University in St Louis, St Louis, MO, USA"},{"name":"Division of Biostatistics, Washington University in St Louis, St Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianle","family":"Chen","sequence":"additional","affiliation":[{"name":"Biogen Inc., Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6549-4038","authenticated-orcid":false,"given":"John","family":"O\u2019Gorman","sequence":"additional","affiliation":[{"name":"Biogen Inc., Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1340-6694","authenticated-orcid":false,"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Neurology, Washington University in St Louis, St Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"CaiYan","family":"Li","sequence":"additional","affiliation":[{"name":"Alector, Inc., South San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5864-8422","authenticated-orcid":false,"given":"Leonard","family":"Guizzetti","sequence":"additional","affiliation":[{"name":"Alector, Inc., South San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1078-6566","authenticated-orcid":false,"given":"Brian","family":"Mangal","sequence":"additional","affiliation":[{"name":"Solara Consulting Corp., North Vancouver, BC, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Whedy","family":"Wang","sequence":"additional","affiliation":[{"name":"Tenaya Therapeutics, South San Francisco, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuang","family":"Wu","sequence":"additional","affiliation":[{"name":"Biogen Inc., Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dave","family":"Inman","sequence":"additional","affiliation":[{"name":"GlaxoSmithKline Medicines Research Centre, Stevenage, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"McDade","sequence":"additional","affiliation":[{"name":"Department of Neurology, Washington University in St Louis, St Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Randall J","family":"Bateman","sequence":"additional","affiliation":[{"name":"Department of Neurology, Washington University in St Louis, St Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,6,30]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/009286150804200402"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2212948"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2023.13239"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1126\/scitranslmed.3007941"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195168655.003.0015"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7811"},{"key":"e_1_3_4_8_2","article-title":"Proportional constrained longitudinal data analysis models for clinical trials in sporadic Alzheimer's disease","volume":"8","author":"Wang G","year":"2022","unstructured":"Wang G, Liu L, Li Y, et al. 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