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We computed biomarker trajectories as a function of time to AD dementia and predicted AD dementia onset age in a disjoint sample.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Quantitative template showed early changes in verbal memory, cerebrospinal fluid A\u03b2\n                      <jats:sub>1\u201342<\/jats:sub>\n                      and p\u2010tau\n                      <jats:sub>181p<\/jats:sub>\n                      , and hippocampal volume. Mean error in predicted AD dementia onset age was\n                      <jats:inline-graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"graphic\/dad2jdadm201901005-math-0003.png\" xlink:title=\"urn:x-wiley:23528729:dad2jdadm201901005:equation:dad2jdadm201901005-math-0003\"\/>\n                      years.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Our method provides a quantitative approach for characterizing the natural history of AD starting at preclinical stages despite the lack of individual\u2010level longitudinal data spanning the entire disease timeline.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1016\/j.dadm.2019.01.005","type":"journal-article","created":{"date-parts":[[2019,2,27]],"date-time":"2019-02-27T23:24:09Z","timestamp":1551309849000},"page":"205-215","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Predicting time to dementia using a quantitative template of disease progression"],"prefix":"10.1002","volume":"11","author":[{"given":"Murat","family":"Bilgel","sequence":"first","affiliation":[{"name":"Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health Baltimore MD USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruno M.","family":"Jedynak","sequence":"additional","affiliation":[{"name":"Dept. of Mathematics and Statistics Portland State University Portland OR USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Alzheimer's Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2019,2,28]]},"reference":[{"key":"e_1_2_7_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S1474-4422(13)70044-9"},{"key":"e_1_2_7_3_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1202753"},{"key":"e_1_2_7_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.01.062"},{"key":"e_1_2_7_5_2","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awu176"},{"key":"e_1_2_7_6_2","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awy050"},{"key":"e_1_2_7_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2012.07.059"},{"key":"e_1_2_7_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.04.001"},{"key":"e_1_2_7_9_2","first-page":"134","volume-title":"Lecture Notes in Computer Science, Information Processing in Medical Imaging","author":"Marinescu RV Eshaghi A.","year":"2017"},{"key":"e_1_2_7_10_2","first-page":"564","volume-title":"Lecture Notes in Computer Science, Information Processing in Medical Imaging","author":"Schiratti J.B.","year":"2015"},{"key":"e_1_2_7_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2013.10.003"},{"key":"e_1_2_7_12_2","unstructured":"D.Li S.Iddi W.K.Thompson M.C.Donohue.Bayesian latent time joint mixed effect models for multicohort longitudinal data.Stat Methods Med Res 2017:1\u20101110.1177\/0962280217737566.arXiv:1703.10266"},{"key":"e_1_2_7_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.06.049"},{"key":"e_1_2_7_14_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2018.00235"},{"key":"e_1_2_7_15_2","doi-asserted-by":"publisher","DOI":"10.1002\/cpt.1166"},{"key":"e_1_2_7_16_2","unstructured":"M.Lorenzi M.Filippone G.B.Frisoni D.C.Alexander S.Ourselin.Probabilistic disease progression modeling to characterize diagnostic uncertainty: Application to staging and prediction in Alzheimer's disease.NeuroImage 201710.1016\/j.neuroimage.2017.08.059[Epub ahead of print]"},{"key":"e_1_2_7_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2010.05.023"},{"key":"e_1_2_7_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.10.002"},{"key":"e_1_2_7_19_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0173372"},{"key":"e_1_2_7_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2014.08.023"},{"key":"e_1_2_7_21_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-017-17765-5"},{"key":"e_1_2_7_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2017.06.027"},{"key":"e_1_2_7_23_2","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awy093"},{"key":"e_1_2_7_24_2","first-page":"215","article-title":"L'examen psychologique dans les cas d'enc\u00e9phalopathie traumatique. 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