{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T16:02:26Z","timestamp":1791302546957,"version":"4.1.0"},"reference-count":36,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2015,12,31]],"date-time":"2015-12-31T00:00:00Z","timestamp":1451520000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2018,1]]},"abstract":"<jats:p>Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.<\/jats:p>","DOI":"10.1177\/0962280215621591","type":"journal-article","created":{"date-parts":[[2015,12,31]],"date-time":"2015-12-31T21:20:30Z","timestamp":1451596830000},"page":"97-113","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data"],"prefix":"10.1177","volume":"27","author":[{"given":"Catherine","family":"Schramm","sequence":"first","affiliation":[{"name":"INSERM UMRS1138, Centre de Recherche des Cordeliers, E22, Universit\u00e9 Paris Descartes, Universit\u00e9 Pierre et Marie Curie, Paris, France"},{"name":"INSERM U955 E01, Neuropsychologie interventionnelle Laboratory IMRB, Cr\u00e9teil, France"},{"name":"Universit\u00e9 Pierre et Marie Curie, Paris 6, Paris, France"},{"name":"\u00c9cole Normale Sup\u00e9rieure, Institut d\u2019\u00c9tudes de la Cognition, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C\u00e9line","family":"Vial","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Lyon, CNRS UMR 5208, Polytech Lyon-Universit\u00e9 de Lyon 1, Institut Camille Jordan, Villeurbanne, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne-Catherine","family":"Bachoud-L\u00e9vi","sequence":"additional","affiliation":[{"name":"INSERM U955 E01, Neuropsychologie interventionnelle Laboratory IMRB, Cr\u00e9teil, France"},{"name":"\u00c9cole Normale Sup\u00e9rieure, Institut d\u2019\u00c9tudes de la Cognition, Paris, France"},{"name":"Assistance Publique-H\u00f4pitaux de Paris, National Reference Center for Huntington\u2019s Disease Henri Mondor Hospital, Cr\u00e9teil, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandrine","family":"Katsahian","sequence":"additional","affiliation":[{"name":"INSERM UMRS1138, Centre de Recherche des Cordeliers, E22, Universit\u00e9 Paris Descartes, Universit\u00e9 Pierre et Marie Curie, Paris, France"},{"name":"Assistance Publique-H\u00f4pitaux de Paris, Service d\u2019informatique et statistiques, Georges Pompidou European Hospital, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2015,12,31]]},"reference":[{"key":"bibr1-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1002\/9780470977811"},{"key":"bibr2-0962280215621591","first-page":"217","volume":"3","author":"Koestler DC","year":"2014","journal-title":"Trans Cancer Res"},{"key":"bibr3-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1016\/j.addbeh.2013.11.013"},{"key":"bibr4-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychres.2012.08.035"},{"key":"bibr5-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1186\/2045-709X-20-20"},{"key":"bibr6-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2012-1422"},{"key":"bibr7-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1111\/j.1530-0277.2000.tb02070.x"},{"key":"bibr8-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1996.10476679"},{"key":"bibr9-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-009-0178-4"},{"key":"bibr10-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780050304"},{"key":"bibr11-0962280215621591","doi-asserted-by":"publisher","DOI":"10.2307\/2529876"},{"key":"bibr12-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1002\/sim.4780070131"},{"key":"bibr13-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1198\/016214502760047131"},{"key":"bibr14-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1137\/1026034"},{"key":"bibr15-0962280215621591","doi-asserted-by":"publisher","DOI":"10.2307\/2532201"},{"key":"bibr16-0962280215621591","doi-asserted-by":"publisher","DOI":"10.2307\/2346830"},{"key":"bibr17-0962280215621591","unstructured":"MacQueen J, et\u00a0al. Some methods for classification and analysis of multivariate observations. In:\n                      Proceedings of the fifth Berkeley symposium on mathematical statistics and probability\n                      , Oakland, CA, USA, vol. 1, pp. 281\u2013297."},{"key":"bibr18-0962280215621591","first-page":"405","volume-title":"Clustering by means of medoids","author":"Kaufman L","year":"1987"},{"key":"bibr19-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1007\/BF01890115"},{"key":"bibr20-0962280215621591","unstructured":"Team RDC. R: a language and environment for statistical computing. R Foundation for statistical computing, Vienna, Austria, http:\/\/www.R-project.org (2013)."},{"key":"bibr21-0962280215621591","unstructured":"Pinheiro J, Bates D, DebRoy S, et\u00a0al. nlme: linear and nonlinear mixed effects models.\n                      R package version 3.1-105\n                      . 2012, http:\/\/CRAN.R-project.org\/package=nlme."},{"key":"bibr22-0962280215621591","unstructured":"Fraley C, Raftery AE, Murphy TB, et\u00a0al. mclust: normal mixture modeling for model-based clustering, classification, and density estimation.\n                      R package version 4.3.\n                      2012, http:\/\/CRAN.R-project.org\/package=mclust."},{"key":"bibr23-0962280215621591","unstructured":"Lucas A.\n                      amap: another multidimensional analysis package\n                      , http:\/\/CRAN.R-project.org\/package=amap. R package version 0.8-12 (2014)."},{"key":"bibr24-0962280215621591","unstructured":"Maechler M and Rousseeuw P.\n                      cluster: cluster analysis basics and extensions\n                      .\n                      R package version 1.14.3.\n                      2012, http:\/\/CRAN.R-project.org\/package=cluster."},{"key":"bibr25-0962280215621591","unstructured":"Proust-Lima C, Philipps V, Diakite A, et\u00a0al.\n                      lcmm: estimation of extended mixed models using latent classes and latent processes\n                      , http:\/\/CRAN.R-project.org\/package=lcmm. R package version 1.6.6 (2014)."},{"key":"bibr26-0962280215621591","volume-title":"Huntington\u2019s disease: oxford monographs on medical genetics","author":"Bates G","year":"2002"},{"key":"bibr27-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0085430"},{"key":"bibr28-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1136\/jmg.31.5.377"},{"key":"bibr29-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.46.2.527"},{"key":"bibr30-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1002\/ajmg.b.30992"},{"key":"bibr31-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1007\/s11695-011-0472-4"},{"key":"bibr32-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1002\/erv.2404"},{"key":"bibr33-0962280215621591","doi-asserted-by":"publisher","DOI":"10.2307\/2530808"},{"key":"bibr34-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwr243"},{"key":"bibr35-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1198\/016214503000189"},{"key":"bibr36-0962280215621591","doi-asserted-by":"publisher","DOI":"10.1038\/nrd3557"}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280215621591","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0962280215621591","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280215621591","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:48:30Z","timestamp":1777679310000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0962280215621591"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,31]]},"references-count":36,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,1]]}},"alternative-id":["10.1177\/0962280215621591"],"URL":"https:\/\/doi.org\/10.1177\/0962280215621591","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,31]]}}}