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Increased patient heterogeneity, while desirable for generalizability of results, can weaken the ability of common statistical approaches to detect treatment differences, potentially hampering the regulatory approval of safe and efficacious therapies. A novel solution to this problem is proposed. A list of baseline covariates that have the potential to be prognostic for survival under either treatment is pre\u2010specified in the analysis plan. At the analysis stage, using all observed survival times but blinded to patient\u2010level treatment assignment, \u201cnoise\u201d covariates are removed with elastic net Cox regression. The shortened covariate list is used by a conditional inference tree algorithm to segment the heterogeneous trial population into subpopulations of prognostically homogeneous patients (risk strata). After patient\u2010level treatment unblinding, a treatment comparison is done within each formed risk stratum and stratum\u2010level results are combined for overall statistical inference. The impressive power\u2010boosting performance of our proposed 5\u2010step stratified testing and amalgamation routine (5\u2010STAR), relative to that of the logrank test and other common approaches that do not leverage inherently structured patient heterogeneity, is illustrated using a hypothetical and two real datasets along with simulation results. Furthermore, the importance of reporting stratum\u2010level comparative treatment effects (time ratios from accelerated failure time model fits in conjunction with model averaging and, as needed, hazard ratios from Cox proportional hazard model fits) is highlighted as a potential enabler of personalized medicine. An R package is available at \n<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/rmarceauwest\/fiveSTAR\">https:\/\/github.com\/rmarceauwest\/fiveSTAR<\/jats:ext-link>.<\/jats:p>","DOI":"10.1002\/sim.8750","type":"journal-article","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T05:27:39Z","timestamp":1600666059000},"page":"4724-4744","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Survival analysis using a <scp>5\u2010step<\/scp> stratified testing and amalgamation routine (5\u2010STAR) in randomized clinical trials"],"prefix":"10.1002","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0316-7362","authenticated-orcid":false,"given":"Devan V.","family":"Mehrotra","sequence":"first","affiliation":[{"name":"Biostatistics and Research Decision Sciences Merck &amp; Co., Inc.  North Wales Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rachel","family":"Marceau West","sequence":"additional","affiliation":[{"name":"Biostatistics and Research Decision Sciences Merck &amp; Co., Inc.  North Wales Pennsylvania USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2020,9,20]]},"reference":[{"issue":"3","key":"e_1_2_8_2_1","first-page":"163","article-title":"Evaluation of survival data and two new rank order statistics arising in its consideration","volume":"50","author":"Mantel N","year":"1966","journal-title":"Cancer Chemother Rep"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.2307\/2344317"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1972.tb00899.x"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.4326"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2017.73.7379"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1470-2045(18)30292-4"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1814017"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2013.52.4892"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1507643"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(15)01281-7"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(16)32517-X"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41416-018-0302-8"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-18-3999"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/69.3.553"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.2307\/2532911"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1999.10473847"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2007.03.006"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2010.03.014"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6366"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1177\/1536867X1601600308"},{"key":"e_1_2_8_22_1","unstructured":"RoychoudhuryS AndersonKM YeJ MukhopadhyayP. 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