{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,22]],"date-time":"2026-09-22T03:19:41Z","timestamp":1790047181043,"version":"4.0.1"},"reference-count":36,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"<jats:sec id=\"ab-zoi260714-4\">\n                    <jats:title>Importance<\/jats:title>\n                    <jats:p>Hierarchical composite end points (HCEs) are a promising tool used in randomized clinical trials (RCTs) to integrate multiple outcomes of varying clinical relevance into a single measure.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-zoi260714-5\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To describe how often HCEs are used as primary outcomes in RCTs, and how they are constructed, analyzed, and reported.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-zoi260714-6\">\n                    <jats:title>Evidence Review<\/jats:title>\n                    <jats:p>MEDLINE, Embase, CENTRAL, and Web of Science were searched on December 9, 2024, complemented by a forward citation search of methodological papers on HCEs. RCTs that used an HCE as their primary outcome were included, defined either by self-declaration (hierarchical composite or outcome ranking) or through use of an HCE-specific analytical approach (win ratio, win odds, probabilistic index, or generalized pairwise comparison). Pilot studies, post hoc analyses, and hierarchically tested coprimary end points were excluded. Data were independently screened and extracted in duplicate. Trial characteristics, end point composition, hierarchy justification, and analytical methods were summarized descriptively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-zoi260714-7\">\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>Among 5188 screened records, 92 RCTs were included, with 79\u202f567 planned participants. The use of an HCE as a primary end point has increased, with 72 trials (78.3%) initiating recruitment within the past decade. Most RCTs were drug trials (43.5% [40 of 92]), in cardiology (43.5% [40 of 92]), multicenter (91.3% [84 of 92]), and non\u2013industry sponsored (67.4% [62 of 92]). The 92 HCEs had a median (IQR) of 4 (3-5) components and the highest ranked component was usually mortality (80.4% [74 of 92]). The last hierarchical component was most often a continuous component (64.1% [59 of 92]). The majority of RCTs did not report any information on how the hierarchy was established (82.2% [60 of 73]; excluding RCTs where only information from registries was available). Generalized pairwise comparison was the most frequent analysis approach (57.3% [26 of 45]) among the 45 published RCTs, yet no standardized way for presenting results was observed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"ab-zoi260714-8\">\n                    <jats:title>Conclusions and Relevance<\/jats:title>\n                    <jats:p>This scoping systematic review of 92 RCTs using HCEs found that their use has increased across medical fields, but their construction, analytical approaches, and reporting of results remained highly heterogeneous. By systematically mapping how HCEs are currently implemented, further review is essential for the development of much needed methodological and reporting standards.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.25935","type":"journal-article","created":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T15:30:25Z","timestamp":1785252625000},"page":"e2625935","source":"Crossref","is-referenced-by-count":1,"title":["Randomized Clinical Trials Using a Hierarchical Composite Primary End Point"],"prefix":"10.1001","volume":"9","author":[{"given":"Selina","family":"Ehrenzeller","sequence":"first","affiliation":[{"name":"CLEAR Methods Center, Division of Clinical Epidemiology, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amos J.","family":"de Jong","sequence":"additional","affiliation":[{"name":"Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yonas","family":"Martin","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marlieke E. 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C.","family":"Tong","sequence":"additional","affiliation":[{"name":"Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia"},{"name":"Victorian Infectious Diseases Service, The Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Khanna","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Kuehl","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, University Hospital Basel, Basel, Switzerland"},{"name":"Center for Musculoskeletal Infections, University Hospital Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Briel","sequence":"additional","affiliation":[{"name":"CLEAR Methods Center, Division of Clinical Epidemiology, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean W. 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