{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T04:03:06Z","timestamp":1754020986300},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,6]]},"abstract":"<jats:p>The CDISC Controlled Terminology (CT) defines the terms that may be used to represent clinical trial data in the CDISC standards. Despite its unique importance, there has been limited systematic examination of the coverage of this terminology. In this work, we performed an assessment of the completeness of CDISC CT\u2019s coverage by comparing clinical outcomes for multiple sclerosis (MS) available in CDISC CT with two independent high-fidelity benchmarks: (1) 71 expert-selected outcomes catalogued by the National Institute of Neurological Disorders and Stroke (NINDS), and, (2) 66 common outcomes used in MS trials registered on ClinicalTrials.gov (CTG). We employed a semi-automated search and term-mapping process to identify possible CDISC equivalents to the benchmarks\u2019 measures. We found that 55% of the NINDS outcomes and 52% of the CTG outcomes are absent from the CDISC Terminology, indicating a need for expanding the terminology to take into account other established standards and real-world practice.<\/jats:p>","DOI":"10.3233\/shti220042","type":"book-chapter","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:30:38Z","timestamp":1654594238000},"source":"Crossref","is-referenced-by-count":3,"title":["Comparative Assessment of Completeness of CDISC Controlled Terminology"],"prefix":"10.3233","author":[{"given":"Anas","family":"Elghafari","sequence":"first","affiliation":[{"name":"Center for Biomedical and Population Health Informatics, Icahn School of Medicine at Mount Sinai, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph","family":"Finkelstein","sequence":"additional","affiliation":[{"name":"Center for Biomedical and Population Health Informatics, Icahn School of Medicine at Mount Sinai, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2021: One World, One Health \u2013 Global Partnership for Digital Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220042","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:30:38Z","timestamp":1654594238000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220042"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,6]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220042","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,6]]}}}