{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T20:47:15Z","timestamp":1789246035621,"version":"build-2803163510"},"reference-count":23,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T00:00:00Z","timestamp":1679356800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Psoriasis and Psoriatic Arthritis"],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Dermatologists would benefit from an easy to use psoriasis severity assessment tool in the clinic.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop psoriasis assessment tools to predict PASI and Dermatology Life Quality Index (DLQI) using simple measures typically collected in clinical practice.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Data included 33\u00a0605 dermatology visits among plaque psoriasis patients enrolled in the CorEvitas Psoriasis Registry (4\/15\/15-7\/11\/20). Performance (adjusted coefficient of determination [R\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sub>adj<\/jats:sub>\n                      ], root mean square error [RMSE]) in predicting PASI and DLQI was assessed for 16 different linear regression models (specified a priori based on combinations of BSA, Investigator\u2019s Global Assessment [IGA], itch, skin pain, patient global assessment, age, sex, BMI, comorbidity index, prior biologic use), and 2 stepwise selection models and 1 elastic net model based on 56 available variables. For each prediction model, concordance (sensitivity, specificity) of predicted PASI75, PASI90 and DLQI 0\/1 with observed values was evaluated.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Mean (SD) age, BSA, and PASI were 51 (14) years, 6 (11), and 4 (6), respectively; 46% were women, and 87% were biologic experienced. A model predicting PASI using BSA plus IGA performed best among a priori specified models (R\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sub>adj<\/jats:sub>\n                      = .72, RMSE = 2.93) and only marginally worse than models including additional variables (R\n                      <jats:sup>2<\/jats:sup>\n                      <jats:sub>adj<\/jats:sub>\n                      range .64-.74, RMSE range 2.82-3.36). Models including IGA had the best concordance between predicted and observed PASI75 (sensitivity range 83-85%, specificity range 88-91%) and PASI90 (sensitivity range 76-82%, specificity range 94-98%). DLQI prediction was limited.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>An assessment tool for psoriasis including BSA and IGA may be an ideal option to predict PASI in a clinic setting.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/24755303231155118","type":"journal-article","created":{"date-parts":[[2023,3,21]],"date-time":"2023-03-21T11:46:34Z","timestamp":1679399194000},"page":"74-82","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Development of Psoriasis Assessment Tools Among Patients in the CorEvitas Psoriasis Registry"],"prefix":"10.1177","volume":"8","author":[{"given":"Wayne P.","family":"Gulliver","sequence":"first","affiliation":[{"name":"St. John\u2019s, Newfoundland and Labrador, Memorial University of Newfoundland, Newfoundland, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyoungah","family":"See","sequence":"additional","affiliation":[{"name":"Eli Lilly and Company, Indianapolis, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baojin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Eli Lilly and Company, Indianapolis, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce W.","family":"Konicek","sequence":"additional","affiliation":[{"name":"Eli Lilly and Company, Indianapolis, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4575-006X","authenticated-orcid":false,"given":"Ryan W.","family":"Harrison","sequence":"additional","affiliation":[{"name":"CorEvitas LLC, Waltham, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert R.","family":"McLean","sequence":"additional","affiliation":[{"name":"CorEvitas LLC, Waltham, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samantha J.","family":"Kerti","sequence":"additional","affiliation":[{"name":"CorEvitas LLC, Waltham, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Russel T.","family":"Burge","sequence":"additional","affiliation":[{"name":"Eli Lilly and Company, Indianapolis, IN, USA"},{"name":"University of Cincinnati, Cincinnati, OH, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Craig L.","family":"Leonardi","sequence":"additional","affiliation":[{"name":"Central Dermatology, St. Louis, MO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,3,21]]},"reference":[{"issue":"2","key":"bibr1-24755303231155118","first-page":"147","volume":"16","author":"Duffin KC","year":"2017","journal-title":"J Drugs 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