{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T00:10:45Z","timestamp":1786666245471,"version":"build-2736575974"},"reference-count":28,"publisher":"American Medical Association (AMA)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Dermatol"],"published-print":{"date-parts":[[2022,10,1]]},"abstract":"<jats:sec id=\"ab-doi220041-4\"><jats:title>Importance<\/jats:title><jats:p>Identifying the optimal long-term biologic therapy for patients with psoriasis is often done through trial and error.<\/jats:p><\/jats:sec><jats:sec id=\"ab-doi220041-5\"><jats:title>Objective<\/jats:title><jats:p>To identify the optimal biologic therapy for individual patients with psoriasis using predictive statistical and machine learning models.<\/jats:p><\/jats:sec><jats:sec id=\"ab-doi220041-6\"><jats:title>Design, Setting, and Participants<\/jats:title><jats:p>This population-based cohort study used data from Danish nationwide registries, primarily DERMBIO, and included adult patients treated for moderate-to-severe psoriasis with biologics. Data were processed and analyzed between spring 2021 and spring 2022.<\/jats:p><\/jats:sec><jats:sec id=\"ab-doi220041-7\"><jats:title>Main Outcomes and Measures<\/jats:title><jats:p>Patient clusters of clinical relevance were identified and their success rates estimated for each drug. Furthermore, predictive prognostic models to identify optimal biologic treatment at the individual level based on data from nationwide registries were evaluated.<\/jats:p><\/jats:sec><jats:sec id=\"ab-doi220041-8\"><jats:title>Results<\/jats:title><jats:p>Assuming a success criterion of 3 years of sustained treatment, this study included 2034 patients with a total of 3452 treatment series. Most treatment series involved male patients (2147 [62.2%]) originating from Denmark (3190 [92.4%]), and 2414 (69.9%) had finished an education longer than primary school. The average ages were 24.9 years at psoriasis diagnosis and 45.5 years at initiation of biologic therapy. Gradient-boosted decision trees and logistic regression were able to predict a specific cytokine target (eg, interleukin-17 inhibition) associated with a successful treatment with accuracies of 63.6% and 59.2%, and top 2 accuracies of 95.9% and 93.9%. When predicting specific drugs resulting in success, gradient boost and logistic regression had accuracies of 48.5% and 44.4%, top 2 accuracies of 77.6% and 75.9%, and top 3 accuracies of 89.9% and 89.0%.<\/jats:p><\/jats:sec><jats:sec id=\"ab-doi220041-9\"><jats:title>Conclusions and Relevance<\/jats:title><jats:p>Of the treatment prediction models used in this cohort study of patients with psoriasis, gradient-boosted decision trees performed significantly better than logistic regression when predicting specific biologic therapy (by drug as well as target) leading to a treatment duration of at least 3 years without discontinuation. Predicting the optimal biologic could benefit patients and clinicians by minimizing the number of failed treatment attempts.<\/jats:p><\/jats:sec>","DOI":"10.1001\/jamadermatol.2022.3171","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T15:01:18Z","timestamp":1660748478000},"page":"1149","source":"Crossref","is-referenced-by-count":25,"title":["Multivariable Predictive Models to Identify the Optimal Biologic Therapy for Treatment of Patients With Psoriasis at the Individual Level"],"prefix":"10.1001","volume":"158","author":[{"given":"Mia-Louise","family":"Nielsen","sequence":"first","affiliation":[{"name":"Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Troels Christian","family":"Petersen","sequence":"additional","affiliation":[{"name":"Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia-Tatjana","family":"Maul","sequence":"additional","affiliation":[{"name":"Department of Dermatology, University of Z\u00fcrich, Z\u00fcrich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jashin J.","family":"Wu","sequence":"additional","affiliation":[{"name":"Dermatology Research and Education Foundation, Irvine, California"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mads Kirchheiner","family":"Rasmussen","sequence":"additional","affiliation":[{"name":"DERMBIO, Denmark"},{"name":"Department of Dermatology, Aarhus University Hospital, Aarhus"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trine","family":"Bertelsen","sequence":"additional","affiliation":[{"name":"DERMBIO, Denmark"},{"name":"Department of Dermatology, Aarhus University Hospital, Aarhus"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kawa Khaled","family":"Ajgeiy","sequence":"additional","affiliation":[{"name":"DERMBIO, Denmark"},{"name":"Department of Dermatology, Odense University Hospital, Odense, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lone","family":"Skov","sequence":"additional","affiliation":[{"name":"DERMBIO, Denmark"},{"name":"Department of Dermatology and Allergy, Herlev and Gentofte Hospital, Hellerup, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon Francis","family":"Thomsen","sequence":"additional","affiliation":[{"name":"Department of Dermatology, Copenhagen University Hospital - Bispebjerg, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob P.","family":"Thyssen","sequence":"additional","affiliation":[{"name":"Department of Dermatology, Copenhagen University Hospital - Bispebjerg, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexander","family":"Egeberg","sequence":"additional","affiliation":[{"name":"DERMBIO, Denmark"},{"name":"Department of Dermatology, Copenhagen University Hospital - Bispebjerg, Copenhagen, Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","reference":[{"issue":"2","key":"doi220041r1","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1038\/jid.2012.339","article-title":"Global epidemiology of psoriasis: a systematic review of incidence and prevalence.","volume":"133","author":"Parisi","year":"2013","journal-title":"J Invest Dermatol"},{"issue":"3 Pt 1","key":"doi220041r2","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/S0190-9622(99)70112-X","article-title":"Psoriasis causes as much disability as other major medical diseases.","volume":"41","author":"Rapp","year":"1999","journal-title":"J Am Acad Dermatol"},{"issue":"14","key":"doi220041r3","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1001\/jama.296.14.1735","article-title":"Risk of myocardial infarction in patients with psoriasis.","volume":"296","author":"Gelfand","year":"2006","journal-title":"JAMA"},{"issue":"1","key":"doi220041r4","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.jaad.2018.06.027","article-title":"Prevalence of psoriatic arthritis in patients with psoriasis: A systematic review and meta-analysis of observational and clinical studies.","volume":"80","author":"Alinaghi","year":"2019","journal-title":"J Am Acad Dermatol"},{"issue":"9583","key":"doi220041r5","doi-asserted-by":"publisher","first-page":"272","DOI":"10.1016\/S0140-6736(07)61129-5","article-title":"Current and future management of psoriasis.","volume":"370","author":"Menter","year":"2007","journal-title":"Lancet"},{"issue":"12","key":"doi220041r6","doi-asserted-by":"publisher","first-page":"2277","DOI":"10.1111\/jdv.13354","article-title":"European S3-Guidelines on the systemic treatment of psoriasis vulgaris--Update 2015--Short version--EDF in cooperation with EADV and IPC.","volume":"29","author":"Nast","year":"2015","journal-title":"J Eur Acad Dermatol Venereol"},{"issue":"2","key":"doi220041r7","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1111\/bjd.16102","article-title":"Safety, efficacy and drug survival of biologics and biosimilars for moderate-to-severe plaque psoriasis.","volume":"178","author":"Egeberg","year":"2018","journal-title":"Br J Dermatol"},{"key":"doi220041r8","doi-asserted-by":"publisher","first-page":"2012","DOI":"10.12688\/f1000research","article-title":"The rise and fall of machine learning methods in biomedical research.","volume":"6","author":"Koohy","year":"2017","journal-title":"F1000Res"},{"issue":"7","key":"doi220041r9","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1111\/jdv.2017.31.issue-7","article-title":"Characteristics of patients receiving ustekinumab compared with secukinumab for treatment of moderate-to-severe plaque psoriasis\u2014nationwide results from the DERMBIO registry.","volume":"31","author":"Egeberg","year":"2017","journal-title":"J Eur Acad Dermatol Venereol"},{"issue":"8","key":"doi220041r10","doi-asserted-by":"publisher","first-page":"541","DOI":"10.1007\/s10654-014-9930-3","article-title":"The Danish Civil Registration System as a tool in epidemiology.","volume":"29","author":"Schmidt","year":"2014","journal-title":"Eur J Epidemiol"},{"key":"doi220041r11","doi-asserted-by":"publisher","first-page":"449","DOI":"10.2147\/CLEP","article-title":"The Danish National Patient Registry: a review of content, data quality, and research potential.","volume":"7","author":"Schmidt","year":"2015","journal-title":"Clin Epidemiol"},{"key":"doi220041r12","doi-asserted-by":"publisher","first-page":"798","DOI":"10.1093\/ije\/dyw213","article-title":"Data resource profile data resource profile: the danish national prescription registry data resource basics nationwide Danish data for research prescription drugs in the Danish healthcare system.","author":"Potteg\u00e5","year":"2017","journal-title":"Int J Epidemiol"},{"key":"doi220041r13","first-page":"12","article-title":"Existing data sources in clinical epidemiology: laboratory information system databases in Denmark.","volume":"2020","author":"Frederik","year":"2020","journal-title":"Clin Epidemiol"},{"key":"doi220041r14","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1080\/1047322X.1990.10389587","article-title":"Estimation of average concentration in the presence of nondetectable values.","volume":"5","author":"Hornung","year":"1990","journal-title":"Appl Occup Environ Hyg"},{"key":"doi220041r16","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1023\/A:1009769707641","article-title":"Extensions to the k-means algorithm for clustering large data sets with categorical values.","volume":"12","author":"Huang","year":"1998","journal-title":"Data Min Knowl Discov"},{"issue":"8","key":"doi220041r18","doi-asserted-by":"publisher","first-page":"1885","DOI":"10.1162\/089976699300016007","article-title":"Combined 5 x 2 cv F test for comparing supervised classification learning algorithms.","volume":"11","author":"Alpaydin","year":"1999","journal-title":"Neural Comput"},{"key":"doi220041r22","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib: A 2D Graphics Environment.","volume":"9","author":"Hunter","year":"2007","journal-title":"Comput Sci Eng"},{"key":"doi220041r23","first-page":"12","article-title":"Scikit-learn: Machine Learning in Python.","volume":"\u2022\u2022\u2022","author":"Pedregosa","year":"2012","journal-title":"J Mach Learn Res"},{"issue":"5","key":"doi220041r24","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1111\/bjd.v182.5","article-title":"Predicting the long-term outcomes of biologics in patients with psoriasis using machine learning.","volume":"182","author":"Emam","year":"2020","journal-title":"Br J Dermatol"},{"issue":"3","key":"doi220041r25","doi-asserted-by":"publisher","first-page":"1845","DOI":"10.1136\/rmdopen-2021-001845","article-title":"Clinically relevant patient clusters identified by machine learning from the clinical development programme of secukinumab in psoriatic arthritis.","volume":"7","author":"Pournara","year":"2021","journal-title":"RMD Open"},{"key":"doi220041r26","doi-asserted-by":"publisher","first-page":"AB60","DOI":"10.1016\/j.jaad.2020.06.326","article-title":"16317 Characterization of patient clusters based on response to treatment with secukinumab: A \u201cpattern recognition\u201d analysis of pooled phase 3 data.","volume":"83","author":"Reich","year":"2020","journal-title":"J Am Acad Dermatol"},{"issue":"1","key":"doi220041r27","doi-asserted-by":"publisher","DOI":"10.2340\/00015555-3722","article-title":"Response to biologics during the first six months of therapy in biologic-na\u00efve patients with psoriasis predicts risk of disease flares: a Danish nationwide study.","volume":"101","author":"Loft","year":"2021","journal-title":"Acta Derm Venereol"},{"key":"doi220041r28","doi-asserted-by":"publisher","first-page":"621","DOI":"10.25251\/skin.5.6.5","article-title":"A machine learning-based test for predicting response to psoriasis biologics.","volume":"5","author":"Bagel","year":"2021","journal-title":"Ski J Cutan Med"},{"key":"doi220041r15","volume-title":"Advances in Neural Information Processing Systems","author":"Ke","year":"2017"},{"key":"doi220041r19","author":"McKinney","year":"2010"},{"key":"doi220041r21","author":"Seabold","year":"2010"},{"key":"doi220041r17","unstructured":"de Vos? NJ. kmodes categorical clustering library. Accessed April 4, 2022. https:\/\/github.com\/nicodv\/kmodes"},{"key":"doi220041r20","unstructured":"The pandas development team. pandas-dev\/pandas: Pandas. (2020) doi:10.5281\/zenodo.3509134."}],"container-title":["JAMA Dermatology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/jamanetwork.com\/journals\/jamadermatology\/articlepdf\/2795009\/jamadermatology_nielsen_2022_oi_220041_1666117424.92867.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T15:11:23Z","timestamp":1666192283000},"score":1,"resource":{"primary":{"URL":"https:\/\/jamanetwork.com\/journals\/jamadermatology\/fullarticle\/2795009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,1]]},"references-count":28,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2022,10,1]]}},"URL":"https:\/\/doi.org\/10.1001\/jamadermatol.2022.3171","relation":{},"ISSN":["2168-6068"],"issn-type":[{"value":"2168-6068","type":"print"}],"subject":[],"published":{"date-parts":[[2022,10,1]]}}}