{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T18:39:57Z","timestamp":1792521597558,"version":"4.5.0"},"reference-count":67,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T00:00:00Z","timestamp":1790380800000},"content-version":"vor","delay-in-days":268,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,21]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To systematically review the methods, validation frameworks, applications and regulatory landscape of synthetic data generation in healthcare, with a specific focus on rheumatology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We searched PubMed\/MEDLINE, Embase and arXiv (January 2016\u2013January 2026). From 1099 database records and 7 expert-identified studies, 701 remained after removing 405 duplicates. Title and abstract screening excluded 353 records; full-text assessment of 348 articles excluded 120 (E1: n\u2009=\u200962; E2: n\u2009=\u20091; E3: n\u2009=\u200923; E4: n\u2009=\u200934), yielding 228 studies. Quality assessment of 13 rheumatology-specific studies using a 10-item checklist revealed 1 high-quality, 8 moderate-quality, and 4 low-quality studies, with systematic gaps in privacy evaluation (2\/13) and reproducibility (1\/13).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The 228 included studies encompassed six generation-method categories (generative adversarial networks, diffusion models, large language models, statistical methods, rule-based simulators and hybrid approaches) and five thematic categories (digital twins, privacy-preserving methods, reviews, validation frameworks and healthcare applications), detailed in the supplementary methods. Validation remained inconsistent, with only a minority evaluating fidelity, utility and privacy simultaneously. In rheumatology, 13 studies spanned rheumatoid arthritis (n\u2009=\u20093), osteoarthritis (n\u2009=\u20093), Sjogren\u2019s syndrome (n\u2009=\u20092), systemic sclerosis (n\u2009=\u20092), systemic lupus erythematosus (n\u2009=\u20092) and ankylosing spondylitis (n\u2009=\u20091). Only 2 of 13 formally evaluated privacy and only 1 shared code for reproducibility.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Synthetic data hold substantial promise for rheumatology, particularly for augmenting small cohorts in low-prevalence diseases, enabling privacy-preserving registry sharing and simulating clinical trial populations. Realizing this potential requires standardized validation, greater attention to privacy and reproducibility and regulatory clarity on synthetic health data.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/rap\/rkag114","type":"journal-article","created":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T11:16:48Z","timestamp":1790335008000},"source":"Crossref","is-referenced-by-count":0,"title":["Synthetic data in rheumatology: a systematic literature review"],"prefix":"10.1093","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2573-5930","authenticated-orcid":false,"given":"Vincenzo","family":"Venerito","sequence":"first","affiliation":[{"name":"Rheumatology Unit, Department of Precision and Regenerative Medicine\u2013Ionian Area (DiMePRe-J), University of Bari \u201cAldo Moro\u201d , Bari,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2513-6583","authenticated-orcid":false,"given":"Maria","family":"Morrone","sequence":"additional","affiliation":[{"name":"Rheumatology Unit, Department of Precision and Regenerative Medicine\u2013Ionian Area (DiMePRe-J), University of Bari \u201cAldo Moro\u201d , Bari,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8970-7351","authenticated-orcid":false,"given":"Sergio","family":"Del Vescovo","sequence":"additional","affiliation":[{"name":"Rheumatology Unit, Department of Precision and Regenerative Medicine\u2013Ionian Area (DiMePRe-J), University of Bari \u201cAldo Moro\u201d , Bari,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2260-4660","authenticated-orcid":false,"given":"Emre","family":"Bilgin","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Department of Internal Medicine, Faculty of Medicine, Sakarya University , Sakarya,","place":["Turkey"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2753-2990","authenticated-orcid":false,"given":"Latika","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Rheumatology, Royal Wolverhampton NHS Trust , Wolverhampton,","place":["UK"]},{"name":"Institute of Inflammation and Ageing, University of Birmingham , Birmingham,","place":["UK"]},{"name":"Francis Crick Institute, Camden , 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