{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T03:53:38Z","timestamp":1777953218934,"version":"3.51.4"},"reference-count":29,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T00:00:00Z","timestamp":1772841600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Muscle and Nerve"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction\/Aims<\/jats:title>\n                    <jats:p>Myasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been reported. This study aimed to evaluate the rates of malignancy in MG patients while accounting for risk factors such as disease characteristics and immunomodulatory treatments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a case\u2013control study using the Clalit Health Services database, applying a machine learning (ML) algorithm to minimize diagnosis misclassification. We included MG patients aged 18\u2009years and older, with a sex\u2010 and age\u2010matched control group in a 1:3 ratio. We compared the prevalence and hazard ratios of extrathymic neoplasms between the groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 1558 patients with a high probability of MG, according to our ML model, were included in the cohort, alongside a control group of 4674 individuals. MG patients had a higher prevalence of malignancy prior to MG diagnosis, with an odds ratio of 1.95 (95% CI, 1.65\u20132.08), and a higher incidence of malignancy after MG diagnosis, with a hazard ratio of 1.56 (95% CI, 1.38\u20131.77). The most prevalent extrathymic neoplasms after MG diagnosis were respiratory, intrathoracic, skin (specifically non\u2010melanoma), urinary tract, soft tissue, and myelodysplastic syndrome. Risk factors for malignancy included age, male sex, and thymoma. Immunosuppressive treatment did not increase the risk of malignancy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>MG patients have a higher prevalence of both solid and hematologic neoplasms compared to non\u2010myasthenic controls, regardless of immunosuppressive treatment. This supports the notion that malignancy is related to MG disease itself rather than external factors.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mus.70207","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T16:02:16Z","timestamp":1772985736000},"page":"1016-1024","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Increased Prevalence of Extrathymic Neoplasms in Myasthenia Gravis Patients\u2010A Population\u2010Based, Matched Case\u2013Control Study"],"prefix":"10.1002","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5056-2368","authenticated-orcid":false,"given":"Keshet","family":"Pardo","sequence":"first","affiliation":[{"name":"Department of Neurology Rabin Medical Center  Petach Tikva Israel"},{"name":"Faculty of Medicine, Tel Aviv University  Petach Tikva 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Consultant, Rabin Medical Center  Petach Tikva Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nadav","family":"Loebl","sequence":"additional","affiliation":[{"name":"Beilinson Medical Center Innovation, Artificial Intelligence Center, Rabin Medical Center  Petah Tikva Israel"},{"name":"Faculty of Computer Science, Reichman University  Herzliya Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bar","family":"Yacobi","sequence":"additional","affiliation":[{"name":"Beilinson Medical Center Innovation, Artificial Intelligence Center, Rabin Medical Center  Petah Tikva Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yitzhak","family":"Friedman","sequence":"additional","affiliation":[{"name":"Department of Neurology Rabin Medical Center  Petach Tikva Israel"},{"name":"Faculty of Medicine, Tel Aviv University  Petach Tikva 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