{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T20:13:16Z","timestamp":1789157596824,"version":"build-2803163510"},"reference-count":40,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Lanzhou Science and Technology Plan Project","award":["No. 2023-ZD-23"],"award-info":[{"award-number":["No. 2023-ZD-23"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Malignant melanoma (MM) is an emerging public health concern in East Asia\u2019s rapidly aging population. This study assessed the burden of MM among older adults aged \u226560 years from 1990 to 2023 and projected age-standardized rates to 2040.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using GBD 2023 data, temporal trends were evaluated using Joinpoint regression and age\u2013period\u2013cohort analysis, together with age-, sex-, and location-specific comparisons. Future trends were projected using a multi-model forecasting framework incorporating ARIMA-derived temporal features. Seven candidate models were compared for each location\u2013indicator combination. Historical data were chronologically divided into an 80% training set (1990\u20132016) and a 20% independent testing set (2017\u20132023), with model selection performed using five-fold rolling time-series cross-validation within the training set. Prediction intervals were generated using residual bootstrap.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>From 1990 to 2023, MM-related deaths among older adults in East Asia increased from 3,417.59 to 7,476.55, while DALYs increased from 116,499.14 to 196,356.14. Joinpoint analysis showed significant overall increases in ASIR and ASPR, whereas ASMR and ASDR exhibited only small, non-significant overall changes. This divergence is consistent with an important contribution from population aging and growth of the older population to the increasing absolute burden. Women generally had higher incidence and prevalence rates, whereas men had higher mortality and DALY rates. Projections to 2040 showed substantial variation across locations, with mortality and DALY rates expected to reach a plateau in several locations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The increasing MM burden and distinct sex and regional patterns require targeted early-detection strategies and equitable access to dermatological care. Future studies should use regional, subtype-specific cancer registries to evaluate ALM-specific burden and inform prevention strategies for East Asian populations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0357767","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T20:02:23Z","timestamp":1789156943000},"page":"e0357767","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Burden of malignant melanoma among the elderly population in East Asia from 1990 to 2023 and machine learning projection to 2040"],"prefix":"10.1371","volume":"21","author":[{"given":"Qian","family":"Liu","sequence":"first","affiliation":[{"name":"Gansu Provincial Hospital & The Third Hospital of Lanzhou University","place":["Lanzhou, Gansu, China"]},{"name":"Lanzhou University","place":["Lanzhou, Gansu, China"],"department":["School of Public Health"]},{"name":"Gansu 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