{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T13:10:37Z","timestamp":1789996237470,"version":"4.0.1"},"reference-count":26,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Translational Sci"],"published-print":{"date-parts":[[2026,9]]},"abstract":"ABSTRACT<\/jats:title>\n \n Given the increasing disease burden of hematological malignancies in Chinese Mainland, a systematic analysis of clinical trials is essential to advancing translational medicine, as these trials serve as the critical nexus between laboratory discoveries and clinical applications. This study integrated registration data from the Center for Drug Evaluation, Chinese Clinical Trial Registry, and\n ClinicalTrials.gov<\/jats:ext-link>\n for trials recorded between 2013 and 2022. Using joinpoint regression and descriptive temporal\u2010correlation analyses, we characterized temporal trends among 2497 identified trials and explored temporal co\u2010movements between annual trial counts and selected macro\u2010level indicators. The included trials comprised 1776 (71.1%) investigator\u2010initiated trials (IITs) and 721 (28.9%) industry\u2010sponsored trials (ISTs). The annual number of trials increased, with an average annual percent change (AAPC) of 23.5%; the AAPC was higher for IITs than for ISTs (25.6% vs. 13.1%). Notably, cell and gene therapy trials increased rapidly before 2019, with an annual percent change (APC) of 53.0%, and subsequently reached a growth plateau. In exploratory macro\u2010level analyses, the original annual series showed strong positive temporal correlations between trial counts and indicators of scientific activity and research capacity, disease burden, and socioeconomic context. However, these correlations were substantially attenuated after linear detrending and showed no consistent pattern in first\u2010difference analyses, indicating a substantial influence of shared secular trends. These findings support coordinated efforts to strengthen high\u2010quality clinical research and accelerate the translation of innovative therapies into patient care.\n <\/jats:p>","DOI":"10.1111\/cts.70708","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T03:57:21Z","timestamp":1787889441000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hematological Malignancy Trials in Chinese Mainland, 2013\u20132022: A Landscape Analysis with Exploratory Macro\u2010Level Temporal Correlations"],"prefix":"10.1111","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-6314-4677","authenticated-orcid":false,"given":"Jianwei","family":"Qi","sequence":"first","affiliation":[{"name":"State Key Laboratory of Experimental Hematology, National Clinical Research Centre for Blood Diseases, Haihe Laboratory of Cell Ecosystem Institute of Hematology & Blood Diseases Hospital, Chinese 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