{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T01:50:54Z","timestamp":1767837054565,"version":"3.49.0"},"reference-count":28,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"9","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:sec>\n            <jats:title>PURPOSE<\/jats:title>\n            <jats:p>There is little guidance for decision making in chronic myeloid leukemia (CML) after patients achieve molecular remission. Our study addresses this gap by developing a risk prediction model for molecular relapse using early longitudinal factors, such as BCR::ABL1 biomarker-level changes and treatment adherence.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS<\/jats:title>\n            <jats:p>We analyzed electronic health record data of patients with CML diagnosed between 2007 and 2019 from an integrated health system. We used a time-to-event modeling framework using a Cox proportional hazards approach where we evaluated time from molecular remission to molecular relapse. The main predictors were early changes in BCR::ABL1 levels from treatment initiation to the first follow-up measurement (typically around 3 months) and treatment adherence in the first 6 months, categorized as perfect (\u22650.98) or less-than-perfect (&lt;0.98). Model performance was assessed through five-fold cross-validation combined with 100 Monte Carlo bootstrapping iterations to ensure robustness and minimize bias.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS<\/jats:title>\n            <jats:p>Patients with early improvement in BCR::ABL1 levels had a 70% lower risk relapse (hazard ratio [HR], 0.30 [95% CI, 0.15 to 0.59]) compared with those without early molecular response. Perfect adherence during this critical early phase of treatment was associated with a 56% lower relapse risk (HR, 0.44 [95% CI, 0.22 to 0.85]). Predictive accuracy was high at 6 months (AUC, 0.90; 95% CI, 0.87 to 0.95) and 1-year postremission (AUC, 0.78; 95% CI, 0.74 to 0.81). Relapse risk was significantly higher among Black, Asian, and Hispanic patients compared with non-Hispanic White patients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSION<\/jats:title>\n            <jats:p>Early biomarker trends and adherence after treatment initiation are critical for accurately predicting relapse among patients who achieve molecular remission. The proposed model addresses a gap in guidance after molecular remission and has the potential to enable personalized monitoring and optimize surveillance strategies, offering transformative potential for CML care.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1200\/cci-25-00003","type":"journal-article","created":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T20:00:45Z","timestamp":1751918445000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":1,"title":["Using Early Biomarker Change and Treatment Adherence to Predict Risk of Relapse Among Patients With Chronic Myeloid Leukemia Who Are in Remission"],"prefix":"10.1200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0641-2500","authenticated-orcid":true,"given":"J. 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Tyson School of Medicine, Pasadena, CA"},{"name":"Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8099-2801","authenticated-orcid":true,"given":"Eric","family":"Haupt","sequence":"additional","affiliation":[{"name":"Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jerald","family":"Radich","sequence":"additional","affiliation":[{"name":"Fred Hutchinson Cancer Research Center, Seattle, WA"},{"name":"Medical Oncology, University of Washington, Seattle, WA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5507-2640","authenticated-orcid":true,"given":"Aasthaa","family":"Bansal","sequence":"additional","affiliation":[{"name":"CHOICE Institute, School of Pharmacy, University of Washington, Seattle, WA"},{"name":"Fred Hutchinson Cancer Research Center, Seattle, WA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"233","reference":[{"key":"e_1_3_7_2_2","first-page":"e7342","article-title":"Risk stratification of chronic myeloid leukemia according to different prognostic scores","volume":"12","author":"Aijaz J","year":"2020","unstructured":"Aijaz J, Junaid N, Naveed MA, et al: Risk stratification of chronic myeloid leukemia according to different prognostic scores. 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