{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T22:21:13Z","timestamp":1793830873526,"version":"4.6.1"},"reference-count":48,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"9","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Precis Oncol"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:sec>\n                    <jats:title>PURPOSE<\/jats:title>\n                    <jats:p>The response of triple-negative breast cancer (TNBC) to neoadjuvant therapy (NAT) varies widely. This study aimed to determine the performance of clinicopathologic biomarkers and volumetric changes on dynamic contrast\u2013enhanced magnetic resonance imaging (DCE-MRI) in predicting pathologic complete response (pCR) to NAT in patients with TNBC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>PATIENTS AND METHODS<\/jats:title>\n                    <jats:p>\n                      This study included 264 patients with stage I to III TNBC enrolled in a prospective clinical trial. These patients underwent DCE-MRI at baseline and after two and\/or after four cycles of dose-dense anthracycline and cyclophosphamide. Tumor volume (TV) was calculated by measuring three tumor dimensions at each time point. Clinicopathologic markers were analyzed. Treatment response at surgery (pCR\n                      <jats:italic toggle=\"yes\">v<\/jats:italic>\n                      non-pCR) was documented. The patients were randomly assigned to discovery and validation cohorts. Multiple logistic regression and receiver operating characteristic analysis were used to assess associations and build predictive models.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Of the 264 patients, 124 (47%) achieved a pCR. The optimal thresholds for TV reduction (TVR) on DCE-MRI were \u226560% after two cycles and \u226590% after four cycles. TVR, Ki-67, and stromal tumor-infiltrating lymphocytes (sTILs) were independently associated with pCR on univariable analysis. A combined model including TVR \u226560% after two cycles, sTILs, and Ki-67 predicted pCR with an AUC of 0.84 (90% CI. 0.76 to 0.92) in the discovery cohort and 0.80 (95% CI, 0.71 to 0.88) in the validation cohort. A combined model including TVR \u226590% after four cycles, sTILs, and Ki-67 predicted pCR with an AUC of 0.79 (90% CI, 0.71 to 0.86) in the discovery cohort and 0.80 (95% CI, 0.72 to 0.88) in the validation cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>A model incorporating imaging and clinicopathologic variables showed good performance in predicting pCR.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1200\/po-25-00410","type":"journal-article","created":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T20:57:16Z","timestamp":1766091436000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":4,"title":["Imaging- and Tumor Biomarker\u2013Based Multivariable Model for Early Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast 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