{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T15:49:43Z","timestamp":1790178583839,"version":"4.1.0"},"reference-count":33,"publisher":"Wiley","issue":"22","license":[{"start":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T00:00:00Z","timestamp":1600387200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2020,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Patients with metastatic triple\u2010negative breast cancer (mTNBC) frequently experience brain metastasis. This study aimed to identify prognostic factors and construct a nomogram for predicting brain metastasis possibility and brain screening benefit in mTNBC patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Patients with mTNBC treated at our institution between January 2011 and December 2018 were retrospectively analyzed. Fine and Gray's competing risks model was used to identify independent prognostic factors. By integrating these prognostic factors, a competing risk nomogram and risk stratification model were developed and evaluated with concordance index (C\u2010index) and calibration curves.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A total of 472 patients were retrospectively analyzed, including 305 patients in the training set, 78 patients in the validation set I and 89 patients in the validation set II. Four clinicopathological factors were identified as independent prognostic factors in the nomogram: lung metastasis, number of metastatic organ sites, hilar\/mediastinal lymph node metastasis and KI\u201067 index. The C\u2010indexes and calibration plots showed that the nomogram exhibited a sufficient level of discrimination. A risk stratification was further generated to divide all the patients into three prognostic groups. The cumulative incidence of brain metastasis at 18\u00a0months was 5.3% (95% confidence interval [CI], 2.5%\u20109.7%) for patients in the low\u2010risk group, while 14.3% (95% CI, 9.3%\u201020.4%) for patients with intermediate risk and 34.3% (95% CI, 26.8%\u201041.9%) for patients with high risk. Routine brain MRI screening improved overall survival in high\u2010risk group (HR 0.67, 95% CI 0.46\u20100.98, <jats:italic>P<\/jats:italic>\u00a0=\u00a0.039), but not in low\u2010risk group (HR 0.93, 95% CI 0.57\u20101.49, <jats:italic>P<\/jats:italic>\u00a0=\u00a0.751) and intermediate\u2010risk group (HR 0.83, 95% CI 0.55\u20101.27, <jats:italic>P<\/jats:italic>\u00a0=\u00a0.386).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>We have developed a robust tool that is able to predict subsequent brain metastasis in mTNBC patients. Our model will allow selection of patients at high risk for brain metastasis who might benefit from routine bran MRI screening.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cam4.3449","type":"journal-article","created":{"date-parts":[[2020,9,18]],"date-time":"2020-09-18T13:33:47Z","timestamp":1600436027000},"page":"8540-8551","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A risk stratification model for predicting brain metastasis and brain screening benefit in patients with metastatic triple\u2010negative breast cancer"],"prefix":"10.1002","volume":"9","author":[{"given":"Mingxi","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Medical Oncology Fudan University Shanghai Cancer Center Shanghai China"},{"name":"Department of Oncology Shanghai Medical College Fudan University Shanghai 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