ArticleEuropean journal of medical research2023
Nomogram for predicting survival in patients with mucinous breast cancer undergoing chemotherapy and surgery: a population-based study.
Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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8 authors at 3 institutions in 1 country.
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Abstract
backgroundThe prognosis of patients with mucinous breast cancer (MuBC) is affected by several factors, but the low incidence of MuBC makes it difficult to conduct extensive and in-depth studies. This study was designed to establish a prognostic model and verify its accuracy in patients with MuBC after chemotherapy and surgery to help develop personalized treatment strategies. MATERIALS AND
methodsPatients with MuBC who underwent chemotherapy and surgery from 2004 to 2015 were identified in the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic factors of patients with MuBC were investigated using a Cox proportional hazards regression analysis. Based on the identified factors, a nomogram was constructed to forecast the overall survival (OS) of patients at 3, 5, and 10 years. Internal (from SEER) and external (from Yunnan Cancer Center, YNCC) verification queues were used to verify the nomogram and demonstrate the predictive capacity of this model.
resultsThe study comprised 1668 MuBC patients from the SEER database and 107 from the YNCC. The nomogram included four characteristics: age, anatomical stage, surgical method, and radiotherapy. The concordance indices in the training, internal verification, and external verification queues were 0.680, 0.768, and 0.864, respectively. The calibration curves for the nomogram showed excellent agreement between the predictions and observations. This nomogram has good clinical application value according to the decision curve analysis.
conclusionsThe prognosis of patients with MuBC who have undergone chemotherapy and surgery can be forecasted using this nomogram, which would be beneficial to help create individualized treatment plans for the affected patients.
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