4.6 Article

Association between socioeconomic factors at diagnosis and survival in breast cancer: A population-based study

期刊

CANCER MEDICINE
卷 9, 期 5, 页码 1922-1936

出版社

WILEY
DOI: 10.1002/cam4.2842

关键词

breast cancer; nomogram; SEER; socioeconomic; survival

类别

资金

  1. National Natural Science Foundation of China [81672601, 81872137, 81602311]
  2. Shanghai Committee of Science and Technology Funds [18ZR1407500]

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Background The associations between socioeconomic statuses and survival outcomes of breast cancer remain unclear. No model has included both histological and socioeconomic factors to predict the survival of breast cancer. This study was designed to develop nomograms to predict breast cancer-specific survival (BCSS) and overall survival (OS) with consideration of socioeconomic factors for breast cancer patients. Materials and methods We included a total of 207 749 female patients, diagnosed with malignant breast cancer between 2007 and 2012 from the Surveillance, Epidemiology, and End Results database. BCSS and OS were evaluated with Gray's test and log-rank tests, respectively. Marital statuses, insurance statuses, residence, median household income, poverty rate, unemployment rate, and education level were included as socioeconomic factors in univariate and multivariate Cox regression analyses. Clinicopathological factors and socioeconomic factors were integrated to construct nomograms. Calibration plots and concordance indexes (C-indexes) were used to evaluate the accuracy and discrimination of the models. Results Four and three socioeconomic factors were involved in constructing the nomograms for 3-, 5-, and 7-year BCSS and OS, respectively. The C-indexes of the final nomograms were higher than those of the TNM staging system for predicting BCSS (0.835 vs 0.782; P < .001) and OS (0.773 vs 0.676; P < .001). The performance of the nomograms for predicting OS was significantly lower when excluding socioeconomic factors (P < .001). Conclusion These findings may highlight the importance of developing health-related policies and the necessity of targeted social support-based interventions for high-risk patients.

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