Establishing a predicted model to evaluate prognosis for initially diagnosed metastatic Her2-positive breast cancer patients and exploring the benefit from local surgery

• Published in: PloS one 2020-11, Vol.15 (11), p.e0242155
• Main Authors: Lin, Hong, Wu, Yanxuan, Liang, Guoxi, Chen, Liming
• Format: Article
• Language: English
• Subjects: Adult; Aged; Algorithms; Brain cancer; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - metabolism; Breast Neoplasms - physiopathology; Breast Neoplasms - surgery; Breast surgery; Calibration; Cancer therapies; Care and treatment; Chemotherapy; Decision making; Epidemiology; Epidermal growth factor; ErbB-2 protein; Estrogen receptors; Estrogens; Female; HER2 positive breast cancer; Histology; Humans; Kaplan-Meier Estimate; Marital status; Medical diagnosis; Medical prognosis; Medical schools; Medicine and Health Sciences; Metastases; Metastasis; Middle Aged; Mortality; Neoplasm Metastasis; Neoplasm Staging; Nomograms; Nomographs; Oncology; Patient outcomes; Performance indices; Prognosis; Rank tests; Receptor, ErbB-2 - metabolism; Regression analysis; Retrospective Studies; Risk; Risk Assessment; SEER Program; Surgery; Survival; Survival analysis; Training; Treatment Outcome; Young Adult
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0242155

For patients initially diagnosed with metastatic Her2-positive breast cancer (MHBC), we intended to construct a nomogram with risk stratification to predict prognosis and to explore the role of local surgery. We retrieved data from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier (KM) method and log-rank test were used for the selection of significant variables. Cox regression analysis and Fine-Gray test were utilized to confirm independent prognostic factors of overall survival (OS) and breast cancer-specific survival (BCSS). A nomogram predicting 1-year, 3-year, and 5-year OS was developed and validated. Patients were stratified based on the optimal cut-off values of total personal score. KM method and log-rank test were used to estimate OS prognosis and benefit from local surgery and chemotherapy. There were 1680 and 717 patients in the training and validation cohort. Age, race, marriage, T stage, estrogen receptor (ER) status, visceral metastasis (bone, brain, liver and lung) were identified as independent prognostic factors for OS and BCSS, while histology was also corelated with OS. C-indexes in the training and validation cohort were 0.70 and 0.68, respectively. Calibration plots indicated precise predictive ability. The total population was divided into low- (208 points) prognostic groups. Local surgery and chemotherapy brought various degrees of survival benefit for patients with diverse-risk prognosis. We constructed a model with accurate prediction and discrimination. It would provide a reference for clinicians' decision-making. Surgery on the primary lesion was recommended for patients with good physical performance status, while further study on optimal surgical opportunity was needed.