Comparative effectiveness study of breast-conserving surgery and mastectomy in the general population: A NCDB analysis

This study aimed to develop a nomogram to predict the overall survival (OS) of stage IV breast cancer patients. We searched the National Cancer Database (NCDB) for stage IV breast cancer patients diagnosed between 2010 and 2013. Predictors of OS were identified and a nomogram was developed and validated using concordance index (C‐index), calibration plots, and risk group stratifications. A total of 7199 patients from the NCDB were included in the study. With a median follow‐up of 25.7 months, the 1‐year and 3‐year OS rates were 80.6% and 52.5%, respectively. Race, age, comorbidity status, T‐stage, grade, ER/PR/Her2 status, the presence of lung/liver/brain metastasis, surgery, radiotherapy, and chemotherapy were significantly associated with OS. The developed nomogram had a C‐index of 0.722 (95% CI 0.710–0.734) and 0.725 (95% CI 0.713–0.736) in the training and the validation cohorts, respectively. The predicted survival using the nomogram is well correlated with actual OS. The nomogram was able to stratify patients into different risk groups, among which the survival benefit of local therapy varied. We developed a nomogram to predict the overall survival of stage IV breast cancer patients. Prospectively designed studies with international collaborations are needed to further validate our nomogram.

Purpose: We evaluated the effect of younger age on recurrence risk in Chinese women diagnosed with T1N0M0 breast cancer (BC), using propensity score matching (PSM) analysis.Methods: We included 365 women who were diagnosed with T1N0M0 BC between 2003 and 2016, and who received surgery at our center. They were classified as younger (≤40 years) and older (>40 years). We used PSM to balance clinicopathologic characteristics between the two age groups. Survival was analyzed by the Kaplan–Meier method, before and after PSM.Results: Over a median follow‐up period of 79 months, 54 patients developed recurrences. Before PSM, younger patients had worse recurrence‐free survival (RFS) than older patients. Significantly worse RFS was seen in younger patients with HER2⁺ BC compared with their older counterparts. Younger patients had higher rates of locoregional recurrence rather than metastasis, especially in the first 5 years after diagnosis. After PSM, the two age groups still significantly differed in 5‐year RFS.Conclusion: Among PSM pairs with T1N0M0 BC, with equal baselines and treatment conditions, we found that patients who presented at younger ages had worse outcomes, independently of other pathological features. Younger patients with BC may require more individualized therapy to improve their prognosis.

Prediction of axillary lymph node (ALN) status preoperatively is critical in the management of breast cancer patients. This study aims to develop a new set of nomograms to accurately predict ALN status. We searched the National Cancer Database to identify eligible female breast cancer patients with profiles containing critical information. Patients diagnosed in 2010–2011 and 2012–2013 were designated the training (n = 99,618) and validation (n = 101,834) cohorts, respectively. We used binary logistic regression to investigate risk factors for ALN status and to develop a new set of nomograms to determine the probability of having any positive ALNs and N2–3 disease. We used ROC analysis and calibration plots to assess the discriminative ability and accuracy of the nomograms, respectively. In the training cohort, we identified age, quadrant of the tumor, tumor size, histology, ER, PR, HER2, tumor grade and lymphovascular invasion as significant predictors of ALNs status. Nomogram-A was developed to predict the probability of having any positive ALNs (P_any) in the full population with a C-index of 0.788 and 0.786 in the training and validation cohorts, respectively. In patients with positive ALNs, Nomogram-B was developed to predict the conditional probability of having N2–3 disease (P_con) with a C-index of 0.680 and 0.677 in the training and validation cohorts, respectively. The absolute probability of having N2–3 disease can be estimated by P_any*P_con. Both of the nomograms were well-calibrated. We developed a set of nomograms to predict the ALN status in breast cancer patients.