Novel nomograms for predicting overall survival and cancer-specific survival in invasive lobular carcinoma of the breast.

PURPOSE

Currently, the clinical diagnosis and treatment for invasive lobular carcinoma of the breast (ILC) often draw on the treatment approaches used for invasive ductal carcinoma (IDC), despite significant differences between the two. Studies evaluating the risk and prognosis of ILC are limited; thus, our goal was to construct a predictive model for the prognosis of ILC.

METHODS

Clinical data of patients diagnosed with unilateral primary ILC from 2010 to 2015 were acquired from the SEER database. Independent prognostic factors affecting patients' overall survival (OS) and cancer-specific survival (CSS) were determined through univariate and multivariate analyses based on COX proportional hazards model and Fine-Gray competing risks model. Nomograms were constructed to forecast the 1-year, 3-year, and 5-year OS and CSS of the patients.

RESULTS

A total of 6,616 patients with ILC were included, with 1,083 deaths, of which 541 were attributed to ILC, and 542 to other causes. The univariate and multivariate analyses indicated that age, N stage, stage, surgery, PR status, radiotherapy, and brain metastasis are independent risk factors for OS of ILC patients, while age, N stage, stage, surgery, PR status, and brain metastasis are independent risk factors for CSS of ILC patients. The C-index, area under the ROC curve, and calibration curve of the 1-, 3-, and 5-year OS and CSS prediction models confirmed that it had good predictive capability.

CONCLUSIONS

This study has developed subtype-specific predictive models for OS and CSS of patients with ILC, offering clinicians a regimen. Reference for assessing patient prognosis and formulating individualized treatment.