Development and validation of a nomogram in survival prediction among advanced breast cancer patients

BACKGROUND: The overall survival (OS) among patients with advanced breast cancer (ABC) varies greatly. Although molecular subtype is known as the most important factor in OS differentiation, significant differences in OS among patients with the same molecular subtype still occur, leading to the need for a more accurate prognostic prediction model. This study aimed to develop a prediction model (nomogram) based on current diagnosis and treatment to predict the OS of newly diagnosed ABC patients in China. METHODS: From the institution’s database, we collected data of 368 ABC patients from Sun Yat-sen Memorial Hospital (national hospital) as a training set to establish a nomogram with prognostic risk factors that calculated the predicted probability of survival. Nomograms were independently validated with 278 patients with ABC from two other institutions using the concordance index (C-index), calibration plots and risk group stratifications. RESULTS: The initial primary tumor stage, molecular subtype, disease-free survival (DFS), presence of brain metastasis, and the tumor burden of metastasis disease (local recurrence, oligo-metastatic disease, or multiple-metastatic disease) were included in the prognostic nomogram. The nomogram had a C-index of 0.77 and 0.71 in the training and the validation sets, respectively. The nomogram was able to stratify patients into different risk groups, respectively (HR 6.81, 95% CI: 4.69 to 9.89, P<0.001). In the lower risk score group (risk score <11), there was no significant difference between the OS with chemotherapy and hormone therapy (HR 0.81, 95% CI: 0.44 to 1.47, P=0.48). CONCLUSIONS: We have constructed a novel prediction nomogram that can guide the physicians to select personalized treatment options. Furthermore, our study is the first to add oligo-metastatic disease and primary endocrine/trastuzumab resistance into the prognostic models.