Development and validation of a nomogram to predict survival after neoadjuvant chemotherapy in elderly women with triple-negative invasive ductal breast cancer: A SEER population-based study

Objectives: To construct and verify a nomogram for post-neoadjuvant chemotherapy survival predication in elderly women with triple-negative invasive ductal breast cancer.

Methods: Elderly patients diagnosed as triple-negative invasive ductal breast cancer between 2019-2000 were screened from surveillance, epidemiology, and end results database. Depending on the post-neoadjuvant chemotherapy pathological response, they were assigned to the complete or non-complete response group. Inter-group clinicopathological characteristics and disease-specific and overall survivals were compared. Then, they were allocated randomly into the training or validation cohort. A prediction nomogram was developed in the training cohort and verified in the validation cohort.

Results: A total of 382 patients were included, with 285 patients in non-response group and 97 patients in response group. After propensity score matching, disease-specific survival showed a significant difference between response and non-response groups (88.7% versus 64.6%, p<0.001). The training cohort included 196 patients and the validation cohort included 82 patients. A total of 7 variables (age, race, tumor location, tumor-node-metastasis stage, summary stage, receipt of surgery, and response to neoadjuvant chemotherapy) were integrated to construct a survival prediction nomogram. The C-indexes were 0.756 in the training cohort and 0.791 in the validation cohort. In both cohorts, the predicted survival showed satisfactory coherence with the actual survival in the calibration curve analysis.

Conclusion: In elderly women with triple-negative invasive ductal breast cancer, post-neoadjuvant chemotherapy pathological complete response could indicate improved disease-specific survival. A novel survival prediction nomogram was created to have satisfactory performance in these patients.