Triple-negative breast cancer (TNBC) patients who achieve a pathologic complete response (pCR) after Neoadjuvant chemotherapy (NAC) have better prognoses. This study intended to develop an intuitive nomogram based on simple blood indexes to predict the pCR of standard NAC in TNBC patients with an ultimate aim to tailor more beneficial treatments and improve outcomes.
A total of 80 TNBC patients who received standard NAC, 4 cycles of anthracycline (epirubicin or adriamycin) and cyclophosphamide followed by 4 cycles of taxane, and subsequent surgery in Zhejiang Cancer Hospital between January 2016 and December 2018 were retrospected and their pre-treatment clinical features and several simple blood indexes were collected. The optimal cutoff values of blood indexes were determined by Youden index using the receiver operating characteristic (ROC) curve analysis. The forward stepwise logistic regression (likelihood ratio) analysis was applied to identify predictive factors for pCR of NAC. Then a nomogram was developed according to the logistic model. The calibration of the nomogram was carried out by internal validation with the bootstrap resampling approach and displayed using a calibration curve. The goodness of fit for the model was checked by a Hosmer-Lemeshow test. The discrimination of the nomogram was graphically shown by the ROC curve and quantified by the area under the curve (AUC).
The pCR was achieved in 39 (48.8%) patients after NAC. Multivariate logistic regression analysis identified four independent indicators: clinical tumor stage, lymphocyte monocyte ratio, fibrinogen and D-dimer. The nomogram established based on those factors showed its discrimination with an AUC of 0.803 (95% CI 0.706-0.899) and a bias-corrected AUC of 0.771. The calibration curve and Hosmer-Lemeshow test showed the prediction of the nomogram was a good fit with actual observation.
Based on four simple, easily accessible, inexpensive and objective factors, the nomogram proposed in the present study exhibited a sufficient ability of discrimination for predicting pCR of NAC in TNBC patients.
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