A nomogram based on clinicopathological features and serological indicators predicting breast pathologic complete response of neoadjuvant chemotherapy in breast cancer

Abstract

A single tumor marker is not enough to predict the breast pathologic complete response (bpCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients. We aimed to establish a nomogram based on multiple clinicopathological features and routine serological indicators to predict bpCR after NAC in breast cancer patients. Data on clinical factors and laboratory indices of 130 breast cancer patients who underwent NAC and surgery in First Affiliated Hospital of Xi'an Jiaotong University from July 2017 to July 2019 were collected. Multivariable logistic regression analysis identified 11 independent indicators: body mass index, carbohydrate antigen 125, total protein, blood urea nitrogen, cystatin C, serum potassium, serum phosphorus, platelet distribution width, activated partial thromboplastin time, thrombin time, and hepatitis B surface antibodies. The nomogram was established based on these indicators. The 1000 bootstrap resampling internal verification calibration curve and the GiViTI calibration belt showed that the model was well calibrated. The Brier score of 0.095 indicated that the nomogram had a high accuracy. The area under the curve (AUC) of receiver operating characteristic (ROC) curve was 0.941 (95% confidence interval: 0.900–0.982) showed good discrimination of the model. In conclusion, this nomogram showed high accuracy and specificity and did not increase the economic burden of patients, thereby having a high clinical application value.

<i>TP53</i> Gene Polymorphism at Codon 72 as a Response Predictor for Neoadjuvant Chemotherapy

“…The immunohistochemical profile was predictive of pCR in multivariate analysis, with TN ( p = 0.04) and HER-2 ( p < 0.001) being the most responsive subtypes, which is consistent with the literature [32]. Ki-67 was not a predictor in the present study, contrary to the results of previous studies [33, 34]. The other variables analyzed were not predictors of pCR, which is consistent with the data published by Li et al [34].…”

A nomogram based on imaging features and serological indicators for predicting efficacy of neoadjuvant chemotherapy in gastric cancer

“…Similar results have been reported in breast cancer patients. [37] This study discovered that the cT stage had a separate bearing on predicting NAC's effectiveness. The disease is frequently more severe in these patients, and a higher cT stage signi es deeper tumor involvement.…”

Systematic Review of Nomograms Used for Predicting Pathological Complete Response in Early Breast Cancer

“…Nevertheless, 1097 titles were excluded due to not being compatible with our preestablished inclusion criteria. During the eligibility phase (full text reading), only seven studies [8,[11][12][13][14][15][16] were included for complete text reading and analyses (Figure 1). Overall, this review included 3822 women with early-stage BC.…”

“…Considering the importance of pCR during NAC and its impact on overall survival, mathematical models between baseline patient characteristics and the outcome of interest were developed (nomograms) [6,7] to predict ways in which clinical information (prior data to NAC) would be able to predict pCR. The objective of the nomograms is to maximize pCR likelihood [8], ensuring that a given patient is only exposed to NAC if they have the highest chances of benefitting from systemic chemotherapy.…”