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Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer

BACKGROUND: Breast cancer patients who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) have favorable outcomes. Reliable predictors for pCR help to identify patients who will benefit most from NAC. The pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR)...

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Autores principales: Qu, Fanli, Li, Zongyan, Lai, Shengqing, Zhong, XiaoFang, Fu, Xiaoyan, Huang, Xiaojia, Li, Qian, Liu, Shengchun, Li, Haiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531528/
https://www.ncbi.nlm.nih.gov/pubmed/34692474
http://dx.doi.org/10.3389/fonc.2021.681905
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author Qu, Fanli
Li, Zongyan
Lai, Shengqing
Zhong, XiaoFang
Fu, Xiaoyan
Huang, Xiaojia
Li, Qian
Liu, Shengchun
Li, Haiyan
author_facet Qu, Fanli
Li, Zongyan
Lai, Shengqing
Zhong, XiaoFang
Fu, Xiaoyan
Huang, Xiaojia
Li, Qian
Liu, Shengchun
Li, Haiyan
author_sort Qu, Fanli
collection PubMed
description BACKGROUND: Breast cancer patients who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) have favorable outcomes. Reliable predictors for pCR help to identify patients who will benefit most from NAC. The pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR) has been shown to be a prognostic predictor in several malignancies, but its predictive value for pCR in breast cancer is still unknown. This study aims to investigate the predictive role of AAPR in breast cancer patients and develop an AAPR-based nomogram for pCR rate prediction. METHODS: A total of 780 patients who received anthracycline and taxane-based NAC from January 2012 to March 2018 were retrospectively analyzed. Univariate and multivariate analyses were performed to assess the predictive value of AAPR and other clinicopathological factors. A nomogram was developed and calibrated based on multivariate logistic regression. A validation cohort of 234 patients was utilized to further validate the predictive performance of the model. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model. RESULTS: Patients with a lower AAPR (<0.583) had a significantly reduced pCR rate (OR 2.228, 95% CI 1.246-3.986, p=0.007). Tumor size, clinical nodal status, histological grade, PR, Ki67 and AAPR were identified as independent predictors and included in the final model. The nomogram was used as a graphical representation of the model. The nomogram had satisfactory calibration and discrimination in both the training cohort and validation cohort (the C-index was 0.792 in the training cohort and 0.790 in the validation cohort). Furthermore, DCA indicated a clinical net benefit from the nomogram. CONCLUSIONS: Pretreatment serum AAPR is a potentially valuable predictor for pCR in breast cancer patients who receive NAC. The AAPR-based nomogram is a noninvasive tool with favorable predictive accuracy for pCR, which helps to make individualized treatment strategy decisions.
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spelling pubmed-85315282021-10-23 Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer Qu, Fanli Li, Zongyan Lai, Shengqing Zhong, XiaoFang Fu, Xiaoyan Huang, Xiaojia Li, Qian Liu, Shengchun Li, Haiyan Front Oncol Oncology BACKGROUND: Breast cancer patients who achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) have favorable outcomes. Reliable predictors for pCR help to identify patients who will benefit most from NAC. The pretreatment serum albumin-to-alkaline phosphatase ratio (AAPR) has been shown to be a prognostic predictor in several malignancies, but its predictive value for pCR in breast cancer is still unknown. This study aims to investigate the predictive role of AAPR in breast cancer patients and develop an AAPR-based nomogram for pCR rate prediction. METHODS: A total of 780 patients who received anthracycline and taxane-based NAC from January 2012 to March 2018 were retrospectively analyzed. Univariate and multivariate analyses were performed to assess the predictive value of AAPR and other clinicopathological factors. A nomogram was developed and calibrated based on multivariate logistic regression. A validation cohort of 234 patients was utilized to further validate the predictive performance of the model. The C-index, calibration plots and decision curve analysis (DCA) were used to evaluate the discrimination, calibration and clinical value of the model. RESULTS: Patients with a lower AAPR (<0.583) had a significantly reduced pCR rate (OR 2.228, 95% CI 1.246-3.986, p=0.007). Tumor size, clinical nodal status, histological grade, PR, Ki67 and AAPR were identified as independent predictors and included in the final model. The nomogram was used as a graphical representation of the model. The nomogram had satisfactory calibration and discrimination in both the training cohort and validation cohort (the C-index was 0.792 in the training cohort and 0.790 in the validation cohort). Furthermore, DCA indicated a clinical net benefit from the nomogram. CONCLUSIONS: Pretreatment serum AAPR is a potentially valuable predictor for pCR in breast cancer patients who receive NAC. The AAPR-based nomogram is a noninvasive tool with favorable predictive accuracy for pCR, which helps to make individualized treatment strategy decisions. Frontiers Media S.A. 2021-10-08 /pmc/articles/PMC8531528/ /pubmed/34692474 http://dx.doi.org/10.3389/fonc.2021.681905 Text en Copyright © 2021 Qu, Li, Lai, Zhong, Fu, Huang, Li, Liu and Li https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Qu, Fanli
Li, Zongyan
Lai, Shengqing
Zhong, XiaoFang
Fu, Xiaoyan
Huang, Xiaojia
Li, Qian
Liu, Shengchun
Li, Haiyan
Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title_full Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title_fullStr Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title_full_unstemmed Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title_short Construction and Validation of a Serum Albumin-to-Alkaline Phosphatase Ratio-Based Nomogram for Predicting Pathological Complete Response in Breast Cancer
title_sort construction and validation of a serum albumin-to-alkaline phosphatase ratio-based nomogram for predicting pathological complete response in breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8531528/
https://www.ncbi.nlm.nih.gov/pubmed/34692474
http://dx.doi.org/10.3389/fonc.2021.681905
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