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A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients

BACKGROUND AND PURPOSE: Web-based prognostic calculators have been developed to inform about the use of adjuvant systemic treatments in breast cancer. CancerMath and PREDICT are two examples of web-based prognostic tools that predict patient survival up to 15 years after an initial diagnosis of brea...

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Autores principales: Polchai, Nuanphan, Sa-nguanraksa, Doonyapat, Numprasit, Warapan, Thumrongtaradol, Thanawat, O-charoenrat, Eng, O-charoenrat, Pornchai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354915/
https://www.ncbi.nlm.nih.gov/pubmed/32753968
http://dx.doi.org/10.2147/CMAR.S258143
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author Polchai, Nuanphan
Sa-nguanraksa, Doonyapat
Numprasit, Warapan
Thumrongtaradol, Thanawat
O-charoenrat, Eng
O-charoenrat, Pornchai
author_facet Polchai, Nuanphan
Sa-nguanraksa, Doonyapat
Numprasit, Warapan
Thumrongtaradol, Thanawat
O-charoenrat, Eng
O-charoenrat, Pornchai
author_sort Polchai, Nuanphan
collection PubMed
description BACKGROUND AND PURPOSE: Web-based prognostic calculators have been developed to inform about the use of adjuvant systemic treatments in breast cancer. CancerMath and PREDICT are two examples of web-based prognostic tools that predict patient survival up to 15 years after an initial diagnosis of breast cancer. The aim of this study is to validate the use of CancerMath and PREDICT as prognostic tools in Thai breast cancer patients. PATIENTS AND METHODS: A total of 615 patients who underwent surgical treatment for stage I to III breast cancer from 2003 to 2011 at the Division of Head Neck and Breast Surgery, Department of Surgery, Siriraj Hospital, Mahidol University, Thailand were recruited. A model-predicted overall survival rate (OS) and the actual OS of the patients were compared. The efficacy of the model was evaluated using receiver-operating characteristic (ROC) analysis. RESULTS: For CancerMath, the predicted 5-year OS was 88.9% and the predicted 10-year OS was 78.3% (p<0.001). For PREDICT, the predicted 5-year OS was 83.1% and the predicted 10-year OS was 72.0% (p<0.001). The actual observed 5-year OS was 90.8% and the observed 10-year OS was 82.6% (p<0.001). CancerMath demonstrated better predictive performance than PREDICT in all subgroups for both 5- and 10-year OS. In addition, there was a marked difference between CancerMath and observed survival rates in patients who were older as well as patients who were stage N3. The area under the ROC curve for 5-year OS in CancerMath and 10-year OS was 0.74 (95% CI; 0.65–0.82) and 0.75 (95% CI; 0.68–0.82). In the PREDICT group, the area under the ROC curve for 5-year OS was 0.78 (95% CI; 0.71–0.85) and for 10-year OS, it was 0.78 (95% CI; 0.71–0.84). CONCLUSION: CancerMath and PREDICT models both underestimated the OS in Thai breast cancer patients. Thus, a novel prognostic model for Thai breast cancer patients is required.
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spelling pubmed-73549152020-08-03 A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients Polchai, Nuanphan Sa-nguanraksa, Doonyapat Numprasit, Warapan Thumrongtaradol, Thanawat O-charoenrat, Eng O-charoenrat, Pornchai Cancer Manag Res Original Research BACKGROUND AND PURPOSE: Web-based prognostic calculators have been developed to inform about the use of adjuvant systemic treatments in breast cancer. CancerMath and PREDICT are two examples of web-based prognostic tools that predict patient survival up to 15 years after an initial diagnosis of breast cancer. The aim of this study is to validate the use of CancerMath and PREDICT as prognostic tools in Thai breast cancer patients. PATIENTS AND METHODS: A total of 615 patients who underwent surgical treatment for stage I to III breast cancer from 2003 to 2011 at the Division of Head Neck and Breast Surgery, Department of Surgery, Siriraj Hospital, Mahidol University, Thailand were recruited. A model-predicted overall survival rate (OS) and the actual OS of the patients were compared. The efficacy of the model was evaluated using receiver-operating characteristic (ROC) analysis. RESULTS: For CancerMath, the predicted 5-year OS was 88.9% and the predicted 10-year OS was 78.3% (p<0.001). For PREDICT, the predicted 5-year OS was 83.1% and the predicted 10-year OS was 72.0% (p<0.001). The actual observed 5-year OS was 90.8% and the observed 10-year OS was 82.6% (p<0.001). CancerMath demonstrated better predictive performance than PREDICT in all subgroups for both 5- and 10-year OS. In addition, there was a marked difference between CancerMath and observed survival rates in patients who were older as well as patients who were stage N3. The area under the ROC curve for 5-year OS in CancerMath and 10-year OS was 0.74 (95% CI; 0.65–0.82) and 0.75 (95% CI; 0.68–0.82). In the PREDICT group, the area under the ROC curve for 5-year OS was 0.78 (95% CI; 0.71–0.85) and for 10-year OS, it was 0.78 (95% CI; 0.71–0.84). CONCLUSION: CancerMath and PREDICT models both underestimated the OS in Thai breast cancer patients. Thus, a novel prognostic model for Thai breast cancer patients is required. Dove 2020-07-08 /pmc/articles/PMC7354915/ /pubmed/32753968 http://dx.doi.org/10.2147/CMAR.S258143 Text en © 2020 Polchai et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Polchai, Nuanphan
Sa-nguanraksa, Doonyapat
Numprasit, Warapan
Thumrongtaradol, Thanawat
O-charoenrat, Eng
O-charoenrat, Pornchai
A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title_full A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title_fullStr A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title_full_unstemmed A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title_short A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients
title_sort comparison between the online prediction models cancermath and predict as prognostic tools in thai breast cancer patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7354915/
https://www.ncbi.nlm.nih.gov/pubmed/32753968
http://dx.doi.org/10.2147/CMAR.S258143
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