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Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population

OBJECTIVE: To analyze the diagnostic accuracy of predictive models of breast cancer risk for the Brazilian population. METHOD: A cross-sectional, study was conducted in a sample of 382 women aged 35-69 years who were users of the Unified Health System (SUS) residing in a municipality in southern Bra...

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Autores principales: Stevanato, Kely Paviani, Pedroso, Raíssa Bocchi, Iora, Pedro, dos Santos, Lander, Pelloso, Fernando Castilho, de Melo, Willian Augusto, de Barros Carvalho, Maria Dalva, Pelloso, Sandra Marisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: West Asia Organization for Cancer Prevention 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063010/
https://www.ncbi.nlm.nih.gov/pubmed/31759366
http://dx.doi.org/10.31557/APJCP.2019.20.11.3407
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author Stevanato, Kely Paviani
Pedroso, Raíssa Bocchi
Iora, Pedro
dos Santos, Lander
Pelloso, Fernando Castilho
de Melo, Willian Augusto
de Barros Carvalho, Maria Dalva
Pelloso, Sandra Marisa
author_facet Stevanato, Kely Paviani
Pedroso, Raíssa Bocchi
Iora, Pedro
dos Santos, Lander
Pelloso, Fernando Castilho
de Melo, Willian Augusto
de Barros Carvalho, Maria Dalva
Pelloso, Sandra Marisa
author_sort Stevanato, Kely Paviani
collection PubMed
description OBJECTIVE: To analyze the diagnostic accuracy of predictive models of breast cancer risk for the Brazilian population. METHOD: A cross-sectional, study was conducted in a sample of 382 women aged 35-69 years who were users of the Unified Health System (SUS) residing in a municipality in southern Brazil. RESULTS: The results showed that the Tyrer-Cuzick model had the highest mean risk values and estimates (proportion) for predicting the 5-year risk of breast cancer, reaching a maximum risk of ±1.63% in the 60-64 year age group. For the 90-year risk, a maximum risk of ±12.8% was predicted for the 50-54 year age group using this model. The 5-year risk calculated by the three tools increased progressively with increasing age, where the mean risk was ±0.8% in women aged 35-39 and reached ±1.50% in women aged 65-69. The 90-year risk declined with increasing age only in the Tyrer-Cuzick model, from ±10.8% to ±9%. The BRCAPRO model presented a greater sensitivity compared to the Gail and Tyrer-Cuzick models. And, the model that presented greater specificity was Gail. CONCLUSION: The Tyrer-Cuzick model presented the highest risk estimates for 5 years and 90 years in the studied population, however, this data is not enough to validate this tool, since when analyzing the sensitivity and specificity the BRCAPRO and Gail have the highest values respectively.
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spelling pubmed-70630102020-03-17 Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population Stevanato, Kely Paviani Pedroso, Raíssa Bocchi Iora, Pedro dos Santos, Lander Pelloso, Fernando Castilho de Melo, Willian Augusto de Barros Carvalho, Maria Dalva Pelloso, Sandra Marisa Asian Pac J Cancer Prev Research Article OBJECTIVE: To analyze the diagnostic accuracy of predictive models of breast cancer risk for the Brazilian population. METHOD: A cross-sectional, study was conducted in a sample of 382 women aged 35-69 years who were users of the Unified Health System (SUS) residing in a municipality in southern Brazil. RESULTS: The results showed that the Tyrer-Cuzick model had the highest mean risk values and estimates (proportion) for predicting the 5-year risk of breast cancer, reaching a maximum risk of ±1.63% in the 60-64 year age group. For the 90-year risk, a maximum risk of ±12.8% was predicted for the 50-54 year age group using this model. The 5-year risk calculated by the three tools increased progressively with increasing age, where the mean risk was ±0.8% in women aged 35-39 and reached ±1.50% in women aged 65-69. The 90-year risk declined with increasing age only in the Tyrer-Cuzick model, from ±10.8% to ±9%. The BRCAPRO model presented a greater sensitivity compared to the Gail and Tyrer-Cuzick models. And, the model that presented greater specificity was Gail. CONCLUSION: The Tyrer-Cuzick model presented the highest risk estimates for 5 years and 90 years in the studied population, however, this data is not enough to validate this tool, since when analyzing the sensitivity and specificity the BRCAPRO and Gail have the highest values respectively. West Asia Organization for Cancer Prevention 2019 /pmc/articles/PMC7063010/ /pubmed/31759366 http://dx.doi.org/10.31557/APJCP.2019.20.11.3407 Text en This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Stevanato, Kely Paviani
Pedroso, Raíssa Bocchi
Iora, Pedro
dos Santos, Lander
Pelloso, Fernando Castilho
de Melo, Willian Augusto
de Barros Carvalho, Maria Dalva
Pelloso, Sandra Marisa
Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title_full Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title_fullStr Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title_full_unstemmed Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title_short Comparative Analysis between the Gail, Tyrer-Cuzick and BRCAPRO Models for Breast Cancer Screening in Brazilian Population
title_sort comparative analysis between the gail, tyrer-cuzick and brcapro models for breast cancer screening in brazilian population
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7063010/
https://www.ncbi.nlm.nih.gov/pubmed/31759366
http://dx.doi.org/10.31557/APJCP.2019.20.11.3407
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