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Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?

OBJECTIVE: To evaluate the accuracy of the Gail model (GM) in women who already have a diagnosis of breast cancer (BC) from the Breast Pathology Service, Hospital Oncology Department of the Venezuelan Social Security Institute (SOH-IVSS) in the period 2004–2014. To compare the accuracy of the GM in...

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Autores principales: del Valle Peña Colmenares, Josepmilly, García, Carmen Cristina, Velásquez, Yazmin José Velásquez, Pino, Leider Arelis Campos, Rodríguez, Álvaro Gómez, Rodríguez, Wladimir José Villegas, Vargas, David José González, Herrera, Douglas José Angulo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cancer Intelligence 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550297/
https://www.ncbi.nlm.nih.gov/pubmed/37799948
http://dx.doi.org/10.3332/ecancer.2023.1590
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author del Valle Peña Colmenares, Josepmilly
García, Carmen Cristina
Velásquez, Yazmin José Velásquez
Pino, Leider Arelis Campos
Rodríguez, Álvaro Gómez
Rodríguez, Wladimir José Villegas
Vargas, David José González
Herrera, Douglas José Angulo
author_facet del Valle Peña Colmenares, Josepmilly
García, Carmen Cristina
Velásquez, Yazmin José Velásquez
Pino, Leider Arelis Campos
Rodríguez, Álvaro Gómez
Rodríguez, Wladimir José Villegas
Vargas, David José González
Herrera, Douglas José Angulo
author_sort del Valle Peña Colmenares, Josepmilly
collection PubMed
description OBJECTIVE: To evaluate the accuracy of the Gail model (GM) in women who already have a diagnosis of breast cancer (BC) from the Breast Pathology Service, Hospital Oncology Department of the Venezuelan Social Security Institute (SOH-IVSS) in the period 2004–2014. To compare the accuracy of the GM in women aged above and below 40 years with a diagnosis of BC. METHOD: Descriptive, retrospective, cross-sectional, 830 records of patients diagnosed with BC were reviewed between 2004 and 2014. RESULTS: The mean age for diagnosis of the disease was 46 ± 13 years; menarche age was 13 years ± 2; age at first birth 22 ± 5 years, with a history of biopsy 32 ± 11, the percentage of relatives with a primary history of BC reported (PHBC) 9.3%. Only 41% of women with a diagnosis of BC reported Gail >1.67 (positive Gail). In the dichotomous logistic regression that related positive Gail with the independent variables, it was observed: greater probability of positive Gail if menarche age <11 years (p < 0.036), PHBC (p = 0.005), previous biopsy (p = 0.007), age at first birth 25–29 years (p = 0.019). When stratifying by age, unlike the bivariate analysis, women over 40 years of age are more likely to have a positive Gail in menarche age <11 years (p = 0.008), PHBC (p = 0.001), previous biopsy (p = 0.025) when compared with younger women, the age at first birth between 25 and 29 years was statistically significant for both groups; however, the probability was higher in younger women (p = 0.008). CONCLUSION: There is no conclusive evidence to consider that the GM is applicable to Venezuelan women due to its low precision since it only identified 41% of the patients who had BC as high risk; however, when the factors are analysed separately, we found a higher probability of a positive Gail with statistical significance in EM <11 years, PHBC, previous biopsy and age at first birth 25–29 years; When stratifying by age, we observed that the age at first birth 25–29 years in women aged 40 or less increases the probability of a positive Gail. It is necessary to develop new risk assessment models that are adapted to our female population.
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spelling pubmed-105502972023-10-05 Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified? del Valle Peña Colmenares, Josepmilly García, Carmen Cristina Velásquez, Yazmin José Velásquez Pino, Leider Arelis Campos Rodríguez, Álvaro Gómez Rodríguez, Wladimir José Villegas Vargas, David José González Herrera, Douglas José Angulo Ecancermedicalscience Review OBJECTIVE: To evaluate the accuracy of the Gail model (GM) in women who already have a diagnosis of breast cancer (BC) from the Breast Pathology Service, Hospital Oncology Department of the Venezuelan Social Security Institute (SOH-IVSS) in the period 2004–2014. To compare the accuracy of the GM in women aged above and below 40 years with a diagnosis of BC. METHOD: Descriptive, retrospective, cross-sectional, 830 records of patients diagnosed with BC were reviewed between 2004 and 2014. RESULTS: The mean age for diagnosis of the disease was 46 ± 13 years; menarche age was 13 years ± 2; age at first birth 22 ± 5 years, with a history of biopsy 32 ± 11, the percentage of relatives with a primary history of BC reported (PHBC) 9.3%. Only 41% of women with a diagnosis of BC reported Gail >1.67 (positive Gail). In the dichotomous logistic regression that related positive Gail with the independent variables, it was observed: greater probability of positive Gail if menarche age <11 years (p < 0.036), PHBC (p = 0.005), previous biopsy (p = 0.007), age at first birth 25–29 years (p = 0.019). When stratifying by age, unlike the bivariate analysis, women over 40 years of age are more likely to have a positive Gail in menarche age <11 years (p = 0.008), PHBC (p = 0.001), previous biopsy (p = 0.025) when compared with younger women, the age at first birth between 25 and 29 years was statistically significant for both groups; however, the probability was higher in younger women (p = 0.008). CONCLUSION: There is no conclusive evidence to consider that the GM is applicable to Venezuelan women due to its low precision since it only identified 41% of the patients who had BC as high risk; however, when the factors are analysed separately, we found a higher probability of a positive Gail with statistical significance in EM <11 years, PHBC, previous biopsy and age at first birth 25–29 years; When stratifying by age, we observed that the age at first birth 25–29 years in women aged 40 or less increases the probability of a positive Gail. It is necessary to develop new risk assessment models that are adapted to our female population. Cancer Intelligence 2023-08-21 /pmc/articles/PMC10550297/ /pubmed/37799948 http://dx.doi.org/10.3332/ecancer.2023.1590 Text en © the authors; licensee ecancermedicalscience. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
del Valle Peña Colmenares, Josepmilly
García, Carmen Cristina
Velásquez, Yazmin José Velásquez
Pino, Leider Arelis Campos
Rodríguez, Álvaro Gómez
Rodríguez, Wladimir José Villegas
Vargas, David José González
Herrera, Douglas José Angulo
Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title_full Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title_fullStr Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title_full_unstemmed Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title_short Is using the Gail model to calculate the risk of breast cancer in the Venezuelan population justified?
title_sort is using the gail model to calculate the risk of breast cancer in the venezuelan population justified?
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10550297/
https://www.ncbi.nlm.nih.gov/pubmed/37799948
http://dx.doi.org/10.3332/ecancer.2023.1590
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