Document Type: Research Articles
Master's Degree in Health Sciences of the Graduate Program in Health Sciences, State University of Maringá (UEM), Brazil.
Postdoctoral Fellowship of the Postgraduate Program in Health Sciences, State University of Maringá (UEM), Brazil.
Student of the Medical School, State University of Maringá (UEM), Brazil.
Student of the Medical at Federal University of Paraná (UFPR), Brazil.
Lecturer at the Nursing Department of the Paraná State University, Paranavaí campus Brazil.
Lecturer at the Department of Medicine at Unicesumar University and Professor at the Department of Postgraduate Science in Health, State University of Maringá (UEM),Brazil.
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.