Abstract A004: Validation of the PREDICT breast version 3.0 prognostic tool in the US breast cancer patients

Abstract PREDICT Breast v3 is the latest version of a prognostic tool designed to predict the treatment responses for early invasive breast cancer patients. It was developed using data from approximately 35,000 women diagnosed between 2000 and 2018 in the United Kingdom. However, its performance in the United States (US) population is unknown. This study aims to validate PREDICT Breast v3 using the newly released Surveillance, Epidemiology, and End Results (SEER) outcome data for US breast cancer patients and to address potential health disparities. We selected over 860,000 female patients diagnosed with primary breast cancer between 2000 and 2021 and followed for at least 5 years from the SEER database. The model’s performance was measured by calibration and discrimination; comparing predicted and observed 5-, 10- and 15-year breast cancer-specific survival outcomes and determining discrimination through the area under the receiver-operator curves (AUC). PREDICT Breast v3 demonstrated good calibration and discrimination for both short- and long-term up breast cancer-specific mortality in US populations. The predicted 10-year breast cancer-specific mortality differed from observed by 11% in ER-positive and 6 % in ER-negative patients. The AUCs for 15-year breast cancer-specific mortality were 0.81 for ER-positive patients and 0.76 for ER-negative patients. When stratified by race and ethnicity, the model showed strong performance in Non-Hispanic Asians ER-positive patients, despite being originally developed based on the UK population. These results are consistent with previous validations in Malaysia, Japan, and other Asian countries for PREDICT Breast v2. However, the model poorly estimated the number of deaths in Non-Hispanic Black individuals for both ER-positive and ER-negative. In conclusion, this study marks the first validation of PREDICT Breast v3 in the US and demonstrates that it is a reliable and generalizable tool, capable of providing longer term follow-up time up to 15 years for a wide and diverse population. Citation Format: Yi-Wen Hsiao, Paul Pharaoh, Pei-Chen Peng. Validation of the PREDICT breast version 3.0 prognostic tool in the US breast cancer patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A004.

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Publication Details

Journal
Cancer Epidemiology Biomarkers & Prevention
Published
2024-09-21
DOI
https://doi.org/10.1158/1538-7755.disp24-a004
Primary Topic
Breast Cancer Treatment Studies
Type
article
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article

Abstract A004: Validation of the PREDICT breast version 3.0 prognostic tool in the US breast cancer patients

Paul Pharaoh, Yi-Wen Hsiao, Pei-Chen Peng
Cancer Epidemiology Biomarkers & Prevention
Breast Cancer Treatment Studies
article

Abstract A004: Validation of the PREDICT breast version 3.0 prognostic tool in the US breast cancer patients

Paul Pharaoh, Yi-Wen Hsiao, Pei-Chen Peng
article en

Abstract

Abstract PREDICT Breast v3 is the latest version of a prognostic tool designed to predict the treatment responses for early invasive breast cancer patients. It was developed using data from approximately 35,000 women diagnosed between 2000 and 2018 in the United Kingdom. However, its performance in the United States (US) population is unknown. This study aims to validate PREDICT Breast v3 using the newly released Surveillance, Epidemiology, and End Results (SEER) outcome data for US breast cancer patients and to address potential health disparities. We selected over 860,000 female patients diagnosed with primary breast cancer between 2000 and 2021 and followed for at least 5 years from the SEER database. The model’s performance was measured by calibration and discrimination; comparing predicted and observed 5-, 10- and 15-year breast cancer-specific survival outcomes and determining discrimination through the area under the receiver-operator curves (AUC). PREDICT Breast v3 demonstrated good calibration and discrimination for both short- and long-term up breast cancer-specific mortality in US populations. The predicted 10-year breast cancer-specific mortality differed from observed by 11% in ER-positive and 6 % in ER-negative patients. The AUCs for 15-year breast cancer-specific mortality were 0.81 for ER-positive patients and 0.76 for ER-negative patients. When stratified by race and ethnicity, the model showed strong performance in Non-Hispanic Asians ER-positive patients, despite being originally developed based on the UK population. These results are consistent with previous validations in Malaysia, Japan, and other Asian countries for PREDICT Breast v2. However, the model poorly estimated the number of deaths in Non-Hispanic Black individuals for both ER-positive and ER-negative. In conclusion, this study marks the first validation of PREDICT Breast v3 in the US and demonstrates that it is a reliable and generalizable tool, capable of providing longer term follow-up time up to 15 years for a wide and diverse population. Citation Format: Yi-Wen Hsiao, Paul Pharaoh, Pei-Chen Peng. Validation of the PREDICT breast version 3.0 prognostic tool in the US breast cancer patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A004.

Cancer Epidemiology Biomarkers & PreventionVol. 33(9_Supplement)
Cedars-Sinai Medical Center (US)
Gender equality
Openalex Percentile: Top 77%
Breast Cancer Treatment Studies
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