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Insights into the performance of PREDICT tool in a large Mainland Chinese breast cancer cohort: a comparative analysis of versions 3.0 and 2.2.
- Source :
-
The oncologist [Oncologist] 2024 Aug 05; Vol. 29 (8), pp. e976-e983. - Publication Year :
- 2024
-
Abstract
- Background: PREDICT is a web-based tool for forecasting breast cancer outcomes. PREDICT version 3.0 was recently released. This study aimed to validate this tool for a large population in mainland China and compare v3.0 with v2.2.<br />Methods: Women who underwent surgery for nonmetastatic primary invasive breast cancer between 2010 and 2020 from the First Affiliated Hospital of Wenzhou Medical University were selected. Predicted and observed 5-year overall survival (OS) for both v3.0 and v2.2 were compared. Discrimination was compared using receiver-operator curves and DeLong test. Calibration was evaluated using calibration plots and chi-squared test. A difference greater than 5% was deemed clinically relevant.<br />Results: A total of 5424 patients were included, with median follow-up time of 58 months (IQR 38-89 months). Compared to v2.2, v3.0 did not show improved discriminatory accuracy for 5-year OS (AUC: 0.756 vs 0.771), same as ER-positive and ER-negative patients. However, calibration was significantly improved in v3.0, with predicted 5-year OS deviated from observed by -2.0% for the entire cohort, -2.9% for ER-positive and -0.0% for ER-negative patients, compared to -7.3%, -4.7% and -13.7% in v2.2. In v3.0, 5-year OS was underestimated by 9.0% for patients older than 75 years, and 5.8% for patients with micrometastases. Patients with distant metastases postdiagnosis was overestimated by 10.6%.<br />Conclusions: PREDICT v3.0 reliably predicts 5-year OS for the majority of Chinese patients with breast cancer. PREDICT v3.0 significantly improved the predictive accuracy for ER-negative groups. Furthermore, caution is advised when interpreting 5-year OS for patients aged over 70, those with micrometastases or metastases postdiagnosis.<br /> (© The Author(s) 2024. Published by Oxford University Press.)
Details
- Language :
- English
- ISSN :
- 1549-490X
- Volume :
- 29
- Issue :
- 8
- Database :
- MEDLINE
- Journal :
- The oncologist
- Publication Type :
- Academic Journal
- Accession number :
- 38943540
- Full Text :
- https://doi.org/10.1093/oncolo/oyae164