Wong, H.S. and Subramaniam, S. and Alias, Z. and Mohd Taib, N.A. and Ho, G.F. and Ng, C.H. and Yip, C.H. and Verkooijen, H.M. and Hartman, M. and Bhoo-Pathy, N. (2015) The Predictive Accuracy of PREDICT. Medicine, 94 (8). e593. ISSN 0025-7974, DOI https://doi.org/10.1097/MD.0000000000000593.
Full text not available from this repository.Abstract
Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged <40 years, and in those receiving neoadjuvant chemotherapy. PREDICT performed well in terms of discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Adult; Aged; Asian Continental Ancestry Group; Breast Neoplasms; Cohort Studies; Decision Support Techniques; Female; Humans; Malaysia; Middle Aged |
| Subjects: | R Medicine |
| Divisions: | Faculty of Medicine |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 28 Sep 2018 04:24 |
| Last Modified: | 28 Sep 2018 04:24 |
| URI: | http://eprints.um.edu.my/id/eprint/19454 |
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