The Predictive Accuracy of PREDICT
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 pa...
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my.um.eprints.194542018-09-28T04:24:42Z http://eprints.um.edu.my/19454/ The Predictive Accuracy of PREDICT Wong, H.S. Subramaniam, S. Alias, Z. Mohd Taib, N.A. Ho, G.F. Ng, C.H. Yip, C.H. Verkooijen, H.M. Hartman, M. Bhoo-Pathy, N. R Medicine 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. Lippincott, Williams & Wilkins 2015 Article PeerReviewed 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 http://dx.doi.org/10.1097/MD.0000000000000593 doi:10.1097/MD.0000000000000593 |
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R Medicine Wong, H.S. Subramaniam, S. Alias, Z. Mohd Taib, N.A. Ho, G.F. Ng, C.H. Yip, C.H. Verkooijen, H.M. Hartman, M. Bhoo-Pathy, N. The Predictive Accuracy of PREDICT |
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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. |
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Wong, H.S. Subramaniam, S. Alias, Z. Mohd Taib, N.A. Ho, G.F. Ng, C.H. Yip, C.H. Verkooijen, H.M. Hartman, M. Bhoo-Pathy, N. |
author_facet |
Wong, H.S. Subramaniam, S. Alias, Z. Mohd Taib, N.A. Ho, G.F. Ng, C.H. Yip, C.H. Verkooijen, H.M. Hartman, M. Bhoo-Pathy, N. |
author_sort |
Wong, H.S. |
title |
The Predictive Accuracy of PREDICT |
title_short |
The Predictive Accuracy of PREDICT |
title_full |
The Predictive Accuracy of PREDICT |
title_fullStr |
The Predictive Accuracy of PREDICT |
title_full_unstemmed |
The Predictive Accuracy of PREDICT |
title_sort |
predictive accuracy of predict |
publisher |
Lippincott, Williams & Wilkins |
publishDate |
2015 |
url |
http://eprints.um.edu.my/19454/ http://dx.doi.org/10.1097/MD.0000000000000593 |
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1643690993249157120 |
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