Gradually implemented new biomarkers for prognostication of breast cancer: complete case analysis may introduce bias

Bhoo-Pathy, Nirmala; Uiterwaal, Cuno S.P.M.; Taib, Nur Aishah Mohd; Verkooijen, Helena M.; Yip, Cheng Har

doi:10.1016/j.jclinepi.2011.09.013

Cited by 2 publications

(1 citation statement)

References 14 publications

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“…Although information on HER2 status was available, the testing was not routine prior to 2005 in UMMC and was highly selective, whereby patients with the highest and lowest baseline prognosis were not tested. 35 This may explain the conflicting results based on HER2 status in the current study. We are uncertain of the influence of lack of data on Ki67 status on our results, given that the model was still largely able to accurately prognosticate our patients with breast cancer.…”

Section: Discussionmentioning

confidence: 61%

The Predictive Accuracy of PREDICT

et al. 2015

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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 3 cm 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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Section: Discussionmentioning

confidence: 61%