ArticleBMC cancer2016
Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia.
Article in BMC cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic models for breast cancer: a systematic review.BMC cancer · 2019Pooled it
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- Mammographic Breast Density at Breast Cancer Diagnosis and Breast Cancer-Specific Survival.Diagnostics (Basel, Switzerland) · 2024Article
- Sociodemographic disparities associated with advanced stages and distant metastatic breast cancers at diagnosis in Indonesia: a cross-sectional study.Annals of medicine and surgery (2012) · 2023Article
- A Comparison between the Online Prognostic Tool PREDICT and myBeST for Women with Breast Cancer in Malaysia.Cancers · 2023Article
- myBeST-A Web-Based Survival Prognostic Tool for Women with Breast Cancer in Malaysia: Development Process and Preliminary Validation Study.International journal of environmental research and public health · 2023Article
- Development of Predictive Models for Survival among Women with Breast Cancer in Malaysia.International journal of environmental research and public health · 2022Article
- A scoping review of interactive and personalized web-based clinical tools to support treatment decision making in breast cancer.Breast (Edinburgh, Scotland) · 2022Article
- Article
- Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.Cancers · 2021Article
- Review
- A Comparison Between the Online Prediction Models CancerMath and PREDICT as Prognostic Tools in Thai Breast Cancer Patients.Cancer management and research · 2020Article
- Article
- Development and External Validation of Prediction Models for 10-Year Survival of Invasive Breast Cancer. Comparison with PREDICT and CancerMath.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
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11 authors.
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Abstract
backgroundCancerMath is a set of web-based prognostic tools which predict nodal status and survival up to 15 years after diagnosis of breast cancer. This study validated its performance in a Southeast Asian setting.
methodsUsing Singapore Malaysia Hospital-Based Breast Cancer Registry, clinical information was retrieved from 7064 stage I to III breast cancer patients who were diagnosed between 1990 and 2011 and underwent surgery. Predicted and observed probabilities of positive nodes and survival were compared for each subgroup. Calibration was assessed by plotting observed value against predicted value for each decile of the predicted value. Discrimination was evaluated by area under a receiver operating characteristic curve (AUC) with 95 % confidence interval (CI).
resultsThe median predicted probability of positive lymph nodes is 40.6 % which was lower than the observed 43.6 % (95 % CI, 42.5 %-44.8 %). The calibration plot showed underestimation for most of the groups. The AUC was 0.71 (95 % CI, 0.70-0.72). Cancermath predicted and observed overall survival probabilities were 87.3 % vs 83.4 % at 5 years after diagnosis and 75.3 % vs 70.4 % at 10 years after diagnosis. The difference was smaller for patients from Singapore, patients diagnosed more recently and patients with favorable tumor characteristics. Calibration plot also illustrated overprediction of survival for patients with poor prognosis. The AUC for 5-year and 10-year overall survival was 0.77 (95 % CI: 0.75-0.79) and 0.74 (95 % CI: 0.71-0.76).
conclusionsThe discrimination and calibration of CancerMath were modest. The results suggest that clinical application of CancerMath should be limited to patients with better prognostic profile.
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