Validation of the online prediction model CancerMath in the Dutch breast cancer population
- PMID: 31471837
- DOI: 10.1007/s10549-019-05399-2
Validation of the online prediction model CancerMath in the Dutch breast cancer population
Abstract
Purpose: CancerMath predicts the expected benefit of adjuvant systemic therapy on overall (OS) and breast cancer-specific survival (BCSS). Here, CancerMath was validated in Dutch breast cancer patients.
Methods: All operated women diagnosed with stage I-III primary invasive breast cancer in 2005 were identified from the Netherlands Cancer Registry. Calibration was assessed by comparing 5- and 10-year predicted and observed OS/BCSS using χ2 tests. A difference > 3% was considered as clinically relevant. Discrimination was assessed by area under the receiver operating characteristic (AUC) curves.
Results: Altogether, 8032 women were included. CancerMath underestimated 5- and 10-year OS by 2.2% and 1.9%, respectively. AUCs of 5- and 10-year OS were both 0.77. Divergence between predicted and observed OS was most pronounced in grade II, patients without positive nodes, tumours 1.01-2.00 cm, hormonal receptor positive disease and patients 60-69 years. CancerMath underestimated 5- and 10-year BCSS by 0.5% and 0.6%, respectively. AUCs were 0.78 and 0.73, respectively. No significant difference was found in any subgroup.
Conclusion: CancerMath predicts OS accurately for most patients with early breast cancer although outcomes should be interpreted with care in some subgroups. BCSS is predicted accurately in all subgroups. Therefore, CancerMath can reliably be used in (Dutch) clinical practice.
Keywords: Breast cancer; Breast cancer-specific survival; CancerMath; Overall survival; Prediction model; Validation.
Similar articles
-
Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population.Eur J Cancer. 2017 Nov;86:364-372. doi: 10.1016/j.ejca.2017.09.031. Epub 2017 Nov 5. Eur J Cancer. 2017. PMID: 29100191
-
Validation of the CancerMath prognostic tool for breast cancer in Southeast Asia.BMC Cancer. 2016 Oct 21;16(1):820. doi: 10.1186/s12885-016-2841-9. BMC Cancer. 2016. PMID: 27769212 Free PMC article.
-
Calibration and discriminatory accuracy of prognosis calculation for breast cancer with the online Adjuvant! program: a hospital-based retrospective cohort study.Lancet Oncol. 2009 Nov;10(11):1070-6. doi: 10.1016/S1470-2045(09)70254-2. Epub 2009 Oct 2. Lancet Oncol. 2009. PMID: 19801202
-
Communicating prognosis to women with early breast cancer - overview of prediction tools and the development and pilot testing of a decision aid.BMC Health Serv Res. 2019 Mar 15;19(1):171. doi: 10.1186/s12913-019-3988-2. BMC Health Serv Res. 2019. PMID: 30876414 Free PMC article.
-
Overview of resistance to systemic therapy in patients with breast cancer.Adv Exp Med Biol. 2007;608:1-22. doi: 10.1007/978-0-387-74039-3_1. Adv Exp Med Biol. 2007. PMID: 17993229 Review.
Cited by
-
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.Oncologist. 2024 Aug 5;29(8):e976-e983. doi: 10.1093/oncolo/oyae164. Oncologist. 2024. PMID: 38943540 Free PMC article.
-
A scoping review of interactive and personalized web-based clinical tools to support treatment decision making in breast cancer.Breast. 2022 Feb;61:43-57. doi: 10.1016/j.breast.2021.12.003. Epub 2021 Dec 6. Breast. 2022. PMID: 34896693 Free PMC article.
-
Gene expression profiles in clinically T1-2N0 ER+HER2- breast cancer patients treated with breast-conserving therapy: their added value in case sentinel lymph node biopsy is not performed.Breast Cancer Res Treat. 2024 Jan;203(1):103-110. doi: 10.1007/s10549-023-07128-2. Epub 2023 Oct 5. Breast Cancer Res Treat. 2024. PMID: 37794289 Free PMC article.
-
Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis.Diagnostics (Basel). 2022 Oct 18;12(10):2526. doi: 10.3390/diagnostics12102526. Diagnostics (Basel). 2022. PMID: 36292218 Free PMC article. Review.
-
Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.Cancers (Basel). 2021 Jan 19;13(2):352. doi: 10.3390/cancers13020352. Cancers (Basel). 2021. PMID: 33477893 Free PMC article.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical