Validation of the online prediction model CancerMath in the Dutch breast cancer population

Liza A. Hoveling, Marissa C. van Maaren, Tom Hueting, Luc J.A. Strobbe, Mathijs P. Hendriks, Gabe S. Sonke, Sabine Siesling

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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.
Original languageEnglish
Pages (from-to)665-681
Number of pages17
JournalBreast cancer research and treatment
Volume178
Issue number3
Early online date30 Aug 2019
DOIs
Publication statusPublished - 1 Dec 2019

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Breast Neoplasms
Population
Area Under Curve
Survival
ROC Curve
Netherlands
Calibration
Registries
Neoplasms
Therapeutics

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Hoveling, Liza A. ; van Maaren, Marissa C. ; Hueting, Tom ; Strobbe, Luc J.A. ; Hendriks, Mathijs P. ; Sonke, Gabe S. ; Siesling, Sabine . / Validation of the online prediction model CancerMath in the Dutch breast cancer population. In: Breast cancer research and treatment. 2019 ; Vol. 178, No. 3. pp. 665-681.
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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.",
author = "Hoveling, {Liza A.} and {van Maaren}, {Marissa C.} and Tom Hueting and Strobbe, {Luc J.A.} and Hendriks, {Mathijs P.} and Sonke, {Gabe S.} and Sabine Siesling",
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Validation of the online prediction model CancerMath in the Dutch breast cancer population. / Hoveling, Liza A.; van Maaren, Marissa C.; Hueting, Tom; Strobbe, Luc J.A.; Hendriks, Mathijs P.; Sonke, Gabe S.; Siesling, Sabine .

In: Breast cancer research and treatment, Vol. 178, No. 3, 01.12.2019, p. 665-681.

Research output: Contribution to journalArticleAcademicpeer-review

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N2 - 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.

AB - 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.

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