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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.
Afiliação
  • Hoveling LA; Department of Research, Netherlands Comprehensive Cancer Organisation, P.O. Box 19079, 3501 DB, Utrecht, The Netherlands.
  • van Maaren MC; Department of Research, Netherlands Comprehensive Cancer Organisation, P.O. Box 19079, 3501 DB, Utrecht, The Netherlands. m.vanmaaren@iknl.nl.
  • Hueting T; Evidencio Medical Decision Support, Haaksbergen, The Netherlands.
  • Strobbe LJA; Department of Surgical Oncology, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands.
  • Hendriks MP; Department of Medical Oncology, Northwest Clinics, Alkmaar, The Netherlands.
  • Sonke GS; Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
  • Siesling S; Department of Research, Netherlands Comprehensive Cancer Organisation, P.O. Box 19079, 3501 DB, Utrecht, The Netherlands.
Breast Cancer Res Treat ; 178(3): 665-681, 2019 Dec.
Article em En | MEDLINE | ID: mdl-31471837
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Modelos Estatísticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Middle aged País como assunto: Europa Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Modelos Estatísticos Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Middle aged País como assunto: Europa Idioma: En Ano de publicação: 2019 Tipo de documento: Article