Predicting the risk of locoregional recurrence after early breast cancer: an external validation of the Dutch INFLUENCE-nomogram with clinical cancer registry data from Germany

Vinzenz Voelkel (Corresponding Author), Teresa Maria Cornelia Draeger, C Oudshoorn, Linda de Munck, Tom Hueting, Michael Gerken, Monika Klinkhammer-Schalke, Miha Lavric, Sabine Siesling

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Abstract

Purpose: Follow-up after breast cancer treatment aims for an early detection of locoregional breast cancer recurrences (LRR) to improve the patients’ outcome. By estimating individual’s 5-year recurrence-risks, the Dutch INFLUENCE-nomogram can assist health professionals and patients in developing personalized risk-based follow-up pathways. The objective of this study is to validate the prediction tool on non-Dutch patients. Material and methods: Data for this external validation derive from a large clinical cancer registry in southern Germany, covering a population of 1.1 million. Patients with curative resection of early-stage breast cancer, diagnosed between 2000 and 2012, were included in the analysis (n = 6520). For each of them, an individual LRR-risk was estimated by the INFLUENCE-nomogram. Its predictive ability was tested by comparing estimated and observed LRR-probabilities using the Hosmer–Lemeshow goodness-of-fit test and C-statistics. Results: In the German validation-cohort, 2.8% of the patients developed an LRR within 5 years after primary surgery (n = 184). While the INFLUENCE-nomogram generally underestimates the actual LRR-risk of the German patients (p < 0.001), its discriminative ability is comparable to the one observed in the original Dutch modeling-cohort (C-statistic German validation-cohort: 0.73, CI 0.69–0.77 vs. C-statistic Dutch modeling-cohort: 0.71, CI 0.69–0.73). Similar results were obtained in most of the subgroup analyses stratified by age, type of surgery and intrinsic biological subtypes. Conclusion: The outcomes of this external validation underline the generalizability of the INFLUENCE-nomogram beyond the Dutch population. The model performance could be enhanced in future by incorporating additional risk factors for LRR.

Original languageEnglish
Pages (from-to)1823-1833
Number of pages11
JournalJournal of Cancer Research and Clinical Oncology
Volume145
Issue number7
Early online date29 Mar 2019
DOIs
Publication statusPublished - 1 Jul 2019

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Keywords

  • UT-Hybrid-D

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