Zusammenfassung
PurposeFollow-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 ...
Zusammenfassung
PurposeFollow-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 methodsData for this external validation derive from a large clinical cancer registry in southern Germany, covering a population of 1.1million. 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.ResultsIn the German validation-cohort, 2.8% of the patients developed an LRR within 5years 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.ConclusionThe 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.
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