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Abstract
PurposeTo extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches.MethodsData on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples.ResultsAge, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74–0.76) and SP (0.67, 95%CI: 0.65–0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77–0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created.ConclusionsINFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.
Highlights
In the Netherlands, more than 14,000 women per year are diagnosed with invasive breast cancer [1], rendering it the most frequently diagnosed malignancy among women [2]
Data for the development of the INFLUENCE 2.0 model were derived from the Netherlands Cancer Registry (NCR), a nationwide database collecting records of all newly diagnosed malignant tumors in the country hosted by the Netherlands Comprehensive Cancer Organisation (IKNL) since 1989
A direct comparison to the Area Under the Curve (AUC) values of the INFLUENCE 2.0 model is not possible due to differences in outcome definition
Summary
In the Netherlands, more than 14,000 women per year are diagnosed with invasive breast cancer [1], rendering it the most frequently diagnosed malignancy among women [2]. The current average 5-year survival rate of women diagnosed with breast cancer (all stages) is 88% in the Netherlands [6]. The Dutch breast cancer guideline recommends annual mammograms and physical examinations during the first five years following curative treatment, unless bilateral mastectomy was performed [7]. This follow-up program is uniform for all patients and does not take individual risk profiles into account. To avoid unnecessary follow-up visits and examinations possibly inflicting psychological harm [8,9,10] and causing additional societal costs, the creation of personalized follow-up patterns based on individual risk estimations would be reasonable
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