Department of Pathology, Region Zealand, Denmark
Anne-Vibeke Lænkholm , Maj-Britt Jensen , Jens Ole Eriksen , Torben Kibøll , Birgitte Bruun Rasmussen , Ann S. Knoop , Sean Ferree , Taryn Haffner , Carl Schaper , Bent Ejlertsen
Background: The Prosigna (PAM50) risk of recurrence (ROR) score has been validated in two randomized clinical trials to predict 10yr DR in EBC patients treated with ET alone. Here we examine the value of PAM50 for predicting risk of DR in a comprehensive nationwide cohort from Denmark consisting of all postmenopausal women diagnosed with HR+ EBC allocated to 5yr of ET alone. Methods: Using the population based DBCG database FFPE primary tumor blocks and follow-up data were collected from all patients diagnosed from 2000-2003 (N = 2749) who by nationwide guidelines were allocated to 5yr of ET alone. PAM50 was conducted using the NanoString nCounter Analysis System. Univariate and multivariate analyses tested the ability of PAM50 to predict DR. Patients were categorized as Low, Intermediate, or High risk based upon pre-specified ROR cutoffs varied by number of positive nodes. Results: Blocks from 2749 patients were identified and data from 2722 samples (1256 N0, 1466 N1) were included in the analysis (99%). Median follow-up was 9.25yr. High risk patients (n = 1200) had a DR risk of 20.8% [95%CI: 18.3-23.4] at 10 years, compared to 4.3% [2.9-6.2] for Low risk patients (n = 733). These figures were consistent across nodal status. Adding ROR to a Fine and Gray’s proportional sub-hazards model containing clinical and pathological variables significantly improved the model (likelihood ratio: p < 0.0001; HR for a 20-point change in ROR = 1.7 [1.5-1.9]. Luminal B tumors (N = 977, DR risk = 18.0% [15.4-20.9]) and Her2-enriched tumors (N = 203, DR risk = 27.7% [21.5-34.3]) had a significantly worse outcome than Luminal A (N = 1515, DR risk = 7.7% [6.2-9.3]), both p < 0.0001. Conclusions: To our knowledge, this is the first genomic study of breast cancer on a comprehensive nationwide population. Prosigna (PAM50) improved the prediction of outcome over and above standard clinical and pathological variables in this DBCG cohort devoid of physician selection bias. PAM50 can reliably identify patients in a real world setting who may be spared overtreatment with chemotherapy.
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Abstract Disclosures
2015 ASCO Annual Meeting
First Author: Anne-Vibeke Lænkholm
2015 ASCO Annual Meeting
First Author: Bent Ejlertsen
2023 ASCO Annual Meeting
First Author: Lauren Claire Brown
2021 ASCO Annual Meeting
First Author: Vladislav Berdunov