In:
Cancers, MDPI AG, Vol. 14, No. 12 ( 2022-06-09), p. 2854-
Abstract:
Background: The current standard of care for patients without sentinel node (SN) metastasis (i.e., stage I–II melanoma) is watchful waiting, while 〉 40% of patients with stage IB–IIC will eventually present with disease recurrence or die as a result of melanoma. With the prospect of adjuvant therapeutic options for patients with a negative SN, we assessed the performance of a clinicopathologic and gene expression (CP-GEP) model, a model originally developed to predict SN metastasis, to identify patients with stage I–II melanoma at risk of disease relapse. Methods: This study included patients with cutaneous melanoma ≥18 years of age with a negative SN between October 2006 and December 2017 at the Sahlgrenska University Hospital (Sweden) and Erasmus MC Cancer Institute (The Netherlands). According to the CP-GEP model, which can be applied to the primary melanoma tissue, the patients were stratified into high or low risk of recurrence. The primary aim was to assess the 5-year recurrence-free survival (RFS) of low- and high-risk CP-GEP. A secondary aim was to compare the CP-GEP model with the EORTC nomogram, a model based on clinicopathological variables only. Results: In total, 535 patients (stage I–II) were included. CP-GEP stratification among these patients resulted in a 5-year RFS of 92.9% (95% confidence interval (CI): 86.4–96.4) in CP-GEP low-risk patients (n = 122) versus 80.7% (95%CI: 76.3–84.3) in CP-GEP high-risk patients (n = 413; hazard ratio 2.93 (95%CI: 1.41–6.09), p 〈 0.004). According to the EORTC nomogram, 25% of the patients were classified as having a ‘low risk’ of recurrence (96.8% 5-year RFS (95%CI 91.6–98.8), n = 130), 49% as ‘intermediate risk’ (88.4% 5-year RFS (95%CI 83.6–91.8), n = 261), and 26% as ‘high risk’ (61.1% 5-year RFS (95%CI 51.9–69.1), n = 137). Conclusion: In these two independent European cohorts, the CP-GEP model was able to stratify patients with stage I–II melanoma into two groups differentiated by RFS.
Type of Medium:
Online Resource
ISSN:
2072-6694
DOI:
10.3390/cancers14122854
Language:
English
Publisher:
MDPI AG
Publication Date:
2022
detail.hit.zdb_id:
2527080-1
Permalink