Departments of, Department of, Surgical Oncology, Erasmus Medical Centre (MC) Cancer Institute, Rotterdam, the Netherlands.
Department of, Medical Oncology, Erasmus Medical Centre (MC) Cancer Institute, Rotterdam, the Netherlands.
Br J Dermatol. 2021 May;184(5):944-951. doi: 10.1111/bjd.19499. Epub 2020 Nov 2.
The Clinicopathological and Gene Expression Profile (CP-GEP) model was developed to accurately identify patients with T1-T3 primary cutaneous melanoma at low risk for nodal metastasis.
To validate the CP-GEP model in an independent Dutch cohort of patients with melanoma.
Patients (aged ≥ 18 years) with primary cutaneous melanoma who underwent sentinel lymph node biopsy (SLNB) between 2007 and 2017 at the Erasmus Medical Centre Cancer Institute were eligible. The CP-GEP model combines clinicopathological features (age and Breslow thickness) with the expression of eight target genes involved in melanoma metastasis (ITGB3, PLAT, SERPINE2, GDF15, TGFBR1, LOXL4, CXCL8 and MLANA). Using the pathology result of SLNB as the gold standard, performance measures of the CP-GEP model were calculated, resulting in CP-GEP high risk or low risk for nodal metastasis.
In total, 210 patients were included in the study. Most patients presented with T2 (n = 94, 45%) or T3 (n = 70, 33%) melanoma. Of all patients, 27% (n = 56) had a positive SLNB, with nodal metastasis in 0%, 30%, 54% and 16% of patients with T1, T2, T3 and T4 melanoma, respectively. Overall, the CP-GEP model had a negative predictive value (NPV) of 90·5% [95% confidence interval (CI) 77·9-96.2], with an NPV of 100% (95% CI 72·2-100) in T1, 89·3% (95% CI 72·8-96·3) in T2 and 75·0% (95% CI 30·1-95·4) in T3 melanomas. The CP-GEP indicated high risk in all T4 melanomas.
The CP-GEP model is a noninvasive and validated tool that accurately identified patients with primary cutaneous melanoma at low risk for nodal metastasis. In this validation cohort, the CP-GEP model has shown the potential to reduce SLNB procedures in patients with melanoma.
Clinicopathological and Gene Expression Profile(CP-GEP)模型旨在准确识别低风险发生淋巴结转移的 T1-T3 期原发性皮肤黑色素瘤患者。
在荷兰独立的黑色素瘤患者队列中验证 CP-GEP 模型。
符合条件的患者为 2007 年至 2017 年期间在伊拉斯姆斯医学中心癌症研究所接受前哨淋巴结活检(SLNB)的原发性皮肤黑色素瘤(年龄≥18 岁)患者。CP-GEP 模型结合了临床病理特征(年龄和 Breslow 厚度)和黑色素瘤转移涉及的 8 个靶基因的表达(ITGB3、PLAT、SERPINE2、GDF15、TGFBR1、LOXL4、CXCL8 和 MLANA)。以 SLNB 的病理结果为金标准,计算 CP-GEP 模型的性能指标,得出淋巴结转移的 CP-GEP 高风险或低风险。
本研究共纳入 210 例患者。大多数患者为 T2(n=94,45%)或 T3(n=70,33%)黑色素瘤。所有患者中,27%(n=56)的 SLNB 阳性,T1、T2、T3 和 T4 黑色素瘤患者的淋巴结转移率分别为 0%、30%、54%和 16%。总体而言,CP-GEP 模型的阴性预测值(NPV)为 90.5%(95%CI 77.9-96.2),T1 黑色素瘤的 NPV 为 100%(95%CI 72.2-100),T2 为 89.3%(95%CI 72.8-96.3),T3 为 75.0%(95%CI 30.1-95.4)。CP-GEP 在所有 T4 黑色素瘤中均提示高风险。
CP-GEP 模型是一种非侵入性和经过验证的工具,可准确识别低风险发生淋巴结转移的原发性皮肤黑色素瘤患者。在本验证队列中,CP-GEP 模型显示出在黑色素瘤患者中减少 SLNB 程序的潜力。