Janka Eszter Anna, Szabó Imre Lőrinc, Toka-Farkas Tünde, Soltész Lilla, Szentkereszty-Kovács Zita, Ványai Beatrix, Várvölgyi Tünde, Kapitány Anikó, Szegedi Andrea, Emri Gabriella
Department of Dermatology, MTA Centre of Excellence, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary.
HUN-REN-UD Allergology Research Group, University of Debrecen, 4032 Debrecen, Hungary.
Cancers (Basel). 2025 Sep 21;17(18):3080. doi: 10.3390/cancers17183080.
Risk assessment models are increasingly being used in oncology to improve therapeutic and follow-up decisions for individual patients.
In our study, we used a university hospital registry database containing data on patients diagnosed with invasive cutaneous melanoma between 2000 and 2019 (training cohort: N = 1402; validation cohort: N = 601). Using multivariate Cox regression models, we identified clinicopathological variables that are independent risk factors for melanoma recurrence at specific sites. We then constructed nomograms to predict the probability of recurrence at 3, 5, and 10 years.
Age, sex, primary tumor location, histological subtype, Clark invasion level and AJCC pT category were independent prognostic factors for melanoma recurrence in regional lymph nodes. Age, sex, primary tumor location, Clark level of invasion, AJCC pT stage and regional lymph node metastasis were risk factors for skin/soft tissue (including muscle)/non-regional lymph node metastases. We found that AJCC pT category and sex were also independent prognostic factors for melanoma recurrence in the lung, visceral sites, and brain. Furthermore, the nomogram predicting recurrence in the lung and visceral sites incorporated the presence of regional lymph node and skin/soft tissue/non-regional lymph node metastases. ROC curves showed good performance of the nomograms in both the training and validation cohorts. The calibration curve showed a good fit.
Our results support the high prognostic value of AJCC pT stage and patient sex, which remained consistent across all melanoma stages, and demonstrate the feasibility of creating nomogram models to predict recurrence risk in melanoma patients.
风险评估模型在肿瘤学中越来越多地用于改善个体患者的治疗和随访决策。
在我们的研究中，我们使用了一个大学医院登记数据库，其中包含2000年至2019年间被诊断为侵袭性皮肤黑色素瘤患者的数据（训练队列：N = 1402；验证队列：N = 601）。使用多变量Cox回归模型，我们确定了作为特定部位黑色素瘤复发独立危险因素的临床病理变量。然后我们构建了列线图以预测3年、5年和10年复发的概率。
年龄、性别、原发肿瘤部位、组织学亚型、Clark浸润水平和美国癌症联合委员会（AJCC）pT分类是区域淋巴结黑色素瘤复发的独立预后因素。年龄、性别、原发肿瘤部位、Clark浸润水平、AJCC pT分期和区域淋巴结转移是皮肤/软组织（包括肌肉）/非区域淋巴结转移的危险因素。我们发现AJCC pT分类和性别也是肺、内脏部位和脑黑色素瘤复发的独立预后因素。此外，预测肺和内脏部位复发的列线图纳入了区域淋巴结以及皮肤/软组织/非区域淋巴结转移的情况。受试者工作特征（ROC）曲线显示列线图在训练队列和验证队列中均表现良好。校准曲线显示拟合良好。
我们的结果支持AJCC pT分期和患者性别的高预后价值，这在所有黑色素瘤分期中均保持一致，并证明了创建列线图模型以预测黑色素瘤患者复发风险的可行性。
