Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

Yuxin Ding; Runyi Jiang; Yuhong Chen; Jing Jing; Xiaoshuang Yang; Xianjie Wu; Xiaoyang Zhang; Jiali Xu; Piaopiao Xu; Shu Chen LiuHuang; Zhongfa Lu

doi:10.1186/s12885-021-08105-y

Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study

BMC Cancer. 2021 Apr 16;21(1):420. doi: 10.1186/s12885-021-08105-y.

Authors

Affiliations

¹ Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China, No. 88, Jiefang Road, Hangzhou, 310009, China.
² Spinal Tumor Center, Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, China.
³ China Academy of Art, Hangzhou, 310000, China.
⁴ Department of Dermatology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China, No. 88, Jiefang Road, Hangzhou, 310009, China. lzfskin@zju.edu.cn.

^# Contributed equally.

Abstract

Background: Previous studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM.

Methods: The information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots.

Results: Of 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785-0.896) and AUC values (0.81-0.925), and the calibration plots showed great consistency.

Conclusions: The characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.

Keywords: Cutaneous melanoma; Head and neck melanoma; Nomogram; Prognostic factors; SEER; Survival.

MeSH terms

Adult
Aged
Aged, 80 and over
Area Under Curve
Female
Head and Neck Neoplasms / epidemiology
Head and Neck Neoplasms / mortality*
Head and Neck Neoplasms / pathology*
Humans
Kaplan-Meier Estimate
Male
Melanoma / epidemiology
Melanoma / mortality*
Melanoma / pathology*
Middle Aged
Neoplasm Grading
Neoplasm Metastasis
Neoplasm Staging
Nomograms
Organ Specificity
Population Surveillance
Prognosis
Proportional Hazards Models
ROC Curve
Reproducibility of Results
SEER Program