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

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.

Fig. 1

Flowchart of patient selection

Fig. 2

The optimal cut-off values for age (a-b) based on CSS were ≤ 58, 59–78, and ≥ 79 years old; (c-d) based on OS were ≤ 63, 64–79, and ≥ 80 years old. The optimal cut-off values for thin HNM (0–1.00 mm) (e-f) based on CSS were ≤ 0.6 and > 0.6 mm; (g-h) based on OS were < 0.6 and ≥ 0.6 mm. CSS = cancer-specific survival; OS = overall survival; HNM = head and neck melanoma

Fig. 3

Kaplan-Meier curves of cancer-specific and overall survival based on anatomic location. a cancer-specific survival (CSS); b overall survival (OS). HNM = head and neck melanoma; BM = body melanoma

Fig. 4

Kaplan-Meier curves of CSS were delineated based on the identified independent prognostic factors, including age, sex, histology, thickness, ulceration, stage, metastases, and surgery (a-d, i-l) for HNM training cohort, e-h, m-p for BM training cohort. CSS = cancer-specific survival; HNM = head and neck melanoma; BM = body melanoma

Fig. 5

Nomograms predicted the individual 3-, 5- and 10-year survival rates of patients. a, c Predicting CSS and OS for HNM patients. b, d Predicting CSS and OS for BM patients. CSS = cancer-specific survival; OS = overall survival; HNM = head and neck melanoma; BM = body melanoma

Fig. 6

ROC curves evaluated the predictive ability of the nomograms. a-d Predicting 3-, 5- and 10-year CSS rates for HNM training and validation cohort, BM training and validation cohort, respectively. e-h Predicting 3-, 5- and 10-year OS rates for HNM training and validation cohort, BM training and validation cohort, respectively. CSS = cancer-specific survival; OS = overall survival

Fig. 7

Calibration curves showed the probability of 3-, 5- and 10-year cancer-specific survival (CSS) between the nomogram prediction and the actual observation. Perfect prediction would correspond to the 45-degree line. The calibration curves predicted CSS of patients with HNM in the training cohort (a-c) and in the validation cohort (d-f). The calibration curves predicted CSS of patients with BM in the training cohort (g-h) and in the validation cohort (j-l)