Trends in cutaneous melanoma mortality in Italy from 1982 to 2016

• Published in: International journal of dermatology Vol. 61; no. 10; pp. 1237 - 1244
• Main Authors: Briatico, Giulia, Mancuso, Pamela, Argenziano, Giuseppe, Longo, Caterina, Mangone, Lucia, Moscarella, Elvira, Brancaccio, Gabriella, Pampena, Riccardo
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01-10-2022
• Subjects: Age; Aged; Female; Humans; Italy - epidemiology; Male; Melanoma; Melanoma, Cutaneous Malignant; Men; Mortality; Regression models; Skin Neoplasms; Syndrome; Trends; Women; Italy
• ISSN: 0011-9059; 1365-4632
• DOI: 10.1111/ijd.16173

Background
In Italy, comprehensive national studies, about mortality rates for cutaneous melanoma, are missing. The aim of this study was to analyze the trend of cutaneous melanoma mortality in Italy from 1982 to 2016.
Methods
Data on death certificates were obtained from Italian National Institute of Statistics (ISTAT: Istituto nazionale di STATistica, Indagine sulle cause di morte). Mortality rates were age‐standardized on the European population 2013 and presented per 100,000 individuals. Age‐adjusted mortality rates (AMRs) were calculated by sex, age group, and geographic areas. To identify changes in mortality rate trends, a joinpoint regression model was used, and the annual percent change (APC) was estimated.
Results
In Italy, a total number of 49,312 patients (44.0% women) died for cutaneous melanoma from 1982 to 2016. Melanoma mortality rates significantly increased in the study period in both sexes, with higher AMR values and a steeper increase in men (from 2.71 to 4.02; APC: 1.43; 95% CI 1.26–1.61) than women (from 1.94–2.10; APC: 0.23; 95% CI 0.00–0.46). The largest difference between men and women was observed in patients aged ≥65 years with APC of 2.17 in men (95% CI 1.97–2.37) and 0.37 in women (95% CI 0.08–0.66).
Conclusion
In conclusion, the melanoma mortality rate in Italy progressively increased especially in elderly men. Several hypotheses might explain the observed age and geographic differences such as sun exposure habits or different strategies of prevention campaigns.