We estimated crude incidence rates of ocular melanoma in each age group by the use of the number of identified ocular melanoma cases as the numerator and the sum of the mid-year populations during the study period as the denominator. All estimated crude incidence rates were applied by direct age standardization, using Segi's world standard population
21; expected cases of each age group were obtained by multiplying the age-specific crude incidence rate by proportion of population in the corresponding age groups of Segi's world standard population.
21 Then, age-standardized incidence rate was calculated as the sum of expected cases of each age group per 1,000,000 person-years; the age-standardized incidence rate was presented as numbers of new cases per 1,000,000 person-years. Specific age-standardized incidence rates according to the defined characteristics were also calculated. In addition, trends in incidence of ocular melanoma and its subtypes throughout the study periods were assessed with the Joinpoint regression model.
22 Joinpoint regression model is a segmented linear regression analysis to investigate trends in rates and identify statistically significant changes over time.
22 Furthermore, the model is used to detect time points where there are significant changes in trends. In the analysis of population-based cancer registry data, the model is often used to characterize trends in incidence and mortality rates. In our analysis, trends in incidence rates were modeled. The model can be fitted using the Joinpoint software developed by the US National Cancer Institute (
http://surveillance.cancer.gov/joinpoint). We carried out the Joinpoint regression model by using the biennial age-standardized incidence rates from 2002 to 2011 and the age-standardized incidence rate of the first 3 years (1999–2001) to reduce instability due to the small sample size in the present study. Incidence trends were investigated separately in men and women. The result of Joinpoint analysis is represented as annual percent changes (APC), which is calculated as summary measurements.
22 P values of <0.05 were considered statistically significant. Statistical analyses were performed using Stata version 12.0 (StataCorp LP, College Station, TX, USA), SAS version 9.3 (SAS Institute, Cary, NC, USA), and Joinpoint regression version 4.1.1 (Surveillance Research Program, National Cancer Institute, Bethesda, MD, USA) software.