Hepatocellular carcinoma incidence is decreasing in Korea but increasing in the very elderly

Background/Aims@#A comprehensive analysis of trends in the incidence of hepatocellular carcinoma (HCC) is important for planning public health initiatives. We aimed to analyze the trends in HCC incidence in South Korea over 10 years and to predict the incidence for the year 2028. @*Methods@#Data from patients with newly diagnosed HCC between 2008 and 2018 were obtained from Korean National Health Insurance Service database. Age-standardized incidence rates (ASRs) were calculated to compare HCC incidence. A poisson regression model was used to predict the future incidence of HCC. @*Results@#The average crude incidence rate (CR) was 22.4 per 100,000 person-years, and the average ASR was 17.6 per 100,000 person-years between 2008 and 2018. The CR (from 23.9 to 21.2 per 100,000 person-years) and ASR (from 21.9 to 14.3 per 100,000 person-years) of HCC incidence decreased during the past ten years in all age groups, except in the elderly. The ASR of patients aged ≥80 years increased significantly (from 70.0 to 160.2/100,000 person-years; average annual percent change, +9.00%; P<0.001). The estimated CR (17.9 per 100,000 person-years) and ASR (9.7 per 100,000 person-years) of HCC incidence in 2028 was declined, but the number of HCC patients aged ≥80 years in 2028 will be quadruple greater than the number of HCC patients in 2008 (from 521 to 2,055), comprising 21.3% of all HCC patients in 2028. @*Conclusions@#The ASRs of HCC in Korea have gradually declined over the past 10 years, but the number, CR, and ASR are increasing in patients aged ≥80 years.

Omission of Chemotherapy for the Treatment of Mucinous Breast Cancer: A Nationwide Study from the Korean Breast Cancer Society / 한국유방암학회지

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.