The number of persons infected by HIV/AIDS has consistently increased in Korea since the first case of HIV/AIDS infection in 1985 and reached 15,208 by 2016. About 1,100 new patients with HIV/ AIDS infections have emerged every year since 2013. In Korea, the Korea HIV/AIDS Cohort Study was established for the evidenced-based prevention, treatment, and effective management of patients infected with human immunodeficiency virus (HIV) in December 2006. This study monitored 1,438 patients, who accounted for about 10% of all patients with HIV/AIDS in Korea, for 10 years with the following aims: (1) to develop an administrative system for the establishment of a HIV/AIDS cohort-based study; (2) to standardize methodologies and the case report forms; and (3) to standardize multi-cohort data and develop a data cleaning method. This study aims to monitor at least 1,000 patients (excluding those for whom investigation had been completed) per year (estimated number of patients who can be monitored by January 2018: 939). By December 2016, the sex distribution was 93.3% for men, and 6.7% for women (gender ratio, 13.9:1.0), and 98.9% of all participants were Korean. More than 50.0% of the participants were confirmed as HIV positive after 2006. This study reports competitive, long-term research that aimed to develop policies for the prevention of chronic infectious diseases for patients with HIV. The data collected over the last decade will be used to develop indices for HIV treatment and health promotion.

Seong H, et al. Infect Chemother. 2023 Feb;55:e4. https://doi.org/10.3947/ic.2022.0059

The mortality rate and causes of death among individuals diagnosed with human immunodeficiency virus (HIV) infection in Korea were described and compared to those of the general population of Korea using a nationwide population-based claims database. We included 13,919 individuals aged 20–79 years newly diagnosed with HIV between 2004 and 2018. The patients’ vital status and cause of death were linked until 31 December 2019. Standardized mortality ratios (SMRs) for all-cause death and specific causes of death were calculated. By the end of 2019, 1669 (12.0%) of the 13,919 HIV-infected participants had died. The survival probabilities of HIV-infected individuals at 1, 5, 10, and 15 years after diagnosis in Korea were 96.2%, 91.6%, 85.9%, and 79.6%, respectively. The main causes of death during the study period were acquired immunodeficiency syndrome (AIDS; 59.0%), non-AIDS-defining cancer (8.2%), suicide (7.4%), cardiovascular disease (4.9%), and liver disease (2.7%). The mortality rate of men and women infected with HIV was 5.60-fold (95% CI = 5.32–5.89) and 6.18-fold (95% CI = 5.30–7.09) that of men and women in the general population, respectively. After excluding deaths due to HIV, the mortality remained significantly higher, with an SMR of 2.16 (95% CI = 1.99–3.24) in men and 3.77 (95% CI = 3.06–4.48) in women. HIV-infected individuals had a higher overall mortality than the general population, with AIDS the leading cause of mortality. Additionally, mortality due to non-AIDS-related causes was higher in HIV-infected individuals.

Seong H, et al. Infect Chemother. 2023 Aug;55:e37. https://doi.org/10.3947/ic.2023.0045

Kim Y, et al. J Korean Med Sci. 2019 Dec;35(3):e7. https://doi.org/10.3346/jkms.2020.35.e7

OBJECTIVES: The aim of effective data quality control and management is to minimize the impact of errors on study results by identifying and correcting them. This study presents the results of a data quality control system for the Korea HIV/AIDS Cohort Study that took into account the characteristics of the data. METHODS: The HIV/AIDS Cohort Study in Korea conducts repeated measurements every 6 months using an electronic survey administered to voluntarily consenting participants and collects data from 21 hospitals. In total, 5,795 sets of data from 1,442 participants were collected from the first investigation in 2006 to 2016. The data refining results of 2015 and 2019 were converted into the data refining rate and compared. RESULTS: The quality control system involved 3 steps at different points in the process, and each step contributed to data quality management and results. By improving data quality control in the pre-phase and the data collection phase, the estimated error value in 2019 was 1,803, reflecting a 53.9% reduction from 2015. Due to improvements in the stage after data collection, the data refining rate was 92.7% in 2019, a 24.21%p increase from 2015. CONCLUSIONS: Despite this quality management strategy, errors may still exist at each stage. Logically possible errors for the post-review refining of downloaded data should be actively identified with appropriate consideration of the purpose and epidemiological characteristics of the study data. To improve data quality and reliability, data management strategies should be systematically implemented.