Sangjun Lee1,2,3, Kwang-Pil Ko4, Jung Eun Lee5, Inah Kim6, Sun Ha Jee7, Aesun Shin1,2,8, Sun-Seog Kweon9, Min-Ho Shin9, Sangmin Park3,10, Seungho Ryu11, Sun Young Yang12, Seung Ho Choi12, Jeongseon Kim13, Sang-Wook Yi14, Daehee Kang1,2,8, Keun-Young Yoo15,16, Sue K Park1,2,8. 1. Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea. 2. Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea. 3. Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Korea. 4. Clinical Preventive Medicine Center, Seoul National University Bundang Hospital, Seongnam, Korea. 5. Department of Food and Nutrition, Seoul National University, Seoul, Korea. 6. Department of Occupational and Environmental Medicine, Hanyang University College of Medicine, Seoul, Korea. 7. Department of Epidemiology and Health Promotion, Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea. 8. Integrated Major in Innovative Medical Science, Seoul National University College of Medicine, Seoul, Korea. 9. Department of Preventive Medicine, Chonnam National University Medical School, Hwasun, Korea. 10. Department of Family Medicine, Seoul National University Hospital, Seoul, Korea. 11. Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea. 12. Department of Internal Medicine, Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea. 13. Graduate School of Science and Policy, National Cancer Center, Korea. 14. Department of Preventive Medicine and Public Health, Catholic Kwandong University College of Medicine, Gangneung, Korea. 15. Veterans Health Service Medical Center, Seoul, Korea. 16. Seoul National University College of Medicine, Seoul, Korea.
Abstract
OBJECTIVES: We introduced the cohort studies included in the Korea Cohort Consortium (KCC), focusing on large-scale cohort studies established in Korea with a prolonged follow-up period. Moreover, we also provided projections of the follow-up and estimates of the sample size that would be necessary for big-data analyses based on pooling established cohort studies, including population-based genomic studies. METHODS: We mainly focused on the characteristics of individual cohort studies from the KCC. We developed "PROFAN", a Shiny application for projecting the follow-up period to achieve a certain number of cases when pooling established cohort studies. As examples, we projected the follow-up periods for 5000 cases of gastric cancer, 2500 cases of prostate and breast cancer, and 500 cases of non-Hodgkin lymphoma. The sample sizes for sequencing-based analyses based on a 1:1 case-control study were also calculated. RESULTS: The KCC consisted of 8 individual cohort studies, of which 3 were community-based and 5 were health screening-based cohorts. The population-based cohort studies were mainly organized by Korean government agencies and research institutes. The projected follow-up period was at least 10 years to achieve 5000 cases based on a cohort of 0.5 million participants. The mean of the minimum to maximum sample sizes for performing sequencing analyses was 5917-72 102. CONCLUSIONS: We propose an approach to establish a large-scale consortium based on the standardization and harmonization of existing cohort studies to obtain adequate statistical power with a sufficient sample size to analyze high-risk groups or rare cancer subtypes.
OBJECTIVES: We introduced the cohort studies included in the Korea Cohort Consortium (KCC), focusing on large-scale cohort studies established in Korea with a prolonged follow-up period. Moreover, we also provided projections of the follow-up and estimates of the sample size that would be necessary for big-data analyses based on pooling established cohort studies, including population-based genomic studies. METHODS: We mainly focused on the characteristics of individual cohort studies from the KCC. We developed "PROFAN", a Shiny application for projecting the follow-up period to achieve a certain number of cases when pooling established cohort studies. As examples, we projected the follow-up periods for 5000 cases of gastric cancer, 2500 cases of prostate and breast cancer, and 500 cases of non-Hodgkin lymphoma. The sample sizes for sequencing-based analyses based on a 1:1 case-control study were also calculated. RESULTS: The KCC consisted of 8 individual cohort studies, of which 3 were community-based and 5 were health screening-based cohorts. The population-based cohort studies were mainly organized by Korean government agencies and research institutes. The projected follow-up period was at least 10 years to achieve 5000 cases based on a cohort of 0.5 million participants. The mean of the minimum to maximum sample sizes for performing sequencing analyses was 5917-72 102. CONCLUSIONS: We propose an approach to establish a large-scale consortium based on the standardization and harmonization of existing cohort studies to obtain adequate statistical power with a sufficient sample size to analyze high-risk groups or rare cancer subtypes.
Entities:
Keywords:
Cohort studies; Data pooling; Follow-up studies
Authors: Scott H Williamson; Ryan Hernandez; Adi Fledel-Alon; Lan Zhu; Rasmus Nielsen; Carlos D Bustamante Journal: Proc Natl Acad Sci U S A Date: 2005-05-19 Impact factor: 11.205
Authors: M Woodward; F Barzi; A Martiniuk; X Fang; D F Gu; Y Imai; T H Lam; W H Pan; A Rodgers; I Suh; S H Jee; H Ueshima; R Huxley Journal: Int J Epidemiol Date: 2006-10-22 Impact factor: 7.196
Authors: Changhyun Lee; Eun Kyung Choe; Sue Kyung Park; Sang-Heon Cho; Ji Min Choi; Yunji Hwang; Young Lee; Boram Park; Su Jin Chung; Min-Sun Kwak; Jong-Eun Lee; Joo Sung Kim Journal: BMJ Open Date: 2018-04-19 Impact factor: 2.692
Authors: Clare Bycroft; Colin Freeman; Desislava Petkova; Gavin Band; Lloyd T Elliott; Kevin Sharp; Allan Motyer; Damjan Vukcevic; Olivier Delaneau; Jared O'Connell; Adrian Cortes; Samantha Welsh; Alan Young; Mark Effingham; Gil McVean; Stephen Leslie; Naomi Allen; Peter Donnelly; Jonathan Marchini Journal: Nature Date: 2018-10-10 Impact factor: 49.962