- 著者
- Makoto Hirata Yoichiro Kamatani Akiko Nagai Yutaka Kiyohara Toshiharu Ninomiya Akiko Tamakoshi Zentaro Yamagata Michiaki Kubo Kaori Muto Taisei Mushiroda Yoshinori Murakami Koichiro Yuji Yoichi Furukawa Hitoshi Zembutsu Toshihiro Tanaka Yozo Ohnishi Yusuke Nakamura BioBank Japan Cooperative Hospital Group Koichi Matsuda
- 出版者
- 日本疫学会
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- vol.27, no.Supplement_III, pp.S9-S21, 2017 (Released:2017-04-14)
- 参考文献数
- 33
- 被引用文献数
- 116
Background: To implement personalized medicine, we established a large-scale patient cohort, BioBank Japan, in 2003. BioBank Japan contains DNA, serum, and clinical information derived from approximately 200,000 patients with 47 diseases. Serum and clinical information were collected annually until 2012.Methods: We analyzed clinical information of participants at enrollment, including age, sex, body mass index, hypertension, and smoking and drinking status, across 47 diseases, and compared the results with the Japanese database on Patient Survey and National Health and Nutrition Survey. We conducted multivariate logistic regression analysis, adjusting for sex and age, to assess the association between family history and disease development.Results: Distribution of age at enrollment reflected the typical age of disease onset. Analysis of the clinical information revealed strong associations between smoking and chronic obstructive pulmonary disease, drinking and esophageal cancer, high body mass index and metabolic disease, and hypertension and cardiovascular disease. Logistic regression analysis showed that individuals with a family history of keloid exhibited a higher odds ratio than those without a family history, highlighting the strong impact of host genetic factor(s) on disease onset.Conclusions: Cross-sectional analysis of the clinical information of participants at enrollment revealed characteristics of the present cohort. Analysis of family history revealed the impact of host genetic factors on each disease. BioBank Japan, by publicly distributing DNA, serum, and clinical information, could be a fundamental infrastructure for the implementation of personalized medicine.
- 著者
- Makoto Hirata Akiko Nagai Yoichiro Kamatani Toshiharu Ninomiya Akiko Tamakoshi Zentaro Yamagata Michiaki Kubo Kaori Muto Yutaka Kiyohara Taisei Mushiroda Yoshinori Murakami Koichiro Yuji Yoichi Furukawa Hitoshi Zembutsu Toshihiro Tanaka Yozo Ohnishi Yusuke Nakamura BioBank Japan Cooperative Hospital Group Koichi Matsuda
- 出版者
- 日本疫学会
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- vol.27, no.Supplement_III, pp.S22-S28, 2017 (Released:2017-04-14)
- 参考文献数
- 34
- 被引用文献数
- 36
Background: We established a patient-oriented biobank, BioBank Japan, with information on approximately 200,000 patients, suffering from any of 47 common diseases. This follow-up survey focused on 32 diseases, potentially associated with poor vital prognosis, and collected patient survival information, including cause of death. We performed a survival analysis for all subjects to get an overview of BioBank Japan follow-up data.Methods: A total of 141,612 participants were included. The survival data were last updated in 2014. Kaplan–Meier survival analysis was performed after categorizing subjects according to sex, age group, and disease status. Relative survival rates were estimated using a survival-rate table of the Japanese general population.Results: Of 141,612 subjects (56.48% male) with 1,087,434 person-years and a 97.0% follow-up rate, 35,482 patients died during follow-up. Mean age at enrollment was 64.24 years for male subjects and 63.98 years for female subjects. The 5-year and 10-year relative survival rates for all subjects were 0.944 and 0.911, respectively, with a median follow-up duration of 8.40 years. Patients with pancreatic cancer had the least favorable prognosis (10-year relative survival: 0.184) and patients with dyslipidemia had the most favorable prognosis (1.013). The most common cause of death was malignant neoplasms. A number of subjects died from diseases other than their registered disease(s).Conclusions: This is the first report to perform follow-up survival analysis across various common diseases. Further studies should use detailed clinical and genomic information to identify predictors of mortality in patients with common diseases, contributing to the implementation of personalized medicine.
- 著者
- Akiko Nagai Makoto Hirata Yoichiro Kamatani Kaori Muto Koichi Matsuda Yutaka Kiyohara Toshiharu Ninomiya Akiko Tamakoshi Zentaro Yamagata Taisei Mushiroda Yoshinori Murakami Koichiro Yuji Yoichi Furukawa Hitoshi Zembutsu Toshihiro Tanaka Yozo Ohnishi Yusuke Nakamura BioBank Japan Cooperative Hospital Group Michiaki Kubo
- 出版者
- 日本疫学会
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- vol.27, no.Supplement_III, pp.S2-S8, 2017 (Released:2017-04-14)
- 参考文献数
- 21
- 被引用文献数
- 423
Background: The BioBank Japan (BBJ) Project was launched in 2003 with the aim of providing evidence for the implementation of personalized medicine by constructing a large, patient-based biobank (BBJ). This report describes the study design and profile of BBJ participants who were registered during the first 5-year period of the project.Methods: The BBJ is a registry of patients diagnosed with any of 47 target common diseases. Patients were enrolled at 12 cooperative medical institutes all over Japan from June 2003 to March 2008. Clinical information was collected annually via interviews and medical record reviews until 2013. We collected DNA from all participants at baseline and collected annual serum samples until 2013. In addition, we followed patients who reported a history of 32 of the 47 target diseases to collect survival data, including cause of death.Results: During the 5-year period, 200,000 participants were registered in the study. The total number of cases was 291,274 at baseline. Baseline data for 199,982 participants (53.1% male) were available for analysis. The average age at entry was 62.7 years for men and 61.5 years for women. Follow-up surveys were performed for participants with any of 32 diseases, and survival time data for 141,612 participants were available for analysis.Conclusions: The BBJ Project has constructed the infrastructure for genomic research for various common diseases. This clinical information, coupled with genomic data, will provide important clues for the implementation of personalized medicine.