Cross-sectional analysis of BioBank Japan clinical data: A large cohort of 200,000 patients with 47 common diseases

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BackgroundWe 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.MethodsA 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.ResultsOf 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).ConclusionsThis 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.

Section: Discussionmentioning

confidence: 91%

“…Approximately 200,000 patients diagnosed with any of 47 target common diseases were enrolled in the BBJ in the first 5-year period of the project 1, 2, 3. In this project, DNA, serum, and clinical information was collected from participants.…”

Section: Introductionmentioning

confidence: 99%

Overview of BioBank Japan follow-up data in 32 diseases

Hirata

Nagai

Kamatani

et al. 2017

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“…Baseline clinical information was obtained from interviews using a standardized questionnaire and medical records 9, 10, 11, 12. Patient interviews included questions concerning smoking and alcohol habits, height, weight, exercise frequency, and a family history of prostate cancer.…”

Section: Methodsmentioning

confidence: 99%

Clinical and histopathological characteristics of patients with prostate cancer in the BioBank Japan project

Ukawa

Nakamura

Okada

et al. 2017

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BackgroundProstate cancer is the sixth leading cause of cancer-related deaths in Japan. We aimed to elucidate the clinical and histopathological characteristics of patients with prostate cancer in the BioBank Japan (BBJ) project.MethodsFour thousand, seven hundred and ninety-three patients diagnosed with prostate cancer in the BBJ project were included. Clinical and histopathological data, including causes of death, were analyzed. Relative survival (RS) rates of prostate cancer were calculated.ResultsFour thousand, one hundred and seventy-one prostate cancer patients with available histological data had adenocarcinoma. The mean age of the patients was 72.5 years. The proportion of patients who were non-smokers, non-drinkers, had a normal body mass index, did not exercise, had a normal prostate-specific antigen level, and had a family history of prostate cancer were 30.7%, 28.0%, 66.6%, 58.1%, 67.6%, and 6.5%, respectively. The proportion of patients with Stage II, III, and IV disease were 24.4%, 7.3%, and 4.4%, respectively. After limiting to patients with a time from the initial diagnosis of prostate cancer to entry into the study cohort of ≤90 days (n = 869), the 5- and 10-year RS rates were 96.3% and 100.5%, respectively, although we were unable to consider management strategies due to a plenty of data missing.ConclusionsWe provide an overview of patients with prostate cancer in the BBJ project. Our findings, coupled with those from various high throughput “omics” technologies, will contribute to the implementation of prevention interventions and medical management of prostate cancer patients.

“…From June 2003 to March 2008, approximately 200,000 patients with any of 47 target common diseases were registered in the BBJ registry. The detailed study design and protocol were described elsewhere 17, 18, 19. In this registry, 29,065 patients were registered as having ischemic stroke, myocardial infarction or both.…”

Section: Methodsmentioning

confidence: 99%

Risk prediction models for mortality in patients with cardiovascular disease: The BioBank Japan project

Hata

Nagai

Hirata

et al. 2017

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BackgroundCardiovascular disease (CVD) is a leading cause of death in Japan. The present study aimed to develop new risk prediction models for long-term risks of all-cause and cardiovascular death in patients with chronic phase CVD.MethodsAmong the subjects registered in the BioBank Japan database, 15,058 patients aged ≥40 years with chronic ischemic CVD (ischemic stroke or myocardial infarction) were divided randomly into a derivation cohort (n = 10,039) and validation cohort (n = 5019). These subjects were followed up for 8.55 years in median. Risk prediction models for all-cause and cardiovascular death were developed using the derivation cohort by Cox proportional hazards regression. Their prediction performances for 5-year risk of mortality were evaluated in the validation cohort.ResultsDuring the follow-up, all-cause and cardiovascular death events were observed in 2962 and 962 patients from the derivation cohort and 1536 and 481 from the validation cohort, respectively. Risk prediction models for all-cause and cardiovascular death were developed from the derivation cohort using ten traditional cardiovascular risk factors, namely, age, sex, CVD subtype, hypertension, diabetes, total cholesterol, body mass index, current smoking, current drinking, and physical activity. These models demonstrated modest discrimination (c-statistics, 0.703 for all-cause death; 0.685 for cardiovascular death) and good calibration (Hosmer-Lemeshow χ2-test, P = 0.17 and 0.15, respectively) in the validation cohort.ConclusionsWe developed and validated risk prediction models of all-cause and cardiovascular death for patients with chronic ischemic CVD. These models would be useful for estimating the long-term risk of mortality in chronic phase CVD.