BACKGROUND: Previous cardiovascular risk prediction models in Japan have utilized prospective cohort studies with concise data. As the health information including health check-up records and administrative claims becomes digitalized and publicly available, application of large datasets based on such real-world data can achieve prediction accuracy and support social implementation of cardiovascular disease risk prediction models in preventive and clinical practice. In this study, classical regression and machine learning methods were explored to develop ischemic heart disease (IHD) and stroke prognostic models using real-world data. METHODS: IQVIA Japan Claims Database was searched to include 691,160 individuals (predominantly corporate employees and their families working in secondary and tertiary industries) with at least one annual health check-up record during the identification period (April 2013-December 2018). The primary outcome of the study was the first recorded IHD or stroke event. Predictors were annual health check-up records at the index year-month, comprising demographic characteristics, laboratory tests, and questionnaire features. Four prediction models (Cox, Elnet-Cox, XGBoost, and Ensemble) were assessed in the present study to develop a cardiovascular disease risk prediction model for Japan. RESULTS: The analysis cohort consisted of 572,971 invididuals. All prediction models showed similarly good performance. The Harrell's C-index was close to 0.9 for all IHD models, and above 0.7 for stroke models. In IHD models, age, sex, high-density lipoprotein, low-density lipoprotein, cholesterol, and systolic blood pressure had higher importance, while in stroke models systolic blood pressure and age had higher importance. CONCLUSION Our study analyzed classical regression and machine learning algorithms to develop cardiovascular disease risk prediction models for IHD and stroke in Japan that can be applied to practical use in a large population with predictive accuracy.
Humans ; Cardiovascular Diseases/epidemiology* ; Prognosis ; Prospective Studies ; Japan/epidemiology* ; Stroke/etiology* ; Myocardial Ischemia/epidemiology* ; Risk Assessment/methods*

Metabolic syndrome is a long-term complication of systemic chemotherapy for testicular germ cell tumor (TGCT). It is believed to be caused by secondary hypogonadism or toxic medicines because of orchidectomy followed by systemic chemotherapy. In this study, changes in the body composition of patients over time were quantitatively analyzed up to 24 months after chemotherapy. This study retrospectively analyzed 44 patients with TGCT who underwent chemotherapy at our institution from January 2008 to December 2016. Subcutaneous and visceral fat areas and psoas and skeletal muscle areas were measured by computed tomography before and immediately after chemotherapy as well as 3 months, 6 months, 12 months, and 24 months after chemotherapy. The subcutaneous and visceral fat indices and psoas and skeletal muscle indices were calculated as each area divided by body height squared. The total fat area had already significantly increased 3 months after the initiation of chemotherapy (P = 0.004). However, it did not return to prechemotherapeutic levels even at 24 months after chemotherapy. The skeletal muscle area was significantly decreased at the end of chemotherapy (P < 0.001); however, the value returned to baseline within 12 months. In multivariable analysis, the prechemotherapeutic skeletal muscle index and number of chemotherapy cycles were independently associated with the reduction of skeletal muscle at the end of chemotherapy (P = 0.001 and P = 0.027, respectively). In patients with TGCT, skeletal muscle mass decreased during chemotherapy and recovered within 12 months, whereas fat mass progressively increased from the initiation of chemotherapy until 24 months after chemotherapy.
Body Composition ; Body Mass Index ; Humans ; Male ; Muscle, Skeletal ; Neoplasms, Germ Cell and Embryonal ; Obesity ; Retrospective Studies ; Sarcopenia ; Testicular Neoplasms

The establishment of enhanced surveillance systems for mass gatherings to detect infectious diseases that may be imported during an event is recommended. The World Health Organization Regional Office for the Western Pacific contributed to enhanced event-based surveillance for the Tokyo 2020 Olympic and Paralympic Games (the Games) by using Epidemic Intelligence from Open Sources (EIOS) to detect potential imported diseases and report them to the National Institute of Infectious Diseases (NIID), Japan. Daily screening of media articles on global infectious diseases was conducted using EIOS, which were systematically assessed to determine the likelihood of disease importation, spread and significant impact to Japan during the Games. Over 81 days of surveillance, 103 830 articles were screened by EIOS, of which 5441 (5.2%) met the selection criteria for initial assessment, with 587 (0.6%) assessed as signals and reported to NIID. None of the signals were considered to pose a significant risk to the Games based on three risk assessment criteria. While EIOS successfully captured media articles on infectious diseases with a likelihood of importation to and spread in Japan, a significant manual effort was required to assess the articles for duplicates and against the risk assessment criteria. Continued improvement of artificial intelligence is recommended to reduce this effort.

In 2021, the National Institute of Infectious Diseases, Japan, undertook enhanced event-based surveillance (EBS) for infectious diseases occurring overseas that have potential for importation (excluding coronavirus disease 2019 [COVID-19]) for the Tokyo 2020 Olympic and Paralympic Summer Games (the Games). The pre-existing EBS system was enhanced using the World Health Organization Epidemic Intelligence from Open Sources system and the BlueDot Epidemic Intelligence platform. The enhanced EBS before and during the Games did not detect any major public health event that would warrant action for the Games. However, information from multiple sources helped us identify events, characterize risk and improve confidence in risk assessment. The collaboration also reduced the surveillance workload of the host country, while ensuring the quality of surveillance, even during the COVID-19 pandemic.

Abstract In the Western Pacific Region, event-based surveillance has been conducted for over a decade for rapid detection and assessment of acute public health events. This report describes the establishment and evolution of the Western Pacific regional event-based surveillance system and presents an analysis of public health events in the Region. Between July 2008 and June 2017 there was a total of 2396 events reported in the Western Pacific Region (average of 266 events per year). Events related to infectious diseases in humans account for the largest proportion of events recorded (49%). Maintaining this well-established system is critical in supporting rapid detection, assessment and response to acute public health events, to maintain regional health security.

The World Health Organization recommends that countries or organizations that host mass gatherings plan ahead and prepare for possible public health events to ensure a safe environment for local residents, participants and travellers.1 Public health events during mass gatherings can also affect non-host countries. There are numerous reports of the spread of infectious diseases by travellers returning from mass gatherings,2 which can potentially pose the risk of an outbreak of new infectious diseases to travellers’ home countries. With more frequent travel across borders, it is prudent that non-host countries prepare for mass gathering events.

Introduction: In Japan, syphilis notifications have increased. Men who have sex with men (MSM) in Tokyo have contributed substantially to the increase in syphilis notifications. We thus aimed to determine the correlates of incident syphilis among them. Methods: MSM who attended a Tokyo clinic that serves sexual minorities were recruited in a case-control study in 2015. A case was seropositive for primary/secondary/asymptomatic syphilis at enrolment visit and seronegative at prior visit or had oral ulcers positive for Treponema pallidum DNA at enrolment. For each case, two controls seronegative at enrolment and prior visit were selected. Using logistic regression, odds ratios (ORs) and 95% confidence intervals (CIs) were estimated to assess for correlates of case status. Results: Among 35 cases, the median age was 37 (range = 21–63) years and was similar to the 71 controls. Among HIV-positive participants (26 cases and 67 controls), cases were independently associated with higher frequency of anal or oral sex (OR = 3.4; 95% CI = 1.4–8.6; increase per category from < 1/month, ≥ 1/month but < 1/week, to ≥ 1/week) and no or inconsistent condom use during anal or oral sex (OR = 3.0; 95% CI = 1.1–8.3; increase per category from using every time, occasionally, to never), adjusted for residency and time between visits. Discussion Modifiable behaviours were associated with incident syphilis, and dissemination of prevention messages are needed.

Field Epidemiology Training Programmes (FETPs), which are modelled after the Centers for Disease Control and Prevention’s Epidemic Intelligence Service programme, began in 1980 and have produced graduates in more than 70 countries, including 12 in the Western Pacific Region.1,2 These programmes aim to “build sustainable capacity for detecting and responding to public health threats” and “develop expertise so that disease outbreaks can be detected locally and prevented from spreading”.3 FETPs thus include training in applied epidemiology and public health services. FETP trainees and graduates, however, often have additional responsibilities: mentoring newer trainees, supervising in the field, leading short training courses, facilitating meetings, etc. Programmes therefore must provide trainees with the knowledge and skills to fulfil these responsibilities.

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