In Japan, an increasing interest in real-world evidence for hypothesis generation and decision-making has emerged in order to overcome limitations and restrictions of clinical trials. We sought to characterize the context and concrete considerations of when to use Medical Data Vision (MDV) and JMDC databases, the main Japanese real-world data (RWD) sources accessible by pharmaceutical companies. Use cases for these databases, and related issues and considerations, were identified and summarized based on a literature search and experience-based knowledge. Studies conducted using MDV or JMDC were mostly descriptive in nature, or explored potential risk factors by evaluating associations with a target outcome. Considerations such as variable ascertainment at different time points, including issues relating to treatment identification and missing data, were highlighted for these two databases. Although several issues were commonly shared (e.g., only month of event occurrence reported), some database-specific issues were also identified and need to be accounted for. In conclusion, MDV and JMDC present limitations that are relatively typical of RWD sources, though some of them are unique to Japan, such as the identification of event occurrence and the inability to track patients visiting different healthcare settings. Addressing study design and careful result interpretation with respect to the specificities and uniqueness of the Japanese healthcare system is of particular importance. This aspect is especially relevant with respect to the growing global interest of conducting RWD studies in Japan.

Background Time-related bias can lead to misleading conclusions. Properly setting the "time zero" of follow-up is crucial for avoiding these biases. However, the time-zero setting is challenging when comparing users and non-users of a study drug because the latter do not have a time point for starting treatment. Objective This methodological study aimed to illustrate the impact of different time-zero settings on effect estimates in a comparative effectiveness study using real-world data with a non-user comparator. Methods Data for type 2 diabetes patients were extracted from an administrative claims database, and the onset of diabetic retinopathy (study outcome) was compared between users (treatment group) and non-users (non-use group) of lipid-lowering agents. We applied six time-zero settings to the same dataset. The adjusted hazard ratio (HR) for the outcome was estimated using a Cox regression model in each time-zero setting, and the obtained results were compared among the settings. Results Of the six settings, three (study entry date [SED] vs SED [naïve approach], treatment initiation [TI] vs SED, TI vs Matched [random order]) showed that the treatment had a reduced risk of the outcome (HR [95%

Background Administrative claims data are a valuable source for clinical studies; however, the use of validated algorithms to identify patients is essential to minimize bias. We evaluated the validity of diagnostic coding algorithms for identifying patients with colorectal cancer from a hospital’s administrative claims data. Methods This validation study used administrative claims data from a Japanese university hospital between April 2017 and March 2019. We developed diagnostic coding algorithms, basically based on the International Classification of Disease (ICD) 10th codes of C18–20 and Japanese disease codes, to identify patients with colorectal cancer. For random samples of patients identified using our algorithms, case ascertainment was performed using chart review as the gold standard. The positive predictive value (PPV) was calculated to evaluate the accuracy of the algorithms. Results Of 249 random samples of patients identified as having colorectal cancer by our coding algorithms, 215 were confirmed cases, yielding a PPV of 86.3% (95% confidence interval [CI], 81.5–90.1%). When the diagnostic codes were restricted to site-specific (right colon, left colon, transverse colon, or rectum) cancer codes, 94 of the 100 random samples were true cases of colorectal cancer. Consequently, the PPV increased to 94.0% (95% CI, 87.2–97.4%). Conclusion Our diagnostic coding algorithms based on ICD-10 codes and Japanese disease codes were highly accurate in detecting patients with colorectal cancer from this hospital’s claims data. The exclusive use of site-specific cancer codes further improved the PPV from 86.3 to 94.0%, suggesting their desirability in identifying these patients more precisely.

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Purpose To evaluate the associations between comorbidities and kidney function decline at 6-month and 1-year follow-up in outpatients with initial estimated glomerular filtration rate (eGFR) ≥ 30 mL/min/1.73 m2. Materials and methods Outpatients aged 18 and older with confirmed diagnosis, who had eGFR ≥ 30 mL/min/1.73 m2 measured between April 2017 and March 2019, were included in this retrospective observational study. Of them, 30,595 included outpatients had 6-month eGFR test and 27,698 included outpatients had 1-year eGFR test. The outpatients were further divided into two groups based on initial eGFR: between 30 and 59 and ≥ 60 mL/min/1.73 m2. Impaired renal function was defined as eGFR declined to below 30 mL/min/1.73 m2. The comorbidities with P values less than 0.1 identified in univariable logistic regression models were entered into the multivariable analysis with backward selection, thereby identifying comorbidities that increased the risk of eGFR decline at 6-month and 1-year follow-up. Results Outpatients with initial eGFR between 30 and 59 mL/min/1.73 m2 were 175.94 times more likely to have eGFR decline at 6 months, and were 94.10 times more likely to have eGFR decline at 1 year, compared with their corresponding initial eGFR ≥ 60 counterparts. Multivariable logistic regression analyses disclosed that chronic kidney disease, hypertension, and heart failure were independent risk factors for eGFR decline in outpatients with initial eGFR between 30 and 59 mL/min/1.73 m2. Conclusions Outpatients with initial eGFR ≥ 60 mL/min/1.73 m2 might not need routine eGFR test prior to contrast-enhanced CT scan for 1 year. In addition, chronic kidney disease, hypertension, and heart failure increased the risk of declined renal function, particularly, in outpatients with initial eGFR between 30 and 59 mL/min/1.73 m2.