Table 1.

Example of real-world evidence generation studies leveraging MDV or JMDC databases

Research question	References	Database	Method	Strength/impact	Limitations
Disease epidemiology/pharmacoepidemiology	Kobayashi 2020 [13]	MDV	Population: Inflammatory bowel disease patients Exposure: Thiopurine/anti-tumor necrosis factor-α Outcome: Incidence of malignancies	Impact No increase of the incidence of non-Hodgkin lymphoma associated with thiopurine or anti-tumor necrosis factor-α treatment in Japanese patients with inflammatory bowel disease Strength Conduction of sensitivity analysis by setting a stricter definition for the identification of the exposure	Lack of information on important confounders (disease duration and severity) Very few outcome events were observed
	Chang 2018 [14]	JMDC	Population: All patients with sufficient enrollment Exposure: None Outcome: MA-AGE, MA-NGE	Impact The study confirmed that norovirus is an important cause of MA-AGE in Japan, not only in children, but also in other age groups Strength Since only a small proportion of episodes are cause specified, the proportion attributable to norovirus was estimated using an indirect modeling method	The number of elderly individuals included in the analysis is relatively small, especially for women No information on 75 years and older Restrictive assumption of the residuals modeling method since all cause unspecified MA-AGE episodes in the database were considered due to norovirus
Healthcare resource use/economic burden	Yamazaki 2019 [15]	MDV	Population: Chronic hepatitis C patients Exposure: Antiviral treatment Outcome: Medical cost, healthcare resource use (including inpatient and outpatient visits)	Impact This study generated evidence that delaying antiviral treatment initiation for Japanese patients with chronic hepatitis C may increase the clinical and economic burden associated Strength Use of an algorithm to identify delayed treatment and early treatment cohort based on cirrhosis diagnosis record	Validation of the algorithm was performed with another claims database, but not in MDV Sustained virologic response status was not observed and thus could not be used for subpopulation analyses
	Inoue 2019 [16]	JMDC	Population: Asthma patients Exposure: Asthma severity (Japanese Society of Allergology guidelines) Outcome: Healthcare resource utilization (including direct costs)	Impact The results highlight a potential deviation from consensus care guidelines, and present an opportunity for further examining real-world clinical practices Strength Healthcare resource use data were generated in a large Japanese population, severe and non-severe asthma cohorts were characterized, and confirmation of age and comorbidities as relevant variables for asthma outcomes	Drug treatment was used as a proxy for disease severity since the information on disease severity was not available Smoking behavior and body mass index were not included in the analysis.
Product utilization pattern	Tanabe 2017 [17]	MDV	Population: Type 2 diabetes patients Exposure: Alpha-glucosidase inhibitor, biguanide, dipeptidyl peptidase-4 inhibitor, thiazolidinedione vs sulfonylurea Outcome: Treatment choice and adherence	Impact Cardiovascular disease history was not associated with treatment choice Strength Large population of diabetic patients allowed selection of patients with HbA1c data and capture of the elderly population	Analyses were restricted to patients with HbA1c, and these patients may present different characteristics when compared to those without HbA1c measurement Specialty of physicians administering treatment and some clinical information that may affect treatment selection were not available
	Matsuoka 2021 [18]	JMDC	Population: Patients diagnosed with ulcerative colitis Exposure: Corticosteroids, thiopurine, biologics Outcome: Prescription rate	Impact The study showed corticosteroid use became more appropriate as use of thiopurine and biologics increased, although there were still many cases of inappropriate use Strength This study captured the changes in corticosteroid use from 2006 to 2016 and the difference in characteristics of patients with long-term and non-long-term corticosteroid use, and identified factors associated with long-term corticosteroid use in ulcerative colitis patients	The population of elderly patients was limited Due to the unavailability of the information, the study did not address the differences in disease severity, which probably influenced corticosteroid use The reason for drug prescription could not be determined when more than one disease code was recorded
Characteristics of the patient population	Fuji 2017 [19]	MDV	Population: Patients with orthopedic surgeries Exposure: Multiple risk factors (including type of surgery, gender, history of venous thromboembolism, thrombophilia, age) Outcome: Pulmonary thromboembolism and deep venous thrombosis	Impact The incidence of thromboembolism and deep venous thrombosis, and the risk factors for thromboembolism and deep venous thrombosis were comparable to data obtained in previous studies Strength Validation of the outcome definitions was performed based on the clinical laboratory data from a sample of medical records and a high positive predictive value could be obtained	Inherent broader definitions of orthopedic surgeries in the database Lack of information to identify the cause of death No information on bleeding event date that was identified based on date of diagnostic imaging or examinations
	Yamada-Harada 2019 [20]	JMDC	Population: Diabetic patients Exposure: Number of risk factors (blood pressure, LDL-C, HbA1c, current smoking) Outcome: Coronary artery disease	Impact The study suggested that composite control of modifiable risk factors is important in patients with and without diabetes Strength Large sample size and long follow-up (at least 3 years). Use of health examination data (not only hospital data)	Issue of population sampling considering that only patients who had undergone physical examinations with blood tests were included Presence of unmeasured confounders such as undetected comorbidities, severity, duration of diabetes, and socio-economic status Lack of information on the symptomatic nature of coronary artery disease Target blood parameter values were assessed based on a single measurement
Comparative effectiveness/safety	Kohsaka 2020 [21]	MDV	Population: Patients with non valvular atrial fibrillation Exposure: apixaban, dabigatran, edoxaban and rivaroxaban versus warfarin Outcome: Risks of stroke and systemic embolism	Impact This study suggested that exposures were associated with a significantly lower risk of major bleeding and stroke/systemic embolism compared with warfarin Strength Large population and various treatment groups identified. Balancing among treatment group using stabilized inverse probability of treatment weighting was performed. Sensitivity analyses on time horizon and an alternative balancing method were used to assess the robustness of the results	Patients may present poorer health compared to the average population Due to the lack of information on the follow-up loss, the incidence of stroke may have been underestimated
	Hashimoto 2020 [22]	JMDC	Population: Pregnant women with allergic conjunctivitis Exposure: Topical ophthalmic corticosteroids Outcome: Congenital anomalies, preterm birth, low birth weight, and the composite of these three outcomes	Impact The study showed the use of topical ophthalmic corticosteroids in pregnant women with allergic conjunctivitis was not associated with congenital anomalies, preterm birth, or low birth weight Strength Availability of family identifiers to link newborn data to mother data	No possibility to confirm whether ophthalmic corticosteroids were actually used Daily frequency, duration of treatment, and dosage could not be accounted for

All studies listed adopted a cohort design

HbA1c glycated hemoglobin, LDL-C low-density lipoprotein cholesterol, MA-AGE medically attended acute gastroenteritis, MA-NGE medically attended norovirus-attributable gastroenteritis, MDV Medical Data Vision