鈴木 隆弘

OBJECTIVE: We compared the incidences of four opportunistic infections (OI) in patients with rheumatoid arthritis (RA) treated with molecular-targeted drugs from big claims data. MATERIALS AND METHODS: We identified 205 906 patients with RA who were prescribed molecular-targeted drugs 2010-2017 from the National Database of Japan, and calculated the incidence of four OIs (Pneumocystis pneumonia [PCP], tuberculosis [TB], nontuberculous mycobacterial infection [NTM], and herpes zoster [HZ]). RESULTS: The total number of PCP, TB, NTM, and HZ patients with biological disease-modifying antirheumatic drugs (bDMARDs) or tofacitinib treatment history in RA were 765, 1158, 834, and 18 336, respectively. The incidence rates (IRs) of each OI for all bDMARDs were 0.14, 0.14, 0.09, and 2.40 per 100 person-years, respectively; while for tofacitinib they were 0.22, 0.22, 0.07, and 7.00 per 100 person-years. No big difference was observed among bDMARDs. All OIs showed higher incidence in those older than 65 years; but PCP, NTM and HZ showed no difference between those 65-74 years old and those over 75 years old. The median of occurrence was the third, seventh, ninth, and thirteenth month after treatment, respectively. CONCLUSION: We counted real IRs of OIs for the whole nation from big claims data.

PURPOSE: We aimed to develop a reliable identification algorithm combining diagnostic codes with several treatment factors for inpatients with acute ischemic stroke (AIS) to conduct pharmacoepidemiological studies using the administrative database MID-NET® in Japan. METHODS: We validated 11 identification algorithms based on 56 different diagnostic codes (International Classification of Diseases, Tenth Revision; ICD-10) using Diagnosis Procedure Combination (DPC) data combined with information on AIS therapeutic procedures added as "AND" condition or "OR" condition. The target population for this study was 366 randomly selected hospitalized patients with possible cases of AIS, defined as relevant ICD-10 codes and diagnostic imaging and prescription or surgical procedure, in three institutions between April 1, 2015 and March 31, 2017. We determined the positive predictive values (PPVs) of these identification algorithms based on comparisons with a gold standard consisting of chart reviews by experienced specialist physicians. Additionally, the sensitivities of them among 166 patients with the possible cases of AIS at a single institution were evaluated. RESULTS: The PPVs were 0.618 (95% confidence interval [CI]: 0.566-0.667) to 0.909 (95% CI: 0.708-0.989) and progressively increased with adding or limiting information on AIS therapeutic procedures as "AND" condition in the identification algorithms. The PPVs for identification algorithms based on diagnostic codes I63.x were >0.8. However, the sensitivities progressively decreased to a maximum of ~0.2 after adding information on AIS therapeutic procedures as "AND" condition. CONCLUSIONS: The identification algorithms based on the combination of appropriate ICD-10 diagnostic codes in DPC data and other AIS treatment factors may be useful to studies for AIS at a national level using MID-NET®.

OBJECTIVES: The objective of the study was to determine the seasonal changes in the initiation of biological disease-modifying antirheumatic drugs (bDMARDs) and methotrexate (MTX) using big claims data. METHODS: We counted the monthly number of initial administrations of each bDMARD and MTX in patients with rheumatoid arthritis (RA) between April 2010 and March 2017. Data were collected from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB). This database covers more than 95% of Japanese citizens. Seasonal changes in the number of initiations were determined. Patient claims were also classified according to drugs, districts, gender and ages. RESULTS: The initiation of bDMARDs and MTX administration varied according to the season in a sine curve shape, with the highest numbers in May to July and the lowest numbers in November to January. The same changing pattern was observed among each bDMARD, district, gender and age groups particularly when the number was on the higher side. CONCLUSION: We noted an apparent seasonal change in the number of bDMARDs initiated, with a peak during spring, suggesting an exacerbation of RA in the spring in Japan. These changes are overlooked in daily practice and are only visible using big data.

OBJECTIVES: To describe the real-world prescription and treatment retention of molecular-targeted drugs for rheumatoid arthritis (RA) in Japan. MATERIALS AND METHODS: 204,416 patients with RA prescribed at least one of the eight molecular-targeted drugs in 7 years from the National Database of Health Insurance Claims and Specific Health Checkups of Japan covering 98.3% of the Japanese population. The retention rate of each drug as well as head-to head comparisons were estimated by Kaplan-Meier method. RESULTS: 121,131 RA patients were prescribed any molecular-targeted drug for the first time, while 36,633 uses of molecular-targeted drug switched from another (switch use). The overall retention rates of molecular-targeted drugs at 12, 36, and 60 months were 0.64, 0.42, and 0.32 for the naïve use and 0.59, 0.40, and 0.31 for the switch use, respectively. Non-tumor necrosis factor (TNF)-inhibitor molecular-targeted drugs, particularly tocilizumab and tofacitinib, had higher retention rates than TNF inhibitors for both naïve and switch uses regardless of the previous drug, and showed higher retention rates in head-to-head comparisons between eight molecular-targeted drugs. CONCLUSIONS: Our data reveal that the real-world drug retention is overall lower than previously reported and higher with non-TNF inhibitors than with TNF inhibitors.