Validation of claims-based algorithms for rheumatoid arthritis in Japan: Results from the VALIDATE-J study.

AIM: Validity of Algorithms in Large Databases: Infectious Diseases, Rheumatoid Arthritis, and Tumor Evaluation in Japan (VALIDATE-J) study examined algorithms for identifying rheumatoid arthritis (RA) in Japanese claims data. METHODS: VALIDATE-J was a multicenter, cross-sectional retrospective study. Disease-identifying algorithms were used to detect RA diagnosed between January 2012 and December 2016 using claims data from two Japanese hospitals. An RA diagnosis was confirmed using one of four gold standard definitions. Positive predictive values (PPVs) were calculated for prevalent (regardless of baseline RA-free period) and incident (preceded by a 12-month RA-free period) cases. RESULTS: Of patients identified using claims-based algorithms, a random sample of 389 prevalent and 134 incident cases of RA were included. Cases identified by an RA diagnosis, no diagnosis of psoriasis, and treatment with any disease-modifying antirheumatic drugs (DMARDs) resulted in the highest PPVs versus other claims-based treatment categories (29.0%-88.3% [prevalent] and 41.0%-78.2% [incident]); cases identified by an RA diagnosis, no diagnosis of psoriasis, and glucocorticoid-only treatment had the lowest PPVs. Across claims-based algorithms, PPVs were highest when a physician diagnosis or decision by adjudicators (confirmed and probable cases) was used as the gold standard and were lowest when American College of Rheumatology/European Alliance of Associations for Rheumatology 2010 criteria were applied. PPVs of claims-based algorithms for RA in patients aged ≥66 years were slightly higher versus a USA Medicare population (maximum PPVs of 95.0% and 88.9%, respectively). CONCLUSION: VALIDATE-J demonstrated high PPVs for most claims-based algorithms for diagnosis of prevalent and incident RA using Japanese claims data. These findings will help inform appropriate RA definitions for future claims database research in Japan.

Validation of a claims-based algorithm to identify cases of ulcerative colitis in Japan.

BACKGROUND AND AIM: The prevalence of ulcerative colitis (UC) is increasing in Japan. Validated claims-based definitions are required to investigate the epidemiology of UC and its treatment and disease course in clinical practice. This study aimed to develop a claims-based algorithm for UC in Japan. METHODS: A committee of epidemiologists, gastroenterologists, and internal medicine physicians developed a claims-based definition for UC, based on diagnostic codes and claims for UC treatments, procedures (cytapheresis), or surgery (postoperative claims). Claims data and medical records for a random sample of 200 cases per site at two large tertiary care academic centers in Japan were used to calculate the positive predictive value (PPV) of the algorithm for three gold standards of diagnosis, defined as physician diagnosis in the medical records, adjudicated cases, or registration in the Japanese Intractable Disease Registry (IDR). RESULTS: Overall, 1139 claims-defined UC cases were identified. Among 393 randomly sampled cases (mean age 44; 48% female), 94% had received ≥ 1 systemic treatment (immunosuppressants, tumor necrosis factor inhibitors, corticosteroids, or antidiarrheals), 7% had cytapheresis, and 7% had postoperative claims. When physician diagnosis was used as a gold standard, PPV was 90.6% (95% confidence interval [CI]: 87.7-93.5). PPV with expert adjudication was also 90.6% (95% CI: 87.7-93.5). PPVs with enrollment in the IDR as gold standard were lower at 41.5% (95% CI: 36.6-46.3) due to incomplete case registration. CONCLUSIONS: The claims-based algorithm developed for use in Japan is likely to identify UC cases with high PPV for clinical studies using administrative claims databases.

Validity of claims-based algorithms for selected cancers in Japan: Results from the VALIDATE-J study.

PURPOSE: Real-world data from large administrative claims databases in Japan have recently become available, but limited evidence exists to support their validity. VALIDATE-J validated claims-based algorithms for selected cancers in Japan. METHODS: VALIDATE-J was a multicenter, cross-sectional, retrospective study. Disease-identifying algorithms were used to identify cancers diagnosed between January or March 2012 and December 2016 using claims data from two hospitals in Japan. Positive predictive values (PPVs), specificity, and sensitivity were calculated for prevalent (regardless of baseline cancer-free period) and incident (12-month cancer-free period; with claims and registry periods in the same month) cases, using hospital cancer registry data as gold standard. RESULTS: 22 108 cancers were identified in the hospital claims databases. PPVs (number of registry cases) for prevalent/incident cases were: any malignancy 79.0% (25 934)/73.1% (18 119); colorectal 84.4% (3519)/65.6% (2340); gastric 87.4% (3534)/76.8% (2279); lung 88.1% (2066)/79.9% (1636); breast 86.4% (4959)/59.9% (3185); pancreatic 87.1% (582)/80.4% (508); melanoma 48.7% (46)/42.9% (36); and lymphoma 83.6% (1457)/77.8% (1035). Specificity ranged from 98.3% to 100% (prevalent)/99.5% to 100% (incident); sensitivity ranged from 39.1% to 67.6% (prevalent)/12.5% to 31.4% (incident). PPVs of claims-based algorithms for several cancers in patients ≥66 years of age were slightly higher than those in a US Medicare population. CONCLUSIONS: VALIDATE-J demonstrated high specificity and modest-to-moderate sensitivity for claims-based algorithms of most malignancies using Japanese claims data. Use of claims-based algorithms will enable identification of patient populations from claims databases, while avoiding direct patient identification. Further research is needed to confirm the generalizability of our results and applicability to specific subgroups of patient populations.