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Phenotype Submission - Polyarticular juvenile idiopathic arthritis (JIA)

Cohort Definition Name : Earliest event of Polyarticular juvenile idiopathic arthritis (JIA)
Contributor name : Joel Swerdel’
Contributor OrcId : 0000-0002-6976-2594’
Logic Description : First occurrence of Polyarticular juvenile idiopathic arthritis (JIA)) indexed on diagnosis date, for the first time in history. Requiring that events occurred on or after January of 2016 and limited to patients with age less or equal to 16 years old. cohort exit is the end of continuous observation.
Recommended study application : target or outcome
Assertion statement : This cohort definition was executed on at least one real person-level observational health data source and resulted in a cohort with at least 1 person.
Target Clinical Description : Polyarticular Juvenile Idiopathic Arthritis is a subset of juvenile idiopathic arthritis (JIA) defined by the presence of more than four affected joints during the first six months of illness. pJIA makes up approximate 20-30% of patients with JIA, is more common in females than males, and has a bimodal distribution of age at onset, with the first peak between 2-5 years and the second between 10-14 years.
"Evaluation conclusion : We developed a prevalent cohort definition for Polyarticular Juvenile Idiopathic Arthritis (PJIA) using a concept set of 6 concepts which incorporated all those found from the literature review, the analysis of PHOEBE, and orphan concepts in cohort diagnostics as well as after consultation with a rheumatologist. We performed the evaluation across a network of claim data sources and 1 EHR US data source. The data sources are:
IBM® MarketScan® Commercial Database (CCAE), Optum’s longitudinal EHR repository (Optum EHR), Optum’s Clinformatics® Data Mart (DOD), IBM® MarketScan® Multi-State Medicaid Database (MDCD), IBM® MarketScan® Medicare Supplemental Database (MDCR), Japan Claims Database (JMDC), Clinical Practice Research Datalink (CPRD) , IQVIA® Australia Longitudinal Patient Data (LPD) database (Australia), IQVIA® Disease Analyzer (DA) France database (France), QVIA® Disease Analyzer (DA) Germany database (Germany), IQVIA® Adjudicated Health Plan Claims Data (formerly PharMetrics Plus) - US database (PharMetrics), IQVIA® Ambulatory EMR (EMR).

The algorithm retrieves subjects from 11 databases tested, although subject counts were near 0 in Australia. In the month prior to index, there were many codes indicative of arthropathy, e.g., Arthropathy, Arthritis, and Inflammatory disorder of musculoskeletal system. However, these are not specific for polyarthropathy, where 5 or more joints are involved in the condition. As such, it is not advised to change the index date of the cohort. We developed a more specific cohort requiring a second diagnosis or observation code for PJIA in the time period 31-365 days after index. This cohort improves the specificity of the algorithm with a relatively small loss in sensitivity as determined by PheValuator. However, our analytical use case requires a specific treatment for the condition after the condition index date. This secondary indicator for the disease will likely increase the PPV for PJIA similar to requiring a second code with likely a smaller loss in sensitivity. In studies without requiring a concomitant specific drug exposure, the dual code algorithm should be considered. As a caution, due to the small sample sizes, the confidence intervals in PheValuator were wide. This may have ramifications if qualitative bias analysis is considered in studies.

Cohort Performance Characteristics using PheValuator – Performance characteristics were determined for 6 of the 11 databases. The remaining databases did not contain enough subjects to produce an accurate diagnostic model. Using one code only (the submitted cohort deffinition), sensitivity ranged from about 32% in Amb EMR to about 77% in CCAE and Optum SES while positive predictive value ranged from about 49% in Optum EHR to about 73% in Pharmetrics. Using two codes, sensitivity decreased, ranging from about 24% in Amb EMR to about 67% in CCAE while positive predictive value increased, ranging from 70% in Optum EHR to 93% in Pharmetrics.


Imported to the OHDSI Phenotype Library. It may be expected to be found with id = 1016 in the next release. Thank you