Creating a Real-World Data, United States Healthcare Claims-Based Adaptation of Kurtzke Functional Systems Scores for Assessing Multiple Sclerosis Severity and Progression.

INTRODUCTION: This article describes the development of a unique mapping of the Kurtzke Functional Systems Scores (KFSS) from International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) codes among multiple sclerosis (MS) patients within a US Integrated Delivery Network (IDN). Valid identification of increasing disability may allow deeper insight into MS progression and possible treatments. METHODS: This cohort study identified MS patients in the IDN, Intermountain Healthcare. Experienced clinicians and informaticists mapped electronic health record ICD-9-CM codes to KFSS components generating a modified Kurtzke Expanded Disability Status Scale (EDSS). Modified EDSS scores were used to assess disability progression by calculating means, medians, ranges, and changes in KFSS and modified EDSS scores. RESULTS: Overall, 608/2960 (20.5%) patients were identified as having MS progression and presented a wide range of scores on the EDSS 10-point scale. The median (range) first and second EDSS scores were 0 (0-6) and 5 (1-8), respectively. The median (range) change from first to second score was 5 (1-7.5). The median first KFSS score for all systems was 0, and the mean differed among components. The highest mean first KFSS score (1.06) was measured for sensory function and lowest (0.12) for cerebellar functions. Of the 544 patients with their first EDSS scores in the ≤ 2.5 group, 75.2% and 15.1% had their second EDSS scores in group 3-5.5 and ≥ 6, respectively. Of the 62 patients with their first EDSS score in the 3-5.5 group, 58.1% had their second EDSS scores in group ≥ 6. CONCLUSION: This innovative mapping technique is a promising method for future comparative effectiveness and safety research of Disease-Modifying Therapy in Real-World Data repositories. Future research to validate and expand on this method in another healthcare database is encouraged.

Identification of responders to inhaled corticosteroids in a chronic obstructive pulmonary disease population using cluster analysis.

OBJECTIVES: To identify clusters of patients who may benefit from treatment with an inhaled corticosteroid (ICS)/long-acting ß2 agonist (LABA) versus LABA alone, in terms of exacerbation reduction, and to validate previously identified clusters of patients with chronic obstructive pulmonary disease (COPD) (based on diuretic use and reversibility). DESIGN: Post hoc supervised cluster analysis using a modified recursive partitioning algorithm of two 1-year randomised, controlled trials of fluticasone furoate (FF)/vilanterol (VI) versus VI alone, with the primary end points of the annual rate of moderate-to-severe exacerbations. SETTING: Global. PARTICIPANTS: 3255 patients with COPD (intent-to-treat populations) with a history of exacerbations in the past year. INTERVENTIONS: FF/VI 50/25 µg, 100/25 µg or 200/25 µg, or VI 25 µg; all one time per day. OUTCOME MEASURES: Mean annual COPD exacerbation rate to identify clusters of patients who benefit from adding an ICS (FF) to VI bronchodilator therapy. RESULTS: Three clusters were identified, including two groups that benefit from FF/VI versus VI: patients with blood eosinophils >2.4% (RR=0.68, 95% CI 0.58 to 0.79), or blood eosinophils ≤2.4% and smoking history ≤46 pack-years, experienced a reduced rate of exacerbations with FF/VI versus VI (RR=0.78, 95% CI 0.63 to 0.96), whereas those with blood eosinophils ≤2.4% and smoking history >46 pack-years were identified as non-responders (RR=1.22, 95% CI 0.94 to 1.58). Clusters of patients previously identified in the fluticasone propionate/salmeterol (SAL) versus SAL trials of similar design were not validated; all clusters of patients tended to benefit from FF/VI versus VI alone irrespective of diuretic use and reversibility. CONCLUSIONS: In patients with COPD with a history of exacerbations, those with greater blood eosinophils or a lower smoking history may benefit more from ICS/LABA versus LABA alone as measured by a reduced rate of exacerbations. In terms of eosinophils, this finding is consistent with findings from other studies; however, the validity of the 2.4% cut-off and the impact of smoking history require further investigation. TRIAL REGISTRATION NUMBERS: NCT01009463; NCT01017952; Post-results.

Effects of aggregation of drug and diagnostic codes on the performance of the high-dimensional propensity score algorithm: an empirical example.

BACKGROUND: The High-Dimensional Propensity Score (hd-PS) algorithm can select and adjust for baseline confounders of treatment-outcome associations in pharmacoepidemiologic studies that use healthcare claims data. How hd-PS performance is affected by aggregating medications or medical diagnoses has not been assessed. METHODS: We evaluated the effects of aggregating medications or diagnoses on hd-PS performance in an empirical example using resampled cohorts with small sample size, rare outcome incidence, or low exposure prevalence. In a cohort study comparing the risk of upper gastrointestinal complications in celecoxib or traditional NSAIDs (diclofenac, ibuprofen) initiators with rheumatoid arthritis and osteoarthritis, we (1) aggregated medications and International Classification of Diseases-9 (ICD-9) diagnoses into hierarchies of the Anatomical Therapeutic Chemical classification (ATC) and the Clinical Classification Software (CCS), respectively, and (2) sampled the full cohort using techniques validated by simulations to create 9,600 samples to compare 16 aggregation scenarios across 50% and 20% samples with varying outcome incidence and exposure prevalence. We applied hd-PS to estimate relative risks (RR) using 5 dimensions, predefined confounders, ≤ 500 hd-PS covariates, and propensity score deciles. For each scenario, we calculated: (1) the geometric mean RR; (2) the difference between the scenario mean ln(RR) and the ln(RR) from published randomized controlled trials (RCT); and (3) the proportional difference in the degree of estimated confounding between that scenario and the base scenario (no aggregation). RESULTS: Compared with the base scenario, aggregations of medications into ATC level 4 alone or in combination with aggregation of diagnoses into CCS level 1 improved the hd-PS confounding adjustment in most scenarios, reducing residual confounding compared with the RCT findings by up to 19%. CONCLUSIONS: Aggregation of codes using hierarchical coding systems may improve the performance of the hd-PS to control for confounders. The balance of advantages and disadvantages of aggregation is likely to vary across research settings.