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Background: Real-world data regarding anti-tumor necrosis factor alpha (anti-TNFα) biologic therapy use in psoriatic arthritis (PsA) are limited; therefore, we described treatment patterns and costs of anti-TNFα therapy in PsA patients in the United States.Methods: PsA patients (N = 990) aged ≥18 years who initiated anti-TNFα therapy were selected from MarketScan claims databases (10/1/2009 to 9/30/2010). Number of patients on first- (n = 881), second- (n = 72), or third- or greater (n = 37) line of anti-TNFα therapy, persistence, time-to-switch or modification, pharmacy and medical costs (measured per patient per month [PPPM]) for each line of therapy were observed during the 3-year follow-up.Results: PsA patients receiving only one line of anti-TNFα therapy remained on first-line for ~17 months while those who switched to second- or third- or greater persisted on first-line for ~11 to 12 months, respectively. Time to first-line modification was longer for patients who switched to third- or greater line therapy (7 months) than those who did not switch or switched to second-line (range, ~2 to 4 months). Time-to-switch and time to first-line modification was progressively shorter with each line of therapy for patients who received third- or greater line. PPPM medical costs were higher for patients who did not switch ($322) than those who switched to second- ($167) or third- or greater ($217) line. PPPM pharmacy costs were greater for patients with third- or greater line therapy ($2539) than those who did not switch ($1985) or switched to second-line ($2045).Conclusion: While the majority of patients received only one line of anti-TNFα therapy, a subset of patients switched to multiple lines of therapy during the 3-year follow-up period. Persistence and therapy modifications differed between these patients and those receiving only one line. Overall medical costs were highest for patients who did not switch, and pharmacy costs increased as patients switched to each new line of therapy. [ABSTRACT FROM AUTHOR]

Background: Cluster analysis (CA) is a frequently used applied statistical technique that helps to reveal hidden structures and "clusters" found in large data sets. However, this method has not been widely used in large healthcare claims databases where the distribution of expenditure data is commonly severely skewed. The purpose of this study was to identify cost change patterns of patients with end-stage renal disease (ESRD) who initiated hemodialysis (HD) by applying different clustering methods.Methods: A retrospective, cross-sectional, observational study was conducted using the Truven Health MarketScan® Research Databases. Patients aged ≥18 years with ≥2 ESRD diagnoses who initiated HD between 2008 and 2010 were included. The K-means CA method and hierarchical CA with various linkage methods were applied to all-cause costs within baseline (12-months pre-HD) and follow-up periods (12-months post-HD) to identify clusters. Demographic, clinical, and cost information was extracted from both periods, and then examined by cluster.Results: A total of 18,380 patients were identified. Meaningful all-cause cost clusters were generated using K-means CA and hierarchical CA with either flexible beta or Ward's methods. Based on cluster sample sizes and change of cost patterns, the K-means CA method and 4 clusters were selected: Cluster 1: Average to High (n = 113); Cluster 2: Very High to High (n = 89); Cluster 3: Average to Average (n = 16,624); or Cluster 4: Increasing Costs, High at Both Points (n = 1554). Median cost changes in the 12-month pre-HD and post-HD periods increased from $185,070 to $884,605 for Cluster 1 (Average to High), decreased from $910,930 to $157,997 for Cluster 2 (Very High to High), were relatively stable and remained low from $15,168 to $13,026 for Cluster 3 (Average to Average), and increased from $57,909 to $193,140 for Cluster 4 (Increasing Costs, High at Both Points). Relatively stable costs after starting HD were associated with more stable scores on comorbidity index scores from the pre-and post-HD periods, while increasing costs were associated with more sharply increasing comorbidity scores.Conclusions: The K-means CA method appeared to be the most appropriate in healthcare claims data with highly skewed cost information when taking into account both change of cost patterns and sample size in the smallest cluster. [ABSTRACT FROM AUTHOR]