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Kan H, Swindle JP, Bae J, Dunn JP, Buysman EK, Gronroos NN, Bengtson L, Chinthammit C, Ford J, Ahmad N. Weight management treatment modalities in patients with overweight or obesity: A retrospective cohort study of administrative claims data. OBESITY PILLARS 2023; 7:100072. [PMID: 37990675 PMCID: PMC10661997 DOI: 10.1016/j.obpill.2023.100072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/22/2023] [Accepted: 05/22/2023] [Indexed: 11/23/2023]
Abstract
Background The purpose of this study was to describe demographic and clinical characteristics among patients who have medical encounters for weight management treatments and to investigate the association of those characteristics with treatment modality. Methods This was a retrospective database study using medical claims, pharmacy claims, and enrollment information from commercial and Medicare Advantage with Part D members in the Optum Research Database from 01/01/2011-2/29/2020. Adult patients with a claim for a weight management treatment from 01/01/2012-2/28/2019 were categorized into cohorts according to the highest intensity intervention received. To examine the association between patient characteristics and treatment modality received, a multinomial logit model was performed. Results Cohorts by increasing intensity included lifestyle intervention (LSI, n = 67,679), weight reduction pharmacotherapy (WRRx) with an anti-obesity medication (AOM, n = 6,905), weight reduction procedure (WRP, n = 1,172), and weight reduction surgery (WRS, n = 18,036). Approximately 32.1% and 16.6% of patients who received WRS or WRP had an LSI during the 12-month baseline, and only 0.6% and 0.4% had treatment with long-term AOMs. In a multinomial logit model, patients with type 2 diabetes (not including WRRx cohort), respiratory disorders, cardiovascular risk factors, pain disorders, and mental health conditions had increased odds of treatment with higher intensity intervention versus LSI. Patients who were male, received an intervention more recently (2016-2019), or had a Charlson comorbidity score of 1 (compared to 0) had decreased odds of treatment with higher intensity interventions. Conclusion In this study, age, sex, body mass index, obesity-related complications, and Charlson comorbidity score appeared to influence the type of weight management treatment modality received. This study improves understanding of weight management treatment utilization and identifies gaps and opportunities to improve obesity care with the appropriate use of different treatment modalities.
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Affiliation(s)
- Hong Kan
- Eli Lilly, 893 Delaware St, Indianapolis, IN, USA
| | - Jason P. Swindle
- Evidera, 500 Totten Pond Rd, Waltham, MA, 02451, USA
- Formerly Optum, 11000 Optum Circle, Eden Prairie, MN, USA
| | - Jay Bae
- Eli Lilly, 893 Delaware St, Indianapolis, IN, USA
| | | | | | | | - Lindsay Bengtson
- Boehringer Ingelheim, 900 Ridgebury Rd, Ridgefield, CT, USA
- Formerly Optum, 11000 Optum Circle, Eden Prairie, MN, USA
| | | | - Janet Ford
- Agios Pharmaceuticals, Inc., Cambridge, MA, USA
- Formally Eli Lilly, 893 Delaware St, Indianapolis, IN, USA
| | - Nadia Ahmad
- Eli Lilly, 893 Delaware St, Indianapolis, IN, USA
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Khosrow-Khavar F, Desai RJ, Lee H, Lee SB, Kim SC. Tofacitinib and Risk of Malignancy: Results From the Safety of Tofacitinib in Routine Care Patients With Rheumatoid Arthritis (STAR-RA) Study. Arthritis Rheumatol 2022; 74:1648-1659. [PMID: 35643956 PMCID: PMC9529806 DOI: 10.1002/art.42250] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 04/14/2022] [Accepted: 05/24/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVES Results of the ORAL Surveillance safety trial have indicated that there is an increased risk for the development of malignancies with tofacitinib therapy when compared to treatment with tumor necrosis factor inhibitors (TNFi). This study was undertaken to further examine this safety concern in rheumatoid arthritis (RA) patients in a real-world setting. METHODS Using US insurance claims data from Optum Clinformatics (2012-2020), IBM MarketScan Research Databases (2012-2018), and Medicare (parts A, B, and D, 2012-2017), we created 2 cohorts of RA patients who had initiated treatment with tofacitinib or TNFi. The first cohort, designated the real-world evidence (RWE) cohort, included RA patients from routine care. For the second cohort, designated the randomized controlled trial (RCT)-duplicate cohort, we emulated the inclusion and exclusion criteria that were applied in the ORAL Surveillance trial of tofacitinib, which allowed us to assess the comparability of our results with the results of that trial. Cox proportional hazards models with propensity score fine-stratification weighting were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the risk of any malignancy (excluding nonmelanoma skin cancer). Database-specific estimates were meta-analyzed using fixed-effects models with inverse-variance weighting. RESULTS The RWE cohort consisted of 83,295 patients, including 10,504 patients (12.6%) who received treatment with tofacitinib. The pooled weighted HR for the primary outcome of any malignancy associated with tofacitinib treatment compared to any malignancy associated with TNFi therapy was 1.01 (95% CI 0.83, 1.22) in the RWE cohort and 1.17 (95% CI 0.85, 1.62) in the RCT-duplicate cohort (compared to the ORAL Surveillance trial HR of 1.48 [95% CI 1.04, 2.09]). CONCLUSION We did not find evidence of an increased risk of malignancy development with tofacitinib therapy, in comparison with TNFi therapy, in RA patients treated in a real-world setting. However, our results cannot rule out the possibility of an increase in risk that may accrue with a longer duration of treatment with tofacitinib.
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Affiliation(s)
- Farzin Khosrow-Khavar
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Rishi J. Desai
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Hemin Lee
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Su Been Lee
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - Seoyoung C. Kim
- Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
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