This study aimed to validate the Short-Form 12-Item Survey—version 2 (SF−12v2) in an older (≥65 years old) US population as well as estimate disutilities associated with relevant conditions, using data from the Medical Expenditure Panel Survey longitudinal panel (2014–2015). The physical component summary (PCS) and mental component summary (MCS) scores were examined for reliability (internal consistency, test-retest), construct validity (convergent and discriminant, structural), and criterion validity (concurrent and predictive). The study sample consisted of 1040 older adults with a mean age of 74.09 years (standard deviation: 6.19) PCS and MCS demonstrated high internal consistency (Cronbach’s alpha—PCS: 0.87, MCS: 0.86) and good and moderate test-retest validity, respectively (intraclass correlation coefficient: PCS:0.79, MCS:0.59)). The questionnaire demonstrated sufficient convergent and discriminant ability. Confirmatory factor analysis showed adequate fit with the theoretical model and structural validity (goodness of fit = 0.9588). Concurrent criterion validity and predictive criterion validity were demonstrated. Activity limitations, functional limitations, arthritis, coronary heart disease, diabetes, myocardial infarction, stroke, angina, and high blood pressure were associated with disutilities of 0.18, 0.15, 0.06, 0.07, 0.07, 0.06, 0.09, 0.06, and 0.08, respectively, and demonstrated the responsiveness of the instrument to these conditions. The SF−12v2 is a valid and reliable instrument in an older US population.

Uses of real-world data in drug safety and effectiveness studies are often challenged by various sources of bias. We undertook a systematic search of the published literature through September 2020 to evaluate the state of use and utility of negative controls to address bias in pharmacoepidemiologic studies. Two reviewers independently evaluated study eligibility and abstracted data. Our search identified 184 eligible studies for inclusion. Cohort studies (115, 63%) and administrative data (114, 62%) were, respectively, the most common study design and data type used. Most studies used negative control outcomes (91, 50%), and for most studies the target source of bias was unmeasured confounding (93, 51%). We identified 4 utility domains of negative controls: 1) bias detection (149, 81%), 2) bias correction (16, 9%), 3) P-value calibration (8, 4%), and 4) performance assessment of different methods used in drug safety studies (31, 17%). The most popular methodologies used were the 95% confidence interval and P-value calibration. In addition, we identified 2 reference sets with structured steps to check the causality assumption of the negative control. While negative controls are powerful tools in bias detection, we found many studies lacked checking the underlying assumptions. This article is part of a Special Collection on Pharmacoepidemiology.

This study quantifies costs associated with comorbid conditions among adults diagnosed with chronic obstructive pulmonary disease (COPD) who experience acute exacerbations (AECOPD) needing inpatien...

Background: While forced expiratory volume in 1 s (FEV₁) is a hallmark of disease progression in chronic obstructive lung diseases, little is known about the relationship between baseline FEV₁and future risks of other medical conditions.Objective: The aim of this study was to investigate the association between baseline FEV₁and future risks of diabetes, asthma, myocardial infarction, hypertension and all-cause mortality.Methods: We used data from the National Health and Nutrition Examination Survey and its Epidemiological Follow-Up Study. Our data provided longitudinal follow-up of the original cohort for up to 12 years. We used two competing risks approaches, the cause-specific hazard model and the Fine–Gray sub-distribution hazard model, to measure the associations between baseline FEV₁and future risks of the outcomes of interest. All models were adjusted for major confounding factors.Results: The final sample included 3020 participants (mean±sdbaseline age 44.64±13.44 years). In the cause-specific hazard model, for every per cent increase in the baseline per cent predicted FEV₁, the hazard of the event reduced by 2.5% (HR 0.975; 95% CI 0.958–0.994) for diabetes, 4.3% (HR 0.957; 95% CI 0.932–0.983) for asthma and 1.8% (HR 0.982; 95% CI 0.971–0.992) for all-cause mortality. There was no statistically significant association between baseline per cent predicted FEV₁and future risks of myocardial infarction (HR 0.987; 95% CI 0.970–1.004) and hypertension (HR 0.998; 95% CI 0.992–1.005). Consistent results were observed for the Fine–Gray sub-distribution hazard model.Conclusion: Our data suggest that lower per cent predicted FEV₁values at baseline were significantly associated with higher future risks of diabetes, asthma and all-cause mortality.

Investigate trends in paid lanadelumab costs over time in a population of patients persistent for 18 months, and to understand overall hereditary angioedema (HAE) treatment cost trends, including costs of acute medication/short-term prophylaxis and supportive care. Lastly, we sought to describe the proportion of lanadelumab patients with evidence of down titration via changes in total paid amounts for lanadelumab in a fixed time period. Patients were identified in the Merative MarketScan Databases who had ≥1 claim for lanadelumab during 1/1/2018-6/30/2022 (index), a ≤ 60-d gap in days of supply over 18 months, and were enrolled for ≥6 months pre-index and 18 months post-index. Lanadelumab and HAE-specific costs were assessed during follow-up months 0-6, 7-12, and 13-18. Down titration was defined as a ≥ 25% decrease in lanadelumab costs from months 0-6 to months 7-12 or 13-18. Outcomes were compared between time periods using paired t-tests and McNemar's test. Fifty-four lanadelumab users were included; 25 (46%) had evidence of down titration. Lanadelumab costs decreased from $316,724 to $269,861 to $246,919 in months 0-6, 7-12, and 13-18, respectively (p < .01); total HAE treatment costs decreased from $377,076 to $329,855 to $286,074 in months 0-6, 7-12, and 13-18, respectively (p < .01). Persistence was determined via days of supply on medication claims; use of the medication was not confirmed. Down titration was based on costs; the lanadelumab regimen could not be assessed. Results may not be generalizable to uninsured patients or those without commercial or Medicare insurance. Patients on long-term prophylaxis with lanadelumab experienced a significant reduction (24%) in HAE treatment costs over 18 months, driven by lower costs of acute medications and lanadelumab down titration. Down titration among appropriate patients with controlled HAE may lead to substantial savings in healthcare costs.