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Timely administration of denosumab every 6 mo is critical in osteoporosis treatment to avoid multiple vertebral fracture risk upon denosumab discontinuation or delay. This study aimed to estimate the immediate and prolonged impact of the COVID-19 pandemic on the timing of denosumab doses. We identified older adults (≥66 yr) residing in the community who were due to receive denosumab between January 2016 and December 2020 using Ontario Drug Benefit data. We completed an interrupted time-series analysis to estimate the impact of the COVID-19 pandemic (March 2020) on the monthly proportion of on-time denosumab doses (183 +/−30 d). Analyses were stratified by user type: patients due for their second dose (novice users), third or fourth dose (intermediate users), or ≥5th dose (established users). In additional analyses, we considered patients living in nursing homes, switching to other osteoporosis drugs, and reported trends until February 2022. We studied 148 554 patients (90.9% female, mean [SD] age 79.6 [8.0] yr) receiving 648 221 denosumab doses. The average pre-pandemic proportion of on-time therapy was steady in the community, yet differed by user type: 64.9% novice users, 72.3% intermediate users, and 78.0% established users. We identified an immediate overall decline in the proportion of on-time doses across all user types at the start of the pandemic: −17.8% (95% CI, −19.6, −16.0). In nursing homes, the pre-pandemic proportion of on-time therapy was similar across user types (average 83.5%), with a small decline at the start of the pandemic: −3.2% (95% CI, −5.0, −1.2). On-time therapy returned to pre-pandemic levels by October 2020 and was not impacted by therapy switching. Although on-time dosing remains stable as of February 2022, approximately one-fourth of patients in the community do not receive denosumab on-time. In conclusion, although pandemic disruptions to denosumab dosing were temporary, levels of on-time therapy remain suboptimal. [ABSTRACT FROM AUTHOR]

Background: Community pharmacies typically require patients to request medication refills. The appointment-based model (ABM) is a proactive approach that synchronizes refills and schedules patient–pharmacist appointments. These appointments provide opportunities for medication reviews, medication optimization and health promotion services. The primary aim of this study was to describe the types of patients who received an ABM service in a community pharmacy in Ontario in 2017. The secondary aim was to describe reimbursable clinical service uptake. Methods: In September 2017, the ABM was implemented across 3 Ontario community pharmacies within a Canadian pharmacy banner. Patients who filled at least 1 chronic oral medication and consented to enrolment were eligible. In December 2018, data were extracted from pharmacies using pharmacy management software. Descriptive statistics and frequencies were generated. Results: Analysis of 131 patients (51.1% female; mean ± SD age 70.8 ± 10.5 years) revealed patients were dispensed a mean ± SD of 5.1 ± 2.7 medications, and 73 (55.7%) experienced polypharmacy. Hypertension (87.8%) and dyslipidemia (68.7%) were the most common medical conditions. There were 74 (56.5%) patients who received ≥1 medication review service (MedsCheck). Of 79 unique drug therapy problems (DTPs) identified, the most common categories related to patients needing additional drug therapy and adverse drug reactions. Discussion and conclusion: Patients enrolled in the ABM were generally older adults experiencing polypharmacy. The ABM presented opportunities for DTP identification and delivery of reimbursed services. Findings support continued exploration of the ABM to support integration of clinical services within community practice. [ABSTRACT FROM AUTHOR]

We identified inconsistency in fracture definitions in a prior review of studies that utilized claims data. Here, we aimed to compare fracture rates estimated using thirteen hip and seven radius/ulna fracture definitions. Our primary analysis compared results in a cohort of 120,363 older adults treated with oral bisphosphonates for ≥3 years. The most inclusive definition (hip: inpatient or emergency diagnosis; radius/ulna: inpatient, emergency, or outpatient diagnosis) served as a referent to compare the number and proportion of fractures captured. In sensitivity analyses, we considered a 180-day washout, excluded fractures associated with trauma; and hip only, excluded: (1) subtrochanteric fractures, and (2) hip replacement procedures. Hip fractures varied by definition in number (52–8058) and incidence (0.7–111.8/10,000 person-years). The second most inclusive definition required one inpatient diagnosis and identified 8% fewer hip fractures than the referent. Excluding hip replacements missed 33% of hip fractures relative to the primary analysis. Radius/ulna fractures also ranged in number (1589–6797) and incidence (22.0–94.3/10,000 person-years). Outpatient data were important, when restricted to inpatient or emergency data, only 78% of radius/ulna fractures were identified. Other than hip replacement procedures, sensitivity analyses had minimal impact on fracture identification. Analyses were replicated in a cohort of patients treated with long-term glucocorticoids. This study highlights the importance and impact of coding decisions on fracture outcome definitions. Further research is warranted to inform best practice in fracture outcome identification. [ABSTRACT FROM AUTHOR]

For self-controlled studies of medication-related effects, time-varying confounding by indication can occur if the indication varies over time. We describe how active comparators might mitigate such bias, using an empirical example. Approaches to using active comparators are described for case-crossover design, case-time-control design, self-controlled case-series, and sequence symmetry analyses. In the empirical example, we used Danish data from 1996–2018 to study the association between penicillin and venous thromboembolism (VTE), using roxithromycin, a macrolide antibiotic, as comparator. Upper respiratory infection is a transient risk factor for VTE, thus representing time-dependent confounding by indication. Odds ratios for case-crossover analysis were 3.35 (95% confidence interval: 3.23, 3.49) for penicillin and 3.56 (95% confidence interval: 3.30, 3.83) for roxithromycin. We used a Wald-based method or an interaction term to estimate the odds ratio for penicillin with roxithromycin as comparator. These 2 estimates were 0.94 (95% confidence interval: 0.87, 1.03) and 1.03 (95% confidence interval: 0.95, 1.13). Results were similar for the case-time-control analysis, but both the self-controlled case-series and sequence symmetry analysis suggested a weak protective effect of penicillin, seemingly explained by VTE affecting future exposure exclusively for penicillin. The strong association of antibiotics with VTE suggests presence of confounding by indication. Such confounding can be mitigated by using an active comparator. [ABSTRACT FROM AUTHOR]

Observational studies of osteoporosis medications can provide critical real-world evidence (RWE) that fills knowledge gaps left by clinical trials. However, careful consideration of study design is needed to yield reliable estimates of association. In particular, obtaining valid measurements of exposure to osteoporosis medications from real-world data (RWD) sources is complicated due to different medication classes, formulations, and routes of administration, each with different pharmacology. Extended half-lives of bisphosphonates and extended dosing of denosumab and zoledronic acid require particular attention. In addition, prescribing patterns and medication taking behavior often result in gaps in therapy, switching, and concomitant use of osteoporosis therapies. In this review, we present important considerations and provide specialized guidance for measuring osteoporosis drug exposures in RWD. First, we compare different sources of RWD used for osteoporosis drug studies and provide guidance on identifying osteoporosis medication use in these data sources. Next, we provide an overview of osteoporosis pharmacology and how it can influence decisions on exposure measurement within RWD. Finally, we present considerations for the measurement of osteoporosis medication exposure, adherence, switching, long-term exposures, and drug holidays using RWD. Ultimately, a thorough understanding of the differences in RWD sources and the pharmacology of osteoporosis medications is essential to obtain valid estimates of the relationship between osteoporosis medications and outcomes, such as fractures, but also to improve the critical appraisal of published studies., Competing Interests: KNH has received grant funding paid directly to Brown University for collaborative research from Insight Therapeutics, Sanofi, and Genentech for research on complex insulin regimens and influenza outbreak control in nursing homes. KNH has also served as a consultant for the Canadian Agency for Drugs and Technologies in Health. Other authors have no conflicts of interest to report., (© 2023 The Author(s).)