Risk of fractures following bariatric surgery with Roux-en-Y gastric bypass or sleeve gastrectomy: a Danish population-based cohort study.

OBJECTIVE: We examined the association between Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) and fracture risk, including major osteoporotic fractures (MOF), and the use of anti-osteoporosis medication (AOM). While RYGB is associated with impaired bone health and increased fracture risk, it remains uncertain whether SG has a similar impact and whether this risk is primarily due to MOF or any fracture. DESIGN: We conducted a nationwide cohort study covering patients treated with RYGB (n = 16 121, 10.2-year follow-up) or SG (n = 1509, 3.7-year follow-up), from 2006 to 2018, comparing them with an age- and sex-matched cohort (n = 407 580). METHODS: We computed incidence rates and adjusted hazard ratios (HRs) with 95% CIs, using Cox regression for any fracture, MOF, and use of AOM with adjustment for comorbidities. RESULTS: Compared with the general population cohort, RYGB was associated with an increased risk of any fracture (HR 1.56 [95% CI, 1.48-1.64]) and MOF (HR 1.49 [1.35-1.64]). Sleeve gastrectomy was associated with an increased risk of any fracture (HR 1.38 [1.13-1.68]), while the HR of MOF was 1.43 (0.97-2.12). The use of AOM was low but similar in all cohorts (approximately 1%). CONCLUSIONS: Bariatric surgery increased the risk of any fracture and MOF to similar extend. Risks were similar for RYGB and SG. However, SG had a shorter follow-up than RYGB, and the cohort size was rather small. More research is needed for long-term SG fracture risk assessment. The use of AOM was low in all cohorts.

Drug utilization analysis of osteoporosis medications in seven European electronic health databases.

We studied the characteristics of patients prescribed osteoporosis medication and patterns of use in European databases. Patients were mostly female, older, had hypertension. There was suboptimal persistence particularly for oral medications. Our findings would be useful to healthcare providers to focus their resources on improving persistence to specific osteoporosis treatments. PURPOSE: To characterise the patients prescribed osteoporosis therapy and describe the drug utilization patterns. METHODS: We investigated the treatment patterns of bisphosphonates, denosumab, teriparatide, and selective estrogen receptor modulators (SERMs) in seven European databases in the United Kingdom, Italy, the Netherlands, Denmark, Spain, and Germany. In this cohort study, we included adults aged ≥ 18 years, with ≥ 1 year of registration in the respective databases, who were new users of the osteoporosis medications. The study period was between 01 January 2018 to 31 January 2022. RESULTS: Overall, patients were most commonly initiated on alendronate. Persistence decreased over time across all medications and databases, ranging from 52-73% at 6 months to 29-53% at 12 months for alendronate. For other oral bisphosphonates, the proportion of persistent users was 50-66% at 6 months and decreased to 30-44% at 12 months. For SERMs, the proportion of persistent users at 6 months was 40-73% and decreased to 25-59% at 12 months. For parenteral treatment groups, the proportions of persistence with denosumab were 50-85% (6 month), 30-63% (12 month) and with teriparatide 40-75% (6 month) decreasing to 21-54% (12 month). Switching occurred most frequently in the alendronate group (2.8-5.8%) and in the teriparatide group (7.1-14%). Switching typically occurred in the first 6 months and decreased over time. Patients in the alendronate group most often switched to other oral or intravenous bisphosphonates and denosumab. CONCLUSION: Our results show suboptimal persistence to medications that varied across different databases and treatment switching was relatively rare.

Using multiple random index dates with the reverse waiting time distribution improves precision of estimated prescription durations.

PURPOSE: To improve the precision of prescription duration estimates when using the reverse waiting time distribution (rWTD). METHODS: For each patient we uniformly sampled multiple random index dates within a sampling window of length δ . For each index date, we identified the last preceding prescription redemption, if any, within distance δ . Based on all pairs of last prescription and index date, we estimated prescription durations using the rWTD with robust variance estimation. In simulation studies with increasing misspecification we investigated bias, root mean square error (RMSE) and coverage probability of the rWTD using multiple index dates (1, 5, 10, and 20). We applied the method to Danish data on warfarin prescriptions from 2013 to 2014 stratifying by and adjusting for sex and age. RESULTS: In simulation scenarios without misspecification, the relative bias was negligible (-0.04% to 0.01%) and nominal coverage probabilities almost retained (93.8%-95.4%). RMSE decreased with the number of random index dates (e.g., from 1.3 with 1 index date to 0.6 days with 5). With misspecification, the relative bias was higher irrespective of the number of index dates. Precision increased with the number of index dates, and hence coverage probabilities decreased. When estimating durations of warfarin prescriptions in Denmark, precision increased with number of index dates, in particular in strata with few patients (e.g., men 90+ years: width of 95% confidence interval was 16.2 days with 5 index dates versus 35.4 with 1). CONCLUSIONS: Increasing the number of random index dates used with the rWTD improved precision without affecting bias.

Using the waiting time distribution with random index dates to estimate prescription durations in the presence of seasonal stockpiling.

PURPOSE: A pervasive problem in registry-based pharmacoepidemiological studies is what exposure duration to assign to individual prescriptions. The parametric waiting time distribution (WTD) has been proposed as a method to estimate such durations. However, when prescription durations vary due to seasonal stockpiling, WTD estimates will vary with choice of index date. To counter this, we propose using random index dates. METHODS: Within a calendar period of a given length, δ, we randomly sample individual index dates. We include the last prescription redemption prior to the index date in the analysis. Only redemptions within distance δ of the index date are included. In a simulation study with varying types and degrees of stockpiling at the end of the year, we investigated bias and precision of the reverse WTD with fixed and random index dates, respectively. In addition, we applied the new method to estimate durations of Norwegian warfarin prescriptions in 2014. RESULTS: In simulation settings with stockpiling, the reverse WTD with random index dates had low relative biases (-0.65% to 6.64%) and high coverage probabilities (92.0% to 95.3%), although when stockpiling was pronounced, coverage probabilities decreased (2.7% to 85.8%). Using a fixed index date was inferior. The estimated duration of warfarin prescriptions in Norway using random index dates was 131 (130; 132) days. CONCLUSIONS: In the presence of seasonal stockpiling, the WTD with random index dates provides estimates of prescription durations, which are more stable, less biased and with better coverage when compared to using a fixed index date.