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Background

Laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding all lead to substantial weight loss in obese patients. Long-term weight loss can be highly variable beyond 1-year postsurgery. This study examines and compares the frequency distribution of weight loss and lack of treatment effect rates after laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding.

Methods

A total of 1,331 consecutive patients at a single academic institution were reviewed from a prospectively collected database. Preoperative data collected included demographics, body mass index, and percent excess weight loss. Postoperative BMI and %EWL were collected at 12, 24, and 36 months. Percent excess weight loss was analyzed by the percentiles of excess weight lost, and the distribution of percent excess weight loss was evaluated in 10% increments. Lack of a successful treatment effect was defined as <25% excess weight loss.

Results

Of the 1,331 patients, 72.4% (963) underwent laparoscopic Roux-en-Y gastric bypass, 18.3% (243) laparoscopic sleeve gastrectomy, and 9.4%(125) laparoscopic adjustable gastric banding. Mean percent excess weight loss was greatest for laparoscopic Roux-en-Y gastric bypass, followed by laparoscopic sleeve gastrectomy, and then by laparoscopic adjustable gastric banding at every time point: at 2 years mean percent excess weight loss was 77.9± 24.4 for laparoscopic Roux-en-Y gastric bypass, 50.8 ± 25.8 for laparoscopic sleeve gastrectomy, and 40.8± 25.9 for laparoscopic adjustable gastric banding (P < .0001). The rates of a successful treatment effect s for laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding were 0.9%, 5.2%, and 24.3% at 1 year; 0.3%, 11.1%, and 26.0% at 2 years; and 1.0%, 25.3%, and 30.2% at 3 years. At 1 year, the odds ratio of lack of a successful treatment effect of laparoscopic sleeve gastrectomy versus laparoscopic Roux-en-Y gastric bypass was 6.305 (2.125–19.08; P?=?.0004), the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic Roux-en-Y gastric bypass was 36.552 (15.64–95.71; P < .0001), and the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic sleeve gastrectomy was 5.791 (2.519–14.599; P < .0001). At 2 years, the odds ratio for laparoscopic sleeve gastrectomy versus laparoscopic Roux-en-Y gastric bypass increased to 70.7 (9.4–531.7; P < .0001), the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic Roux-en-Y gastric bypass increased to 128.1 (16.8–974.3; P < .0001), and the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic sleeve gastrectomy decreased to 1.8 (0.9–3.6; P?=?.09).

Conclusion

This study emphasizes the existing variability in weight loss across bariatric procedures as well as in the lack of a treatment effect for each procedure. Although laparoscopic adjustable gastric banding has the greatest rate of a lack of a successful treatment effect, the rate remained stable over 3 years postoperatively. Laparoscopic sleeve gastrectomy showed a doubling in the rate of a lack of a successful treatment effect every year reaching 25% at year 3. The rates for lack of a successful treatment effect for laparoscopic Roux-en-Y gastric bypass remained stable at about 1% for the first 3 years postoperatively.  相似文献   
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Background

Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.

Objective

We examined how different modeling assumptions influenced the results of 6 BIMs from the Institute for Clinical and Economic Review (ICER).

Study Design

Retrospective analysis of pharmaceutical sales data.

Methods

From ICER reports issued before 2016, we collected estimates of 3 BIM outputs: aggregate therapy cost (ie, cost to treat the patient population with a particular therapy), therapy uptake, and price. We compared these against real-world estimates that we generated using drug sales data. We considered 2 classes of BIM estimates: those forecasting future uptake of new agents, which assumed “unmanaged uptake,” and those describing the contemporaneous market state (ie, estimates of current, managed uptake and budget impact for compounds already on the market).

Results

Differences between ICER's estimates and our own were largest for forecasted studies. Here, ICER's uptake estimates exceeded real-world estimates by factors ranging from 7.4 (sacubitril/valsartan) to 54 (hepatitis C treatments). The “unmanaged uptake” assumption (removed from ICER's approach in 2017) yields large deviations between BIM estimates and real-world consumption. Nevertheless, in some cases, ICER's BIMs that relied on current market estimates also deviated substantially from real-world sales data.

Conclusions

This study highlights challenges with forecasting budget impact. In particular, assumptions about uptake and data source selection can greatly influence the accuracy of results.  相似文献   
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