Demand for bariatric surgery to treat severe and resistant obesity far outstrips supply. We aimed to comprehensively synthesise health economic evidence regarding bariatric surgery from 1995 to 2018 (PROSPERO registration number: CRD42018094189). Meta-analyses were conducted to calculate the annual cost changes "before" and "after" surgery, and cumulative cost differences between surgical and nonsurgical groups. An updated narrative review also summarized the full and partial health economic evaluations of surgery from September 2015. N = 101 studies were eligible for the qualitative analyses since 1995, with n = 24 studies after September 2015. Quality of reporting has increased, and the inclusion of complications/reoperations was predominantly contained in the full economic evaluations after September 2015. Technical improvements in surgery were also reflected across the studies. Sixty-one studies were eligible for the quantitative meta-analyses. Compared with no/conventional treatment, surgery was cost saving over a lifetime scenario. Additionally, consideration of indirect costs through sensitivity analyses increased cost savings. Medication cost savings were dominant in the before versus after meta-analysis. Overall, bariatric surgery is cost saving over the life course even without considering indirect costs. Health economists are hearing the call to present higher quality studies and include the costs of complications/reoperations; however, indirect costs and body contouring surgery are still not appropriately considered.

For the first time in Australia, we have quantified the impact of increasing severity of MS on health utility of people with MS. The HSUVs we have generated will be useful in further health economic analyses of interventions that slow progression of MS.

Objective: Determine the prevalence of multiple sclerosis (MS) in Australia in 2017 using MS-specific disease-modifying therapy (DMT) prescription data and estimate the change in prevalence from 2010. Methods: DMT prescriptions were extracted from Australia’s Pharmaceutical Benefits Scheme (PBS) data for January–December 2017. Percentages of people with MS using DMTs (DMT penetrance) were calculated using data from the Australian MS Longitudinal Study. Prevalence was estimated by dividing the total number of monthly prescriptions by 12 (except alemtuzumab), adjusted for DMT penetrance and Australian population estimates. Prevalences in Australian states/territories were age-standardised to the Australian population. Comparisons with 2010 prevalence data were performed using Poisson regression. Results: Overall DMT penetrance was 64%, and the number of people with MS in Australia in 2017 was 25,607 (95% confidence interval (CI): 24,874–26,478), a significant increase of 4324 people since 2010 ( p < 0.001). The prevalence increased significantly from 95.6/100,000 (2010) to 103.7/100,000 (2017), with estimates highest in Tasmania in 2017 (138.7/100,000; 95% CI: 137.2–140.1) and lowest in Queensland (74.6/100,000; 95% CI: 73.5–75.6). From 2010 to 2017 using the median latitudes for each state/territory, the overall latitudinal variation in MS prevalence was an increase of 3.0% per degree-latitude. Conclusion: Consistent with global trends, Australia’s MS prevalence has increased; this probably reflecting decreased mortality, increased longevity and increased incidence.

Background:Little is known about the relative contribution of comorbidities in predicting the health-related quality of life (HRQoL) of people with Multiple Sclerosis (PwMS).Objective: To determine the associations between the number of and individual comorbidities and HRQoL and estimate the relative contribution of different comorbidities on HRQoL.Methods: Cross-sectional analysis of data on self-reported presence of 30 comorbidities and HRQoL from the Australian MS Longitudinal Study (AMSLS) participants(n=902). HRQoL was measured using the Assessment of Quality of Life-8 Dimensions (AQoL-8D). Linear regression and general dominance analysis were used.Results: Higher number of comorbidities was associated with lower HRQoL (p-trend p<0.01).Comorbidities accounted for 18.1% of the variance in HRQoL. Mental health and musculoskeletal disorders were the strongest contributors to lower HRQoL. Of individual comorbidities, systemic lupus erythematosus (SLE) (β=-0.16(-0.27,-0.05)) and depression (β=-0.15(-0.18,-0.13)) were most strongly associated with overall HRQoL, depression (β=-0.14(-0.16,-0.11)) and anxiety (β=-0.10(-0.13,-0.07)) with psychosocial HRQoL, and SLE (β=-0.18(-0.29,-0.07)), rheumatoid arthritis (β=-0.11(-0.19,-0.02)) and hyperthyroidism (β=-0.11(-0.19,-0.03)) with physical HRQoL. Conclusions:Comorbidities potentially make important contributions to HRQoL in PwMS.Our findings highlight groups of and individual comorbidities that could provide the largest benefits for the HRQoL of PwMS if they were targeted for prevention, early detection, and optimal treatment.

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