Incremental Net Monetary Benefit of Bariatric Surgery: Systematic Review and Meta-Analysis of Cost-Effectiveness Evidences

Graphical abstract This systematic review aimed to comprehensively synthesize cost-effectiveness evidences of bariatric surgery by pooling incremental net monetary benefits (INB). Twenty-eight full economic evaluation studies comparing bariatric surgery with usual care were identified from five databases. In high-income countries (HICs), bariatric surgery was cost-effective among mixed obesity group (i.e., obesity with/without diabetes) over a 10-year time horizon (pooled INB = $53,063.69; 95% CI $42,647.96, $63,479.43) and lifetime horizon (pooled INB = $101,897.96; 95% CI $79,390.93, $124,404.99). All studies conducted among obese with diabetes reported that bariatric surgery was cost-effective. Also, the pooled INB for obesity with diabetes group over lifetime horizon in HICs was $80,826.28 (95% CI $32,500.75, $129,151.81). Nevertheless, no evidence is available in low- and middle-income countries. Supplementary Information The online version contains supplementary material available at 10.1007/s11695-021-05415-9.


Introduction
Bariatric surgery is an attractive treatment option for obese patients, who could not achieve weight control by conservative, non-surgical therapies. The clinical effectiveness of bariatric surgery has been well established. Evidences from previous systematic reviews consistently indicated that bariatric surgery could significantly reduce body weight and improve comorbidities, as compared with usual care (e.g., pharmacotherapy and/or lifestyle modification) [1][2][3][4][5]. In addition, bariatric surgery might be superior to usual care for shortterm remission of diabetes mellitus [1,6]. Nevertheless, with the growing demand for bariatric surgery, demonstrating only the clinical effectiveness is not sufficient given the limited resources for healthcare. Evidences on the value for money are strongly required to support policy decision-making. To date, there were many published systematic reviews and metaanalyses on bariatric surgery [7][8][9]. However, most studies were limited to the description of methodologies and economic evaluation results [9]. Existing quantitative synthesis pertained only to differences in healthcare cost pre-and postsurgery or between surgical and non-surgical approaches [7,8]. Consequently, determining whether bariatric surgery provides value for money or in which condition it might be costeffective is still controversial. Therefore, a meta-analysis which pools the value for money of bariatric surgery is required.
Most economic evaluation studies report incremental costeffectiveness ratios (ICERs), which represent the ratio of incremental cost (ΔC) between the two interventions and incremental effectiveness (ΔE) between the same groups [10,11]. The effectiveness (E) is usually measured in terms of amount of quality-adjusted life year (QALY) gained or disabilityadjusted life year (DALY) averted. The ICER is then compared with the pre-defined cost-effectiveness threshold (K), the maximum amount a decision-maker is willing to pay for one QALY or DALY (e.g., £20,000 per QALY in the UK [12], or one time the GDP per capita per DALY in several countries [13]). If the ICER is less than K, the intervention is cost-effective; otherwise, it is not cost-effective. Nevertheless, the interpretation of ICER is problematic when its value is negative, which may indicate a lower cost with higher effectiveness or higher cost along with lower effectiveness of interventions. Thus, there is ambiguity in interpretation [10].
The incremental net monetary benefit (INB), which is the difference in net monetary benefit between the new intervention and the standard intervention [10], has been recently used instead of the ICER. The INB can be computed as the difference of incremental monetary benefit and incremental cost (INB = (ΔE×K) − ΔC) [10,11]. It is relatively easier to interpret than the ICER. A positive INB (INB > 0) indicates that an intervention is cost-effective as compared with the standard intervention at the given threshold, whereas a negative INB indicates the new intervention is not cost-effective relative to the standard one [10,11,14,15]. Up until now, few meta-analyses have been conducted to pool INBs [15][16][17][18]. Since there is still controversy on the value of money of bariatric surgery, we, therefore, conducted a meta-analysis which systematically reviewed and pooled INBs of bariatric surgery as compared with usual care among patients with obesity. Our main hypothesis is bariatric surgery is cost-effective for patients with obesity. Whenever possible, we examined whether bariatric surgery was cost-effective in particular type of patients (i.e,. obese with DM) and determined which specific procedures of bariatric surgery (i.e., SG, AGB, RYGB) were cost-effective when compared with usual care.

Materials and Methods
The protocol of this systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [19] (see Table S1). The review protocol was registered at the PROSPERO (registration number CRD42019142147).

Data Sources and Search Strategies
We searched relevant studies from PubMed, Scopus, the Cochrane Central Register of Controlled Trials-Wiley library, the Cost-Effective Analysis (CEA) Registry (The CEA Registry), and the Centre for Reviews and Dissemination (CRD) since inception to July 2019 without language restrictions. We constructed search terms based on the population, intervention, outcome, and study design domains (i.e., obesity, bariatric surgery, incremental cost-effectiveness ratio, and economic evaluation) (see Table S2).

Study Selection
Two reviewers (P.N. and M.T.) independently selected studies by screening titles and abstracts.Full texts were then reviewed based on the following criteria: any full economic evaluation study (i.e., cost-effectiveness analysis (CEA), cost-utility analysis (CUA), cost-benefit analysis (CBA)) of adult obesity (i.e., BMI > 32 kg/m 2 ); compared any pair of bariatric surgery (e.g., open or laparoscopic surgeries of adjustable gastric banding (AGB), Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and a mix of these bariatric surgeries (BS)) with usual care (e.g., pharmacotherapy and/or lifestyle modification); provided sufficient data for calculating INB [17]. The studies were excluded if they studied patients with other specific diseases or their full texts were not available.

Data Extraction
Data were extracted by two independent reviewers (P.N. and B.S.). A standardized data extraction form was developed. The data required for estimating INB were extracted: cost (C), incremental cost (ΔC), effectiveness (E), incremental effectiveness (ΔE), and ICER. These parameter values were extracted as means and dispersions (i.e., SDs, SEs, and 95% CIs). In some cases, ΔC and ΔE data were extracted from probabilistic sensitivity analyses (PSA). Authors of original studies were contacted further in case of incomplete information.

Data Preparation
INB was calculated as follows [10,15]: INB = (K × ΔE) − ΔC or ΔE × (K − ICER), where K is the cost-effectiveness threshold, and ΔE and ΔC are incremental effective and incremental cost, respectively. The INB variance was estimated as follows [15,17]: is variance of ΔC, and ρ ΔCΔE is covariance of ΔC and ΔE. In case of incomplete data, the variance of INB was simulated according to data availability (scenarios 1 to 5), as suggested by Bagepally et al. [17] If the study did not report the costeffectiveness threshold, the GDP per capita was used [13]. To pool data across studies, all currencies were converted to the international standard currency 2019 (international dollars; Int$) using consumer price index (CPI) and purchasing power parity (PPP) obtained from the World Economic Outlook Database (2019) [20].

Risk-of-Bias Assessment
The quality of each study was assessed by two independent reviewers (P.N. and M.T.), using the ECOBIAS checklist [21]. Disagreement was resolved by consensus with a third reviewer (U.C.).
To minimize heterogeneity, studies were stratified by country income level, which was classified according to the World Bank as high-income countries (HICs) and upper-middle-income countries (UMICs) [22]. In addition, the INBs were pooled according to perspective, type of model, type of patients (i.e., mixed obesity group, which included patients with/without diabetes, obesity with diabetes group), and time horizon (i.e., lifetime, 10 years). Subgroup analysis by types of bariatric surgery (i.e., AGB, RYGB, SG, BS) was also performed. A fixedeffect model by an inverse variance method was applied for pooling if heterogeneity was not present; otherwise, a random-effect model (DerSimonian and Laird) was used [23]. The heterogeneity of INBs among the studies was assessed using the Cochrane's Q statistic and I 2 statistics. Publication bias was assessed using the funnel plot and Egger's test. A contour-enhanced funnel plot was applied to distinguish publication bias from other causes of asymmetry [24].

INBs of Bariatric Surgery in HICs
The estimated INBs from HICs were presented separately by types of patients (see Tables S4 and S5). For mixed obesity group, bariatric surgery was found to be cost-effective in all except for three studies, which adopted 2-year [27], 5-year [30], and 10-year [31] time horizons. For obesity with diabetes group, all studies revealed that bariatric surgery was costeffective.

Discussion
We conducted a systematic review and meta-analysis for pooling INBs of bariatric surgery as compared with usual care. A total of 24 and 4 studies from HICs and UMICs were included in the review, but only data from HICs were sufficiently pooled. We found that bariatric surgery was a cost-effective intervention for mixed obesity group (i.e., with/without diabetes) in HICs over 10-year and lifetime time horizons. In addition, it was a cost-effective intervention for patients with obesity and diabetes in both HICs and UMICs from a payer perspective. For HICs, our analysis provides economic evidences in support of the current clinical practice guideline [53], which recommends bariatric surgery for patients with BMI ≥40 kg/m 2 and patients with BMI ≥35 kg/ m 2 with co-morbidity.
For mixed obesity group (i.e., with/without diabetes), all evidences from HICs indicated that bariatric surgery was costeffective over lifetime time horizon. Nevertheless, three studies, which adopted 2-year [27], 5-year [30], and 10-year [31] time horizons, found that bariatric surgery was not cost-effective. Our findings revealed that bariatric surgery might be cost-effective in studies employing a ≥10-year time horizon and more cost-effective over lifetime horizon. This could be possibly explained by the fact that costs for bariatric surgery were driven by high cost of surgery in the first few years [66], while the benefit of significantly lower healthcare expenditures due to the reduction of comorbidities could be observed in the long term after surgery [7]. Most included studies performed bariatric surgery on patients with a mean age ≥40 years. They projected all costs and outcomes incurred after the surgery throughout a lifetime period. It should be noted that INB with a lifetime horizon for these patients can be considered cost-effective as bariatric surgery can help prevent them from comorbidities and complications related to obesity, which finally can improve their health outcomes and decrease healthcare costs. In addition, performing the bariatric surgery with a lifetime horizon among patients with younger ages (i.e., 20 years) was even more cost-effective [38,40]. This is due to the fact that the young patients continue to gain benefits from surgery for a longer period as compared with their older counterparts.
Nevertheless, there is currently limited evidence on the long-term effects of bariatric surgery. Further studies on the long-term effectiveness and safety of bariatric surgery are warranted to improve the validity of cost-effectiveness studies.
According to our review, bariatric surgery was costeffective (i.e., positive INB) in all 14 studies (29 comparisons) conducted among obesity with diabetes group. This is similar to a previous systematic review [9], which found that almost all studies (6/7) conducted among obesity with diabetes group indicated that bariatric surgery was cost-effective. Bariatric surgery was generally believed to be more cost-effective in obesity with diabetes group than general obesity group. However, we found that the pooled INB (95% CI) in obesity with diabetes group over lifetime horizon was lower than mixed obesity group but not significant, i.e., $80,826.28 ($32,500.75, $129,151.81) vs. $101,897.96 ($79,390.93, $124,404.99), respectively. It should be noted that remission was higher among patients with recent onset of diabetes and those who were not taking insulin [67,68]. Less benefit of bariatric surgery was reported in diabetic patients who had already developed complications [67]. Variation in such characteristics of diabetes patients in each included study might possibly lead to the unclear conclusion when comparing the benefits of bariatric surgery between mixed obesity and obesity with diabetes group. Further studies carefully designed to compare cost-effectiveness of bariatric surgery among various characteristics of patients with diabetes (i.e., early diagnosed vs. long-term diabetes) are also warranted.
Presently, many types of bariatric surgery have been used in clinical practice. Nevertheless, most included studies reported mixed types of bariatric surgery. Subgroup analysis by types of bariatric surgery was performed for AGB, SG, and RYGB. We found that SG and AGB were cost-effective when compared with usual care, but not for RYGB. This could be explained by the fact that only three studies for RYGB were included for pooling and they had very large variances. Consequently, the pooled INB has high uncertainty and the interpretation should be made with caution. Based on current evidence, it is still inconclusive on which specific types of bariatric surgery should be selected. Further studies comparing cost-effectiveness among different types of the surgery are thus warranted.
Although this study was the first to provide quantitative evidences on value for money of bariatric surgery by estimating and pooling INB of bariatric surgery, certain limitations were needed to be addressed. First, all included economic evaluation studies were performed in HICs and UMICs, but none was conducted in lower-middle-income countries (LMICs) and low-income countries (LICs). Therefore, future economic evaluation studies of bariatric surgery in such settings should be further investigated. Second, in some cases, where dispersion parameters had not been reported (scenario 5), variances of INBs were adopted from other studies, which had comparable characteristics in terms of country, country income level, characteristics of patients, types of intervention, perspective, discount rate, and time. Nevertheless, adopted dispersion might not fully represent the actual dispersion of the INBs. Third, according to the quality assessment, almost all studies had biases related to treatment effects such that evidences on long-term effects of bariatric surgery were scarce. To improve validity of cost-effectiveness evidences, studies on the long-term treatment effect of bariatric surgery are warranted. Finally, due to data availability, we could only pool the value for money of bariatric surgery among obese patients with diabetes but not with other comorbidities, such as hypertension and obstructive sleep apnea.
In conclusion, our findings indicated that bariatric surgery seems to be cost-effective over 10-year and lifetime horizons in HICs for both mixed obesity group (i.e., with/ without diabetes) and obesity with diabetes group. The pooled INB for bariatric surgery as compared with usual care in HICs was estimated to be between $81,000 and $102,000 over the lifetime horizon. For UMICs, bariatric surgery seemed to be cost-effective as compared with usual care among obesity with diabetes group with the INBs ranging from $4,000 to $41,000.
Acknowledgments This work was part of training at Mahidol University Health Technology Assessment (MUHTA) program, with scholarship provided by Mahidol University and the International Decision Support Initiative (iDSI). This work was produced as part of the International Decision Support Initiative (www.idsihealth.org) which supports countries to get the best value for money from health spending. iDSI receives funding support from the Bill & Melinda Gates Foundation, the UK Department for International Development, and the Rockefeller Foundation. This work was supported in part by the Bill & Melinda Gates Foundation (grant number OPP1087363). Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. The findings, interpretations and conclusions expressed in this article do not necessarily reflect the views of the aforementioned funding agencies.
Authors' contribution All authors contributed to the study conception and design. Searching: P.N. Study selection: P.N., M.T., and B.S.B. Quality assessment and data extraction: P.N., M.T., and B.S.B. Data analysis: P.N., U.C., B.S.B., A.T., and M.T. The first draft of the manuscript was written by P.N. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Declarations
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Ethical statement We confirm that the manuscript has not been published elsewhere as a whole or partly and is not under consideration by another journal. Each author has contributed significantly to the work and agreed to this submission. All authors have approved the manuscript for submission

Conflicts of interest The authors declare no competing interests.
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