Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2015 Mar 1.
Published in final edited form as: JAMA Surg. 2014 Mar 1;149(3):275–287. doi: 10.1001/jamasurg.2013.3654

Bariatric surgery: an updated systematic review and meta-analysis, 2003–2012

Su-Hsin Chang 1, Carolyn RT Stoll 1, Jihyun Song 2, J Esteban Varela 3, Christopher J Eagon 3, Graham A Colditz 1
PMCID: PMC3962512  NIHMSID: NIHMS494690  PMID: 24352617

Abstract

Importance

The prevalence of obesity and outcomes of bariatric surgery are well established. However, analyses of the surgery impact have not been updated and comprehensively investigated since 2003.

Objective

Up-to-date, comprehensive data and appropriate meta-analytic techniques were used to examine effectiveness and risks of bariatric surgery.

Data Sources

Literature searches of Medline, Embase, Scopus, Current Contents, Cochrane Library, and Clinicaltrials.gov between 2003 and 2012 were performed.

Study Selection

Exclusion criteria included publication of abstracts only, case reports, letters, comments, or reviews; animal studies; languages other than English; duplicate studies; no surgical intervention; and no population of interest. Inclusion criteria were at least one outcome of interest resulting from the studied surgery was reported – comorbidities, mortality, complications, reoperations, or weight loss. Of the 25,060 initially identified articles, 24,023 studies met the exclusion criteria, and 259 met the inclusion criteria.

Data Extraction

A review protocol was followed throughout. Three reviewers independently reviewed studies, abstracted data, and resolved disagreements by consensus. Studies were evaluated for quality.

Results

A total of 164 studies were included (37 randomized controlled trials (RCTs) and 127 observational studies). Analyses included 161,756 patients with mean age 45 years and body mass index (BMI) 46 kg/m2. We conducted random-effects and fixed-effect meta-analyses and meta-regression. In RCTs, ≤30 days mortality rate was 0.08% [95%CI, 0.01%–0.24%]; >30 days mortality rate was 0.31% [95%CI, 0.01%–0.75%]. BMI loss at the post-surgery five years was 12–17 kg/m2. The complication rate was 17% [95%CI, 11%–23%], and the reoperation rate was 7% [95%CI, 3%–12%]. Gastric bypass (GB) was more effective in weight loss but associated with more complications. Adjustable gastric banding (AGB) had lower mortality and complication rates; yet, the reoperation rate was higher and weight loss was less substantial than GB. Sleeve gastrectomy appeared to be more effective in weight loss than AGB and comparable to GB.

Conclusions

Bariatric surgery provides substantial and sustained effects on weight loss and ameliorates obesity-attributable comorbidities in the majority of bariatric patients, although risks of complication, reoperation, and death exist. Death rates were lower than those reported in previous meta-analyses.

1. INTRODUCTION

The prevalence of overweight and obesity is increasing globally.1 Among high-income countries, the United States has the highest mean body mass indexa (BMI) for men and women,2 and over two-thirds of U.S. adults aged 20 or older are overweight or obese.3 Overweight and obesity are associated with increased risk of morbidity4–9 and mortality.10–13 Approximately 112,000 deaths per year are associated with obesity in the United States.14

Treatments of obesity, except surgery, are generally ineffective in long-term weight control.15–20 In addition to sustained weight loss, surgical treatment provides additional benefits to people with obesity-related comorbidities and reduces relative risk of death due to significant weight loss.20–24 Consequently, the demand for bariatric surgery has risen dramatically in recent years. The total number of operations performed in the United States and Canada reached 220,000 in 2008 to 2009.25,26

Clinical trials have provided data for targeted surgical procedure(s) on different sets of patients, but general questions regarding effectiveness of surgical treatment of obesity and which surgical procedure is the most efficacious remain unanswered. Previous reviews, e.g., Buchwald et al.27 and Maggard et al.,28 provided comprehensive analyses, but included data from clinical trials and studies published before 2003. A recent systematic review and meta-analysis conducted by Padwal and colleagues29 focused only on randomized controlled trials (RCTs). Their data included recently published trials, but did not exclude early publications. Due to advances in technology of bariatric surgeryb and accumulation of surgeons’ experience, information provided in previous reviews is outdated. Therefore, it is necessary to reassess surgical treatments using more up-to-date data.

The goal of the study is to quantify risks and benefits of various bariatric surgery procedures focusing on adult patients. Specifically, we report the risks (defined as peri- and post-operative mortality, complications, and reoperations) and the effectiveness (defined as weight loss and remission of obesity-related diseases). We conducted a systematic review and meta-analysis on relevant studies selected from recent publications, including both RCTs and observational studies (OBSs). For each study design,30 random-effects (RE) or/and fixed-effect (FE) models31 were considered, and appropriate meta-analytic techniques were used to analyze the data.

2. METHODS

This systematic review and meta-analysis was conducted and reported according to the established guidelines.32,33 A review protocolc was followed throughout.

2.1 Data Sources and Searches

A search strategy was created by an MLIS qualified librarian. Comprehensive searches of the literature were performed on MEDLINE, EMBASE, SCOPUS, COCHRANE, and CLINICALTRIALS.GOV with the timeframe of January 1st, 2003 to March 31st, 2012. Searches were performed using the Firefox browser, and results were imported to EndNote X5. Search terms are detailed in the Appendix (Section 1).

2.2 Study Selection and Criteria

Search results were screened by scanning abstracts for the following exclusion criteria: publication of abstracts only, case reports, letters, comments, reviews, or meta-analyses; animal studies; languages other than English; duplicate studies; no surgical intervention; lack of outcomes of interest (weight change, surgical mortality and complications, and disease impacts); and not population of interest (adults aged>18 years). After removing excluded abstracts, full articles were obtained and studies were screened again more thoroughly using the same exclusion criteria.

2.3 Data Extraction

Studies were included in data extraction if they reported surgical procedure performed and at least one outcome of interest resulting from that surgery. Data needed to be presented separately by surgical procedure if more than one procedure was performed. Initial study population size and sample size at all data collection points was recorded. Characteristics of the starting study sample, such as age, race, sex, and weight information were collected when available. Pre- and post-surgery data regarding comorbid conditions, body composition, and any other pertinent category were extracted. The target obesity-related comorbidities included type-2 diabetes mellitus, cardiovascular disease, hypertension, dyslipidemia, and sleep apnea. Conversion of units to keep data consistent was performed when necessary. Extracted studies included RCTs and OBSs. Three reviewers independently reviewed the studies, abstracted data, and resolved disagreements by consensus.

2.4 Quality Assessment

All studies were evaluated for quality using a six-category scoring system (range 0–6).34 The categories were (1) clear definition of surgeries; (2) clear time points given for outcomes; (3) adjustment for potential confounders in analysis (for OBSs only) and adequate randomization (for RCTs only); (4) defined a priori sample size calculations; (5) loss to follow up less than 20%; (6) reports of funding sources/conflicts of interest.29,34–37 For categories 1–4, studies received a score of 1 if the study fulfilled the criteria, and 0 otherwise. For categories 5 and 6, studies could receive a score of 0, 0.5, or 1. For category 5, a score of 0 indicated that no information regarding loss to follow up was given, a score of 0.5 indicated that loss to follow up information was given, but loss to follow up was >20%, and a score of 1 indicated that loss to follow up was <20%. For category 6, a score of 0 indicated that the article gave no information regarding funding sources or conflicts of interest, a score of 0.5 indicated that the article was funded by surgical-related industry, and a score of 1 indicated that funding and conflicts of interest were declared, and there was no link to industry. A higher score indicated a higher quality study. Categories 3–6 were designed to assess the risk of study bias.

2.5 Statistical Analysis

Analyses were performed using only the data from studies in the data extraction subset. Study and individual-level data were summarized using descriptive statistics. Different surgical procedures were grouped into five categories: (i) gastric bypass (GB); (ii) adjustable gastric banding (AGB); (iii) vertical banded gastroplasty (VBG); (iv) sleeve gastrectomy (SG); and (v) non-surgical interventions (Control). Surgical outcomes in terms of percent excess weight lossd (%EWL), BMI change (ΔBMI), peri- and post-operative mortality, complication and reoperation rate, and percentage of remission of the obesity-attributable comorbidities were synthesized by meta-analysis. Meta-analyses were done separately for RCTs and OBSs.

2.5.1 Operative mortality, complication rate, and percentage of remission of the obesity-attributable comorbidities

We recorded the incidence of these outcomes in each study. For operative mortality, we ran separate analyses on studies which identified the deaths occurring within 30 days of the surgery and studies which identified the deaths occurring after 30 days of the surgery. Unclear timing of death was treated as if deaths were observed at the latest time of follow-up.e Surgical complications included all adverse events associated with surgery reported in the studies, such as bleeding, stomal stenosis, leak, vomiting, reflux, gastrointestinal symptoms, and nutritional and electrolyte abnormalities.f Reoperation rate was analyzed separately. Percentage of remission of comorbidities was defined as the proportion of the surgery patients who reported the target comorbid condition being either resolved or improved after surgery.g

Mortality, complication, and comorbidity remission rates were estimated by Bayesian random-effects meta-analysis method40,41 to avoid statistical problems caused by zero or rare events in each study.42–44 In addition, simple averaging method proposed by Bhaumik et al.44 was conducted as an alternative to the Bayesian RE meta-analysis. Both methods are detailed in the Appendix (Section 2).

2.5.2 Weight loss outcomes

All yearly post-surgery weight outcomes were compared to the pre-surgery weight. FE and RE models were constructed, and the Frequentist approach was used. The I2 index was computed to quantify the degree of study heterogeneity.45,46 Publication bias was evaluated using funnel plots and Egger’s test.47,48 We report post-surgery ΔBMI and %EWL for both study designs. Meta-regression of ΔBMI was conducted to account for patient characteristics (e.g., pre-surgery BMI, gender composition, and age), study design and quality, surgical procedure, and geographic location. We performed a preliminary meta-regression, using overall quality scores to determine if analyses of ΔBMI should be limited to studies with higher scores, followed by a main meta-regression analysis controlling for each quality category.

To make use of the information on repeated measurements of ΔBMI at different study time points in the trials and to compare and contrast the findings in Padwal et al.,29 we conducted mixed treatment comparison (MTC) meta-analysis using a Bayesian approach,49 targeting all RCTs from which we extracted data. This method allows us to statistically combine information on multiple pairwise comparisons to make inferences about relative effects between multiple surgical procedures.50 We categorized into 11 surgical procedures/interventions, and further grouped those procedures into 5 larger surgery categories (Appendix, Section 3 and eTable 3).h Four MTC models were considered (Appendix, Section 3). We estimated post-surgery ΔBMI compared to the referencei (relative surgery effect) in these models, taking advantage of the direct and indirect comparisons within study arms of RCTs. Here, we only present the first two models.

We computed the standard deviations of ΔBMI whenever possiblej if they were not reported in the original articles. Otherwise, we imputed the missing values by conducting a separate meta-analysis to estimate the distribution of standard deviations and then using the estimated distribution to predict the missing values.49

FE and RE meta-analyses using the Frequentist approach were performed using STATA (SE/11.2, Stata Corp, College Station, TX). Bayesian RE meta-analysis was conducted by R (2.14.0, R Development Core Team, Vienna, Austria) and JAGS, “runjags” package (0.9.9-2). Bhaumik estimates and the numerical solutions of the standard errors were obtained using MATLAB (7.11, R2012a, MathWorks Inc, Natick, MA). MTC meta-analyses were conducted using WinBUGS 1.4.3 (The BUGS Project, Cambridge, UK). For weight outcomes, we report the means for RE, the relative surgery effect for MTC, and the estimates for meta-regression; for the other outcomes, we report the means for Bayesian RE models, while the rest is presented in Appendix. 95% confidence/credible intervals (CIs) associated with the Frequentist/Bayesian estimates are reported in brackets.

3. RESULTS

3.1 Data Retrieval

A flow diagram outlining the systematic review process is provided in Figure 1. The initial searches resulted in 25,060 articles. After reviewing abstracts for exclusion criteria, 1,037 abstracts remained. Full articles were retrieved, and after screening for exclusion and inclusion criteria, data were extracted from 259 articles. Of these, 164 articles (37 RCTs and 127 OBSs) were included in meta-analyses.k Studies could contribute to more than one analysis.

Figure 1. Study attrition diagram.

Figure 1

Open in a new tab

BMI: body mass index; ΔBMI: BMI change; %EWL: percent excess weight loss; RCT: randomized controlled trial; OBS: observational studies. Remission is defined as the target comorbid condition being either resolved or improved after surgery.

3.2 Study and Patient Characteristics

Sixty-two of the included articles were published between 2003 and 2007, and 102 were published between 2008 and 2012 (Table 1). Ninety-one studies had follow-up periods of at least 2 years. Fifty-four studies were conducted in North America, 72 in Europe, 13 in Asia, and 25 in other locations (Australia, New Zealand, South America, and multinational studies). One hundred and forty studies reported patients’ mean age, and 142 contained their pre-surgery BMI information.

Table 1.

Study and patient characteristics

Study characteristics No. of studies No. of patients Patient characteristics No./Total (mean or %)
Publication year Age (years) (44.56)
 2003–2007 62 41,382 BMI (kg/m2) (45.62)
 2008–2012 102 120,374 Weight (kg) (124.53)
Study design Sex
 RCT 37 3,385  Male 32,384/153,267 (21.13)
 OBS 127 158,371  Female 120,883/153,267 (78.87)
Follow-up years Race
 >=2 years 91 28,671  White 87,653/117,430 (74.64)
 <2 years 73 133,085  Non-white 29,777/117,430 (25.36)
Study location Comorbidities
 North America 54 130,045  Type 2 diabetes 19,258/73,378 (26.24)
 Europe 72 22,703  Hypertension 34,092/71,938 (47.39)
 Asia 13 3,099  Cardiovascular disease 1,913/26,752 (7.15)
 Multinational 1 18  Dyslipidemia 11,533/41,235 (27.97)
 Other 24 5,891  Sleep Apnea 11,794/46,609 (25.30)
Age 140 100,094
BMI 142 90,587
Weight 68 16,790
Open in a new tab

RCT: randomized controlled trial; OBS: observational studies; BMI: body mass index; kg: kilogram; m: meter.

A total of 161,756 patients were included in our analyses. Among studies reporting participants’ information, mean age of the participants was 44.6 years, 79% were female, and 75% were white. Pre-surgery BMI was 45.6 kg/m2 and pre-surgery weight was 124.5 kg. Among the studies that provided information about obesity-related comorbidities, 26% of the patients had type-2 diabetes, 47% had hypertension, 28% had dyslipidemia, 7% had cardiovascular diseases, and 25% had sleep apnea.

3.3 Meta-analysis Results

3.3.1 Operative mortality, post-operative complication, and reoperation rates

Table 2 shows the meta-analytic results of surgical risks. Operative mortality was relatively low. Sixty-three studies (109 study arms) reported peri-operative (≤30 days) mortality data; and 47 studies (81 study arms) reported post-operative (>30 days) mortality data. For RCTs, peri-operative mortality rate was 0.08% [0.01%–0.24%], and post-operative mortality rate was 0.31% [0.01%–0.75%]. For OBSs, both peri- and post-operative mortality rates were higher – 0.22% [0.14%–0.31%] and 0.35% [0.20%–0.52%]. In OBSs, AGB had the lowest peri- and post-operative mortality rates (0.07% [0.02%–0.12%] and 0.21% [0.08%–0.37%]), followed by SG (0.29% [0.11%–0.63%] and 0.34% [0.14%–0.60%]) and then GB (0.38% [0.22%–0.59%] and 0.72% [0.28%–1.30%]).

Table 2.

Meta-analyses of surgery risk and comorbidities remission outcomes: means and 95% credible intervals are in brackets

GB AGB SG Control Overall
Mortality ≤ 30 days
RCT Estimates (%) 0.08 [0.01, 0.30] 0.11 [0.01, 0.50] 0.50 [0.01, 3.88] -- [--, --] 0.08 [0.01, 0.24]
Study/arm/patient # 11/18/934 5/8/743 1/2/40 0/0/0 15/30/1,803
OBS Estimates (%) 0.38 [0.22, 0.59] 0.07 [0.02, 0.12] 0.29 [0.11, 0.63] -- [--, --] 0.22 [0.14, 0.31]
Study/arm/patient # 19/30/90,090 26/29/40,538 10/11/3,647 1/1/9 48/79/136,903
Mortality > 30 days
RCT Estimates (%) 0.39 [0.01,0.86] 0.14 [0.00, 0.55] 6.00 [0.00, 100.00] -- [--, --] 0.31 [0.01, 0.75]
Study/arm/patient # 11/19/954 5/7/613 2/2/40 0/0/0 15/30/1,703
OBS Estimates (%) 0.72 [0.28, 1.30] 0.21 [0.08, 0.37] 0.34 [0.14, 0.60] -- [--, --] 0.35 [0.20, 0.52]
Study/arm/patient # 13/18/29,256 18/22/33,950 8/9/3,099 0/0/0 32/51/66,897
Complication rates
RCT Estimates (%) 21.00 [12.00, 33.00] 13.00 [5.20, 26.00] 13.00 [0.70, 44.00] -- [--, --] 17.00 [11.00, 23.00]
Study/arm/patient # 10/14/649 7/11/855 2/2/137 2/2/59 16/30/1,778
OBS Estimates (%) 12.00 [7.30, 17.00] 7.80 [3.90, 13.00] 8.90 [5.60, 13.00] -- [--, --] 9.80 [7.40, 13.00]
Study/arm/patient # 19/28/71,020 22/24/36,778 8/20/4,987 0/0/0 48/74/113,002
Reoperation rates
RCT Estimates (%) 2.56 [0.61, 5.36] 12.23 [4.46, 24.46] 9.05 [0.77, 34.56] -- [--, --] 6.95 [3.27, 12.04]
Study/arm/patient # 6/8/512 8/10/502 2/2/161 0/0/0 12/23/1,322
OBS Estimates (%) 5.34 [4.48, 6.48] 7.01 [3.99, 11.24] 2.96 [1.70, 4.71] -- [--, --] 5.75 [4.05, 7.83]
Study/arm/patient # 6/8/23,688 18/21/30,314 7/7/2,912 0/0/0 25/39/57,171
Diabetes remission rates
RCT Estimates (%) 95.15 [88.38, 98.80] 73.88 [36.06, 96.18] -- [--, --] 17.64 [0.98, 69.27] 91.99 [84.68, 97.18]
Study/arm/patient # 6/10/152 2/2/35 0/0/0 1/1/30 8/14/206
OBS Estimates (%) 92.83 [85.29, 97.21] 67.58 [49.51, 82.83] 85.53 [72.69, 94.07] -- [--, --] 86.05 [78.74, 91.62]
Study/arm/patient # 16/22/5,924 18/19/2,509 14/15/597 0/0/0 43/57/9,037
Hypertension remission rates
RCT Estimates (%) 80.98 [68.21, 91.52] 53.55 [12.52, 89.63] -- [--, --] 49.00 [0.00, 99.00] 75.18 [61.52, 86.35]
Study/arm/patient # 6/11/183 2/2/27 0/0/0 1/1/27 8/15/243
OBS Estimates (%) 78.13 [63.67, 88.76] 63.73 [51.74, 75.43] 82.23 [68.19, 92.01] 15.00 [1.40, 53.00] 74.36 [66.53, 81.19]
Study/arm/patient # 11/15/9,586 18/19/6,214 11/12/1,152 2/2/82 37/47/16,962
Dyslipidemia remission rates
RCT Estimates (%) 80.16 [61.68, 94.19] 39.95 [4.69, 87.05] -- [--, --] -- [--, --] 75.77 [55.63, 91.49]
Study/arm/patient # 5/8/147 1/1/132 0/0/0 0/0/0 5/9/279
OBS Estimates (%) 63.22 [40.86, 82.34] 60.91 [49.45, 72.36] 82.86 [62.67, 94.55] 5.42 [0.12, 30.41] 67.93 [58.08, 77.01]
Study/arm/patient # 5/7/556 11/11/351 5/5/570 1/1/63 20/23/1,477
Cardiovascular disease remission rates
RCT Estimates (%) -- [--, --] -- [--, --] -- [--, --] -- [--, --] 65.81 [6.21, 99.46]
Study/arm/patient # 0/0/0 0/0/0 0/0/0 0/0/0 1/1/3
OBS Estimates (%) 22.00 [0.00, 100.00] 78.00 [0.00, 100.00] -- [--, --] -- [--, --] 58.00 [0.00, 100.00]
Study/arm/patient # 1/1/17 2/2/10 0/0/0 0/0/0 3/3/27
Sleep apnea remission rates
RCT Estimates (%) 95.41 [84.49, 99.79] 94.26 [49.43, 100.00] -- [--, --] -- [--, --] 96.16 [86.66, 99.80]
Study/arm/patient # 3/6/41 2/2/2 0/0/0 0/0/0 5/9/44
OBS Estimates (%) 94.68 [86.36, 98.72] 71.14 [48.29, 89.16] 90.77 [80.06, 97.39] -- [--, --] 89.53 [81.33, 95.08]
Study/arm/patient # 8/11/5,748 13/14/3,598 8/9/498 0/0/0 27/35/9,845
Open in a new tab

Estimates were computed using Bayesian random-effects meta-analysis. Arms refer to subgroups within studies receiving different surgical procedures. GB: gastric bypass; AGB: adjustable gastric banding; SG: sleeve gastrectomy; Control: non-surgical interventions (non-surgical interventions were included in the analyses only when they were compared with surgical interventions); Overall: all surgery except for Control; RCT: randomized controlled trials; OBS: observational studies; --: estimates are not available when 0/0/0 (no data were included in the analysis) are presented or not relevant. Remission rate is defined as the proportion of the surgery patients who reported the target comorbid condition being either resolved or improved after surgery.

Sixty-four studies (16 RCTs and 48 OBSs) contributed to meta-analyses of complications. The complication rate was 17% [11%–23%] for RCTs, but lower for OBSs (10% [7%–13%]). This pattern persisted across all surgical procedures. For RCTs, complications rates were relatively low for SG (13% [1%–44%]) and AGB (13% [5%–26%]) compared to GB (21% [12%–33%]).

Reoperation rates were not as high as complication rates: 7% [3%–12%] for RCTs and 6% [4%–8%] for OBSs. In RCTs, GB appeared to have the lowest reoperation rate (3% [1%–5%]), followed by SG (9% [1%–35%]), while in OBSs, SG has the lowest reoperation rate (3% [2%–5%]), followed by GB (5% [4%–6%]). AGB appeared to have the highest reoperation rate (12% [4%–24%] for RCTs and 7% [4%–11%] for OBSs).

3.3.2 Weight loss

Table 3 presents results of the post-surgery BMI loss and %EWL analysis. Only studies that reported yearly ΔBMI and %EWL were incorporated into our meta-analysis. Sixty-nine studies (109 study arms) provided information on ΔBMI at one year after surgery, but only 11 studies (17 study arms) reported ΔBMI at five years after surgery. BMI loss within five years after surgery was persistent in the range of 12 to 17 kg/m2 for OBSs (Figure 2A).l There was no evidence of publication bias in any analysis, except for post-surgery years 1 and 3 ΔBMI for OBSs (Appendix, eFigure 2).

Table 3.

Meta-analyses of weight change outcomes: means and 95% confidence intervals are in brackets

ΔBMI GB AGB SG Control Overall
Year 1
RCT Estimates (kg/m2) −14.53 [−16.82, −12.25] −10.48 [−13.70, −7.25] −16.20 [−24.45, −7.95] -- [--, --] −13.53 [−15.51, −11.55]
# of studies/arms 9/15 3/3 1/1 0/0 12/22
OBS Estimates (kg/m2) −14.32 [−19.02, −9.62] −7.70 [−9.37, −6.03] −12.14 [−14.02, −10.26] −1.01 [−5.26, 3.23] −11.79 [−13.89, −9.69]
# of studies/arms 27/37 24/27 17/18 3/4 57/87
Year 2
RCT Estimates (kg/m2) −14.47 [−16.98, −11.97] −11.35 [−14.24, −8.46] -- [--, --] -- [--, --] −13.23 [−15.36, −11.11]
# of studies/arms 6/10 2/2 0/0 0/0 8/15
OBS Estimates (kg/m2) −12.93 [−17.39, −8.47] −8.75 [−10.37, −7.13] −13.39 [−19.52, −7.26] 0.10 [−7.39, 7.60] −11.80 [−13.92, −9.69]
# of studies/arms 12/16 14/16 5/5 1/2 29/40
Year 3
RCT Estimates (kg/m2) -- [--, --] −9.20 [−15.85, −2.54] -- [--, --] -- [--, --] −9.20 [−15.85, −2.54]
# of studies/arms 0/0 1/2 0/0 0/0 1/2
OBS Estimates (kg/m2) −16.78 [−20.57, −12.99] −11.43 [−18.14, −4.72] −21.88 [−27.96, −15.79] -- [--, --] −15.48 [−18.79, −12.18]
# of studies/arms 6/9 7/8 2/2 0/0 17/21
Year 4
RCT Estimates (kg/m2) -- [--, --] -- [--, --] -- [--, --] -- [--, --] -- [--, --]
# of studies/arms 0/0 0/0 0/0 0/0 0/0
OBS Estimates (kg/m2) −17.86 [−22.20, −13.53] −6.20 [−18.62, 6.22] -- [--, --] -- [--, --] −17.00 [−20.80, −13.19]
# of studies/arms 5/8 1/1 0/0 0/0 8/11
Year 5
RCT Estimates (kg/m2) -- [--, --] −11.40 [−28.08, 5.28] -- [--, --] -- [--, --] −11.40 [−28.08, 5.28]
# of studies/arms 0/0 1/1 0/0 0/0 1/1
OBS Estimates (kg/m2) −15.96 [−20.52, −11.40] −12.36 [−16.92, −7.79] −16.10 [−28.22, −3.98] -- [--, --] −14.32 [−17.19, −11.45]
# of studies/arms 4/7 4/7 1/1 0/0 10/16
%EWL GB AGB SG Control Overall
Year 1
RCT Estimates (%) 72.32 [64.60, 80.04] 33.39 [22.57, 44.21] 69.70 [41.09, 98.32] -- [--, --] 59.82 [50.46, 69.17]
# of studies/arms 5/7 4/4 1/1 0/0 9/15
OBS Estimates (%) 63.31 [54.20, 72.43] 34.26 [33.98, 34.54] 51.49 [44.41, 58.56] 20.00 [−25.08,65.08] 46.16 [43.89, 48.43]
# of studies/arms 17/25 14/15 11/11 1/1 39/55
Year 2
RCT Estimates (%) 74.39 [66.22, 82.55] 53.58 [32.80, 74.87] -- [--, --] -- [--, --] 70.58 [62.67, 78.50]
# of studies/arms 4/6 3/3 0/0 0/0 7/12
OBS Estimates (%) 80.09 [65.74, 94.43] 52.29 [48.67, 55.92] 46.72 [42.89, 50.55] -- [--, --] 63.98 [55.21, 72.74]
# of studies/arms 7/9 11/11 3/3 0/0 22/27
Year 3
RCT Estimates (%) -- [--, --] 56.72 [51.59, 61.85] -- [--, --] -- [--, --] 56.72 [51.59, 61.85]
# of studies/arms 0/0 2/2 0/0 0/0 2/2
OBS Estimates (%) 76.35 [65.21, 87.50] 58.30 [42.12, 74.49] 59.42 [48.05, 70.78] -- [--, --] 66.93 [65.05, 68.82]
# of studies/arms 6/8 6/6 2/2 0/0 16/19
Year 4
RCT Estimates (%) -- [--, --] -- [--, --] -- [--, --] -- [--, --] -- [--, --]
# of studies/arms 0/0 0/0 0/0 0/0 0/0
OBS Estimates (%) 76.36 [59.02, 93.70] 74.91 [58.54, 91.29] -- [--, --] -- [--, --] 74.82 [65.85, 83.80]
# of studies/arms 3/5 3/3 0/0 0/0 8/10
Year 5
RCT Estimates (%) -- [--, --] 41.60 [−9.75, 92.95] -- [--, --] -- [--, --] 41.60 [−9.75, 92.95]
# of studies/arms 0/0 1/1 0/0 0/0 1/1
OBS Estimates (%) 64.92 [44.27, 85.58] 57.23 [47.23, 67.23] -- [--, --] -- [--, --] 62.24 [58.71, 65.78]
# of studies/arms 3/5 5/8 0/0 0/0 10/15
Open in a new tab

Estimates were obtained from random-effects models using the Frequentist approach. Arms refer to subgroups within studies receiving different surgical procedures. GB: gastric bypass; AGB: adjustable gastric banding; SG: sleeve gastrectomy; Control: non-surgical interventions (non-surgical interventions were included in the analyses only when they were compared with surgical interventions); Overall: all surgery except for Control; RCT: randomized controlled trials; OBS: observational studies; BMI: body mass index; ΔBMI: BMI change; %EWL: percent excess weight loss; --: estimates are not available when 0/0 (no data were included in the analysis) are presented.

Figure 2. Meta-analysis of BMI change after surgery.

A. FRE meta-analysis results of BMI change for observational studies

Figure 2

Marker size is proportional to the number of study arms included in each analysis; FRE: random-effects meta-analysis using the Frequentist approach; GB: gastric bypass; AGB: adjustable gastric banding; SG: laparoscopic sleeve gastrectomy; Overall: all surgery except for Control.

B. MTC meta-analysis results of BMI change (Model 1 and 2) for randomized controlled trials

Estimates of Model 1 are presented in the format of forest plot; each estimate is the relative surgery effect compared to the laparoscopic Roux-en-Y Gastric Bypass (LRYGB); estimates of Model 2 are presented in rhombuses; each estimate of Model 2 is the relative category effect compared to the Gastric bypass (GB). A negative value means that the referent procedure/intervention (category) resulted in a lower BMI change, and vice versa; MTC: mixed treatment comparison; ORYGB: open RYGB; LBD-DS: laparoscopic biliopancreatic diversion with duodenal switch; BPD-RYGB: biliopancreatic diversion with RYGB; AGB: adjustable gastric banding; LLAGB: laparoscopic AGB-Lapband; LSAGB: laparoscopic AGB-Swedish; VBG: vertical banded gastroplasty; LVBG: laparoscopic VBG; OVBG: open VBG; SG: sleeve gastrectomy; Control: nonsurgical interventions.

Figure 2

Open in a new tab

The preliminary meta-regression showed that quality scores were not associated with post-surgery BMI changes.m Therefore, analyses including only studies with higher quality scores were not performed. The main meta-regression results showed that pre-surgery BMI and younger age were positively associated with post-surgery BMI loss (Appendix, Section 4.3 and eTable 4). RCT design, whether an RCT had adequate randomization, and whether a study provided a priori sample size calculations were associated with more BMI loss in the first year post-surgery. Having loss to follow up >20% was associated with more significant weight loss in the second year after surgery. BMI loss was significantly less for AGB, SG, and non-surgical interventions compared to GB in the first year after surgery. Proportion of female patients, geographical location, and the unmentioned categories of study quality did not have a significant association with BMI loss.

Forty-eight studies (9 RCTs and 39 OBSs) reported %EWL at one year post-surgery, and 18 studies (2 RCTs and 16 OBSs) reported %EWL three years after surgery (lower panel of Table 3). For RCTs, year 1 %EWL was 60% [50%–70%], I2=85%; year 2 %EWL was 71% [63%–79%], I2=63%; and year 3 %EWL was 57% [52%–62%], I2=0%. For OBSs, %EWL in the first three years were 46% [44%–48%], I2=90%; 64% [55%–73%], I2=90%; and 67% [65%–69%], I2=0%.

BMI loss was larger for GB than AGB. Both VBG (Appendix, eTable 2) and SG (Table 3) appeared to have significant effects on BMI loss, although data was limited for these surgical procedures. The one OBS that had 5-year follow-up data on ΔBMI after SG reported sustained BMI loss (~16 kg/m2) in year 5n54 To make more meaningful comparison between surgical procedures, MTC meta-analysis was used.

Figure 2B demonstrates the MTC meta-analysis results of ΔBMI from 17 RCTs. Relative surgery effects compared to the LRYGB procedure are presented in a forest plot. Relative category effects compared to the GB category are presented in the shape of rhombuses. Non-surgical intervention had the least BMI loss, 14 [6–22] kg/m2 less than LRYGB (Appendix, eTable 5). Among the 5 categories, AGB and VBG resulted in less BMI loss than GB, while SG had similar effect. Within the GB category, the combined methodso led to higher BMI loss than LRYGB alone, while ORYGB did not result in as much BMI loss as LRYGB. The AGB procedures did not help patients lose as much BMI as LRYGB, nor did open or laparoscopic VBG. LAGB using Lapband or unspecified brand of band appeared to be slightly more effective than LAGB using Swedish band, and LVBG led to more weight loss than OVBG.

3.3.3 Comorbidity outcomes

Fifty-three articles were included in our meta-analysis of comorbidity outcomes. Comorbid conditions were significantly improved after surgery as shown in our meta-analysis (Table 2). Eight RCTs (206 patients) and 43 OBSs (9,037 patients) provided diabetes information. The percentage of diabetes remission after surgery was 92% [85%–97%] for RCTs and 86% [79%–92%] for OBSs. The remission rates of hypertension were somewhat lower – 75% [62%–86%] for RCTs and 74% [67%–81%] for OBSs. Fewer studies (5 RCTs and 20 OBSs) investigated dyslipidemia; however, a large number of patients were included (279 patients in RCTs and 1,477 patients in OBSs). Data from RCTs showed 76% [56%–91%] remission of dyslipidemia after surgery. In OBSs, the remission rate was 68% [58%–77%]. Only 3 OBSs (27 patients) studied post-surgery conditions of cardiovascular disease, and the remission rate was 58% [0%–100%]. Five RCTs with 44 patients and 27 OBSs with 9,845 patients were included in the sleep apnea analysis. The remission rates were high: 96% [87%–100%] for RCTs and 90% [81%–95%] for OBSs.

4. COMMENT

We conducted an up-to-date and comprehensive systematic review and meta-analysis of bariatric surgery based on literature published after 2003. We evaluated risks and benefits associated with bariatric surgery.

In accordance with previous systematic reviews and meta-analyses,27–29 we found significant weight reduction and low mortality outcomes associated with surgery. However, the estimated mortality rates in our study were lower than those in previous meta-analyses,27,28 Buchwald et al. and Maggard et al.p. We also found significant improvement in comorbidities, which is consistent with findings in Buchwald et al.q,27 while Padwal et al.29 did not find this relationship. Consistent with Padwal et al. and others, our study found that GB is more effective than AGB and much more effective than non-surgical intervention in weight loss. A detailed comparison of findings across previous and our meta-analyses are summarized in eTable 10 in the Appendix.

Our findings are consistent with previous literature that AGB has lower mortality and complication rates than GB,36,37 but not a decreased reoperation rate. SG was positioned between AGB and GB56 in terms of mortality and complication rates in OBSs (but not in RCTs) and post-surgery BMI change in MTC meta-analysis of RCTs (but not in RE meta-analyses). The inconsistency is possibly due to the smaller numbers of studies included in the analyses. Overall, SG appeared to be more effective in weight loss than AGB and seemed to be comparable to GB even at five years. However, this conclusion cannot be made without noting that 7 studies were included in the analysis for GB, while only 1 study was included in the analysis for SG. Within the GB category, ORYGB had the least BMI loss, and LBD-DS had the most BMI loss among all procedures. We also found that LBD-DS and BPD-RYGB had better short- (<1 year) and mid-term (≥1 and <3 years) effects on BMI loss (Appendix, eTable 8).

We observed systematic differences in outcomes between RCTs and OBSs in the magnitude of the effects.57,58 We observed higher mortality in OBSs than in RCTs, which could be attributed to longer follow-up time in OBSs or a higher chance that mortality recorded in OBSs was not associated with surgery. We also found higher complication, reoperation, and comorbidity remission rates in RCTs.r This could be explained by more detailed monitoring and reporting of outcomes in RCTs due to smaller sample sizes and shorter follow-up times. Despite these differences, the direction of the effects is the same in all aspects. Agreeing with the findings in Benson et al.,59 we did not find larger effects in OBSs than in RCTs; on the contrary, estimates of the first-year BMI loss for RCTs are higher than those in OBSs.

Our study is restrained b the following limitations. First, like all other meta-analyses, the results need to be interpreted acknowledging that surgery effects vary based on characteristics of individual patient, e.g., age, gender, pre-surgery BMI, although we controlled for these in the meta-regression. Second, the number of studies included in the analyses was not balanced because (i) some procedures were not as popular as others;60 (ii) fewer studies reported post-surgery year 3–5 weight loss outcomes. Third, although the employment of MTC of repeated measurement circumvents the need to approximate the observed outcomes at various follow-up times to the closest study times and takes advantage of all information reported at different time points, the limited number of RCTs in our study restricts the estimation capability. Fourth, deaths of unspecified causes were not excluded in mortality analyses, and only overall complication rates were analyzed, which weakened the usefulness of the analyses. Last, although the data synthesis was carefully conducted in this study, the results needs to be interpreted with caution due to the heterogeneous outcome reporting of each included study, e.g., no standardized criteria of comorbidity improvement across studies.s

In conclusion, our study suggests that bariatric surgery has substantial and sustained effects on weight and significantly ameliorates obesity-attributable comorbidities in the majority of bariatric surgery patients. However, complication rates associated with bariatric surgery range from 10% to 17% and reoperation rates approximately 7%; nonetheless, mortality associated with surgery is generally low (0.08–0.35%). Among different surgical procedures, GB is more effective in weight change outcomes, but generates more adverse events. AGB is considered safer61,62 in terms of lower mortality and complication rates. However, the reoperation rate of AGB is higher than that of GB and SG, and the weight loss outcomes of AGB are less substantial than GB and SG.

Supplementary Material

Appendix

Acknowledgments

Funding/Support: Funding from the KM1 CA156708-01, U54 CA 155496, and Barnes-Jewish Hospital Foundation supported this research. G.A. Colditz is supported by an American Cancer Society Clinical Research Professorship.

Role of the Sponsor: The sponsor had no role in the design and conduct of the study, collection, management, analysis, or interpretation of the data; or the preparation, review, approval of the manuscript.

We thank Ms. Carol Murray, an MLIS qualified librarian at the Bernard Becker Medical Library at the Washington University in St. Louis, who helped develop search strategies and performed computerized searches. We also thank Dr. Helen Dakin at the Health Economics Research Centre, University of Oxford, for providing computer codes to help understand using WINGBUGS to perform MTC meta-analysis. We acknowledge Jennifer Rowley, Ellen Murray, Misty Lewis, Amanda Calhoun, and Nikki Freeman for performing substantive data extraction and table editing. Finally, we thank Drs. Jean Wang in the Division of Gastroenterology and Michael Awad in the Department of Surgery, Washington University School of Medicine, for helpful conversation regarding complications associated with bariatric surgery. This publication was made possible by Grant Number KM1CA156708-01 through the National Cancer Institute (NCI) at the National Institutes of Health (NIH) and Grant Numbers UL1 TR000448, KL2 TR000450, TL1 TR000449 through The Clinical and Translational Science Award (CTSA) program of the National Center for Advancing Translational Sciences at the National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCATS or NIH.

Footnotes

a

BMI is defined by weight in kilograms (kg) divided by the square of height in meters (m).

b

For example, new procedures, such as sleeve gastrectomy, were developed.

c

The review protocol is available on the website: http://www.publichealthsciences.wustl.edu/en/Faculty/ChangSu-Hsin.

d

Percent excess weight loss = [(operative weight-follow-up weight)/operative excess weight]×100, where excess weight = actual weight-ideal weight,38 and ideal weight is derived from the 1983 Metropolitan insurance height and weight tables.39

e

Deaths of unspecified causes were not excluded in any mortality analyses.

f

Specific surgical complications were variably reported and difficult to catalog. Therefore, only overall complication rate was analyzed.

g

Due to the heterogeneity in the reporting of comorbidity outcomes, we provided a table recording the definitions of the target comorbidity and surgical outcomes associated with the target comorbidity in eTable 9 in the Appendix.

h

The 5 categories were the same as the aforementioned 5 categories. 11 surgical procedures/interventions included (1) laparoscopic Roux-en-Y Gastric Bypass (LRYGB); (2) open RYGB (ORYGB); (3) LRYGB with presurgery weight loss; (4) laparoscopic biliopancreatic diversion with duodenal switch (LBD-DS); (5) biliopancreatic diversion with RYGB (BPD-RYGB); (6) laparoscopic adjustable gastric banding (LAGB) – Lapband; (7) LAGB – Swedish; (8) laparoscopic vertical banded gastroplasty (VBG); (9) open VBG; (10) laparoscopic sleeve gastrectomy (SG); and (11) nonsurgical interventions. Among them, (1)–(5) belong to procedure 1, GB; (6)–(7) are procedure 2, AGB; (8) and (9) belong to procedure 3, VBG; (10) is procedure 4, SG, and (11) belongs to procedure 5, Control.

i

Among those procedures, the laparoscopic Roux-en-Y Gastric Bypass (LRYGB) was the mostly commonly compared procedure (Appendix, Section 3 and eFigure 1), and, therefore, LRYGB procedure was the reference in Model 1. In Model 2, GB category was the reference.

j

We computed standard deviation from the reported 95% confidence intervals or exact p-values when a statistical test was conducted in the original study to compare the pre- and post- surgery BMI.

k

The extracted studies were excluded in the analyses if they reported outcomes inconsistent with our stratification or missed reporting at least one key element to be included in our analyses, e.g., time points, clear definition of the outcome, aggregately reported outcomes. A list of the included articles is available on the website: http://www.publichealthsciences.wustl.edu/en/Faculty/ChangSu-Hsin.

l

Very few studies reported weight loss information beyond five years after surgery. However, two articles51,52 based on the Swedish Obese Subjects study reporting BMI change 10+ years after surgery reported the mean BMI reduction 10 years and 15 years after surgery was still approximately 6.5 and 7.1 kg/m2.

m

p-value = 0.153 for year 1, and p-value = 0.962 for year 2.

n

In addition, the one OBS that had 5 year follow-up data on ΔBMI after VBG was performed reported sustained BMI change – approximately −16 kg/m2 for years 4 and 5.53

o

The combined methods included LBD-DS, BPD-RYGB, and LRYGB with pre-surgery weight loss.

p

Even though zeros were imputed for missing data and grouped into the early death outcome in Maggard et al., lower early mortality rates for RCTs were still found in our study.

q

In another review article, Buchwald and colleagues found that type-2 diabetes were resolved or improved in the greater majority of bariatric patients.55

r

This holds true for all surgical procedures, except VBG for complication and comorbidity remission rates; and GB for reoperation rates.

s

Analyses might be weakened by heterogeneous criteria of comorbidity improvements, and the lack of consistent details in the individual studies prevented further subgroup analyses. A table (eTable 9 in the Appendix) comparing criteria across studies was provided to allow interpretation of results in context.

Conflict of Interest Disclosures: None.

Disclaimer: The conclusions and opinions presented herein are solely the responsibility of the authors and do not necessarily represent the official views of NCATS, NIH, or the Barnes-Jewish Hospital Foundation.

Authors’ contributions: Dr. Chang had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Chang, Colditz

Analysis and interpretation of data: Chang, Stoll, Song, Varela, Eagon, Colditz

Drafting of the manuscript: Chang, Stoll

Critical revision of the manuscript for important intellectual content: Chang, Stoll, Song, Varela, Eagon, Colditz

Statistical expertise: Chang, Song

Obtained funding: Chang, Colditz

Administrative, technical, or material support: Chang, Stoll, Colditz

Study supervision: Chang, Colditz

References

  • 1.World Health Statistics 2010. World Health Organization; 2010. [Google Scholar]
  • 2.Farzadfar F, Finucane MM, Danaei G, et al. National, regional, and global trends in serum total cholesterol since 1980: systematic analysis of health examination surveys and epidemiological studies with 321 country-years and 3.0 million participants. Lancet. 2011 Feb 12;377(9765):578–586. doi: 10.1016/S0140-6736(10)62038-7. [DOI] [PubMed] [Google Scholar]
  • 3.Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999–2008. JAMA. 2010 Jan 20;303(3):235–241. doi: 10.1001/jama.2009.2014. [DOI] [PubMed] [Google Scholar]
  • 4.Beason TS, Colditz GA. Obesity and Multiple Myeloma. In: Mittelman SD, Berger NA, editors. Energy Balance and Jematologic Malignancies. Vol. 5. New York: Springer; 2012. pp. 71–95. [Google Scholar]
  • 5.Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999 Oct 27;282(16):1523–1529. doi: 10.1001/jama.282.16.1523. [DOI] [PubMed] [Google Scholar]
  • 6.Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summary. Expert Panel on the Identification, Evaluation, and Treatment of Overweight in Adults. Am J Clin Nutr. 1998 Oct;68(4):899–917. doi: 10.1093/ajcn/68.4.899. [DOI] [PubMed] [Google Scholar]
  • 7.Mokdad AH, Marks JS, Stroup DF, Gerberding JL. Actual causes of death in the United States, 2000. JAMA. 2004 Mar 10;291(10):1238–1245. doi: 10.1001/jama.291.10.1238. [DOI] [PubMed] [Google Scholar]
  • 8.Tessier DJ, Eagon JC. Surgical management of morbid obesity. Current problems in surgery. 2008 Feb;45(2):68–137. doi: 10.1067/j.cpsurg.2007.12.003. [DOI] [PubMed] [Google Scholar]
  • 9.Wolin KY, Carson K, Colditz GA. Obesity and cancer. The oncologist. 2010;15(6):556–565. doi: 10.1634/theoncologist.2009-0285. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Adams KF, Schatzkin A, Harris TB, et al. Overweight, obesity, and mortality in a large prospective cohort of persons 50 to 71 years old. N Engl J Med. 2006 Aug 24;355(8):763–778. doi: 10.1056/NEJMoa055643. [DOI] [PubMed] [Google Scholar]
  • 11.Calle EE, Thun MJ, Petrelli JM, Rodriguez C, Heath CW., Jr Body-mass index and mortality in a prospective cohort of U.S. adults. N Engl J Med. 1999 Oct 7;341(15):1097–1105. doi: 10.1056/NEJM199910073411501. [DOI] [PubMed] [Google Scholar]
  • 12.Flegal KM, Graubard BI, Williamson DF, Gail MH. Excess deaths associated with underweight, overweight, and obesity. JAMA. 2005 Apr 20;293(15):1861–1867. doi: 10.1001/jama.293.15.1861. [DOI] [PubMed] [Google Scholar]
  • 13.Flegal KM, Graubard BI, Williamson DF, Gail MH. Cause-specific excess deaths associated with underweight, overweight, and obesity. JAMA. 2007 Nov 7;298(17):2028–2037. doi: 10.1001/jama.298.17.2028. [DOI] [PubMed] [Google Scholar]
  • 14.CDC. [Accessed March 25, 2011]; http://www.cdc.gov/PDF/Frequently_Asked_Questions_About_Calculating_Obesity-Related_Risk.pdf.
  • 15.McTigue KM, Harris R, Hemphill B, et al. Screening and interventions for obesity in adults: summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2003 Dec 2;139(11):933–949. doi: 10.7326/0003-4819-139-11-200312020-00013. [DOI] [PubMed] [Google Scholar]
  • 16.Avenell A, Broom J, Brown TJ, et al. Systematic review of the long-term effects and economic consequences of treatments for obesity and implications for health improvement. Health Technol Assess. 2004 May;8(21):iii–iv. 1–182. doi: 10.3310/hta8210. [DOI] [PubMed] [Google Scholar]
  • 17.Chauhan V, Vaid M, Gupta M, Kalanuria A, Parashar A. Metabolic, renal, and nutritional consequences of bariatric surgery: implications for the clinician. South Med J. 2010 Aug;103(8):775–783. doi: 10.1097/SMJ.0b013e3181e6cc3f. quiz 784–775. [DOI] [PubMed] [Google Scholar]
  • 18.Lara MD, Kothari SN, Sugerman HJ. Surgical management of obesity: a review of the evidence relating to the health benefits and risks. Treat Endocrinol. 2005;4(1):55–64. doi: 10.2165/00024677-200504010-00006. [DOI] [PubMed] [Google Scholar]
  • 19.Ochner CN, Gibson C, Carnell S, Dambkowski C, Geliebter A. The neurohormonal regulation of energy intake in relation to bariatric surgery for obesity. Physiol Behav. 2010 Jul 14;100(5):549–559. doi: 10.1016/j.physbeh.2010.04.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Chang SH, Stoll CR, Colditz GA. Cost-effectiveness of bariatric surgery: should it be universally available? Maturitas. 2011 Jul;69(3):230–238. doi: 10.1016/j.maturitas.2011.04.007. [DOI] [PubMed] [Google Scholar]
  • 21.Christou NV, Sampalis JS, Liberman M, et al. Surgery decreases long-term mortality, morbidity, and health care use in morbidly obese patients. Ann Surg. 2004 Sep;240(3):416–423. doi: 10.1097/01.sla.0000137343.63376.19. discussion 423–414. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Marsk R, Naslund E, Freedman J, Tynelius P, Rasmussen F. Bariatric surgery reduces mortality in Swedish men. Br J Surg. 2010 Jun;97(6):877–883. doi: 10.1002/bjs.6985. [DOI] [PubMed] [Google Scholar]
  • 23.Matarasso A, Roslin MS, Kurian M. Bariatric surgery: an overview of obesity surgery. Plast Reconstr Surg. 2007 Apr 1;119(4):1357–1362. doi: 10.1097/01.prs.0000254785.31020.e6. [DOI] [PubMed] [Google Scholar]
  • 24.Bradley D, Conte C, Mittendorfer B, et al. Effects of gastric bypass and adjustable gastric banding on glucose homeostasis. Journal of Clinical Investigation. 2012:112. [Google Scholar]
  • 25.Buchwald H, Oien DM. Metabolic/bariatric surgery Worldwide 2008. Obes Surg. 2009 Dec;19(12):1605–1611. doi: 10.1007/s11695-009-0014-5. [DOI] [PubMed] [Google Scholar]
  • 26. [Accessed December, 12, 2012]; http://www.ama-assn.org/amednews/2012/04/23/bisa0423.htm.
  • 27.Buchwald H, Avidor Y, Braunwald E, et al. Bariatric surgery: a systematic review and meta-analysis. JAMA. 2004 Oct 13;292(14):1724–1737. doi: 10.1001/jama.292.14.1724. [DOI] [PubMed] [Google Scholar]
  • 28.Maggard MA, Shugarman LR, Suttorp M, et al. Meta-analysis: surgical treatment of obesity. Ann Intern Med. 2005 Apr 5;142(7):547–559. doi: 10.7326/0003-4819-142-7-200504050-00013. [DOI] [PubMed] [Google Scholar]
  • 29.Padwal R, Klarenbach S, Wiebe N, et al. Bariatric surgery: a systematic review and network meta-analysis of randomized trials. Obes Rev. 2011 Mar 28; doi: 10.1111/j.1467-789X.2011.00866.x. [DOI] [PubMed] [Google Scholar]
  • 30.Golder S, Loke YK, Bland M. Meta-analyses of adverse effects data derived from randomised controlled trials as compared to observational studies: methodological overview. PLoS medicine. 2011 May;8(5):e1001026. doi: 10.1371/journal.pmed.1001026. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Mosteller F, Colditz GA. Understanding research synthesis (meta-analysis) Annual review of public health. 1996;17:1–23. doi: 10.1146/annurev.pu.17.050196.000245. [DOI] [PubMed] [Google Scholar]
  • 32.Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med. 2009 Aug 18;151(4):W65–94. doi: 10.7326/0003-4819-151-4-200908180-00136. [DOI] [PubMed] [Google Scholar]
  • 33.Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA. 2000 Apr 19;283(15):2008–2012. doi: 10.1001/jama.283.15.2008. [DOI] [PubMed] [Google Scholar]
  • 34.Harris RP, Helfand M, Woolf SH, et al. Current methods of the US Preventive Services Task Force: a review of the process. Am J Prev Med. 2001 Apr;20(3 Suppl):21–35. doi: 10.1016/s0749-3797(01)00261-6. [DOI] [PubMed] [Google Scholar]
  • 35.Cho MK, Bero LA. The quality of drug studies published in symposium proceedings. Ann Intern Med. 1996 Mar 1;124(5):485–489. doi: 10.7326/0003-4819-124-5-199603010-00004. [DOI] [PubMed] [Google Scholar]
  • 36.Schulz KF, Altman DG, Moher D, Group C. CONSORT 2010 statement: updated guidelines for reporting parallel group randomized trials. Ann Intern Med. 2010 Jun 1;152(11):726–732. doi: 10.7326/0003-4819-152-11-201006010-00232. [DOI] [PubMed] [Google Scholar]
  • 37.Wolin KY, Yan Y, Colditz GA, Lee IM. Physical activity and colon cancer prevention: a meta-analysis. British journal of cancer. 2009 Feb 24;100(4):611–616. doi: 10.1038/sj.bjc.6604917. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Deitel M, Greenstein RJ. Recommendations for reporting weight loss. Obes Surg. 2003 Apr;13(2):159–160. doi: 10.1381/096089203764467117. [DOI] [PubMed] [Google Scholar]
  • 39.1983 metropolitan height and weight tables. Statistical bulletin. 1983 Jan-Jun;64(1):3–9. [PubMed] [Google Scholar]
  • 40.Smith TC, Spiegelhalter DJ, Thomas A. Bayesian approaches to random-effects meta-analysis: a comparative study. Stat Med. 1995 Dec 30;14(24):2685–2699. doi: 10.1002/sim.4780142408. [DOI] [PubMed] [Google Scholar]
  • 41.Warn DE, Thompson SG, Spiegelhalter DJ. Bayesian random effects meta-analysis of trials with binary outcomes: methods for the absolute risk difference and relative risk scales. Stat Med. 2002 Jun 15;21(11):1601–1623. doi: 10.1002/sim.1189. [DOI] [PubMed] [Google Scholar]
  • 42.Sweeting MJ, Sutton AJ, Lambert PC. What to add to nothing? Use and avoidance of continuity corrections in meta-analysis of sparse data. Stat Med. 2004 May 15;23(9):1351–1375. doi: 10.1002/sim.1761. [DOI] [PubMed] [Google Scholar]
  • 43.Sutton AJ, Cooper NJ, Lambert PC, Jones DR, Abrams KR, Sweeting MJ. Meta-analysis of rare and adverse event data. Expert review of pharmacoeconomics & outcomes research. 2002 Aug;2(4):367–379. doi: 10.1586/14737167.2.4.367. [DOI] [PubMed] [Google Scholar]
  • 44.Bhaumik DK, Amatya A, Normand SL, et al. Meta-Analysis of Rare Binary Adverse Event Data. Journal of the American Statistical Association. 2012;107(498):555–567. doi: 10.1080/01621459.2012.664484. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002 Jun 15;21(11):1539–1558. doi: 10.1002/sim.1186. [DOI] [PubMed] [Google Scholar]
  • 46.Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Bmj. 2003 Sep 6;327(7414):557–560. doi: 10.1136/bmj.327.7414.557. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Light RJ, Pillemer DB. Summing up: the science of reviewing research. Cambridge, Mass: Harvard University Press; 1984. [Google Scholar]
  • 48.Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj. 1997 Sep 13;315(7109):629–634. doi: 10.1136/bmj.315.7109.629. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Dakin HA, Welton NJ, Ades AE, Collins S, Orme M, Kelly S. Mixed treatment comparison of repeated measurements of a continuous endpoint: an example using topical treatments for primary open-angle glaucoma and ocular hypertension. Stat Med. 2011 Jul 5; doi: 10.1002/sim.4284. [DOI] [PubMed] [Google Scholar]
  • 50.Lu G, Ades AE, Sutton AJ, Cooper NJ, Briggs AH, Caldwell DM. Meta-analysis of mixed treatment comparisons at multiple follow-up times. Stat Med. 2007 Sep 10;26(20):3681–3699. doi: 10.1002/sim.2831. [DOI] [PubMed] [Google Scholar]
  • 51.Sjostrom L, Lindroos AK, Peltonen M, et al. Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med. 2004 Dec 23;351(26):2683–2693. doi: 10.1056/NEJMoa035622. [DOI] [PubMed] [Google Scholar]
  • 52.Sjostrom L. Bariatric surgery and reduction in morbidity and mortality: experiences from the SOS study. Int J Obes (Lond) 2008 Dec;32(Suppl 7):S93–97. doi: 10.1038/ijo.2008.244. [DOI] [PubMed] [Google Scholar]
  • 53.Avsar FM, Ozel H, Topaloglu S, et al. Improvement of vertical banded gastroplasty by strict dietary management. Obes Surg. 2004 Feb;14(2):265–270. doi: 10.1381/096089204322857681. [DOI] [PubMed] [Google Scholar]
  • 54.Strain GW, Gagner M, Pomp A, et al. Comparison of weight loss and body composition changes with four surgical procedures. Surg Obes Relat Dis. 2009 Sep-Oct;5(5):582–587. doi: 10.1016/j.soard.2009.04.001. [DOI] [PubMed] [Google Scholar]
  • 55.Buchwald H, Estok R, Fahrbach K, et al. Weight and type 2 diabetes after bariatric surgery: systematic review and meta-analysis. Am J Med. 2009 Mar;122(3):248–256. e245. doi: 10.1016/j.amjmed.2008.09.041. [DOI] [PubMed] [Google Scholar]
  • 56.Hutter MM, Schirmer BD, Jones DB, et al. First report from the American College of Surgeons Bariatric Surgery Center Network: laparoscopic sleeve gastrectomy has morbidity and effectiveness positioned between the band and the bypass. Ann Surg. 2011 Sep;254(3):410–420. doi: 10.1097/SLA.0b013e31822c9dac. discussion 420–412. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Miller JN, Colditz GA, Mosteller F. How study design affects outcomes in comparisons of therapy. II: Surgical. Stat Med. 1989 Apr;8(4):455–466. doi: 10.1002/sim.4780080409. [DOI] [PubMed] [Google Scholar]
  • 58.Colditz GA, Miller JN, Mosteller F. How study design affects outcomes in comparisons of therapy. I: Medical. Stat Med. 1989 Apr;8(4):441–454. doi: 10.1002/sim.4780080408. [DOI] [PubMed] [Google Scholar]
  • 59.Benson K, Hartz AJ. A comparison of observational studies and randomized, controlled trials. N Engl J Med. 2000 Jun 22;342(25):1878–1886. doi: 10.1056/NEJM200006223422506. [DOI] [PubMed] [Google Scholar]
  • 60.Varela JE. Laparoscopic sleeve gastrectomy versus laparoscopic adjustable gastric banding for the treatment severe obesity in high risk patients. JSLS: Journal of the Society of Laparoendoscopic Surgeons/Society of Laparoendoscopic Surgeons. 2011 Oct-Dec;15(4):486–491. doi: 10.4293/108680811X13176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Nguyen NT, Slone JA, Nguyen XM, Hartman JS, Hoyt DB. A prospective randomized trial of laparoscopic gastric bypass versus laparoscopic adjustable gastric banding for the treatment of morbid obesity: outcomes, quality of life, and costs. Ann Surg. 2009 Oct;250(4):631–641. doi: 10.1097/SLA.0b013e3181b92480. [DOI] [PubMed] [Google Scholar]
  • 62.Angrisani L, Lorenzo M, Borrelli V. Laparoscopic adjustable gastric banding versus Roux-en-Y gastric bypass: 5-year results of a prospective randomized trial. Surg Obes Relat Dis. 2007 Mar-Apr;3(2):127–132. doi: 10.1016/j.soard.2006.12.005. discussion 132–123. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix
NIHMS494690-supplement-Appendix.docx (327.1KB, docx)

RESOURCES