Kidney transplantation is the most cost-effective therapy for a substantial portion of patients with end-stage kidney disease (1, 2). Compared with patients on the waiting list, transplant recipients present lower mortality and reduced risk of cardiovascular events (3, 4). Kidney graft survival and patient survival have improved significantly in the last decade (5, 6); however, some patients and graft characteristics are associated with poor outcomes after transplantation (7) including body mass index (BMI) (8).
In patients on renal replacement therapy (RRT) with hemodialysis, the “obesity paradox” was proposed because of the better survival for patients with higher BMI (9, 10). However, because the studies were performed in prevalent populations of patients undergoing dialysis, one cannot exclude potential survivor bias (11). Recently, it has been shown that among younger incident dialysis patients (<65 years), obesity is a risk factor for mortality (12). Furthermore, in renal transplant recipients, the impact of obesity is still a controversial issue.
Previous data have linked obesity to poor outcomes in kidney transplant recipients. Among them, a higher incidence of delayed graft function (DGF), acute rejection, and lower patient and graft survival have been described in the medical literature (13–16). For these reasons, many transplantation centers discourage transplantation for obese patients. However, the evidence to that suggests that obesity as a risk factor for poor outcomes in kidney transplantation is not robust, and in many studies, differences between obese and nonobese recipients on these outcomes were not found (17–19).
The prevalence of obesity in patients on RRT continues to increase, and it is perhaps now even more important to identify the risks of kidney transplantation on these patients. To better understand the association between obesity and kidney transplantation outcomes, we performed a systematic review with meta-analysis of observational studies that included obese and nonobese recipients of a kidney transplant and appropriately reported follow-up and outcomes.
Literature Search Results and Study Characteristics
We identified 1,973 potentially relevant citations from an electronic database search and 2 from a manual search (Figure S1, SDC, http://links.lww.com/TP/B21). Of these, 1,665 were excluded on the basis of title and abstract, leaving 112 studies for full-text evaluation. Twenty-one studies (17–37) fulfilled inclusion criteria, providing data on 9,296 study subjects.
The characteristics of the studies are presented in Table 1. The articles were published from 1990 to 2013 and had large variability in sample size. In addition to the variables shown in Table 1, other population characteristics were investigated but were not accessible in most of the studies. Induction therapy were presented in five studies (17, 21, 29, 33, 34); panel-reactive antibodies in four (17, 18, 32, 36); dialysis duration (25, 27), tacrolimus use (17, 18), and previous dyslipidemia (25, 34) in two. Smoking status was not reported by any study. Primary kidney disease was reported differently between articles (17, 22, 24, 25, 27, 32, 34).
According to the Newcastle-Ottawa Quality Assessment Scale for cohort studies, 12 studies were considered with moderate quality and 9 were considered to be of high quality (see quality scores for each domain in Table S1, SDC,http://links.lww.com/TP/B21). Because all studies demonstrated direct evidence, no statistical heterogeneity of results, narrow 95% confidence intervals (CIs), and no publication bias, the quality level of evidence was not decreased; however, because this systematic review includes only observational studies, the overall GRADE (Grading of Recommendations Assessment, Development and Evaluation) quality rating was considered low.
Obesity and Posttransplantation Outcomes
Delayed Graft Function
This outcome was assessed by 13 studies, including 4,419 patients. Pretransplantation obesity was associated with increased risk of DGF (relative risk [RR], 1.41; 95% CI, 1.26–1.57; I2=8%; Pheterogeneity=0.36) (Fig. 1A). After sensitivity analyses, this result remained unchanged.
Eleven studies evaluated acute rejection episodes, accounting for 3,307 patients. No effect of pretransplantation obesity was observed (RR, 0.95; 95% CI, 0.82–1.11; I2=18%; Pheterogeneity=0.27) (Fig. 1B). This result remained unchanged after sensitivity analyses.
One-year graft survival was assessed by 15 studies, including 8,214 patients. An association between obesity and graft loss at 1 year after transplantation (RR, 1.31; 95% CI, 1.11–1.55; I2=0%; Pheterogeneity=0.75) was found. By univariate meta-regression, the year of publication influenced this association (P=0.047; adjusted R2=100%). Then, meta-analyses were rerun stratifying studies by those published before or after year 2003 (Fig. 2A). Only studies published before 2003 (17, 19, 23, 27, 28, 32, 36) presented this association (RR, 1.51; 95% CI, 1.19–1.91; I2=0%; Pheterogeneity=0.85). The association was not found (RR, 1.16; 95% CI, 0.91–1.48; I2=0%; Pheterogeneity=0.69) in the analysis of recently published studies (18, 20–22, 25, 29, 30, 33).
Five-year graft survival was assessed by 13 studies, including 7,284 patients, and obesity was associated with graft loss at 5 years (RR, 1.21; 95% CI, 1.08–1.34; I2=38%; Pheterogeneity=0.08). Heterogeneity was explained by the year of publication, as identified by univariate meta-regression analysis (P=0.009; adjusted R2=100%). Subgroup analysis, stratifying studies by those published before or after year 2003, presented results similar to those observed at 1 year after transplantation (Fig. 2B). Studies published before 2003 (17, 19, 23, 26, 27, 32, 36) showed an association with graft loss at 5 years (RR, 1.39; 95% CI, 1.22–1.60; I2=10%; Pheterogeneity=0.36), but no association was found in the analysis of recent studies (18, 20, 22, 25, 30, 33) (RR, 0.99; 95% CI, 0.83–1.19; I2=0%; Pheterogeneity=0.62).
Death by Cardiovascular Disease
Five studies assessed death by cardiovascular disease (CVD) according to the presence of pretransplantation obesity, including 2,198 recipients. Most studies included in this analysis were published before 2003 (17, 19, 26, 32). An association between obesity and death by CVD (RR, 2.07; 95% CI, 1.17–3.64; I2=0%; Pheterogeneity=0.59) was found and is shown in Figure 3. After sensitivity analyses, this result remained unchanged.
One-year patient survival was assessed by 12 studies, including 6,750 patients. Obesity was not associated with death within the first posttransplantation year (RR, 1.30; 95% CI, 1.00–1.69; I2=0%; Pheterogeneity=0.90). Univariate meta-regression showed that the year of publication significantly influenced this outcome (P=0.027; adjusted R2=100%). Subgroup analysis according to the year of the study publication (before or after 2003) is shown in Figure 4(A). An association of obesity with death at 1 year after transplantation was observed among studies published before 2003 (17, 19, 27, 28, 32) (RR, 1.65; 95% CI, 1.10–2.49; I2=0%; Pheterogeneity=0.54); however, no association was found in the analysis of recent studies (18, 20–22, 25, 29, 33) (RR, 1.10; 95% CI, 0.78–1.56; I2=0%; Pheterogeneity=1.00).
Five-year patient survival was assessed by 10 studies, including 5,820 recipients. Obesity was associated with death at 5 years after transplantation (RR, 1.39; 95% CI, 1.19–1.63; I2=70%; Pheterogeneity=0.0004). Heterogeneity was evaluated by univariate meta-regression, and the year of publication was significant (P=0.031; adjusted R2=44%). Subgroup analysis, stratifying studies by year of publication (before or after 2003) (Fig. 4B), showed that studies published before 2003 (17, 19, 26, 27, 32) presented an association between obesity and death at 5 years after transplantation (RR, 1.96; 95% CI, 1.55–2.48; I2=73%; Pheterogeneity=0.005). No association was found in the analysis of studies published after 2003 (18, 20, 22, 25, 33) (RR, 1.06; 95% CI, 0.85–1.31; I2=18%; Pheterogeneity=0.30).
In sensitivity analysis using random effects, all results remained unchanged.
Contour-enhanced funnel plots and the Egger regression test revealed no publication bias on the assessed outcomes (DGF, P=0.120; acute rejection, P=0.292; graft loss at 1 year after transplantation, P=0.417; graft loss at 5 years after transplantation, P=0.788; death by CVD, P=0.793; death at 1 year after transplantation, P=0.314; and death at 5 years after transplantation, P=0.520). The funnel plot for each meta-analysis is available in Figure S2, SDC,http://links.lww.com/TP/B21.
The analysis showed that pretransplantation obesity is associated with DGF. The impact of obesity on graft loss, death by CVD, and all-cause mortality depends on the era of transplantation. No association was found between obesity and acute rejection.
The association of obesity with DGF may be related to immunologic and nonimmunologic factors. Obesity is associated with a proinflammatory environment, with elevated levels of cytokines and chemokines that can mediate the immunologic responses and facilitate DGF (38). Moreover, technical difficulties encountered in performing a transplantation in an obese recipient may lead to a more pronounced ischemia-reperfusion injury and consequently an increased risk of DGF (39).
The year of study publication explained heterogeneity in the meta-analyses of graft loss and death at 5 years after transplantation. Furthermore, the analyses of 1-year graft and patient survival also presented relevant results when stratified by this variable. Studies published before 2003 revealed an association of obesity with graft loss and death, whereas recent studies did not. The 2003 year of publication was chosen based on the year when the patients of the studies were transplanted. Studies published before 2003 (17, 19, 23, 26–28, 32, 36) evaluated patients who received a kidney graft before year 2000. Analysis of death by CVD included four studies published before 2003 (17, 19, 26, 32) and was associated with obesity. Sensitivity analysis did not change this result, even after excluding the only study published after the year 2003 (25). These findings suggest that, up to year 2000, obesity was a risk factor for graft loss, death by CVD, and all-cause mortality after kidney transplantation. However, after year 2000, obesity seems not to influence these outcomes.
Large database studies (excluded from our analysis) report that obesity is associated with graft (14–16) and patient (15, 16) survival. Although these studies were published after 2003, patients were transplanted before year 2000, giving support to our findings. A recently published narrative review (40) reported poor outcomes associated with higher BMI. The search did not include a systematic review followed by a meta-analysis; in consequence, the analysis did not allow an adequate pooling of the results. In addition, some relevant studies were not included.
It is now recognized that obesity influences the immune system. Cellular and humoral components sense the physiologic changes that occur with obesity and may be activated (41). Inflammation, which is associated with obesity, seems to play a role on this process (38, 41, 42).
Immunosuppressive therapy has changed substantially in the modern era of kidney transplantation. Antibody induction therapy is largely used, tacrolimus has replaced cyclosporine as the most used calcineurin inhibitor, and mycophenolic acid derivatives largely replaced azathioprine (43). Rapid discontinuation of steroids or low-dose protocols are also currently used by most programs (44,45). These changes in the use of immunosuppressive agents contributed to the better survivals currently observed (5, 46).
Recent guidelines recommend that obese patients should be rigorously screened for CVD, and each case should be considered individually (47, 48). However, obesity should not on its own preclude a patient from being considered for kidney transplantation (47–49). Two guidelines report that individuals with a BMI greater than 40 kg/m2 are less likely to benefit on kidney transplantation (47, 48). Furthermore, supervised weight loss therapy is recommended, targeting a BMI of less than 30 kg/m2 (49). The European Best Practice Guidelines did not provide recommendations regarding obesity and renal transplantation (50). Two guidelines refer to the association between DGF with obesity (47, 49), supporting the present results. Guidelines also suggest an impact of obesity on reduced graft survival and patient survival; however, the supporting studies were made before year 2000 and may not reflect the current practice (47–49).
In the present meta-analysis, it was not possible to evaluate the effects of a BMI greater than 40 kg/m2 on outcomes after kidney transplantation because only one study (23) reported this BMI stratification. The analysis of the effect of BMI equal to greater than 35 kg/m2 was also not applied because only two studies (18, 37) reported the number of patients in this group. Nevertheless, a meta-regression analysis with the mean BMI revealed no significant results (data not shown). Supporting our findings, a large recent study showed that morbid obesity is not independently associated with graft failure or patient mortality in 3 years after transplantation (51).
The reasons for the lack of influence of obesity in more recent cohorts are not entirely clear. It is conceivable that it can be explained by the advances in immunosuppressive therapy along with the improvement in general medical practice exemplified by better control of comorbidities such as lipid disorders, hypertension, diabetes, cardiac conditions, and others and the gain of experience in kidney transplantation.
We found that pretransplantation obesity is associated with DGF; however; graft survival and patient survival are not reduced for obese patients currently transplanted. In the literature available, data suggest that obese patients with end-stage renal disease have better survival after kidney transplantation compared with remaining on dialysis (52). The evidence comes mainly from a large database study and from a single-center study (53, 54). In the first one, obese transplant recipients were compared with wait-listed obese patients undergoing dialysis, and a much lower risk of mortality was found in the transplant cohorts, with living or deceased donors. The benefit however did not apply to transplant recipients with a BMI equal to or greater than 41 kg/m2 (53). In the single-center study, transplant recipients displayed a better survival compared with an external, nonconcurrent comparison group (54). Therefore, obesity per se must not be considered a contraindication for renal transplantation.
Evidently, this systematic review and meta-analysis has limitations. Not all studies report their population characteristics limiting the meta-regression analyses, extremes of obesity are not represented, complications such as wound infection and dehiscence are not evaluated, and there might be some small imprecision on manually extracted data from graft and patient survival curves. Moreover, some outcomes here evaluated are not independently related. However, the strategy of data analysis in this study does not allow their independent evaluation.
Observational studies can not result in high-quality meta-analysis. For this reason, our study is to be considered low quality by GRADE guidelines (55). However, because of the straightforward characteristics of this kind of observations, we believe that observational cohort designs are appropriate to recognize the effects of obesity on kidney transplantation outcomes. Moreover, all studies included demonstrated moderate or high quality by the Newcastle-Ottawa Quality Assessment Scale (56).
In conclusion, obese patients have increased risk for DGF. In the past years, obesity was a risk factor for graft loss, death by CVD, and all-cause mortality. However, for the obese patient more recently transplanted, the graft survival and patient survival are similar to those of the nonobese patient. Obesity should not on its own preclude a patient from being considered for kidney transplantation. Other characteristics, such as age, cardiovascular status, diabetes mellitus, other comorbidities, quality of dialysis, and the desire of the patient, must be considered in this complex equation.
MATERIALS AND METHODS
Search Strategy and Study Selection
All relevant articles, regardless of language, were identified using Medical Subject Heading (MeSH) terms by searching MEDLINE (accessed by PubMed), EMBASE, Cochrane Library, and gray literature up to August 6, 2013. The MEDLINE search strategy was as follows: (“Obesity”[MeSH] OR “Obesity, Abdominal”[MeSH] OR “Overweight”[MeSH] OR “Weight Gain”[MeSH]) AND (“Transplantation”[MeSH] OR “Kidney Transplantation”[MeSH] OR “Transplantation, Heterotopic”[MeSH]). All potentially eligible studies were considered for review. When data were not available, authors were contacted. This systematic review and meta-analysis is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (57).
Studies that compared obese and nonobese patients (obesity defined by BMI≥30 kg/m2 as recommended by the World Health Organization (58)) older than 18 years who underwent kidney transplantation were included in the systematic review. Eligible studies also had to have evaluated one of the following outcomes: DGF (defined by the requirement for dialysis in the first posttransplantation week), acute rejection episode, graft or patient survival at 1 or 5 years after transplantation, or death by CVD.
Studies that presented replicated data and pediatric transplants were excluded. Studies analyzing database population were also excluded because patients evaluated in these studies could have been already included in the original publication.
Titles and abstracts of retrieved articles were independently evaluated by two investigators (B.B.N. and N.K.O.F.). Reviewers were not blinded to the authors, institutions, or article journals. Abstracts that did not provide enough information regarding the inclusion and exclusion criteria were retrieved for full-text evaluation. Reviewers independently evaluated full-text articles and determined study eligibility. The same investigators independently conducted data extraction. Disagreements were resolved by consensus, and if disagreement persisted, a third reviewer (G.C.S.) extracted the data.
Data extraction included the following characteristics of the studies: author’s name, year of publication, number of patients included, follow-up length, and population characteristics, including age, sex, ethnicity, smoking status, primary kidney disease, time on RRT before transplantation, donor type (living or deceased), retransplantation, immunosuppressive therapy, panel reactive antibodies and prevalence of previous CVD, diabetes mellitus, hypertension, and dyslipidemia. Outcomes were identified in the studies’ text or tables. Data regarding death and graft loss was also extracted from survival curves when necessary.
The Newcastle-Ottawa Quality Assessment Scale for cohort studies was applied to recognize risk of bias (56). For assessment of comparability, it was observed whether study groups were controlled by the following variables: age, sex, ethnicity, and donor type. A total score of 5 or less was considered low, 6 or 7 was considered moderate, and 8 or 9 was deemed high quality. Two reviewers (B.B.N. and N.K.O.F.) independently evaluated studies’ quality assessment. Disagreements were resolved by consensus or by a third reviewer (G.C.S.). The quality of evidence for each outcome evaluated in this meta-analysis was accessed by GRADE guidelines, and was based on the following characteristics: limitations in the study design and implementation, indirectness of evidence, unexplained heterogeneity or inconsistency of results, imprecision of results, and probability of publication bias (55).
The RR of posttransplantation outcomes was examined in obese kidney recipients compared to nonobese recipients using the REVIEW MANAGER software version 5.1 (REVIEW MANAGER, REVMAN, Copenhagen, Denmark: The Nordic Cochrane Centre, The Cochrane Collaboration 2012; available at http://ims.cochrane.org/revman/download). Calculations were performed using the Mantel-Haenszel equation. Heterogeneity was examined using the Cochran Q Test with a threshold P value of 0.1 considered statistically significant, and the inconsistency I2 test was applied, with values greater than 50% considered indicative of high heterogeneity. The RR with 95% CI was calculated using the fixed effects model, and the random effect model was used as part of sensitivity analysis.
Heterogeneity between studies was explored using three strategies. First, meta-regression analyses were performed to recognize variables that influenced the association of obesity with posttransplantation outcomes. A threshold P value of 0.05 was considered statistically significant in meta-regression analyses. Second, subgroups analyses were performed with the variables found to be associated with the heterogeneity in the meta-regression analysis. Third, sensitivity analyses were applied, and meta-analyses were rerun, removing each study at a time to check if a particular study was explaining heterogeneity. In the meta-analysis where results presented no association, meta-regression and sensitivity analyses were performed. Publication bias was assessed using funnel plot analysis, with asymmetry evaluated by Begg and Egger tests. A significant publication bias was considered if the P value was less than 0.1. Meta-regression and funnel plot analyses were conducted using Stata software version 11.0 (Stata Inc., College Station, TX).
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