Corticosteroids have been an important part of maintenance immunosuppression protocols since the early 1960s, when they were initially used to supplement the immunosuppressive properties of azathioprine (AZA) (1). Although they are undoubtedly effective at preventing rejection in transplant recipients, the side effect profile of steroids has resulted in attempts first to reduce the dose of steroids and second with the advent of newer more potent immunosuppression to avoid or withdraw steroids to improve long-term safety outcomes.
Of particular interest are the effects of steroids on lipid and glucose metabolism and blood pressure regulation. Death with a functioning graft is an important cause of graft loss after renal transplantation, accounting for more than 40% of graft losses in one registry analysis (2). The leading cause of death with a functioning graft in this analysis of renal transplant recipients was cardiovascular disease, and therefore, there is a strong case for steroid minimization regimens that attempt to reduce long-term cardiovascular risk. Furthermore, hyperlipidemia, hypertension, and diabetes have all been identified as factors directly implicated in the pathogenesis of chronic allograft nephropathy (3, 4). However, any advantage seen in cardiovascular risk must be balanced against the potential reduction in immunosuppression and the risk of acute rejection (AR), which in turn is linked to graft loss and dysfunction that would make withdrawal or avoidance of steroids less attractive.
Another aspect of the many complications of steroid therapy is the potential increase in healthcare costs that they incur. An analysis by Veenstra et al. in the United States has demonstrated that the 10-year cost of treating steroid-related side-effects after transplantation is an additional US $5300 per patient. The bulk of this additional cost is in treating hypertension ($1878), closely followed by posttransplant diabetes mellitus ($1794) (5).
A number of trials have investigated the avoidance or withdrawal of steroids alongside various maintenance immunosuppression regimens over a number of years, with variable results. One of the main problems with such trials is that they rarely have the statistical power to identify differences in uncommon outcomes, such as graft loss and patient death, between the arms. A number of authors have attempted to address this issue by performing meta-analyses of trials of steroid avoidance or withdrawal (SAW) in renal transplant recipients (6–11). These analyses suggest that the risk of AR is increased significantly with steroid withdrawal or avoidance, although the impact on long-term graft function and survival is less clear with only one study demonstrating increased graft failure with steroid withdrawal (7). Only one study with restrictive inclusion criteria investigated cardiovascular risk factors after steroid withdrawal, demonstrating significantly lower serum cholesterol in the withdrawal group (8, 9).
Further conflicting evidence has been provided from nonrandomized registry data. In a retrospective analysis of data from the Collaborative Transplant Study (CTS), Opelz (12) suggested that graft survival was significantly improved during 5-years in renal transplant recipients in whom steroids were withdrawn from protocols including cyclosporine with or without AZA. This prompted a prospective study in which renal and cardiac transplant recipients were withdrawn from steroids beyond 6-months after transplantation and compared with matched controls from the CTS registry (13). This study again demonstrated an improvement in graft survival in the steroid withdrawal patients at 7 years (81.9% vs. 75.3%, P=0.0001), along with an improvement in patient survival at the same time point (88.8% vs. 84.3%, P=0.0016). In contrast to the meta-analyses described earlier, rates of AR and graft dysfunction did not differ between groups. Some evidence was found for an improvement in cardiovascular risk factors after steroid withdrawal.
Clearly, there is still considerable controversy regarding the risks and benefits of withdrawing steroids from maintenance steroid regimens. A number of more recent studies have provided further information and some of the studies included in previous analyses have reported long-term follow-up data. This study will comprise a comprehensive systematic review and meta-analysis of steroid avoidance and withdrawal protocols across all maintenance immunosuppression regimens in renal transplant recipients, with a particular emphasis on investigating the impact on long-term graft function and survival and with the impact on cardiovascular risk factors.
Literature Search and Inclusion Criteria
A systematic literature search was performed using OVID MEDLINE and EMBASE, the Cochrane Central Registry of Controlled Trials, the Transplant Library from the Centre for Evidence in Transplantation (which includes hand-searched journals and conference proceedings), and trial registries (clinicaltrials.gov, the national research register, and current controlled trials). To avoid missing potentially relevant references, searches were performed using only Mesh keywords and free-text aliases for corticosteroids in each database, without limiting searches further using terms for sparing and avoidance. No date or language limits were applied. References of included studies and previous relevant reviews were scanned for potentially relevant studies that had been missed in the literature searching. The final date for literature searches was 18th January 2008. A limited updated search of the Transplant Library was performed from January 2008 to 18th August 2009 to identify any further studies published during preparation of this article.
Inclusion criteria specified any prospective randomized or pseudorandomized study in adult renal transplant recipients, in which outcomes in patients receiving maintenance steroids from the time of transplantation were compared with a cohort in which steroids were withdrawn at any time posttransplant or were avoided. Those studies investigating nonrenal transplants and pediatric recipients are considered elsewhere (14). Studies in which steroids were used for other conditions were excluded. Studies in which steroid doses were minimized, but not withdrawn, were also excluded.
The primary outcome in this analysis was the incidence of AR. Biopsy-proven AR was used for analysis where reported, otherwise the study author's definition of AR was accepted. Secondary outcomes were patient and graft survival, hypertension, diabetes, hypercholesterolemia, infection, malignancy, cataracts, and bone complications.
Studies are referred to throughout this article by the first author and year of the first peer-reviewed publication from that study. In the absence of any peer-reviewed publications, the first author and year of the first published abstract is used. Demographic, quality, and outcome data were extracted from the included studies into a custom-designed online database by the lead author (S.R.K.). The quality of the extracted data was confirmed by double checking by the second author (P.J.M.). Disagreements were resolved by discussion. There was also continuous cross-checking of previous entries during the data analysis.
Quality was assessed both by means of the Jadad score (a score of 3 or greater is considered good quality) and a description of allocation concealment and analysis based on intention-to-treat (15). When assessing study quality, all reports from a trial are assessed and the information pooled.
Summary effects were calculated in each study for outcomes using the meta and rmeta packages for the R statistical analysis language (16). For binary outcomes, the relative risk (RR) was used as a summary statistic, with the weighted mean difference (WMD) used for continuous outcomes. For survival outcomes, the hazard ratio (HR) was used. All summary effects are presented with a 95% confidence interval. If an outcome is reported at more than one time point for a single study, the most recent follow-up data are used.
Meta-analysis was performed using the same statistical software. Heterogeneity was quantified using the I2 test, which describes the percentage of total variation across the studies that is due to heterogeneity rather than chance (17). In the absence of heterogeneity, studies were combined using a Mantel–Haenszel fixed effects meta-analysis. If visual inspection of the forest plot or a high I2 value suggested heterogeneity, potential causes were explored using subgroup analyses, mixed-effects models, funnel plots (to search for evidence of publication bias), and by looking for methodological differences between the studies. If no explanation could be found, a DerSimonian and Laird random effects meta-analysis was performed.
One study was identified with three arms—steroid avoidance, steroid withdrawal, and steroid maintenance (18–24). In subgroup analyses by withdrawal time, the control group (steroid maintenance) was split evenly for comparison with the withdrawal and avoidance groups to prevent duplication of patients in the overall analysis.
For the analysis of patient and graft survival data, the HR was used as it takes into account those patients who were lost to follow-up as well as the time to patient or graft loss. Unfortunately, few articles in transplantation report HRs for survival outcomes. Therefore, the methods of Parmar et al. (25) were used to estimate the HR from the reported data.
For a number of trials, data regarding continuous outcomes were poorly reported. Unless there was evidence of a non-normal distribution of results (skewed range), the median was taken as an estimate of the mean where the latter was not reported. The most common problem was the absence of a standard deviation or standard error. If a range and number of patients was reported, the methods of Walter and Yao (26) were used to estimate the standard deviation. Otherwise, a pooled standard deviation was calculated for all similar studies in the current meta-analysis and applied to studies with missing values (27). A sensitivity analysis was performed with and without studies requiring estimated standard deviations to assess their impact.
The time of steroid withdrawal after transplantation was regarded as likely to be an important factor in the outcome of steroid withdrawal protocols, and so a number of subgroups were defined accordingly:
- Avoidance: No steroid induction or maintenance steroids given (but allowable for treatment of rejection).
- Induction: 7 days or less of steroid therapy (includes single intraoperative steroid bolus).
- Early withdrawal: Withdrawal of steroids from 8 days to 12 months after transplantation.
- Late withdrawal: Withdrawal of steroids at any time from 12 months posttransplantation.
Another possible factor influencing outcome was the concomitant maintenance immunosuppression and the use of antibody induction therapy, and thus subgroup analyses were planned accordingly. Subgroups were compared using the interaction method described by Altman and Bland (28), with a significance level of P less than 0.05.
To further investigate the role of these potentially interacting factors, in particular when residual unexplained heterogeneity remained, attempts to fit a mixed-effects model were made using the MiMa function for the R language (29). This model allows linear (e.g., withdrawal time) and binary (e.g., presence of intention-to-treat analysis, use of antibody induction) moderator variables to be incorporated into a random-effects model. This then allows the amount of residual heterogeneity remaining (after accounting for the amount expected from the moderator variables) to be calculated (the QE statistic), along with the probability that at least one of the moderator variables significantly influences the effect sizes (the QME statistic). The P values for the individual moderator variables can also be calculated. This model has the advantages that linear variables such as withdrawal time can be included in their original form, rather than arbitrarily dividing studies into subgroups, and allows the effects of more than one variable to be analyzed in the same model.
Initial literature searches identified 10,997 references across all databases (OVID MEDLINE, 2614; OVID EMBASE, 5569; Cochrane Central Registry, 1751; and Transplant library, 1063). After removal of duplicates, this number was reduced to 7073 articles (Fig. 1). After exclusion on the basis of titles and abstracts, 497 papers were retrieved for full-text review. A further 13 potentially relevant trials were identified from the trial registries, and authors contacted for further information regarding the fate of the trials. Authors of studies only reported as abstracts with no full publication were also contacted for further information. The limited extended search to August 2009 identified a further two relevant publications—both articles providing long-term follow-up of previously identified studies (30, 31).
One hundred nineteen publications from 34 studies met the inclusion criteria in full. These included a total of 5637 patients. Details of the studies, including concomitant immunosuppression, time of steroid withdrawal, and quality data are shown in Table 1.
In the study by Kumar et al. (32), randomization was ceased early and a steroid withdrawal protocol adopted in all patients after review of interim results. Only reports from the randomized patients before study cessation are included in this review.
The methodological quality of the randomized controlled trials in this meta-analysis ranged from poor to good. Only 15 of the 34 studies (44%) achieved a Jadad score of 3 or greater, 15 studies (44%) reported an intention-to-treat analysis and 13 (38%) reported an adequate method of allocation concealment (Table 1).
Thirty-one studies (4626 patients) reported the incidence of AR, although two reported no events in either group and therefore had no weight in analysis (120, 123). Definitions of rejection varied, the majority (19 of 29, 66%) reported incidence of biopsy-proven AR, with the remainder reporting clinically defined AR (3 of 29, 10%) or giving no definition (7 of 20, 24%). Overall, the steroid avoidance and withdrawal regimens increased the risk of AR over controls (random effects analysis, RR 1.56, 95% confidence interval [CI] 1.31–1.87, P<0.0001; Fig. 2). Heterogeneity was high (I2=54.7%). Tests for interaction between subgroups and mixed-effects analysis incorporating withdrawal time as a linear moderator variable suggest that little of this heterogeneity results from different times of steroid withdrawal: the effect of withdrawal time on effect size was not significant (P=0.60), and residual heterogeneity was significant (P=0.0004). Subgroup analyses also demonstrate that the type of calcineurin inhibitor, antiproliferative agent, or the use or type of antibody induction do not explain the heterogeneity seen between the studies, nor significantly affect the RR of AR with steroid withdrawal (data not shown).
In an attempt to explain the residual heterogeneity, an analysis was performed with just the high-quality studies (see Table 1). Random effects meta-analysis gives an RR of 1.68 (14 studies, 3102 patients, CI 1.30–2.17, P=0.001). Heterogeneity is actually increased, suggesting that study quality does not explain this finding (I2=65.7%). The funnel plot is grossly symmetrical, suggesting that there is no publication bias.
Incidence of corticosteroid-resistant AR was reported in 13 studies (2797 patients). Of these, three studies reported no events in either arm (81, 94, 130) and therefore held no weight in meta-analysis. Overall risk of steroid-resistant AR did not differ significantly between the two groups (fixed effects, RR 0.95, CI 0.70–1.30, P=0.75, I2=0%). Asymmetry of the funnel plot demonstrates the possibility of some publication bias in favor of studies reporting a reduction in risk with avoidance/withdrawal.
Patient and Graft Survival
Twenty-nine studies reported patient survival data, but two (32, 60) reported insufficient data for estimation of the HR, and four reported no deaths in either group (92, 108, 123, 130). The overall HR for death was 0.82 (4650 patients, fixed effects, CI 0.61–1.11, P=0.2) with minimal heterogeneity (I2=0%). Time of withdrawal did not have an effect on patient survival after steroid withdrawal or avoidance. No difference in outcome was observed when only the high-quality studies were included in the analysis (13 studies, 3507 patients, HR 0.79, CI 0.56–1.11, P=0.18, I2=0%). Funnel plot demonstrated no obvious asymmetry.
Graft loss including death with a functioning graft was reported in 27 studies, although three studies reported insufficient data to enable HR estimation (60, 63, 130) and two reported no events in either group (92, 123). The overall HR for graft loss including death with a functioning graft is 0.99 (22 studies, 3790 patients, fixed effects, CI 0.80–1.22, P=0.93, I2=0%). Again, the funnel plot is grossly symmetrical.
Twenty-seven studies reported data regarding death-censored graft loss (excluding death with a functioning graft). Five of these studies reported no graft losses in either arm (73, 81, 92, 123, 142) and so had no weight in the meta-analysis. Two studies reported insufficient data to allow estimation of the HR (63, 130). Overall, no significant difference in death-censored graft loss was seen between maintenance and withdrawal or avoidance groups (20 studies, 4414 patients, fixed effects, HR 1.19, CI 0.92–1.54, P=0.19). No significant heterogeneity was observed (I2=0%). When only high-quality studies are included in the analysis, there is a trend toward an increased hazard of graft loss with SAW, but this remains nonsignificant (fixed effects, 10 studies, HR 1.31, CI 0.98–1.77, P=0.07, I2=0%). There is a suggestion of publication bias in the funnel plot, with an over-emphasis on studies reporting lower HRs. Therefore, the true hazard from withdrawal or avoidance may be higher than that estimated by the present meta-analysis.
No significant interaction is seen between time of withdrawal or concomitant immunosuppression and hazard for patient death or graft loss.
Serum creatinine was reported as an outcome in 26 studies. Where enough data were available, a pooled SD for all studies reporting withdrawal of steroids in the same time period was used for those studies not reporting a measure of variance. However, only one study in the steroid avoidance group (50) reported a standard deviation, and so a pooled estimate could not be calculated leading to exclusion of the other two studies in this subgroup from the meta-analysis (Spanish Monotherapy Study Group  and the steroid avoidance arm in the study by Vincenti et al.). This left 25 studies (4101 patients) in the meta-analysis, which demonstrated a significantly higher serum creatinine in the patients undergoing steroid withdrawal or avoidance (fixed effects, WMD 4.24 μmol/L, CI 2.08–6.40, P=0.0001, I2=25.3%; Fig. 3). The funnel plot is grossly symmetrical.
Fourteen studies were identified that reported renal function as creatinine clearance. One further study reported function as glomerular filtration rate (24)—this was assumed to measure the same underlying effect and therefore the results were included in the meta-analysis. Fixed-effects analysis demonstrates a significant reduction in creatinine clearance across all studies with SAW (15 studies, 3016 patients, WMD −3.06 mL/min, CI −4.66 to −1.45, P=0.0002; Fig. 4). Heterogeneity is low (I2=13.6%). Funnel plot demonstrates some asymmetry, suggesting a degree of publication bias favoring studies with a smaller reduction or increase in creatinine clearance.
No significant relationship between time of withdrawal or study quality and graft function was identified in subgroup analyses. Sensitivity analyses excluding those studies in which missing data were estimated (e.g., use of pooled standard deviations) are consistent with the overall data.
Cardiovascular Risk Factors
The effects of steroid avoidance and withdrawal on cardiovascular risk factors are summarized in Table 2. Overall, significant reductions in the risk of hypertension, new-onset diabetes, and hypercholesterolemia are seen with avoidance or withdrawal (Table 2). When only studies reporting an intention-to-treat analysis are included, the reductions in RR are smaller but remain significant (Table 2).
Significant heterogeneity is found between studies in the analysis of hypercholesterolemia. A large proportion of the heterogeneity can be explained by the time of steroid withdrawal. Fitting of a mixed-effects model to the effect sizes incorporating the time of withdrawal as a linear moderator variable demonstrated no significant residual heterogeneity (test for residual heterogeneity QE=12.2, P=0.35) and identifies time of withdrawal as a significant moderator variable (z=−2.91, P=0.004). Therefore, the reduction in risk of hypercholesterolemia seems to increase with later steroid withdrawal.
No interaction is seen between concomitant immunosuppression or study quality and risk of hypertension, hypercholesterolemia, or new-onset diabetes. Funnel plots for all three outcomes demonstrated some asymmetry, suggesting publication bias in favor of studies demonstrating a larger reduction in risk with SAW.
Quantitative data regarding serum cholesterol levels were reported in 18 studies. Of these, four studies failed to report measures of variance (31, 73, 109, 121). Standard deviations for these studies were estimated from the pooled standard deviations of other studies reporting withdrawal at similar time points. Meta-analysis demonstrated a significant reduction in mean serum cholesterol of −0.39 mmol/L (random effects, CI −0.59 to −0.19, P<0.0001). However, heterogeneity was significant (I2=73.5%). Similar results are seen when only studies reporting intention-to-treat analysis are included (nine studies, random effects, WMD −0.33 mmol/L, CI −0.54 to −0.12, P=0.002, I2=62.2%). Sensitivity analysis removing those studies reporting no measure of variance does not affect the results and there is no interaction between study quality and effect size. The funnel plot is grossly symmetrical. Unlike the data for the risk of hypercholesterolemia, there is no interaction between the mean difference seen and the time of steroid withdrawal. Heterogeneity cannot be explained by concomitant immunosuppression.
Serum triglyceride levels are reported in 12 studies. Of these, only Woodle et al. (31) does not report a measure of variance, and so the standard deviation is estimated from the other studies in the steroid induction group. Meta-analysis demonstrates no significant reduction in triglyceride levels with SAW (random effects, WMD −0.17 mmol/L, CI −0.39 to −0.05, P=0.14). Heterogeneity is significant (I2=81.1%). Sensitivity and subgroup analyses fail to demonstrate a cause for this heterogeneity. The funnel plot is asymmetrical suggesting that there may be unpublished studies demonstrating larger reductions in triglycerides.
The effect of steroid avoidance and withdrawal on other outcomes of interest is shown in Table 3. Risk of infection and malignancy are unaffected, although the risk of leucopenia is significantly increased (fixed effects, RR 1.66, CI 1.42–1.93, P<0.0001). Overall, no difference in the risk of cataracts is observed, although there is significant heterogeneity in this analysis (I2=53.6%).
A number of studies reported outcomes reflecting the effect of steroid therapy on bone metabolism. As the number of studies reporting such outcomes is small, and the reported outcomes vary, a narrative review is considered more appropriate than statistical meta-analysis.
Aroldi et al. (33) evaluated lumbar vertebral bone mineral density (BMD) in a subset of patients from the multicenter trial of Ponticelli et al. (67, 68). Study patients in whom steroids were withdrawn after the induction period demonstrated a significant increase in BMD during 18-month follow-up. In contrast, BMD decreased by 64% in patients in whom steroids were continued (P<0.001). These results are supported by the study by Vanrenterghem et al. (34), who demonstrated a significantly higher bone density in the L2/L3 vertebrae at 12 months in patients in whom steroids were withdrawn 3 months posttransplant. However, no difference was seen in bone density at the L4 vertebra or femoral neck.
Similar results were observed in a subset of patients in the study by Pelletier et al. (35, 36), in whom BMD in both the spine and hip increased in the steroid withdrawal group during the first year after withdrawal. No significant change was seen in the patients continuing steroids. This increase in BMD is seen even after late steroid withdrawal, with Farmer et al. (37) reporting significant increases in the BMD of the lumbar spine and femur in a group of patients undergoing steroid withdrawal greater than 1 year posttransplant.
Measurements of bone density are used in these trials as a surrogate marker for the risk of clinical events such as fractures. In a recent report from the ongoing trial from the Astellas Steroid Withdrawal Group, Woodle et al. (31) reported a significant reduction in the incidence of fractures and avascular necrosis at 5 years after steroid withdrawal (P=0.04).
The main concern with any immunosuppression withdrawal protocol after transplantation is that the risk of acute and chronic rejection will increase, potentially leading to graft damage and dysfunction or loss. The present meta-analysis in renal transplant recipients is based on 34 studies and a total of 5637 patients. It demonstrates an overall RR of AR of 1.56 with SAW. This finding is in keeping with previous meta-analyses, although the RRs in these previous studies have been greater (6–11). These previous meta-analyses have included smaller numbers of studies than the present analysis, often with selected subsets of patients on specific immunosuppressive regimens. Although such an increase in AR rate is of some concern, it should be noted that the baseline risk of AR with modern regimens is approximately 10% to 15% at 1 year and so the absolute increase in risk is relatively small in magnitude.
In keeping with the meta-analysis by Tan et al. (10), who reported that the majority of the increase seen in their study was mild AR of Banff grade I, there was no increase in corticosteroid resistant AR with SAW. Perhaps as a consequence of the mild rejection seen, overall graft survival does not differ significantly between groups. However, there is a trend toward an increase in death-censored graft loss with SAW (HR 1.19, P=0.19), which is stronger when only high-quality studies are included in the analysis (HR 1.31, P=0.07). This trend is lost when all graft losses (including deaths with a functioning graft) are considered (HR 0.99, P=0.93), which may result from a nonsignificant reduction in deaths in the avoidance or withdrawal arm (HR 0.82, P=0.2). Thus, it is possible that the increase in AR seen in the SAW arm slightly increases the risk of graft damage and loss, but this is offset because of a reduction in death from other causes (such as cardiovascular events) in these patients. The finding that the relatively mild AR episodes resulting from steroid avoidance and withdrawal do not have a large impact on long-term graft survival and function is supported by previous case series, in which survival has been related to severity of AR episodes (38, 39). Although there is a statistically significant decrease in graft function, with an increase in serum creatinine of 4.24 μmol/L and a decrease in creatinine clearance of 3.06 mL/min, such small changes are unlikely to be of great clinical significance.
Much of this efficacy data contrast with the findings from the prospective registry study of Opelz et al. (13) described earlier. Patients in this study were withdrawn from steroids at 6 months or later after transplantation, and compared with matched controls in the Collaborative Transplant Study Registry. In contrast to the outcomes identified here, no differences in AR rates or graft function were identified at 7 years after transplantation. In addition, graft and patient survivals were improved in those patients in whom steroids are withdrawn. There are a number of reasons why our current results and that from Opelz may conflict. The most likely explanation is the nonrandomized nature of the CTS study and the likelihood of significant selection bias, as has already been suggested (40). A recent commentary on this topic has suggested that as the effect sizes from interventions in transplantation are relatively small, randomization is essential to ensure that random errors and bias are significantly smaller than the effect size to be measured (41). A counter argument is that registry data allow for much larger numbers of patients to be analyzed, with longer follow-up times. Certainly, the 7-year follow-up in the study by Opelz is longer than the average for studies in the present meta-analysis, although the number of patients (2125 renal recipients) in the CTS study is in fact less than half that in this study (5637 recipients). Other differences in the CTS study are that steroids are withdrawn relatively late (>6 months posttransplantation) compared with those in our analysis. However, no association between withdrawal times and efficacy outcomes was identified in this meta-analysis. Nevertheless, there is no major difference in the general conclusions of the CTS data and this meta-analysis.
Of considerable importance is the finding that there is a significant reduction in cardiovascular risk factors. Hypertension, hypercholesterolemia, and new-onset diabetes are all reduced in patients in whom steroids are avoided or withdrawn. Cardiovascular disease is the most common cause of death with a functioning graft, and therefore any reduction in risk factors is likely to result in a long-term survival benefit (2). However, it is of note that a recent report of the impact of a reduction in some of these risk factors in dialysis patients, in contrast to a normal population, failed to show a reduction in cardiovascular events (42). Although this potential survival benefit is not seen in this analysis, the majority of studies have relatively short follow-up periods and small patient numbers. Individual studies cannot achieve enough statistical power to demonstrate differences in such uncommon long-term outcomes, and those studies included in this review that do report incidence of cardiovascular events unsurprisingly do not demonstrate any significant difference between groups. The only available method for demonstrating differences in these outcomes is likely to be analysis of long-term registry data. Unfortunately, these outcomes were not recorded in the study from Opelz et al., although secondary analysis of risk factors did demonstrate benefits in reduction in hypertension and hypercholesterolemia in patients in whom steroids were withdrawn (13).
Of interest is that later withdrawal of steroids seems to increase the reduction in the risk of hypercholesterolemia. The reason for this is unclear—one might expect the benefit of steroid withdrawal to be greatest when steroids are withdrawn early, thus reducing the total steroid exposure in the study group. It is possible that prolonged steroid use in the study group increases the risk of adrenal insufficiency on withdrawal, leading to a greater fall in serum lipids because of low endogenous steroid levels on steroid cessation. This hypothesis is not, however, supported by the data on measured serum cholesterol levels, which shows no relationship between the time of withdrawal and the reduction in serum cholesterol.
Neither the increase in AR nor the decrease in cardiovascular risk factors observed relate to the type of concurrent immunosuppression used. Perhaps more surprisingly, there also seems to be no relationship between withdrawal time and the effect size seen for outcomes other than serum cholesterol. It is possible that this is just a factor of reduced patient numbers in the subgroup analyses, particularly in the complete avoidance and late withdrawal groups, which reduces statistical power. For example, there is a suggestion that the risk of AR does not differ significantly between the withdrawal and maintenance groups when steroids are withdrawn beyond 12 months posttransplantation. However, the small number of studies in this group means that the RR is not significantly different from the other time points analyzed.
Another interesting finding is the increased risk of leucopenia with SAW. In normal individuals, steroids have a myeloproliferative effect, resulting in a leucocytosis. It is likely that when steroids are withdrawn, the myelosuppressive effect of other agents such as AZA or mycophenolate mofetil predominates and results in a relative leucopenia. This may be compounded by pharmacokinetic interactions between steroids and other immunosuppressants. Steroids are known to induce uridine diphosphate-glucuronosyltransferase activity in a time- and dose-dependent manner, which may increase the clearance of mycophenolic acid (43). Indeed, steroid tapering has been shown to result in an increase in the mycophenolic acid area under the curve (AUC), which may increase the risk of leucopenia (44). Corticosteroids are known to induce the cytochrome P450 3A4 isoenzyme, and this has been suggested as the mechanism for the increased tacrolimus levels seen after withdrawal of steroids (45–47).
Any benefits seen from steroid withdrawal or avoidance will be at least in part offset by the need for some patients to return to long-term steroids after AR episodes or deterioration in graft function. Humar et al. (48) suggested that addition of maintenance steroids in patients experiencing AR may help to reduce the risk of recurrent episodes. The overall benefit in a population treated in this way has been estimated in this analysis by only considering those studies in which an intention-to-treat analysis is reported. In these studies, patients are analyzed according to the randomization group regardless of whether steroids are added to maintenance immunosuppression after AR episodes. The present data in renal transplant recipients suggest that although, as expected, the benefits in the reduction of hypertension, hypercholesterolemia, and new-onset diabetes are reduced when only these studies are included, a significant overall benefit remains when compared with a patient population continuing steroids. This suggests that a population on an avoidance or withdrawal protocol will benefit overall, despite some patients returning to maintenance steroid therapy.
Although the inclusion criteria for the studies in this review are varied, the majority recruit only low-risk transplant recipients, with low or no rejection episodes before randomization and favorable tissue matching. Therefore, generalization of these results to other transplant populations may be inappropriate depending on underlying risk.
Weaknesses in this study are several. The overall methodological quality of the studies included ranges from good to poor. However, sensitivity analyses incorporating only high-quality studies did not affect any of the outcomes analyzed. In a number of outcomes, significant heterogeneity was identified, which could not be explained by predefined subgroup analyses for clinical and methodological factors such as concomitant immunosuppression, withdrawal time, or study quality. The lack of explanation could result from a lack of statistical power in subgroup analysis or from unidentified clinical or methodological factors resulting in heterogeneity. Although this unexplained heterogeneity is of concern, the use of a random-effects model in these cases incorporates the variance in effect size observed between studies, providing a more conservative estimate of the confidence interval for the overall effect. A further caveat to the present results is the suggestion of publication biases in a number of the funnel plots, in particular those for hypercholesterolemia, hypertension, and new-onset diabetes, which may lead to overestimation of the reduction in RR. It is of note that these outcomes are only reported in a small subset of studies, and the bias seen may reflect a “reporting bias” with a tendency to only report such outcomes if the study demonstrates a difference between the withdrawal and maintenance groups.
Definitions of reported outcomes are often variable or not clearly specified. For example, a significant proportion of studies do not report the definition of AR used to instigate therapy. This is also a problem with the definitions of cardiovascular risk factors. Some studies report use of antihypertensive or lipid-lowering drugs, and some report on the incidence of hypertension or hypercholesterolemia (but again with variable definitions). Few studies use the American Diabetes Association/World Health Organization (ADA/WHO) criteria for the definition of diabetes. The assumption made in this analysis is that the same underlying effects are being measured whichever method is used.
Firm conclusions from the survival data in this analysis are limited by the quality of reporting of these outcomes, with estimations for the HRs used in the majority of studies. The HR is used in meta-analysis as it incorporates not only the number of events observed but also withdrawals from the study and time-to-event data. The majority of studies do not report survival outcomes as HRs, meaning that these must be estimated from the log-rank P value from Kaplan-Meier analysis or from the raw event rates. The latter method loses any time-to-event or withdrawal data, approximating the RR of events. The use of estimated HRs in this way allows the full survival data to be used where possible, making the best use of the available data.
Overall, it is likely that in renal transplant recipients, the long-term benefits of a reduction in cardiovascular risk will outweigh the increased risk of AR with steroid-sparing or withdrawal protocols. The optimum time for withdrawal is less clear and although steroids may still be required to protect against the adverse effects of antibody induction therapies in the perioperative period, there is little evidence to suggest that there is any continuing benefit of steroid maintenance beyond this period in a low-risk population on modern immunosuppressive regimens.
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