Hepatorenal syndrome (HRS) is a complication of cirrhosis (1). HRS is classified as type 1 or 2, depending on changes in serum creatinine (1,2). Type 1 HRS is often quickly fatal, whereas type 2 can be more insidious with the highest risk for death over the weeks following diagnosis. HRS results in recalcitrant kidney dysfunction and portends a poor prognosis in patients with cirrhosis. After the diagnosis of HRS, common treatments include discontinuing diuretics and nephrotoxins, volume expansion with albumin, and vasoconstrictive agents (1,3).
Randomized controlled trials (RCTs) have assessed the efficacy of some of these treatments, and terlipressin has been shown to be among the most promising. In a recent open-label RCT, use of terlipressin led to higher rates of HRS reversal compared with norepinephrine (3). Despite this, previous systematic reviews have found only low to very low certainty evidence (4-7).
Since previous reviews, new trials have been published and may provide more precise estimates that would improve the certainty of the evidence. We present a systematic review and network meta-analysis (NMA), addressing the comparative effectiveness of pharmacological treatments for HRS.
MATERIALS AND METHODS
We registered the protocol and posted our data and R-code on open science framework (https://osf.io/nq9k2) on October 4, 2021.
We included published and abstract reports of RCTs that randomized hospitalized adults (≥18 yr old) with HRS type 1 or 2 to any pharmacologic agent used for the treatment of HRS. We did not limit eligibility based on the route of medication administration or language of publication.
Information Sources and Search Strategy
We developed our search in collaboration with an experienced academic librarian. We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Medline In-Process & other non-indexed citations, Scopus, and Web of Science from inception until October 13, 2021. S1 (https://links.lww.com/CCM/H149) presents our search strategy.
Data Management, Selection, and Data Collection Process
We uploaded citations to Covidence (Covidence Systematic Review Software, Veritas Health Innovation, Melbourne, Australia; www.covidence.org). Pairs of reviewers, working independently and in duplicate, screened titles and abstracts of citations, and subsequently, full texts of records deemed potentially eligible at the title- and abstract-screening stage. We documented the reasons for exclusion in the full-text screening stage. Pairs of reviewers independently extracted data on trial characteristics, patient characteristics, and results using a standardized, pilot-tested data extraction form. Reviewers resolved discrepancies and disagreements by discussion or by third-party adjudication when necessary.
Data Items and Outcomes
We collected trial characteristics (trial author, year published, trial registry information, and country of enrollment) and patient characteristics (age, sex, cirrhosis etiology and baseline laboratory markers, and prognostic scores for end-stage liver disease [Child-Pugh score and model for end stage liver disease (MELD)]).
We collected data on the following outcomes: reversal of HRS (as defined by individual study investigators), mortality, transplant-free survival, and severe adverse outcomes (as defined by the study authors). For mortality, we included the longest follow-up time provided.
Risks of Bias
For each trial, pairs of reviewers assessed risk of bias (RoB) independently and in duplicate using a “modified version” of the Cochrane tool for assessing RoB 2.0 in randomized trials (8–10). For each outcome, we judged RoB across the following domains: bias arising from the randomization process, departures from the intended intervention, missing outcome data, measurement of the outcome, and selection of the reported results. Each domain was rated as: 1) low RoB, 2) probably low RoB, 3) probably high RoB, or 4) high RoB. We resolved discrepancies by discussion and adjudication by a third party if necessary. S2 (https://links.lww.com/CCM/H149) presents additional details on criteria used for assessing RoB.
Certainty of the Evidence
We assessed the certainty of the evidence independently and in duplicate using the Grading of Recommendations, Assessment, Development and Evaluations approach for NMA (11). We rated the certainty for each comparison and outcome as high, moderate, low, or very low, based on considerations of RoB, inconsistency, indirectness, publication bias, intransitivity, incoherence (difference between direct and indirect effects), and imprecision—definitions for which are in S3 (https://links.lww.com/CCM/H149) (12).
We made judgments of imprecision using the minimally contextualized approach (13). A minimally contextualized approach considers whether CIs include the minimally important difference and does not consider whether it includes both minimally important and large effects. Ratings of imprecision are not based solely on whether there is statistical significance but rather whether CIs include or exclude the minimally important difference thresholds. In general, p values are limited in their ability to inform the usefulness of an estimate, a well known but underrecognized component of statistical interpretation (14). We sourced minimally important differences (MIDs) based on consensus of the authors. We chose the following MIDs: 2% for HRS reversal, 1% for mortality, and 2% for serious adverse events.
The GRADE approach uses a standardized method for reporting the results (15). The standardized language is as follows: high certainty evidence = drug X reduces mortality, moderate certainty evidence = drug X probably reduces mortality, low certainty evidence = drug X may reduce mortality, and very low certainty evidence = the evidence of drug X on mortality is very uncertain.
We classified drugs into nodes based on molecule and mechanism of action and constructed network plots using STATA Version 17.0 (Stata Corp LLC, College Station, TX) (16).
For all outcomes, we performed a frequentist random-effects NMA using the “netmeta package in R 2.0” (17). A network meta-analysis produces network estimates based on the direct and indirect estimates. Direct estimates are calculated based on traditional pairwise meta-analyses for each comparison (for comparisons that have head-to-head data) (18,19). Indirect estimates are calculated based on contributions from common comparators through indirect loops. We are then able to calculate network estimates, pooled estimates of direct and indirect evidences, using the NMA analytic framework. This affords us many advantages, including improving precision of the estimates and providing head-to-head comparisons of drug treatments not investigated in clinical trials.
We performed pairwise inverse variance random-effects meta-analysis using restricted maximal likelihood estimator. We assessed between-study heterogeneity using visual inspection of CIs, interpretation of the I2 statistic, and chi-square test. We also present I2 for the individual networks. We considered I2 scores of 0–39% as unimportant, 40–60% as moderate, 60–75% as substantial, and greater than 75% as considerable heterogeneity. When estimates included 10 or more studies, we assessed for publication bias by inspecting funnel plots. We used node splitting to test for incoherence.
We tested for prespecified subgroup effects using meta-regression. We examined the following subgroups: RoB (high or probably high vs low or probably low), type 1 versus 2 HRS, etiology of cirrhosis (alcoholic vs viral vs metabolic), and severity of liver disease (MELD and Child-Pugh as continuous variables). When statistical evidence of a subgroup effect was found, we used the Instrument for assessing the Credibility of Effect Modification Analyses tool to assess credibility in the subgroup effect (ICEMAN) (21). Definitions for each of these terms are found in S3 (https://links.lww.com/CCM/H149).
We summarized the effect of interventions of dichotomous outcomes using absolute risk reduction and corresponding 95% CIs. We calculated the baseline risk by taking the median risk in the placebo arm across included trials. We converted relative risk (RR) into absolute risk per 1,000 people, with a negative sign indicating fewer events per 1,000 people and a positive sign indicating more events per 1,000 people. S4 (https://links.lww.com/CCM/H149) presents forest plots with RR and 95% CI for both the network estimates and node splitting results.
We identified 3,079 citations from the search, reviewed 62 full texts, and included 26 RCTs, examining 1,736 patients. Figure 1 presents more details on the search and screening process.
Most patients were male and between the ages of 48.9–55.6 years old. Most of the trials included only type 1 HRS, with one trial including only type 2 (21). Type 1 HRS patients made up approximately 90% of the patients included in the analysis, and therefore, we will refer only to type 1 when referring to HRS henceforth. Most trials were conducted in India or the Middle East (73.1%) (3,21–35). Table 1, and S5 and S6 (https://links.lww.com/CCM/H149) present more details on trial and patient characteristics (3,21–31,33–46).
TABLE 1. -
Basic Demographic and Clinical Characteristics of Participants Across Trials of PAH Treatments
||Median (Interquartile Range)
|Number of trials (n)
|Hepatorenal type (%)
| Model for end stage liver disease
Refer to Supplementary Table 1
(Supplementary material, section 5, https://links.lww.com/CCM/H149
) for full details of the included trials in the network meta-analysis.
All characteristics are reported in median with interquartile range unless otherwise specified.
Risk of Bias
Twenty-two trials (85%) had outcomes that were rated either at high or probably at RoB, most often due to lack of blinding and concerns with allocation concealment. S7 (https://links.lww.com/CCM/H149) presents our RoB judgments.
We did not detect incoherence in our analysis for any of the outcomes of interests using node splitting forest plots (S4, https://links.lww.com/CCM/H149). Our network diagrams (Fig. 2A–C) demonstrate that most trials were connected via terlipressin. The credibility of estimates not directly compared with one another depends directly on the credibility of the connecting node. S8 (https://links.lww.com/CCM/H149) provides detailed information on the ratings of the direct, indirect, and network estimates.
There was unimportant to moderate heterogeneity detected within the networks.
Reversal of Hepatorenal Syndrome
Twenty-four trials, including 1,632 patients and 634 events, with a median follow-up of 15 days, reported on reversal of HRS. Although there was some variability in how each trial defined reversal (S6, https://links.lww.com/CCM/H149), this was most defined as a fall in serum creatinine to less than 1.5 mg/dL (133 umol/L). Figure 2A presents the network geometry. Table 2 presents the network estimates compared with placebo for each comparison.
TABLE 2. -
Drug Nodes Versus Placebo, Presented in Absolute Risk Difference per 1,000 Patients (95% CIs)
||Serious Adverse Events
||–93.7 (–168.7 to –12.5)
||20.4 (–5.1 to 51)
||–30.7 (–88.8 to 107.7)
||–430.5 (–573.7 to 113.1)
||–35.8 (–167.1 to 5,836.7)
|Midodrine + octreotide
||67.8 (–2.8 to 177.4)
||99.1 (–135.8 to 447.1)
||24.089 (–98.7 to 358.5)
||–27.9 (–145.7 to 114.3)
||–39.9 (–115.7 to 141.2)
|Dopamine + furosemide
||–95.6 (–241.6 to 106)
||21.7 (–166.1 to 9,285.7)
drisk of bias, and
All estimates are network estimates.
Grading of Recommendations, Assessment, Development and Evaluations Working Group grades of evidence:
Interpretation: Each node estimate is compared against placebo. Most estimates unless otherwise specified are the network estimates. The relative effectiveness of each drug vs another can be done by simply comparing how well each drug compares against placebo.
High certainty: We are very confident that the true effect lies close to that of the estimate of the effect.
Moderate certainty: We are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different.
Low certainty: Our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect.
Very low certainty: We have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect.
Based on pooled analysis, terlipressin improves HRS reversal compared with placebo (142.8 more reversals per 1,000 [95% CI, 87.7 to >210.9]; high certainty). Norepinephrine may improve HRS compared with placebo (112.7 more reversals [95% CI, >52.6 to >192.3]; low certainty). The effect of Midodrine+octreotide on reversal of HRS compared with placebo is very uncertain (150.9 more reversals per 1,000 [95% CI, <18.6 to >251.7) (very low certainty). We detected publication bias for the norepinephrine estimate as detected by the Egger statistical test (p = 0.013) and funnel plot inspection (S4, https://links.lww.com/CCM/H149). We are uncertain of the effect of monotherapy with octreotide compared with placebo on HRS reversal (30.7 fewer reversals per 1,000 [95% CI, <2.8 to >177.4); very low certainty).
In head-to-head comparisons, terlipressin may improve HRS compared with midodrine+octreotide (72.5 more reversals per 1,000 [95% CI, >198 to <12); low certainty) and norepinephrine (30.4 more reversals per 1,000 [95% CI, >83 to <14.6); low certainty).
Twenty-three trials, including 1,604 patients and 909 deaths, with a median follow-up of 12 weeks reported on mortality. Figure 2B presents the network geometry. Table 2 presents the network estimates compared with placebo for each comparison.
Terlipressin may reduce mortality compared with placebo (93.7 fewer deaths per 1,000 [95% CI, <12.5 to <168.7]; low certainty). We rated down both for RoB and for evidence of publication bias, assessed by inspecting the funnel plot and using the Egger statistical test (p = 0.0013) (funnel plot in S4, https://links.lww.com/CCM/H149). We are uncertain of the effects of norepinephrine (27.9 fewer deaths per 1,000 [95% CI, <145.7 to >1,143), octreotide (430.5 fewer deaths per 1,000 people [95% CI, <573.7 to >113.1), midodrine+octreotide (99.1 more deaths per 1,000 [95% CI, <135.8 to >447.1), and dopamine+furosemide (–95.6 fewer deaths per 1,000 [95% CI, <241.6 to >106]) compared with placebo on mortality in patients with HRS (all very low certainty).
In head-to-head comparisons, terlipressin may reduce mortality compared with midodrine+octreotide (194 fewer deaths per 1,000 [95% CI, <352 to >36]; low certainty) and norepinephrine (66 fewer deaths per 1,000 [95% CI, <142.5 to >24]; low certainty).
Serious Adverse Events
Sixteen trials, including 1,278 patients and 376 events, with a median follow-up of 15 days reported on serious adverse events. Figure 2C presents the network geometry. Table 2 presents the network estimates compared with placebo for each comparison.
Terlipressin probably increases the risk of serious adverse events compared with placebo (20.4 more events per 1,000 [95% CI, <5.1 to >51]; moderate certainty). We are uncertain of the effect of midodrine+octreotide (24.08 more events per 1,000 [95% CI, <98.7 to >358.5]), norepinephrine (39.9 fewer events per 1,000 [95% CI, <115.7 to >141.2]), octreotide (35.8 fewer events per 1,000 [95% CI, <167.1 to >5,836.7]), and dopamine+furosemide (21.7 more events per 1,000 [95% CI, <166.1 to >9,285.7]) on serious adverse events compared with placebo (all very low certainty evidence).
Subgroup analysis using meta-regression did not find evidence of statistically significant subgroup effect based on RoB. For mortality, we found a statistically significant subgroup effect based on RoB (p = 0.04) for terlipressin versus placebo. There was possibly no reduction in mortality with terlipressin when considering low RoB trials (6.2 more deaths per 1,000 [95% CI, <93.7 to >118.7]). However‚ there was possibly a reduction in mortality with terlipressin in the high RoB trials (175 fewer deaths per 1,000 [95% CI, 275 to <50]). Using the ICEMAN tool, this credibility in this subgroup was judged to be low/moderate. This was accounted for in the GRADE rating for mortality for this comparison (lowered certainty for RoB). S4 (https://links.lww.com/CCM/H149) presents the subgroup forest plot. There were no other subgroup effects based on RoB, type of HRS, etiology of cirrhosis, MELD, or Child-Pugh score (p > 0.05).
This review presents an updated summary of the evidence examining the comparative effectiveness of treatments for type 1 HRS. It incorporates recently published, large, randomized trials, not included in previous reviews (3,4,43). We found high certainty evidence supporting the reversal of type 1 HRS with terlipressin, whereas we found only very low certainty evidence for type 1 HRS reversal using a combination of octreotide and midodrine. This is especially interesting considering octreotide and midodrine are widely used in centers across North America in patients with HRS, whereas terlipressin is unavailable. Norepinephrine may reverse type 1 HRS, albeit lower efficacy than terlipressin but with higher certainty than octreotide+midodrine. Terlipressin may reduce mortality in patients with HRS, based on low certainty evidence, whereas we found an uncertain effect of the other investigated drug treatments on the outcome of mortality.
Most clinical practice guidelines suggest using terlipressin in patients with documented type 1 HRS or norepinephrine if not available (47,48). The 2021 American Association for the Study of Liver Disease guidelines recommend terlipressin, despite not being available in the United States and Canada but is used in Europe and other jurisdictions. Vasopressin, a similar, but shorter acting version of terlipressin, has been considered as an alternative but has not been tested in RCTs, despite retrospective cohort studies that have demonstrated efficacy compared with octreotide (49). As administration of norepinephrine most often requires admission to an intensive care or high-dependency unit and is, therefore, associated with increased costs and resources, octreotide and midodrine are often used as lower cost alternatives.
Issues cited in limiting the widespread use of terlipressin include cost-effectiveness and frequency of serious adverse events. Cost-effectiveness is difficult to estimate, as each jurisdiction or hospital has specific methods for negotiating drug prices. However, a systematic review and meta-analysis including a complete economic evaluation through cost minimization found that terlipressin was more economical than norepinephrine (50). Similarly, an economic study under the Brazilian Public Health system found economical efficacy for terlipressin over norepinephrine. Serious adverse events have been cited to be a limiting factor for use of terlipressin (51). In the recent CONFIRM trial, gastrointestinal bleeding (4% vs 0%), sepsis (4% vs 0%), and respiratory failure (10% vs 3%) were seen in higher proportion in the terlipressin group compared with the placebo group (43). Given these risks, careful consideration of individual characteristics and baseline comorbidities are needed before consideration of using terlipressin.
In Relation to Other Findings
Although the qualitative results regarding HRS pharmacotherapy are relatively consistent across previous reviews, the certainty in evidence addressing these interventions has been low or very low, limiting clinical implications. By incorporating the latest data and using an NMA design that maximizes the quantity of data informing comparisons (taking advantage of both direct and indirect evidences), we have been able to overcome some of the imprecision and improve the certainty in findings across comparisons. This is important to patients, clinicians, and stakeholders as higher certainty data will allow for stronger conclusions and possibly stronger recommendations when it comes to producing clinical practice guidelines in HRS treatment.
The greatest limitation in evidence synthesis for HRS has been the small numbers of trials and events resulting in imprecision and the quality of the trials, resulting in RoB concerns. Reviewers of HRS pharmacotherapy have been consistent over the past decade in terms of direction of effect (6,7,52). However, all reviews have rated the certainty of the evidence for pharmacological therapies as low to very low. The rating of the certainty of the evidence casts doubt on the superiority of one pharmacologic therapy over another, as the true effect reported might significantly differ from the report effect. Therefore, the case for a more expensive therapeutic agent such as terlipressin or norepinephrine versus midodrine and octreotide is difficult to make. With the increased trial data and high-quality randomized trials (both for direct and indirect sources), we found high certainty evidence for terlipressin improving HRS reversal. This was primarily the inclusion of the recently published CONFIRM trial, which demonstrated significant benefit in reversing HRS with terlipressin (43). Prior to CONFIRM, the evidence for terlipressin was mostly from smaller nonblinded RCTs, resulting in low event rates and imprecise estimates of the effect.
Strengths and Limitations
The strengths of our review are increased low RoB trial data, careful data collection and review process, and use of updated GRADE methods.
Limitations include heterogeneous definitions of some outcomes including HRS reversal, and low or very low certainty evidence for some comparisons and outcomes, for example, adverse events. Furthermore, our estimate of mortality is likely confounded by eligibility and receipt of liver transplant. We were unable to gather data on transplant-free survival. Although not all of these RCTs examined ICU patients, there is variation in how ICU and high-dependency units are used across the world. Administration of many of the studied interventions requires ICU admission in many jurisdictions (e.g., norepinephrine). Furthermore, although terlipressin can be given in bolus formulation, an RCT comparing the relative efficacy of bolus versus infusion found that infusion resulted in reduced adverse events (53). Terlipressin infusion normally requires high-dependency unit admission. Given this, we believe the findings of this report are relevant to ICU practitioners.
Future Direction and Impact
We are the first to report high certainty evidence for the use of terlipressin in type 1 HRS patients, as well as low certainty evidence for norepinephrine. Perhaps even more importantly, we have cast doubt over the efficacy of midodrine and octreotide as a viable option. These results should prompt centers in North America to reconsider the role, availability, and cost-effectiveness of terlipressin in treating patients with documented HRS. In the absence of access to terlipressin, increased use of norepinephrine for HRS may be beneficial compared with the more widely used combination of octreotide and midodrine. This would mean moving the appropriate initial care setting to ICUs or high-dependency units that are able to administer norepinephrine instead of a medical ward.
Terlipressin increases HRS reversal, and norepinephrine may improve HRS reversal. Terlipressin may reduce mortality. Until terlipressin is available in North American hospitals, initial triage to ICU or high-dependency units for norepinephrine may be more appropriate than the octreotide+midodrine therapy, even though this can be administered on the ward. Our review has the potential to inform future guidelines and practice in the treatment of HRS.
We thank Rachel Couban for her expertise in developing the search strategy.
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