Context with existing literature
Since damage in AKI at first manifests in renal tubular cells, urinary biomarkers are considered most sensitive for AKI diagnosis. Whether this is also true for prediction of RRT has not been addressed extensively. In our systematic review the largest body of evidence was found for urinary NGAL, but overall it showed a very heterogeneous performance in included studies with AUCs ranging between 0.470 [
52] and 0.884 [
21]. Our results are quite similar to those of a previously published meta-analysis reporting a pooled AUC of 0.782 (0.648–0.917) for the prediction of RRT [
81]. Urinary NGAL is present in different molecular forms (mono-, homo-, and heterodimeric) [
35], depending on its origin either representing filtered serum NGAL released by neutrophils or that released directly from damaged tubular cells. Systemic NGAL levels may rise as activated neutrophils release it with their granular content, and increase the filtered quantity and thereby increasing urinary NGAL levels unrelated to any acute renal damage [
82]. It is important to note that different commercially available NGAL assays measure various molecular forms depending on their antibody combination which may partly explain the large variation in the predictive performance of NGAL.
Except for one trial [
40], TIMP-2 × IGFBP-7 [
83] showed a good predictive performance with individual AUCs well above 0.8, with the pooled AUC confirming these values. The performance of the combined biomarkers was superior to the individual markers. Both biomarkers are involved in the G1 cell cycle arrest, which occurs in the early stages of cell injury [
84]. Interestingly, TIMP-2 was found to perform slightly better than IGFBP-7 in patients with sepsis-induced AKI, while IGFBP-7 outperformed TIMP-2 in surgical patients. Clinical applicability of these findings may be limited, but it supports the combined use of those two biomarkers to provide more consistent results [
84]. Despite the fact that those cell cycle arrest biomarkers showed the best predictive performance for the initiation of RRT, the total number of investigated patients is still small and further studies are warranted evaluating possible influences like pulmonary disease and diabetes mellitus on their levels as shown by Bell et al. [
85,
86].
All other biomarkers measured in urine had pooled AUCs below 0.8, leaving considerable uncertainty whether they could sufficiently predict the initiation of RRT.
Of biomarkers measured in blood, plasma/serum cystatin C performed best, followed by plasma/serum creatinine and NGAL. However, differences in AUCs were marginal. Cystatin C is considered an established marker for glomerular filtration rate (GFR) in chronic kidney disease but has also been demonstrated to detect AKI earlier than creatinine does in critically ill patients [
87,
88]. Still, creatinine showed a fair predictive performance, despite being potentially influenced by age, sex, body weight, muscle mass, and drugs [
89‐
91]. One possible explanation for this finding could be the fact that those biomarkers are often used as a trigger for the initiation of RRT and therefore provide a bias for the predictive performance. Serum creatinine can be serially measured with relative ease and low cost, so multiple serum creatinine values over the course of an episode of AKI showing trends for worsening or not improving may also serve as an important trigger. This is the theory behind the concept of creating a kinetic estimation of GFR [
92]. However, two studies [
41,
56] used creatinine both as a trigger for RRT and also evaluated the predictive performance of creatinine in the same cohort. Interestingly, the obtained AUCs in these two studies were still lower than the pooled AUCs for creatinine of this meta-analysis, indicating that the impact of this bias might not be that important. The same pattern can be noticed in BUN, which was along with others a predefined trigger for RRT initiation in two studies [
50,
56].
Investigated in a larger number of studies, plasma, serum, and whole blood NGAL showed quite similar performance compared to cystatin C and creatinine. As mentioned above, NGAL levels were also identified as being influenced by inflammatory processes or sepsis [
93‐
95]. This is an important consideration, because sepsis is the most frequent cause of AKI in critically ill patients [
1]. Interestingly, one study found no significant difference in plasma NGAL levels between septic shock patients with and without AKI [
95]. Furthermore in patients with severe sepsis, NGAL showed only fair prediction of RRT with an AUC of 0.700 [
72]. Overall, though NGAL has been reported by several studies as being a biomarker which predicts AKI earlier than serum creatinine does [
81], we could not confirm that NGAL was superior to creatinine for predicting requirement for RRT. However, when we compared NGAL and creatinine and analyzed only those studies reporting results for both biomarkers, the AUC for NGAL improved, slightly outperforming creatinine.
For most biomarkers measured in blood, different samples were analyzed, namely plasma, serum, and in some cases whole blood samples. When comparing these various samples, no significant differences were noted, so overall it does not seem to have a major impact, where those biomarkers are measured.
Though single biomarker assessments may add incremental support to guide clinical decision-making, it becomes clear from the data that they should not be used in isolation. Therefore a promising approach seems to be the combination between biomarkers and clinical parameters. Unfortunately, only few studies investigated various combinations and none of them have been replicated; thus, a meta-analysis was not possible. However, some of the single studies showed remarkable results. For example, Koyner et al. [
40] showed that an FST outperformed each of the additionally assessed urinary biomarkers. The FST may be considered a functional test revealing the loss of tubular functional capacity or the severity of AKI. As such it adds additional information to clinical criteria alone. This may explain why the general combination of FST with individual biomarkers did improve predictive value only in those patients with increased biomarker levels (urinary NGAL > 150 ng/ml, urinary TIMP-2 × IGFBP-7 > 0.3 [
40]), but not when biomarker levels were not elevated.
A major limitation of biomarker studies evaluating the prediction of RRT is the fact that a gold standard for this end point is missing, because it is still unclear whether and when to commence RRT. As previously mentioned, only 15 studies stated the criteria for initiation of RRT and only seven studies had predefined criteria for RRT initiation. This limits the applicability and significance of published results, especially in the case of AUCs, since those rely heavily on the comparison with an established gold standard [
96‐
98]. Two recent trials (the “Effect of Early vs Delayed Initiation of Renal Replacement Therapy on Mortality in Critically Ill Patients With Acute Kidney Injury” [ELAIN] trial [
5] and the “Comparison of standard and accelerated initiation of renal replacement therapy in acute kidney injury” [STARRT-AKI pilot trial] [
99,
100]) employed a preset NGAL threshold as an inclusion criterion, while another study used NGAL to guide the early initiation of RRT [
101]. While in the ELAIN trial, NGAL was found to detect patients with progressively deteriorating AKI, in the STARRT-AKI pilot trial NGAL was found to be universally elevated, but did not show good discriminative value between patients requiring RRT or not [
5,
100].
Implications for clinicians, policy, and research
The results of this meta-analysis may have significant implications for clinicians and researchers. Clinicians may be encouraged to utilize novel biomarkers to improve risk stratification for patients with AKI but this must be tempered by the fact that there is uncertainty as to the role of the additional information as well as the financial implications associated with this technology. The biomarkers showing fair to good prediction of RRT are actually markers of renal stress, damage, and/or (loss of) glomerular filtration rate. But clinically, the decision to start RRT is not simply based on the severity of kidney damage but rather on the imbalance between the patient’s remaining renal capacity and the demands characterized by the severity of acute disease, comorbidities, metabolism as well as solute and fluid load (i.e., “demand–capacity imbalance”) [
102,
103]. Hence, it is clear that to enable prediction of the need for RRT more focused validation studies are needed, as well as studies investigating outcomes based on various biomarker thresholds. For NGAL, while statistically not significant, there was a trend that a threshold > 600 ng/ml improves prediction of RRT, as can be seen in our sensitivity analysis. As a result of insufficient data, we were not able to perform sensitivity analysis on TIMP-2 × IGFBP-7, for which two cutoffs, one of 0.3 and a high-sensitivity cutoff of 2.0, are available [
104].
Of importance for further evaluation of biomarkers seems to be the time point of assessment. Not all biomarkers have the same “window of opportunity”. For example, urinary VEGF had the best predictive value early after the insult and thereafter it declined over the following 12 h [
70]. The cell cycle arrest biomarkers urinary TIMP-2 and IGFBP-7 demonstrated the opposite kinetics, with their predictive ability rising over the first 12 h [
70]. This is an important detail for future studies evaluating the prognostic ability of biomarkers. Generally, biomarker research evaluating the necessity of a certain treatment (e.g., RRT) should focus on the ability of a biomarker to discriminate patients that may potentially benefit from this therapy from those with low likelihood of benefit. However, the studies in this review aimed to predict a clinical diagnosis (e.g., AKI) or the initiation of a therapy (e.g., RRT) on the basis of biomarker profiles, without examining the impact this treatment has on the outcome. For the case of RRT in AKI patients, this would require a study investigating whether there is benefit in early RRT initiation guided by biomarker profiles.