Biomarkers for assessing acute kidney injury for people who are being considered for admission to critical care: a systematic review and cost-effectiveness analysis

Abstract
Background
Acute kidney injury is a serious complication that occurs in the context of an acute critical illness or during a postoperative period. Earlier detection of acute kidney injury may facilitate strategies to preserve renal function, prevent further disease progression and reduce mortality. Acute kidney injury diagnosis relies on a rise in serum creatinine levels and/or fall in urine output; however, creatinine is an imperfect marker of kidney function. There is interest in the performance of novel biomarkers used in conjunction with existing clinical assessment, such as NephroCheck® (Astute Medical, Inc., San Diego, CA, USA), ARCHITECT® urine neutrophil gelatinase-associated lipocalin (NGAL) (Abbott Laboratories, Abbott Park, IL, USA), and urine and plasma BioPorto NGAL (BioPorto Diagnostics A/S, Hellerup, Denmark) immunoassays. If reliable, these biomarkers may enable earlier identification of acute kidney injury and enhance management of those with a modifiable disease course.
Objective
The objective was to evaluate the role of biomarkers for assessing acute kidney injury in critically ill patients who are considered for admission to critical care.
Data sources
Major electronic databases, conference abstracts and ongoing studies were searched up to June 2019, with no date restrictions. MEDLINE, EMBASE, Health Technology Assessment Database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Central Register of Controlled Trials, Web of Science, World Health Organization Global Index Medicus, EU Clinical Trials Register, International Clinical Trials Registry Platform and ClinicalTrials.gov were searched.
Review methods
A systematic review and meta-analysis were conducted to evaluate the performance of novel biomarkers for the detection of acute kidney injury and prediction of other relevant clinical outcomes. Random-effects models were adopted to combine evidence. A decision tree was developed to evaluate costs and quality-adjusted life-years accrued as a result of changes in short-term outcomes (up to 90 days), and a Markov model was used to extrapolate results over a lifetime time horizon.
Results
A total of 56 studies (17,967 participants), mainly prospective cohort studies, were selected for inclusion. No studies addressing the clinical impact of the use of biomarkers on patient outcomes, compared with standard care, were identified. The main sources of bias across studies were a lack of information on blinding and the optimal threshold for NGAL. For prediction studies, the reporting of statistical details was limited. Although the meta-analyses results showed the potential ability of these biomarkers to detect and predict acute kidney injury, there were limited data to establish any causal link with longer-term health outcomes and there were considerable clinical differences across studies. Cost-effectiveness results were highly uncertain, largely speculative and should be interpreted with caution in the light of the limited evidence base. To illustrate the current uncertainty, 15 scenario analyses were undertaken. Incremental quality-adjusted life-years were very low across all scenarios, ranging from positive to negative increments. Incremental costs were also small, in general, with some scenarios generating cost savings with tests dominant over standard care (cost savings with quality-adjusted life-year gains). However, other scenarios generated results whereby the candidate tests were more costly with fewer quality-adjusted life-years, and were thus dominated by standard care. Therefore, it was not possible to determine a plausible base-case incremental cost-effectiveness ratio for the tests, compared with standard care.
Limitations
Clinical effectiveness and cost-effectiveness results were hampered by the considerable heterogeneity across identified studies. Economic model predictions should also be interpreted cautiously because of the unknown impact of NGAL-guided treatment, and uncertain causal links between changes in acute kidney injury status and changes in health outcomes.
Conclusions
Current evidence is insufficient to make a full appraisal of the role and economic value of these biomarkers and to determine whether or not they provide cost-effective improvements in the clinical outcomes of acute kidney injury patients.
Future work
Future studies should evaluate the targeted use of biomarkers among specific patient populations and the clinical impact of their routine use on patient outcomes and management.