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CONSENSUS
Year : 2019  |  Volume : 1  |  Issue : 4  |  Page : 113-116

Biomarkers and the Potential Role in Clinical Trials of Acute Kidney Injury: Consensus Report of Acute Dialysis Quality Initiative XIX


1 Department of Clinical and Experimental Medicine, Royal Surrey County Hospital NHS Foundation Trust, England, UK
2 Department of Critical Care Medicine, Wuhan University, Zhongnan Hospital, Wuhan, China
3 Division of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, College of Medicine, MN, USA
4 International Renal Research Institute of Vicenza, San Bortolo Hospital, Vicenza, Italy
5 Department of Critical Care Medicine, Center for Critical Care Nephrology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA

Date of Submission21-Aug-2018
Date of Acceptance30-Dec-2019
Date of Web Publication31-Dec-2020

Correspondence Address:
Dr. Lui G Forni
Intensive Care Unit, Royal Surrey County Hospital NHS Foundation Trust, Egerton Road, Guildford, England
UK
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DOI: 10.4103/jtccm.jtccm_11_18

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  Abstract 


Biomarkers play important roles in clinical practices including diagnosis and treatment selection. With regard to acute kidney injury (AKI), the use of biomarkers to guide clinical trials is very promising. The committee of the 19th Acute Dialysis Quality Initiative (ADQI) conference met in April 2017 and discussed the integration of biomarkers within clinical trials of acute kidney injury. Consensus had been reached for the significant benefits of integration of biomarkers in clinical trials as well as some potential limitations. Authors concluded the potential role of biomarkers from risk stratification to identification of AKI as well as to monitor therapeutic effects. The group also concluded that biomarkers included within clinical trails could provide both sensitivity and specificity to facilitate trial design. Then the group discussed the role of biomarkers within the PICO (Patient, Intervention, Comparator, Outcome) framework, including the use of biomarkers in patient selection, intervention guidance, comparator and end-point decision. Finally, the committee concluded both the benefits and potential drawbacks of implementing biomarkers in clinical trials of acute kidney injury.

Keywords: Acute kidney injury, biomarker, clinical trial


How to cite this article:
Forni LG, Peng ZY, Kashani K, Ronco C, Kellum JA. Biomarkers and the Potential Role in Clinical Trials of Acute Kidney Injury: Consensus Report of Acute Dialysis Quality Initiative XIX. J Transl Crit Care Med 2019;1:113-6

How to cite this URL:
Forni LG, Peng ZY, Kashani K, Ronco C, Kellum JA. Biomarkers and the Potential Role in Clinical Trials of Acute Kidney Injury: Consensus Report of Acute Dialysis Quality Initiative XIX. J Transl Crit Care Med [serial online] 2019 [cited 2021 Apr 17];1:113-6. Available from: http://www.tccmjournal.com/text.asp?2019/1/4/113/305778




  Introduction Top


Laboratory testing as well as physiological parameters is used by the physician to aid in decision-making, particularly with regard to diagnosis and perhaps treatment selection. With regard to acute kidney injury (AKI), this includes both urine output and serum creatinine as biomarkers of renal function. Approaching 20 years ago, the National Institutes of Health study group defined a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” Therefore, biomarkers may inform as to the underlying etiology of a condition as well as the probable response to therapy; therefore, they may be diagnostic and/or prognostic. Moreover, they may provide information as to the long-term outcome associated with the condition. Taking serum creatinine as an example, this will inform as to a reduction in the glomerular filtration rate given and it is a marker of filtration, which may be associated with an AKI and will also provide information with regard to the development and monitoring of chronic kidney disease (CKD). However, most of the interest in biomarkers, particularly the so-called “novel” or molecular biomarkers with respect to AKI to date has focused on early recognition of AKI given the inherent flaws in employing serum creatinine as a marker of acute injury. Such a strategy, whereby patients are identified early, may allow specific actions to be taken to attenuate the AKI process; although till date, a considerable evidence gap exists with regard to such potential interventions. As we have discussed to inform the future prevention and treatment of AKI, both in globally further studies have to be performed. Unfortunately, prior studies using serum creatinine as an enrollment criterion are flawed for many reasons not least the enrollment of a heterogeneous group of patients of which only a subset would have had AKI. Therefore, the introduction of biomarkers may allow a subtype (with true AKI) to be identified and studied.

Such a role for biomarkers is outlined in [Figure 1]. This illustrates that biomarkers may play a potential role throughout the patient journey from the potential in risk stratification to real-time assessment of kidney function or identification of injury. Furthermore, molecular biomarkers have the potential to monitor drug therapeutic effects as well as potential renal injury. Others may inform as to the recovery process where such potential exists. The application of a particular biomarker within a clinical trials setting will reflect the characteristics of the biomarker tailored to the question being asked. For example, a biomarker with rapid-onset kinetics would be of interest in risk stratification in determining patients who have suffered an AKI but may be of less value in assessing long-term outcomes, response to therapy or indeed potential recovery from the need for renal replacement therapy. Similarly, biomarkers which reflect a particular type of renal insult or reflect damage to a specific region of the nephron may be of value where assessing a new therapy but less useful where patient risk stratification is desired. Therefore, biomarkers when integrated into the clinical trials model could provide sensitivity and specificity which would allow a more personalized approach but may also aid in the trial design and feasibility. This is best illustrated by considering an interventional trial in patients at high risk of AKI where intervention is being put in place to either prevent progression of or reverse AKI. An example of this would be the PrevAKI trial which examined the implementation of a care bundle in cardiac surgery patients deemed at high risk for AKI. Of 1046 patients identified 882 were screened of which 111 were unsuitable. This left a cohort of 771 patients, 276 of which were randomized following risk stratification with a biomarker. It follows that if this approach was not employed in this study, then a far greater sample size would have been needed to achieve desired statistical power which may have made the approach untenable. In this particular study, the biomarkers used were a combination of tissue inhibitor of metalloproteinase-2 and insulin-likegrowth factor-binding protein-7 (the NephroCheck assay) which have been studied in detail previously and whose performance characteristics are well known. [Figure 2] shows how employing this biomarker combination in different incident populations would impact on potential sample size. As can be seen at a low incidence of the disease state, the impact of adding a biomarker adds little as is the case where the incidence of the disease state is high. In both these studies, enrichment of the patient sample size is minimal; although in the low incidence population, the biomarker effect could be enhanced by application of a risk assessment tool as further selection criteria.
Figure 1: Roles of biomarkers in acute kidney injury. Reproduced with permission from acute dialysis quality initiative

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Figure 2: Effects of biomarker combination in different incident populations on potential sample size. Reproduced with permission from acute dialysis quality initiative

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  Biomarkers: Within the PICO Framework Top


Patient

A particularly promising area for the use of biomarkers in clinical trials is in patient selection as discussed and utilized in one of the few studies in the treatment of AKI. Trial enrichment through the application of biomarkers holds great promise not only in potentially differentiating causes of AKI enabling the study of particular phenotypes but also in effect on reducing sample size. [Figure 3]a illustrates how biomarkers could be integrated into the trial design. However, of potentially equal importance is the identification of patients who do not have AKI or patients who are biomarker positive but do not subsequently reach the Kidney Disease Improving Global Outcomes (KDIGO) criteria. The identification of such “subclinical” AKI is important, particularly in individuals with considerable renal reserve as such patients are still at risk of long-term sequelae following the insult.
Figure 3: Using of biomarkers in clinical trials is in patient selection (a), intervention (b), comparator (c), and outcome (d). Reproduced with permission from acute dialysis quality initiative

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Intervention

[Figure 3]b outlines biomarkers being integrated into an intervention arm of a trial. Following patient selection (which may have been guided through the use of a different biomarker) then patients may be randomized to an intervention or control arm involving therapy. An example may be the use of a guided protocol for diuresis in patients with acutely decompensated heart failure where markers of tubular injury may guide therapy or where the nephrotoxicity of a new antibiotic chemotherapy agent is being studied. The intervention arm again may be in patients at high risk of but who do not have AKI; for example, use of biomarkers to guide the impact of preventive measures on a known nephrotoxin. Examples may include the use of platinum chemotherapeutic agents or other nephrotoxins.

Comparator

This schema is shown in [Figure 3]c. As before biomarkers may have been applied to enrich the sample population. Then following intervention patients may be grouped according to biomarker positivity. Under such conditions, the biomarker-negative population may act as a control group.

Outcome

Clinical endpoints for studies in AKI have focused on changes in the KDIGO classification of longer-term endpoints such as major adverse kidney event (MAKE). However, intervention studies using KDIGO are subject to confounders such as the role of AKI Stage 1 (particularly where classified by urine output alone) or indeed patients with subclinical injury. Therefore, biomarker progression where correlated with injury may be a potential outcome, but this may also reflect an irreversible lesion from which recovery is unlikely. Prognostic biomarkers, such as markers of fibrosis, may prove to be a suitable trial endpoint if strategies were in place to minimize fibrosis and subsequent CKD progression. The appearance of biomarkers may also prove a useful endpoint. Where biomarker-negative patients are exposed to a high-risk procedure, the development of injury biomarker positivity may be a clinically relevant endpoint. The characteristics of the endpoint biomarker may be different from that in the acute setting. For example, in patients who attain KDIGO Stage 1 with biomarker positivity may be randomized to nephrology follow-up or usual care. Here, the derived endpoint may be creatinine as a biomarker for end-stage renal disease or MAKE365 [Figure 3]d.


  Discussion Top


The integration of biomarkers within clinical trials may have significant benefits not least in addressing some of the previously identified pitfalls in the current AKI trial design. The reduction in misclassification of AKI more accurate diagnosis from a population of increased homogeneity may improve statistical power in tandem with reducing sample size. Application of prognostic biomarkers may enhance enrollment of patients likely to successfully meet trial endpoints enabling the use of specific therapies, particularly as they may help identify a cohort at higher risk of developing AKI for example. This is of particular value. The syndrome that is AKI encompasses numerous causes: the specificity of some biomarkers will allow better separation of AKI phenotypes perhaps allowing specific therapy. An example could be a biomarker (or biomarkers) that are specific to sepsis-associated AKI enabling specific therapies. Biomarkers may also predict response to treatment; an area explored in detail in oncology where personalized therapy is a reality, and may also be used to monitor both efficacy of treatment or indeed safety.

Clearly, the potential for employing biomarkers in clinical trials is considerable; however, their impact is not without potential drawbacks. Certainly, a higher degree of screening failures will be observed under many conditions. Although this has a cost implication, this may prove a cost saving if the trial interventions are costly regarding therapies but also physician time. Some may argue that therapy tailored to a particular AKI subset will result in a lack of general applicability, but this may also be viewed as a strength as the use of biomarkers adds granularity to the AKI “diagnosis.” It is our opinion that even in the most pragmatic of trials, the inclusion of biomarkers may enrich sample selection, facilitate rapid clinical trials and potentially due to more specific diagnostics and endpoints result in informative and perhaps more cost-efficient clinical trials in patients with AKI.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.




    Figures

  [Figure 1], [Figure 2], [Figure 3]



 

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