Novel Biomarkers in Critically Ill Patients and the Emergency Room Jay L. Koyner MD Section of Nephrology University of Chicago Research Funding: NIDDK, Abbvie, Astute, Argutus Outline Background / Pitfalls about / ER patients Sources of Scoring Systems Biomarker Tour- Consumers Report Approach Blood and Urine Blood and Urine -ER Differential Diagnosis Limitations Renal Perfusion Drug Metabolism Nephrotoxin Contrast Surgery- Ischemia Comorbidities Immune Function ( or ER) Cardio- Renal Sepsis / Infection Acute Lung Injury Mech. Vent Chronic Kidney Disease 1
in the (Sapphire) N= Endre (Early ARF) KI N=528 Siew (CJASN 2010) N=391 Uchino (JAMA) 2005 N=1,738 Sepsis 19% 19% 41% 47.5% Respiratory 43% 12% 14.8% Surgery 34% 21% 41.1% Cardiovascular 33% 22% 3% 34.5% Neurological 10% 14% 2.7% Trauma 8% 8% 25.3 4.2% Cardiac Surgery 18% 23.2% Other 17% 13% Severity of Illness: Scoring Systems Simplified Acute Physiology Score (SAPS) Sequential Organ Failure Score (SOFA) Acute Physiology and Chronic Health Evaluation (APACHE) Include markers of renal function (SCr, BUN...) Designed to predict inpatient mortality Reactive to pre-existing Non-predictive of severity Warning Scores for the : Not Kidney-Centric Scores to predict who will transfer to the Focused on Vitals not labs / UOP based Churpek et al Chest 2
Renal Angina Goldstein Chawla CJASN 2010 Basu et al Kid Int Biomarkers in Relation to Site of Injury in Nephron Proximal Tubule Injury Urine IL-18 Urine KIM-1 Urine L-FABP Urine Cystatin C α1-microglobulin β2-microglobulin Urine α-gst Urine Netrin-1 Urine NAG Distal Tubule Urine NGAL Urine π-gst Glomerular Filtration Serum Creatinine Blood urine Nitrogen Serum Cystatin C Plasma NGAL Glomerular Injury Urine albumin excretion Loop of Henle Injury Uromodulin Other Mechanisms / Sites of Injury not specific to the Nephron Hepcidin Iron trafficking TIMP-2/ IGFBP7 G1 cell cycle arrest Excellent AUC 1.0-0.85 Sens/ Spec Very Good 0.85 0.75 Good Fair Poor 0.75-0.65 0.65-0.50 < 0.50 P=NS > 90% > 80% >70% >60% >50% 3
Herget- Rosenthal KI 2004 Nejat NDT 2010 (Early ARF) Ahlstrohm Clin Neph 2004 Serum Cystatin C - n % of CKD 85 442 202 (52%) >50% (77%) 50% (27%) Creat. Data Arrival 19% Arrival Arrival (early) 0.99 Injury- 0.98 RRT 0.84 Other Valid 9% 12 hour 12 hour 0.63 0.71 Pickering Blood Pur Cruz 2009 Valid De Gues AJRCCM 2011 Plasma NGAL- n % of CKD 528 301 632 mixed 28% 44% 27% Creat. Data arrival 6.6% w/in 48 hours 12 hour 9% 12 hour admission (early) Mortality / 0.74 0.79- RRT Mortality 0.78 0.85 RRT 0.69 0.64 pngal assoc. w/ APACHE & SOFA 0.77 0.86 F 0.63 Mort. Sepsis 4
Parikh JASN 2005 Doi Med 2011 Siew CJASN 2010 Valid Urine IL-18 n % of CKD 137 ARDS 341 391 50% SCr 28% 39% N 22% All w/ Cr<1.2 2% CKD4 Creat. Data 24 hours before arrival 12.7% arrival 9% 12 hour 12 hour (early) 0.73 0.68 0.67-24hr 0.62 N2/3 0.76 0.69 Mortality / mortality Endre Kid Int 2011 EARLY 529 N 28% arrival 0.62 0.70 RRT 0.68 - mortality Urinary Kidney Injury Molecule-1 (KIM-1)- n % of CKD Creat. Data (early) Mortality / Endre Kid Int 2011 EARLY Valid 529 N 28% arrival 9% 12 hour 12 hour 0.66 0.62 RRT 0.56 0.69 0.70 No data provided No data provided Urine L-FABP n % CKD Creat. Data AUC (time) Mortality / Siew et al Kid Int Crit Care Valid 380 N 34% 0% Arrive 9% 12 hour 0.59-0.65- N2 0.66 0.61- Predicted RRT but not death Doi Med 2011 341 39% 2% CKD4 arrival 0.80 Predicted Mortality 5
LFABP: Meta-analysis Susantitaphong et al AJKD Siew et al Kid Int Endre Kid Int 2011 EARLY Urine Cystatin C - n % CKD Creat. Data 380 N 34% 529 N 28% arrival AUC (time) Arrive AUC 0.67 0.71 RRT Mortality / 0.66 De Gues AJRCCM 2011 Valid Siew et al JASN 2009 Doi Med 2011 Endre Kid Int 2011 EARLY Urine NGAL n CKD (Early) 632 mixed 391 341 529 27% N 22% 39% N 28% arrival 9% 12 hour 12 hour 12% within 24 2% CKD4 arrival arrival 0.80 0.88 F 0.71 0.72 0.71 0.71 0.79 Mortality/ 0.63 Mort. Sepsis Predicted Mortality 0.66 0.79 RRT 0.66 mortal 6
Urine NGAL Haase - Meta-analysis and Pooled data Haase et al AJKD 2009 N Cutoff (95% CI) 123 of 602 (20.4%) 50% 7days 155.0 (150-169) Sens. (95% CI) 76.4% (60-88) Spec. (95% CI) 75.5 (52-90) Diag. Odds (95%CI) I 2 10.0(3-33) 17.5 * Not exclusively * Not exclusively Hasse JACC 2010 TIMP-2 IGFBP7 n % of CKD Creat. Data 9% (early) 0.77 Severity / No data provided Valid 12 hour 0.80 No data provided et al Koyner ASN Abstract oral presentation Friday Others Biomarkers in the Urinary Albumin Doi - Med 2010 N-acetyl-β-D-glucosamine (NAG) - Doi Med 2010 Urine π-gst - FGF-23 Leaf CJASN - 2012 Koyner CJASN 2010 7
Back to Basics: Acutally Looking at Urine Perazella et al CJASN 2010, Bagshaw et al NDT 2012 On to the ER Adding Urinalysis to the mix Schinstock et al NDT 8
Urine NGAL in the ER 635 admitted patients AUC ( R) Urine NGAL 0.95 FENA - 0.71 Serum Creat. 0.92 Nickolas et al Ann Int Med 2008 Hey, what about the physician 665 ER patients 7% (N) Combined Physician assessment w/ NGAL 0.80 + 0.84 = 0.90 DiSomma et al The Lisbon ER: Cystatin & NGAL 616 patients 21% 26% Pre-renal 2.5% CKD AUC for N-1 Serum 0.88 Creatinine P-NGAL 0.77 S-CysC 0.87 U-CysC 0.61 Soto et al CJASN 2010 Soto et al CJASN 9
252 Children 12 with RISK 6 with Injury Don t forget the Kids!! AUC Severity Urine NGAL 0.66 0.80 Urine IL-18 0.44 0.48 Urine KIM-1 Beta-2- microglob. 0.61 0.73 0.59 0.80 Du, Zappitelli et al. Pediatr Neph 2011 Nickolas 2012: JACC Multicenter 1635 pts 96(6%) Intrinsic 254(15.5%)-Pre-Renal 154 (9%) - CKD AUC for INTRINSIC Urine NGAL 0.81 Urine KIM-1 0.71 Urine IL-18 0.64 Urine LFABP 0.70 Urine CysC 0.65 Serum Creat. 0.90 Doi et al. Kid Int 2012 Nejat et al Kid Int 2012 Back to the : Differentiating 10
Your FENA is low, you must be dehydrated Doi Nejat Nickolas Soto De Gues U- NGAL U-KIM1 U- LFABP U- IL-18 U-CysC P-NGAL P-CysC None &T- T & I None &T- T & I None &T- T & I None &T- T & I None &T- T & I None &T- T & I None &T- T & I Limitations Bronze Standard SCr Endre, Kellum et al Contrib Neph 11
Biomarker Positive - Creatinine Negative: A Under-utilized Paradigm!!! DiSomma Haase and Devarajan JACC 2010 Biomarker Quantitation: Impact on Results Normalization to urine creatinine improves prediction of incipient and outcomes No clear benefit for established of interest shapes the ideal method of quantitation. Ralib et al. JASN 2012 Combinations Siew et al Kid Int et al Combine for kinetics Increase the duration of diagnosis Combine for different functions Filtration and injury Functional and Structural Combine for improved accuracy Strategic combinations Diagnostic + Prognostic marker Sensitive +Specific marker 12
Publication Bias Other Limitations Exaggerating the importance of result Standardization of Biomarker Assays Du et al Pediatr Nephrol 2011-2 NGAL assay Frozen Bio-banked samples Unclear how fresh samples/poc assay will differ Limited number of hard endpoints Less focus on RRT / Severity Continued Scr Reliance -Bronze Standard Impact of CKD and other factors on biomarkers Summary remains extremely common in the and ER Hardly a pristine clinical phenotype specific prediction tools are needed (Renal Angina) Several viable biomarker candidates None are clinically available in the United States Factors that impact biomarkers remain poorly studied (CKD, sample handling) Combining the correct biomarkers should improve performance Thanks jkoyner@uchicago.edu 13