Assessing GFR With Proenkephalin
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Cited by 5 publications
References 49 publications
A comparison of the renal function biomarkers serum creatinine, pro-enkephalin and cystatin C to predict clearance of pemetrexed
Introduction For drugs with a narrow therapeutic window, there is a delicate balance between efficacy and toxicity, thus it is pivotal to administer the right dose from the first administration onwards. Exposure of pemetrexed, a cytotoxic drug used in lung cancer treatment, is dictated by kidney function. To facilitate optimized dosing of pemetrexed, accurate prediction of drug clearance is pivotal. Therefore, the aim of this study was to investigate the performance of the kidney function biomarkers serum creatinine, cystatin C and pro-enkephalin in terms of predicting the elimination of pemetrexed. Methods We performed a population pharmacokinetic analysis using a dataset from two clinical trials containing pharmacokinetic data of pemetrexed and measurements of all three biomarkers. A three-compartment model without covariates was fitted to the data and the obtained individual empirical Bayes estimates for pemetrexed clearance were considered the “true” values (Cltrue). Subsequently, the following algorithms were tested as covariates for pemetrexed clearance: the Chronic Kidney Disease Epidemiology Collaboration equation using creatinine (CKD-EPICR), cystatin C (CKD-EPICYS), a combination of both (CKD-EPICR-CYS), pro-enkephalin as an absolute value or in a combined algorithm with age and serum creatinine, and lastly, a combination of pro-enkephalin with cystatin C. Results The dataset consisted of 66 subjects with paired observations for all three kidney function biomarkers. Inclusion of CKD-EPICR-CYS as a covariate on pemetrexed clearance resulted in the best model fit, with the largest decrease in objective function (p < 0.00001) and explaining 35% of the total inter-individual variability in clearance. The predictive performance of the model to containing CKD-EPICR-CYS to predict pemetrexed clearance was good with a normalized root mean squared error and mean prediction error of 19.9% and 1.2%, respectively. Conclusions In conclusion, this study showed that the combined CKD-EPICR-CYS performs best in terms predicting pharmacokinetics of pemetrexed. Despite the hypothesized disadvantages, creatinine remains to be a suitable and readily available marker to predict pemetrexed clearance in clinical practice.
A comparison of the renal function biomarkers serum creatinine, pro-enkephalin and cystatin C to predict clearance of pemetrexed
Introduction For drugs with a narrow therapeutic window, there is a delicate balance between efficacy and toxicity, thus it is pivotal to administer the right dose from the first administration onwards. Exposure of pemetrexed, a cytotoxic drug used in lung cancer treatment, is dictated by kidney function. To facilitate optimized dosing of pemetrexed, accurate prediction of drug clearance is pivotal. Therefore, the aim of this study was to investigate the performance of the kidney function biomarkers serum creatinine, cystatin C and pro-enkephalin in terms of predicting the elimination of pemetrexed. Methods We performed a population pharmacokinetic analysis using a dataset from two clinical trials containing pharmacokinetic data of pemetrexed and measurements of all three biomarkers. A three-compartment model without covariates was fitted to the data and the obtained individual empirical Bayes estimates for pemetrexed clearance were considered the “true” values (Cltrue). Subsequently, the following algorithms were tested as covariates for pemetrexed clearance: the Chronic Kidney Disease Epidemiology Collaboration equation using creatinine (CKD-EPICR), cystatin C (CKD-EPICYS), a combination of both (CKD-EPICR-CYS), pro-enkephalin as an absolute value or in a combined algorithm with age and serum creatinine, and lastly, a combination of pro-enkephalin with cystatin C. Results The dataset consisted of 66 subjects with paired observations for all three kidney function biomarkers. Inclusion of CKD-EPICR-CYS as a covariate on pemetrexed clearance resulted in the best model fit, with the largest decrease in objective function (p < 0.00001) and explaining 35% of the total inter-individual variability in clearance. The predictive performance of the model to containing CKD-EPICR-CYS to predict pemetrexed clearance was good with a normalized root mean squared error and mean prediction error of 19.9% and 1.2%, respectively. Conclusions In conclusion, this study showed that the combined CKD-EPICR-CYS performs best in terms predicting pharmacokinetics of pemetrexed. Despite the hypothesized disadvantages, creatinine remains to be a suitable and readily available marker to predict pemetrexed clearance in clinical practice.
Proenkephalin A 119-159 (penKid) and mortality in stable patients at high cardiovascular risk
Background Proenkephalin A 119–159 (penKid) is a novel blood biomarker for real-time assessment of kidney function and was found to be independently associated with worsening kidney function and mortality. A novel penKid-based estimated GFR-equation (eGFRPENK-Crea), outperforms current creatinine-based eGFR equations in predicting iohexol or iothalamate plasma clearance based measured GFR (mGFR). In this study, we aimed to evaluate the predictive value of penKid and eGFRPENK-Crea for all-cause mortality in stable patients at high cardiovascular risk. Methods Circulating penKid levels were assessed in 615 stable patients hospitalized at the Department of Cardiology at University Hospital Aachen, Germany. The endpoint was all-cause mortality; follow up was 3 years. Results PenKid levels were higher in 46 non-survivors (58.8 [IQR 47.5–85.0] pmol/L) compared to 569 survivors (43.8 [IQR 34.0–58.0] pmol/L; P < 0.0001). Univariable cox regression analyses found penKid and eGFRPENK-Crea to be associated with all-cause mortality (C index: 0.703, χ2: 33.27, P < 0.00001; C index: 0.716, χ2: 36.51, P < 0.00001). This association remained significant after adjustment for significant baseline parameters including age, smoking, chronic heart failure, use of diuretics, leucocytes, body mass index, sex and creatinine (C index: 0.799, χ2: 72.06, P < 0.00001). Importantly, penKid provided significant added value on top of eGFRCKD-EPI 2021 (eGFRCKD-EPI 2021: C index: 0.716, χ2: 34.21; eGFRCKD-EPI 2021 + penKid: C index: 0.727, χ2: 40.02; Delta Chi2: 5.81; all P < 0.00001) for all-cause mortality prediction in our cohort. Conclusions PenKid levels and eGFRPENK-Crea is associated with all-cause mortality within a three-year follow-up period and the addition of penKid on top of eGFRCKD-EPI 2021 provided significant added value in mortality prediction.
Proenkephalin improves cardio-renal risk prediction in acute coronary syndromes: the KID-ACS score
Background and Aims Circulating proenkephalin (PENK) is a stable endogenous polypeptide with fast response to glomerular dysfunction and tubular damage. This study examined the predictive value of PENK for renal outcomes and mortality in patients with acute coronary syndrome (ACS). Methods Proenkephalin was measured in plasma in a prospective multicentre ACS cohort from Switzerland (n = 4787) and in validation cohorts from the UK (n = 1141), Czechia (n = 927), and Germany (n = 220). A biomarker-enhanced risk score (KID-ACS score) for simultaneous prediction of in-hospital acute kidney injury (AKI) and 30-day mortality was derived and externally validated. Results On multivariable adjustment for established risk factors, circulating PENK remained associated with in-hospital AKI [per log2 increase: adjusted odds ratio 1.53, 95% confidence interval (CI) 1.13–2.09, P = .007] and 30-day mortality (adjusted hazard ratio 2.73, 95% CI 1.85–4.02, P < .001). The KID-ACS score integrates PENK and showed an area under the receiver operating characteristic curve (AUC) of .72 (95% CI .68–.76) for in-hospital AKI and .91 (95% CI .87–.95) for 30-day mortality in the derivation cohort. Upon external validation, KID-ACS achieved similarly high performance for in-hospital AKI (Zurich: AUC .73, 95% CI .70–.77; Czechia: AUC .75, 95% CI .68–.81; Germany: AUC .71, 95% CI .55–.87) and 30-day mortality (UK: AUC .87, 95% CI .83–.91; Czechia: AUC .91, 95% CI .87–.94; Germany: AUC .96, 95% CI .92–1.00), outperforming the contrast-associated AKI score and the Global Registry of Acute Coronary Events 2.0 score, respectively. Conclusions Circulating PENK offers incremental value for predicting in-hospital AKI and mortality in ACS. The simple six-item KID-ACS risk score integrates PENK and provides a novel tool for simultaneous assessment of renal and mortality risk in patients with ACS.
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