A simple scoring method to predict augmented renal clearance in haematologic malignancies

Abstract

What is known and objective Augmented renal clearance (ARC; hyperfiltration with over 130 mL/min/1.73 m2 of creatinine clearance (CLcr)) commonly occurs in critically ill patients. Recent reports indicate that ARC also occurs in haematologic malignancies. However, the risk factors for ARC in haematologic malignancies remain unknown, and there is no established method to predict ARC in haematologic malignancies. Our objective was to explore the risk factors for ARC retrospectively and develop a scoring method to predict ARC. Methods A single‐centre, retrospective, observational cohort study was conducted at the Sendai Medical Center (Sendai, Japan); 133 patients (April 2017‐March 2019) and 41 patients (April‐November 2019) with haematopoietic tumours who were administered vancomycin were enrolled in the analysis and validation cohorts, respectively. To define ARC, we calculated the vancomycin serum concentration when CLcr = 130 mL/min/1.73 m2 using a one‐compartment model. Patients with ARC were defined as those whose actual concentration of vancomycin remained lower than the calculated concentration. Using the analysis cohort, we explored risk factors of ARC and developed a scoring method to predict ARC in haematologic malignancies. The reproducibility of the scoring system was demonstrated using the validation cohort. Results and discussion Through multivariate analysis, young age (P < .001), leukaemia (P = .001) and low serum creatinine (P < .001) were identified as risk factors. According to this result, we established the ARC detection method: age ≤ 50 years = 3 points, 50 years < age ≤65 years = 1 point, leukaemia = 2 points, low SCr = 2 points; patients scoring ≥ 5 points represent the ARC high‐risk group. Using this scoring system, we could detect ARC with a sensitivity and specificity of 60.0% and 89.7% in the analysis cohort and 90.0% and 90.9% in the validation cohort, respectively. What is new and conclusion Our scoring method could predict ARC in haematologic malignancies and is useful as a simple screening tool for ARC.

A Regression Model to Predict Augmented Renal Clearance in Critically Ill Obstetric Patients and Effects on Vancomycin Treatment

“…According to the risk factor analysis, many studies have established ARC detection methods, like a scoring method or model (Bilbao-Meseguer et al, 2018;Saito et al, 2020). In our study, ROC curves for single risk factor indicated that the predictive value is not significant, so we established a regression model with nine factors to identify the ARC in critically ill obstetric patients.…”

Augmented renal clearance in critically ill patients with cancer (ARCCAN Study): A prospective observational study evaluating prevalence and risk factors

“…21,22 Unlike previous studies, hematological malignancies, neutropenia, gender, and the severity of illness were not significant predictors in the ARCCAN study. 7,9,10,17,21,22 This makes it challenging for clinicians to predict who may have ARC upon admission to the ICU among a patient population in which sepsis is a common admission diagnosis and in whom the timely administration of appropriate doses of antimicrobial therapy is critical. This calls for the need of additional studies to better understand ARC in this unique population.…”

“…Febrile neutropenia has been reported as an independent risk factor for ARC 7 . In addition, neutropenia and hematological malignancies have been associated with increased clearance of several antimicrobials, suggesting augmented renal clearance 8‐10 . However, those studies had relatively small sample sizes and evaluated non‐critically ill patients.…”

“…7 In addition, neutropenia and hematological malignancies have been associated with increased clearance of several antimicrobials, suggesting augmented renal clearance. [8][9][10] However, those studies had relatively small sample sizes and evaluated non-critically ill patients. In addition, the renal function was determined based on the mathematical equations for estimating renal function rather than measured creatinine clearance, which is a methodology that is recognized as being inaccurate in estimating renal function and augmented renal clearance in the critically ill patient population.…”

Augmented Renal Clearance: What Have We Known and What Will We Do?

“…There are many studies showed that the at-risk groups for ARC include younger patients, especially younger male patients, with lower illness severity scores on the Sequential Organ Failure Assessment (SOFA) or Acute Physiology and Chronic Health Evaluation (APACHE) II ( Udy et al, 2013 , 2017 ; Baptista et al, 2020 ; Nei et al, 2020 ; Saito et al, 2020 ; Johnston et al, 2021 ). Disease-related risk factors include trauma, surgery, sepsis, burn, subarachnoid hemorrhage, and hematological malignancy ( Gerlach et al, 2019 ; Morbitzer et al, 2019 ; Lannou et al, 2020a ; Saito et al, 2020 ).…”