Population pharmacokinetics of imipenem and attainment of pharmacokinetic/pharmacodynamic targets in adult patients with febrile neutropenia and hematological malignancies

Population pharmacokinetics of imipenem and attainment of pharmacokinetic/pharmacodynamic targets in adult patients with febrile neutropenia and hematological malignancies | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 20 May 2025 V1 Latest version Share on Population pharmacokinetics of imipenem and attainment of pharmacokinetic/pharmacodynamic targets in adult patients with febrile neutropenia and hematological malignancies Authors : Qi Rao , Hong Zhu , Lu Jin , huaijun zhu 0000-0002-3659-1282 , Fang Wu , Jie Zhou , Jinping Zhang , Siliang Wang , and Mengying Liu 0009-0007-2401-0421 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174772096.67704962/v1 246 views 145 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Aim: In this study, a population pharmacokinetic (PPK) model for imipenem was developed specifically for patients with febrile neutropenia 189 out of 250 words(FN) and hematological malignancies, with the aim of identifying optimal pharmacokinetic/pharmacodynamic (PK/PD) targets to predict antimicrobial efficacy and guide dosing regimens. Methods: A prospective, single-center, open-label study was conducted, analyzing 207 plasma samples from 121 Chinese patients with FN and hematological malignancies using chromatography. Pharmacokinetic parameters were evaluated using NONMEM to analyze the relationship between drug clearance and various patient-specific covariates. Results and conclusion: The analysis revealed that drug clearance was significantly impacted by creatinine clearance (CLCR), gamma-glutamyltransferase (GGT), and vancomycin (VAN) co-administration. The final PPK model was defined as follows: CL (L·h-1) = 21.36 × (CLCR/110.39)0.444 × (GGT/55.4)-0.119 + VAN × 3.78; central compartment volume (L) = 42.9; intercompartmental clearance (L·h-1) = 3.7; and peripheral compartment volume (L) = 59. The optimal PK/PD target for predicting imipenem’s antibacterial efficacy was determined to be an f%T > MIC of 90.48%. Therefore, dosing adjustments should account for CLCR, GGT levels, and VAN co-administration. For patients with infections caused by Pseudomonas aeruginosa or Acinetobacter baumannii, additional antimicrobial agents are recommended when necessary. Introduction Patients with febrile neutropenia (FN) and hematological malignancies are particularly vulnerable to complications arising from bacterial infections[1] Current guidelines[2] advise the prompt initiation of empirical antibiotic therapy in these high-risk individuals. Gram-negative bacterial infections continue to be a major cause of mortality in this population, especially when involving pathogens like Klebsiella pneumoniae , Pseudomonas aeruginosa , Acinetobacter baumannii , or Escherichia coli [3]. Notably, recent studies have underscored a decline in antimicrobial susceptibility, posing significant challenges to the clinical management of these infections[4, 5].Imipenem, a key agent within the carbapenem class of antibiotics, is recognized for its broad-spectrum efficacy and potent activity. This water-soluble drug exhibits approximately 20% protein binding, with approximately 70% excreted unchanged via renal pathways. In patients with normal renal function, its half-life is roughly 1 hour, classifying it as a time-dependent antimicrobial[6]. Due to its instability when administered alone, imipenem is commonly used in combination with cilastatin, which, while lacking antibacterial activity, preserves imipenem’s pharmacokinetic (PK) properties. The PK profile of imipenem in patients with malignant hematological diseases and fever undergoes significant alterations due to pathophysiological changes and medical interventions[7, 8]. These modifications are primarily reflected in the apparent volume of distribution (Vd) and clearance (CL), resulting in fluctuating drug concentrations[9]. Studies have demonstrated[10] that the incidence of augmented renal clearance (ARC) is higher in this patient population. Hirai et al. [11]dentified granulomatous deficiency with fever as a key risk factor for ARC development. Udy et al. [12] described ARC as increased renal CL, which may prevent antimicrobial agents from reaching therapeutic concentrations in suspected cases. Moreover, common conditions such as cachexia, hypoproteinemia, and pleural effusion in patients with malignant hematological disorders further expand the Vd of imipenem[13]. As a result, conventional dosing regimens may not achieve adequate drug exposure in patients with granulomatous deficiency and fever, highlighting the need for optimized, individualized dosing strategies. Carbapenem efficacy is driven by pharmacokinetic/pharmacodynamic (PK/PD) parameters[14], with the key parameters often used to evaluate their performance being: f %T > MIC (the proportion of the dosing interval during which the free drug concentration exceeds the minimum inhibitory concentration), f AUC/MIC (the ratio of the area under the concentration-time curve to the MIC), and f Cmin/MIC (the ratio of the trough concentration to the MIC). However, the optimal PK/PD targets for carbapenems remain debated[15, 16]. The conventional view[17] suggests bactericidal activity is achieved when f %T > MIC surpasses 40%, while Ariano et al. [18] propose that a threshold of 75% is necessary for optimal clinical and microbiological efficacy. For critically ill patients, C min /MIC > 1 and C min /MIC > 4 are frequently recommended[19], though the most appropriate PK/PD targets for predicting clinical and microbiological outcomes in FN individuals with hematological malignancies have not been conclusively established. Population pharmacokinetic (PPK) analysis has become an essential approach for optimizing individualized therapy, as it evaluates variability in drug concentrations among patients receiving clinically relevant doses[20, 21]. When combined with pharmacodynamic (PPK/PD) analysis and Monte Carlo simulations, it aids clinicians in determining suitable antibiotic dosing regimens to achieve optimal therapeutic results [22]. In this study, PPK/PD analysis of imipenem was performed in patients with FN and hematological malignancies, leading to optimized dosing strategies. Material and Methods Setting and Participants This single-center, prospective study enrolled patients with FN and hematological malignancies who were hospitalized at the Department of Hematology, Nanjing Drum Tower Hospital (Nanjing, China) between September 1, 2021, and December 31, 2022. Data collected from September 1, 2021, to August 31, 2022, were used for model development, while data from September 1, 2022, to December 31, 2022, served as external validation. Ethical approval was granted by the Ethics Committee of Nanjing Drum Tower Hospital (2021-583-01), and the trial was registered at clinicaltrials.gov (NCT05665478). Informed written consent was obtained from all participants, and the study adhered to the principles of the Declaration of Helsinki. The inclusion criteria were as follows: (1) diagnosis of malignant hematological disease[23]; (2) age ≥ 18 years, without gender restriction; (3) temperature exceeding 38.3°C and neutrophil count below 0.5 × 10 9 L -1 ; (4) confirmed bacterial infection with susceptibility to imipenem based on drug sensitivity testing, or empirical use of imipenem; and (5) administration of at least four doses of intravenous imipenem (Imipenem and Cilastatin Sodium for Injection, 500 mg/500 mg, Merck Sharp & Dohme Corp.). The exclusion criteria were as follows: (1) history of hypersensitivity to imipenem; (2) hemophagocytic syndrome; (3) ongoing renal replacement therapy; (4) incomplete clinical data (e.g., missing laboratory parameters, inability to collect blood samples); (5) interference in drug concentration determination (e.g., due to valproic acid, chloramphenicol); and (6) pregnancy or lactation. Data collection Patient data, including age, gender, body weight, liver and renal function indices, underlying diseases, comorbidities, and imipenem administration details (dose, infusion duration, treatment days, and dosing interval), were collected for model development and external evaluation. Creatinine clearance (CLCR) was calculated using the CDK-EPI formula[24]. Demographic characteristics were assessed for their influence on the pharmacokinetic model. The maximum daily dose of imipenem should not exceed 4 g and should be administered every 6 to 12 hours, with an infusion duration of 20 to 60 minutes. Thirty minutes before the administration of at least four doses of imipenem, 3 mL of whole blood was collected in a yellow-top tube containing procoagulant and separator gel, followed by centrifugation at 3000 rpm for 8 minutes. A volume of 300 μL of the upper serum layer was then precisely aspirated into a 1.5 mL centrifuge tube, to which 20 μL of internal standard working solution and 100 μL of stabilizer were added. The mixture was vortexed thoroughly and transferred to an ultrafiltration centrifuge tube for centrifugation at 12000 rpm for 10 minutes at 4°C. After centrifugation, 30 μL of the filtrate was collected for analysis [25]. The concentration of imipenem in the blood was determined using high-performance liquid chromatography[25]. Drug sensitivity test data Data on imipenem’s drug susceptibility and resistance against Gram-negative bacteria were obtained from the Clinical Microbiology Department at Nanjing Drum Tower Hospital. Body fluid specimens, including blood, secretions, sputum, and urine, were processed following standardized procedures, and minimum inhibitory concentration (MIC) values were determined using the twofold dilution method on agar or broth plates. Imipenem assay Imipenem concentrations in plasma were measured using a TSKgel ODS-100V chromatographic column (4.6 mm × 250 mm, 5 μm, Tosoh Corporation, Tokyo, Japan). The mobile phase consisted of methanol and 10 mmol·L -1 potassium phosphate monobasic (6:94, v/v, pH 6.7–7.0), with a flow rate of 0.9 mL·min -1 , UV detection at 300 nm, and a column temperature of 30°C. This method demonstrated excellent linearity (r = 0.9999) across imipenem concentrations ranging from 0.5013 to 50.13 μg·mL -1 . The relative standard deviation (RSD) for precision and stability tests was below 10%, conforming to standards for biological sample detection[25]. PPK modelling PPK models were developed using a non-linear mixed effects modeling approach, implemented with NONMEM ® Version 7.4 (Icon Development Solutions, Hanover, MD, USA). The model utilized the first-order conditional evaluation method with inter- and intrasubject variability interaction (FOCE-I). Pirana ® Version 3.0.0 (Pirana Software & Consulting BV, Utrecht, Netherlands) served as the interface[26], while Perl-speaks-NONMEM ® Version 5.3.0 (Uppsala University, Uppsala, Sweden) [27]facilitated model development and validation. Both one- and two-compartment models with first-order elimination were evaluated to identify the optimal structural model. Interindividual variability was modeled exponentially, while intraindividual (residual) variability was modeled proportionally. The objective function value (OFV), calculated as the -2 log likelihood, was used to assess the model’s overall fit. A decrease in OFV > 3.84 ( P 6.63 ( P < 0.01, d f = 1) was needed to retain the covariate during stepwise backward elimination. For categorical covariates, a piecewise model (Eq. (1)) was used. Continuous covariates were explored using various models, including linear (Eq. (2)), exponential (Eq. (3)), and power models (Eq. (4)): \(P=\left\{\par\begin{matrix}\end{matrix}\right.\ \) (1) \(P=\theta_{1}+\theta_{2}\times(COV-\text{COV}_{\text{median}})\)(2) \(P=\theta_{1}\times EXP\ (\theta_{2}\times(COV-\text{COV}_{\text{median}}))\)(3) \(P=\theta_{1}+{(COV/\text{COV}_{\text{median}})}^{\theta_{2}}\) (4) In this context, P represents the population value, θ 1 denotes the typical value for the population, COV is the value of the covariate, COV median indicates the median value of the covariate, and θ 2 is the correction factor for the covariate’s effect on the parameter. Model diagnostics were generated using R ® Version 4.1.3 (CRAN.R-project.org). Diagnostic plots, including dependent variables (DV) vs population predictions (PRED) or individual predictions (IPRED), and weighted residuals (WRES) vs PRED or time, were used to validate the final model. Bootstrap analysis with 1000 samples was conducted to assess model stability. Additionally, a visual predictive check (VPC) based on 1000 simulations was performed to further evaluate the model. External validation was conducted using demographic data from the validation cohort. Prediction errors (PEs) were calculated with the formula: PE = (PRED − DV)/DV. Model precision and accuracy were assessed through median prediction error (MDPE), median absolute prediction error (MAPE), and the percentage of |PE| within 20% (F 20 ) and 30% (F 30 ), as previously described[28]. The model was considered acceptable if MDPE was ≤ ±15%, MAPE ≤ 30%, F 20 > 35%, and F 30 > 50%. Calculation of individual PK and PK/PD parameters Individual patient PK values were estimated using the Maximum a Posteriori Bayesian (MAPB) method, and imipenem PK/PD parameters were calculated, including f Cmin/MIC, f %T > MIC, and f AUC 24h /MIC[29]. Assessment of efficacy The overall drug efficacy was categorized as either effective or ineffective based on clinical and microbiological outcomes evaluated at the end of treatment or prior to discharge. ”Effective” indicated both clinical cure and microbiological effectiveness, while ”ineffective” referred to cases that were clinically or microbiologically unsuccessful [30]. Clinical efficacy: (i) Cure: Improvement of infection-related symptoms and signs, as well as a reduction in infection markers (e.g., white blood cell count, C-reactive protein, calcitoninogen), compared with pre-treatment levels. Patients’ fever subsided, or their maximum temperature was below 38°C by the end of treatment, without requiring additional antimicrobial therapy; (ii) Ineffective: Continued deterioration of clinical symptoms, appearance of new infection-related signs, or the need for additional antimicrobial agents following the completion of imipenem treatment. Microbiological efficacy: (i) Effective: Bacterial clearance or presumed bacterial clearance; (ii) Ineffective: Bacterial non-clearance or presumed non-clearance. Bacterial clearance refers to the elimination of the causative organism during or after treatment, while presumed clearance occurs when clinical symptoms improve, but eradication of the causative organism cannot be confirmed. Bacterial non-clearance indicates failure to eradicate the original pathogen from the infection site. Presumed non-clearance refers to cases where clinical symptoms do not improve, and eradication of the pathogen remains uncertain. Monte Carlo simulation Monte Carlo simulations of 10,000 virtual patients were conducted using Crystal Ball Version 11.1.2.4 (Oracle Corporation, Denver, CO, USA) to evaluate different imipenem dosing regimens based on the final PK model.The dosing regimens were designed according to standard clinical practices and drug instructions as follows: ① 1.5 g·day -1 (500 mg q8h); ② 2 g·day -1 (500 mg q6h); ③ 2.25 g·day -1 (750 mg q8h); ④ 3 g·day -1 (750 mg q6h or 1000 mg q8h); and ⑤ 4 g·day -1 (1000 mg q6h). Infusion durations of 1 and 3 hours were tested. The Probability of Target Attainment (PTA) was defined as the likelihood that 10,000 simulated patients would achieve a specific PK/PD target. A regimen was deemed acceptable if PTA was ≥90%[31]. The PTA for a given MIC value was multiplied by the fraction of the clinical isolate population within that MIC category, with the sum of these products providing the cumulative fraction of response (CFR) [32]. A CFR between 80% and 90% indicated a moderate probability of success[33], whereas a CFR ≥90% signified an optimal dosing regimen against the target bacterial population. Statistical analysis Continuous variables were reported as mean ± standard deviation for normally distributed data, and median [P 25 , P 75 ] for non-normally distributed data. Categorical variables were presented as counts (percentages). Logistic regression analysis was performed to identify the optimal PK/PD parameters for predicting antimicrobial efficacy, with statistical significance set at P < 0.05. Receiver Operating Characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC ROC ) was calculated to assess the relationship between PK/PD parameters and antimicrobial efficacy. The Youden Index was used to determine the cut-off value for each PK/PD parameter. Demographics and clinical data Data were prospectively collected from patients with neutropenia and malignant hematological diseases who presented with fever between September 1, 2021, and December 31, 2022. A total of 121 patients were included, yielding 207 blood concentration observations after applying inclusion and exclusion criteria. The modeling dataset consisted of 152 observations from 87 patients, while 55 observations from 34 patients were used for external validation. Table 1 provides the baseline characteristics of the patients, and Online Supplementary Table S1 details their medication status. Microbiological detection Among the 60 patients with identified infections, 82 gram-negative bacterial isolates were detected, with Escherichia coli (30.49%), Klebsiella pneumoniae (18.29%), and Pseudomonas aeruginosa (10.98%) being the most common pathogens. Concurrent infections with multiple bacteria were observed in 21.67% of the patients. The primary infection sites included the lungs (55%), perianal region (3.33%), skin and soft tissue (1.67%), and the craniocerebral region (1.67%). In 5% of the patients, multiple infection sites were involved Online Supplementary Table S2. PPK analysis A two-compartment model was selected for imipenem PPK analysis, identifying CL, V1, Q, and V2 as the key parameters. The largest reduction in the OFV (-24.52) occurred when CLCR was incorporated into CL. Further inclusion of gamma-glutamyltransferase (GGT), apolipoprotein A1 (apoA1), and vancomycin (VAN) decreased OFV by 11.048, 6.451, and 6.991, respectively, but apoA1 was ultimately excluded after backward elimination. The final model is presented as follows: CL(L·h -1 ) =21.36×(CLCR/110.39) 0.444 ×(GGT/55.4) -0.119 +VAN×3.78 V1 (L)=42.9 Q (L·h -1 ) =3.9 V2 (L)=59 Goodness-of-fit plots for the final model (Figure 1) demonstrate that conditional weighted residuals (WRES) predominantly ranged between -2 and +2, with no apparent relationship with predicted values (PRED) or time. Additionally, predicted and individual predicted values (IPRED) exhibited a positive correlation with observed values (DV). The model’s stability is supported by bootstrap analysis, with parameter estimates summarized in Table 2. The visual predictive check (VPC) results show that most observed values fell within the 95% confidence interval (CI), indicating good predictive accuracy (Figure 2). External validation metrics, including a mean prediction error (MDPE) of 4%, mean absolute prediction error (MAPE) of 28%, F 20 of 38%, and F 30 of 52%, further confirm the model’s accuracy and precision. Evaluation of efficacy and PK/PD analysis The antibacterial efficacy of imipenem was determined to be 83.33%. Logistic regression analysis of PK/PD parameters, including f C min /MIC, f %T > MIC, and f AUC 24h /MIC, demonstrated that f %T > MIC was the most significant predictor of imipenem efficacy ( P = 0.003, OR = 1.159, 95% CI = 1.010–1.280), as shown in Table 3. The analysis revealed a strong correlation between f %T > MIC and antibacterial efficacy (AUC ROC = 0.728, P = 0.024). Furthermore, the optimal threshold for f %T > MIC was identified as 90.48%, corresponding to the highest efficacy (sensitivity: 0.96; specificity: 0.50). Monte Carlo simulation of dosage regimens Patients co-administered with VAN. Patients receiving VAN were stratified into six groups based on chronic kidney disease (CKD) stages, with GGT levels at the 25th percentile (29.27 U·L -1 ), median (53.94 U·L -1 ), and 75th percentile (108 U·L -1 ) used to evaluate drug efficacy. The simulations revealed that none of the dosing regimens met the standard when the MIC was 4 mg·L -1 . For the 4 g·d -1 regimen (1000 mg q6h, with 1-hour and 3-hour infusions), efficacy was achievable in CKD stages 3–5 when the MIC was 2 mg·L -1 . In CKD stage 2, only the 1000 mg q6h (3-hour infusion) regimen was effective at GGT levels of 29.27 U·L -1 or 53.94 U·L -1 , while at 108 U·L -1 , both 1-hour and 3-hour infusion regimens were effective. For patients with normal renal function, the regimen was only achievable at a GGT level of 108 U·L -1 . The 4 g·d -1 regimen failed to meet the standard in any patients with ARC. For the 3 g·d -1 regimen (750 mg q6h, 1000 mg q8h, with 1-hour and 3-hour infusions), the standard was met in CKD stages 4–5 when the MIC was 2 mg·L -1 . However, only the 3-hour infusion met the standard in CKD stage 4 at a GGT level of 29.27 U·L -1 . For the 2.25 g·d -1 regimen (750 mg q8h, with 1-hour and 3-hour infusions), efficacy was only achievable in CKD stage 5 patients with a GGT level of 108 U·L -1 when the MIC was 2 mg·L -1 . These results are summarized in Figure 3. The CFR for VAN combination regimens in patients with FN and hematological malignancies was further evaluated based on the MIC of common pathogens (Online Supplementary Table S3). For Escherichia coli , the 4 g·d -1 (1000 mg q6h) and 3 g·d -1 (750 mg q6h, 1000 mg q8h) regimens achieved sufficient CFR. For Klebsiella pneumoniae , the 4 g·d -1 (1000 mg q6h) regimen was also effective. However, none of the regimens achieved adequate CFR for Pseudomonas aeruginosa or Acinetobacter baumannii . Patients not co-administered with VAN. At an MIC of 4 mg·L -1 , only the 4 g·d -1 regimens (1000 mg q6h with 1-hour and 3-hour infusions) were effective in patients with CKD stage 5 and a GGT level of 180 U·L -1 . When the MIC was reduced to 2 mg·L -1 , the same 4 g·d -1 regimens were achievable across CKD stages 2–5. In patients with normal renal function, the regimen was effective at GGT levels of 53.94 U·L -1 and 108 U·L -1 , though only the 3-hour infusion met the standard for patients with a GGT of 29.27 U·L -1 . For patients with ARC, the 4 g·d -1 regimen met the standard only with the 3-hour infusion and a GGT level of 108 U·L -1 . For the 3 g·d -1 regimens (750 mg q6h, 1000 mg q8h with 1-hour and 3-hour infusions), efficacy was achieved in CKD stages 3–5 when the MIC was 2 mg·L -1 . However, in patients with CKD stage 3 exhibiting a GGT of 29.27 U·L -1 , only the 3-hour infusion regimen met the standard. In patients with CKD stage 2 exhibiting a GGT of 108 U·L -1 , the 3 g·d -1 regimens were effective as well. For the 2.25 g·d -1 regimens (750 mg q8h with 1-hour and 3-hour infusions), efficacy was only achieved in CKD stages 4–5 at an MIC of 2 mg·L -1 . No other patient groups met the standard. The results are summarized in Figure 4. Further evaluation of CFR for each dosing regimen targeting specific bacteria in patients not receiving concurrent VAN therapy revealed that, for Escherichia coli , the 4 g·d -1 (1000 mg q6h) and 3 g·d -1 (750 mg q6h, 1000 mg q8h) regimens achieved sufficient CFR. For Klebsiella pneumoniae , the 4 g·d -1 (1000 mg q6h) regimen also reached adequate CFR. In the case of Pseudomonas aeruginosa , only the 4 g·d -1 (1000 mg q6h) regimen was successful in patients with CKD stage 5, while no other regimens achieved adequate CFR. None of the evaluated regimens met the CFR standard for Acinetobacter baumannii . Detailed results are presented in Online Supplementary Table S4 with CFR values ≥ 80% highlighted in bold. Discussion This study presents the first PPK model developed specifically for Chinese patients with FN and hematological malignancies, identifying key covariates that significantly influence pharmacokinetic parameters. By integrating in vitro drug sensitivity data, the study establishes optimal parameters and targets for predicting imipenem’s antimicrobial efficacy in this population, with the goal of optimizing dosing regimens. The two-compartment model was found to more accurately describe the pharmacokinetics of imipenem in patients with FN and hematological malignancies, aligning with findings from several other studies[34, 35]. Among the clinical covariates analyzed, CLCR was confirmed as a significant factor affecting drug CL, consistent with previous research[34]. Additionally, the study revealed that GGT also significantly influences clearance. GGT, a cell surface enzyme involved in metabolizing extracellular glutathione, is a recognized marker of oxidative stress[36]. Elevated GGT levels, particularly in the presence of iron, may generate reactive oxygen species, potentially leading to renal vasoconstriction, reduced glomerular filtration rate, and impaired drug clearance[37]. However, the precise mechanisms underlying GGT’s impact on drug clearance remain underexplored and warrant further investigation. The study also found that the co-administration of VAN affected imipenem CL. According to guidelines[38], patients with FN and hematological malignancies at risk for Gram-positive cocci infections, such as those with imaging-confirmed pneumonia or skin and soft tissue infections, should receive antimicrobials targeting these pathogens, with VAN being a common choice. Both VAN and imipenem are renally excreted, and several studies [39, 40]suggest that imipenem and cilastatin are substrates of organic anion transporter proteins 1 (OAT1) and 3 (OAT3), with cilastatin reducing imipenem-induced nephrotoxicity by inhibiting OAT-mediated uptake[39]. This suggests that OAT transporters and cilastatin may be potential targets for improving the therapeutic efficacy and reducing the nephrotoxicity of imipenem[41]. Wang et al. [41] hypothesized that OAT transport is the rate-limiting step in imipenem’s renal elimination. Additionally, VAN’s renal excretion has been linked to OAT activity, leading to a hypothesized renal transporter interaction between VAN and imipenem. This interaction may promote imipenem’s renal excretion by modulating OAT activity, thereby increasing clearance and reducing drug concentration. However, further research is needed to validate this potential interaction. The pharmacokinetic parameters of imipenem in patients with FN and hematological malignancies were as follows: CL of 19.7 L·h -1 , central compartment volume of distribution (V1) of 42.9 L, intercompartmental clearance (Q) of 3.7 L·h -1 , and peripheral compartment volume of distribution (V2) of 59 L. Both CL and volume of distribution (Vd) were notably higher compared to those observed in healthy volunteers [42]. Online Supplementary Table S5 presents a summary of PPK studies on imipenem in various special populations. The elevated CL and Vd in this patient cohort can likely be attributed to their unique pathophysiological conditions and treatment regimens. For example, patients with FN and hematological malignancies often undergo aggressive hydration, alkalinization, and parenteral nutrition, leading to fluid overload that expands Vd. Additionally, these patients, especially those with acute leukemia, may experience renal hyperfunction, which can accelerate the clearance of hydrophilic antimicrobials—an observation consistent with our previous findings [43]. During the early phase of chemotherapy, the rapid lysis of tumor cells releases intracellular components, increasing the renal workload and potentially enhancing renal blood flow and filtration rates, thereby promoting drug elimination [44]. Furthermore, elevated clearance in FN individuals with hematological malignancies aligns with prior observations [45]. Notably, ARC was identified in over 25% of patients in this study, potentially leading to increased imipenem clearance and the risk of underexposure when standard dosing regimens are applied. The logistic analysis conducted in this study demonstrated that the optimal PK/PD parameter for assessing imipenem’s clinical efficacy is the free drug concentration over time ( f %T > MIC), a characteristic consistent with other time-dependent antimicrobials [18]. While specific PK/PD targets for imipenem in patients with FN and hematological malignancies have been largely absent from the literature, our findings indicate that achieving 90.48% f T > MIC offers the best efficacy. For a MIC of 2 mg·L -1 , the 4 g·d -1 (1000 mg q6h, 3-hour infusion) regimen was effective in patients with CKD stages 2–5, as well as in those with normal renal function and elevated GGT levels (108 U·L -1 ) when co-administered with VAN. The 3 g·d -1 (750 mg q8h, 1-hour and 3-hour infusions; and 1000 mg q6h, 3-hour infusion) regimen also achieved the target in patients with CKD stages 4–5 under similar conditions. In the absence of VAN, the 4 g·d -1 (1000 mg q6h, 3-hour infusion) regimen met the target in patients with CKD stages 2–5, normal renal function, and in those with ARC with a GGT level of 108 U·L -1 . Likewise, the 3 g·d -1 regimen (750 mg q8h, 1-hour and 3-hour infusions; and 1000 mg q6h, 3-hour infusion) was effective in CKD stages 3–5, and in patients with normal renal function and a GGT of 108 U·L -1 . Therefore, for an MIC of 2 mg·L -1 , the 4 g·d -1 (1000 mg q6h, 3-hour infusion) regimen is recommended for patients with CKD stages 2–5, those with normal renal function receiving VAN with a GGT level of 108 U·L -1 , and those with normal renal function not receiving VAN. Conversely, at an MIC of 4 mg·L -1 , most regimens failed to meet the efficacy threshold, with only the 4 g·d -1 (1000 mg q6h) regimen proving effective in CKD stage 5 patients without VAN co-administration. The observed MIC values were lower than in prior studies[46, 47], suggesting reduced bacterial sensitivity in patients with FN and hematological malignancies. The frequent use of broad-spectrum antimicrobials, such as carbapenems, in high-risk febrile patients may contribute to increased bacterial resistance and diminished drug susceptibility. As a result, the development of individualized dosing regimens for carbapenems is crucial for this vulnerable population. Monte Carlo simulations revealed that for patients receiving VAN, a 4 g·d -1 (1000 mg q6h) or a 3 g·d -1 (750 mg q8h or 1000 mg q6h) regimen is effective for Escherichia coli infections, while a 4 g·d -1 (1000 mg q6h) regimen is recommended for Klebsiella pneumoniae . In patients not receiving VAN, appropriate regimens for Escherichia coli include 4 g·d -1 (1000 mg q6h), 3 g·d -1 (750 mg q8h or 1000 mg q6h), and 2.25 g·d -1 (750 mg q8h, 3-hour infusion). For Klebsiella pneumoniae , the 4 g·d -1 (1000 mg q6h) regimen is recommended. However, none of the evaluated regimens met the efficacy standard for Pseudomonas aeruginosa or Acinetobacter baumannii . Previous research [48] shows that carbapenems are highly effective against Escherichia coli and Klebsiella pneumoniae , with low resistance rates, while resistance in Pseudomonas aeruginosa and Acinetobacter baumannii has risen to approximately 80% and 50%, respectively[49]. Consequently, combining additional antimicrobial agents is advised for treating infections caused by these resistant pathogens. Disclosures No conflicts of interest to disclose. Data Availability Statement Research data are not shared. Acknowledgments The authors wish to thank Bullet Edits Limited for linguistic editing and proofreading of the manuscript. Author contributions Conceptualization, Jinping Zhang, Siliang Wang and Mengying Liu; Data curation, Lu Jin, Fang Wu and Jie Zhou; Funding acquisition, Mengying Liu; Methodology, Lu Jin and Huaijun Zhu; Project administration, Siliang Wang and Mengying Liu; Supervision, Jinping Zhang, Siliang Wang and Mengying Liu; Validation, Huaijun Zhu; Writing – original draft, Qi Rao; Writing – review & editing, Qi Rao and Hong Zhu. Funding This research was supported by fundings for Clinical Trials from the Affiliated Drum Tower Hospital, Medical School of Nanjing University [grant number 2022-LCYJ-PY-48 and 2023-LCYJ-MS-32] and supported by Research Project established by Chinese Pharmaceutical Association Hospital Phamacy department. NO. CPA-Z05-ZC-2023002 References [1] Cojutti PG, Candoni A, Lazzarotto D, Filì C, Zannier M, Fanin R, et al. 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Modelling Validation P -value a Patients 121 87 34 - Age (years) 50.87±16.13 51.15±16.44 50.11±15.23 0.788 Sex (male/female) 82/39 61/26 21/13 0.377 Body weight (kg) 63.46±9.71 62.70±9.79 65.56±9.18 0.368 CLCR （mL·min -1 ·1.73 m -2 ） 109.64[95.25,124.77] 113.39[98.13,126.22] 103.78[79.01,116.33] 0.356 GGT（U·L -1 ） 53.94[29.27,108.00] 54.55[31.56,111.03] 46.80[25.95,105.45] 0.663 ARC patients 25（20.67） 20（22.99） 5（14.71） 0.312 Underlying disease 0.140 Acute myeloid leukaemia 53（43.80） 42（48.28） 11（32.35） - Lymphoma 29（23.97） 20（22.99） 9（26.47） - Acute lymphocytic leukaemia 15（12.40） 9（10.34） 6（17.65） - Multiple myeloma 15（12.40） 11（12.64） 4（11.76） - Myelodysplastic syndromes 8（6.61） 4（4.60） 4（11.76） - Others 1（0.83） 1（1.15） 0（0） - Imipenem blood drug concentration （mg·L -1 ） 1.40[0.70,2.85] 1.15[0.70,2.80] 2.00[1.25,2.90] 0.110 Concomitant medication Vancomycin 52（42.98） 41（47.13） 11（32.35） 0.140 Antiviral drugs 54（44.63） 39（44.83） 15（44.12） 0.944 Fluconazole 29（23.97） 17（19.54） 12（35.29） 0.068 Linezolid 22（18.18） 16（18.39） 6（17.65） 0.924 Hormone 20（16.53） 16（18.39） 4（11.76） 0.378 ARC, augmented renal clearance (defined as CLCR>130 mL·min -1 ·1.73 m -2 ); CLCR, creatinine clearance; GGT, gamma-glutamyltransferase. Data are presented as the mean ± standard deviation for normally distributed continuous variables and the median [P 25 ,P 75 ] for non-normally distributed variables. Data for dichotomous variables are expressed as n (%). a Pearson’s Chi-squared test was used to compare proportions, and Mann–Whitney U -test was used to compare continuous variables. Table 2. Final estimates of population pharmacokinetic parameters for imipenem. Estimate RSE(%) Shrinkage(%) 95% CI Median 95% CI OFV 132.050 - - - 121.388 38.457~190.838 CL(θ 1 ) 19.7 17.7 - 12.86~26.54 19.23 12.467~28.192 V 1 (θ 2 ) 42.9 37.5 - 11.344~74.456 41.81 18.266~108.545 Q (θ 3 ) 3.7 38.6 - 0.897~6.503 3.447 1.348~7.924 V 2 (θ 4 ) 59 42.9 - 9.412~108.588 57.238 21.554~185.086 CLCR on CL(θ 5 ) 0.444 11.2 - 0.347~0.541 0.441 0.286~0.594 GGT on CL (θ 6 ) -0.119 31.1 - -0.192~ -0.0465 -0.118 -0.213~ -0.046 VAN on CL (θ 7 ) 3.78 54.5 - -0.258~7.818 3.658 0.386~10.694 ω 1 0.0808 31.3 11.3 - 0.074 0.032~0.141 σ 0.162 16.6 17.7 - 0.157 0.106~0.212 CI, confidence interval; CL, total clearance; mean value of the fixed-effects parameter in the population; CLCR, creatinine clearance; GGT, gamma-glutamyltransferase; OFV, objective function value; Q, intercompartmental clearance; RSE, relative standard error; V1, central compartment volume of distribution; V2, peripheral compartment volume of distribution; VAN, vancomycin co-administration; ω, interindividual variable; σ, variance of residual variability. Table 3. Factors associated with imipenem efficacy and logistic regression analysis. OR 95% CI P f C min /MIC 390.40[124.36~470.97] 0.985 0.801~1.211 0.883 f %T > MIC 100% [100%~100%] 1.159 1.010~1.280 0.003 f AUC 24h /MIC 3.15[1.25~5.50] 0.998 0.992~1.003 0.402 Fig.1 Final model goodness-of-fit plots for imipenem. (a) Dependent variables vs population predictions (DV vs PRED)；(b) Dependent variables vs individual predictions (DV-IPRED)；(c) Conditional weighted residuals vs population predictions (CWRES vs PRED)；(d) Conditional weighted residuals vs time (CWRES-TIME). Fig.2 Final model VPC of imipenem concentration vs time. Black dots represent the observed imipenem concentrations. Lines represent the 10th, 50th, and 90th percentiles of the predictions, respectively. Shaded areas represent the 95% confidence interval of each line. Fig.3 Probability of target attainment for imipenem dosing regimens in FN patients co-administered with VAN. Fig.4 Probability of target attainment for imipenem dosing regimens in FN patients not co-administered with VAN. Supplementary Material File (image1.tif) Download 3.04 MB Information & Authors Information Version history V1 Version 1 20 May 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords clinical pharmacology clinical pharmacy pharmacotherapy therapeutics Authors Affiliations Qi Rao Nanjing Medical University View all articles by this author Hong Zhu Nanjing Drum Tower Hospital View all articles by this author Lu Jin Nanjing Drum Tower Hospital View all articles by this author huaijun zhu 0000-0002-3659-1282 Nanjing Drum Tower Hospital View all articles by this author Fang Wu China Pharmaceutical University View all articles by this author Jie Zhou The Affiliated Hospital of Yangzhou University School of Medicine View all articles by this author Jinping Zhang Nanjing Drum Tower Hospital View all articles by this author Siliang Wang Nanjing Drum Tower Hospital View all articles by this author Mengying Liu 0009-0007-2401-0421 [email protected] Nanjing Drum Tower Hospital View all articles by this author Metrics & Citations Metrics Article Usage 246 views 145 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Qi Rao, Hong Zhu, Lu Jin, et al. Population pharmacokinetics of imipenem and attainment of pharmacokinetic/pharmacodynamic targets in adult patients with febrile neutropenia and hematological malignancies. Authorea . 20 May 2025. DOI: https://doi.org/10.22541/au.174772096.67704962/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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