Search

Background We evaluated whether carbapenem-colistin combination therapy reduces the emergence of colistin resistance, compared to colistin monotherapy, when given to patients with infections due to carbapenem-resistant Gram-negative organisms. Methods This is a pre-planned analysis of a secondary outcome from a randomized, controlled trial comparing colistin monotherapy with colistin-meropenem combination for the treatment of severe infections caused by carbapenem-resistant, colistin-susceptible Gram-negative bacteria. We evaluated rectal swabs taken on Day 7 or later for the presence of new colistin-resistant (ColR) isolates. We evaluated the emergence of any ColR isolate and the emergence of ColR Enterobacteriaceae (ColR-E). Results Data were available for 214 patients for the primary analysis; emergent ColR organisms were detected in 22 (10.3%). No difference was observed between patients randomized to treatment with colistin monotherapy (10/106, 9.4%) versus patients randomized to colistin-meropenem combination therapy (12/108, 11.1%; P =.669). ColR-E organisms were detected in 18/249 (7.2%) patients available for analysis. No difference was observed between the 2 treatment arms (colistin monotherapy 6/128 [4.7%] vs combination therapy 12/121 [9.9%]; P =.111). Enterobacteriaceae, as the index isolate, was found to be associated with development of ColR-E (hazard ratio, 3.875; 95% confidence interval, 1.475–10.184; P =.006). Conclusions Carbapenem-colistin combination therapy did not reduce the incidence of colistin resistance emergence in patients with infections due to carbapenem-resistant organisms. Further studies are necessary to elucidate the development of colistin resistance and methods for its prevention. [ABSTRACT FROM AUTHOR]

Background We evaluated the association between mortality and colistin resistance in Acinetobacter baumannii infections and the interaction with antibiotic therapy. Methods This is a secondary analysis of a randomized controlled trial of patients with carbapenem-resistant gram-negative bacterial infections treated with colistin or colistin-meropenem combination. We evaluated patients with infection caused by carbapenem-resistant A. baumannii (CRAB) identified as colistin susceptible (CoS) at the time of treatment and compared patients in which the isolate was confirmed as CoS with those whose isolates were retrospectively identified as colistin resistant (CoR) when tested by broth microdilution (BMD). The primary outcome was 28-day mortality. Results Data were available for 266 patients (214 CoS and 52 CoR isolates). Patients with CoR isolates had higher baseline functional capacity and lower rates of mechanical ventilation than patients with CoS isolates. All-cause 28-day mortality was 42.3% (22/52) among patients with CoR strains and 52.8% (113/214) among patients with CoS isolates (P =.174). After adjusting for variables associated with mortality, the mortality rate was lower among patients with CoR isolates (odds ratio [OR], 0.285 [95% confidence interval {CI},.118–.686]). This difference was associated with treatment arm: Mortality rates among patients with CoR isolates were higher in those randomized to colistin-meropenem combination therapy compared to colistin monotherapy (OR, 3.065 [95% CI, 1.021–9.202]). Conclusions Colistin resistance determined by BMD was associated with lower mortality among patients with severe CRAB infections. Among patients with CoR isolates, colistin monotherapy was associated with a better outcome compared to colistin-meropenem combination therapy. Clinical Trials Registration NCT01732250 [ABSTRACT FROM AUTHOR]

To assess circulating biomarkers as predictors of antitumor response to atezolizumab (anti‐programmed death‐ligand 1 (PD‐L1), Tecentriq) serum pharmacokinetic (PK) and 95 plasma biomarkers were analyzed in 88 patients with relapsed/refractory non‐small cell lung cancer (NSCLC) receiving atezolizumab i.v. q3w (10–20 mg/kg) in the PCD4989g phase I clinical trial. Following exploratory analyses, two plasma biomarkers were chosen for further study and correlation with change in tumor size (the sum of the longest diameter) was assessed in a pharmacokinetic/pharmacodynamic (PK/PD) tumor modeling framework. When longitudinal kinetics of biomarkers and tumor size were modeled, tumor shrinkage was found to significantly correlate with area under the curve (AUC), baseline factors (metastatic sites, liver metastases, and smoking status), and relative change in interleukin (IL)‐18 level from baseline at day 21 (RCFBIL‐18,d21). Although AUC was a major predictor of tumor shrinkage, the effect was estimated to dissipate with an average half‐life of 80 days, whereas RCFBIL‐18,d21 seemed relevant to the duration of the response. [ABSTRACT FROM AUTHOR]

In 2012, a new journal was launched from the ASCPT family, CPT: Pharmacometrics and Systems Pharmacology (PSP) as both quantitative system pharmacology (QSP) and pharmacometrics were growing fields in pharmacology, drug development, and drug use. In this Perspective, the present editors and associate editors of PSP want to share their strategic vision of where these two fields, separately and together, should, would, or could be 10 years from now. [ABSTRACT FROM AUTHOR]

AIMS Early identification of patients with febrile neutropenia (FN) is desirable for initiation of preventive treatment, such as with antibiotics. In this study, the time courses of two inflammation biomarkers, interleukin (IL)-6 and C-reactive protein (CRP), following adjuvant chemotherapy of breast cancer, were characterized. The potential to predict development of FN by IL-6 and CRP, and other model-derived and clinical variables, was explored. METHODS The IL-6 and CRP time courses in cycles 1 and 4 of breast cancer treatment were described by turnover models where the probability for an elevated production following initiation of chemotherapy was estimated. Parametric time-to-event models were developed to describe FN occurrence to assess: (i) predictors available before chemotherapy is initiated; (ii) predictors available before FN occurs; and (iii) predictors available when FN occurs. RESULTS The IL-6 and CRP time courses were successfully characterized with peak IL-6 typically occurring 2 days prior to CRP peak. Of all evaluated variables the CRP time course was most closely associated with the occurrence of FN. Since the CRP peak typically occurred at the time of FN diagnosis it will, however, have limited value for identifying the need for preventive treatment. The time course of IL-6 was the predictor that could best forecast FN events. Of the variables available at baseline, age was the best, although in comparison a relatively weak, predictor. CONCLUSIONS The developed models add quantitative knowledge about IL-6 and CRP and their relationship to the development of FN. The study suggests that IL-6 may have potential as a clinical predictor of FN if monitored during myelosuppressive chemotherapy. [ABSTRACT FROM AUTHOR]

Background: Pharmacokinetic/pharmacodynamic (PKPD) models developed based on data from in vitro time-kill experiments have been suggested to contribute to more efficient drug development programmes and better dosing strategies for antibiotics. However, for satisfactory predictions such models would have to show good extrapolation properties.Objectives: To evaluate if a previously described mechanism-based PKPD model was able also to predict drug efficacy for higher bacterial densities and across bacterial strains.Methods: A PKPD model describing the efficacy of ciprofloxacin on Escherichia coli was evaluated. The predictive performance of the model was evaluated across several experimental conditions with respect to: (i) bacterial start inoculum ranging from the standard of ∼106 cfu/mL up to late stationary-phase cultures; and (ii) efficacy for seven additional strains (three laboratory and four clinical strains), not included during the model development process, based only on information regarding their MIC. Model predictions were performed according to the intended experimental protocol and later compared with observed bacterial counts.Results: The mechanism-based PKPD model structure developed based on data from standard start inoculum experiments was able to accurately describe the inoculum effect. The model successfully predicted the time course of drug efficacy for additional laboratory and clinical strains based on only the MIC values. The model structure was further developed to better describe the stationary phase data.Conclusions: This study supports the use of mechanism-based PKPD models based on preclinical data for predictions of untested scenarios. [ABSTRACT FROM AUTHOR]

Neutrophil granulocytes are key components of the host response against pathogens, and severe neutropenia, with neutrophil counts below 0.5 × 106 cells/mL, renders patients increasingly vulnerable to infections. Published in vitro (n = 7) and in vivo (n = 5) studies with time‐course information on bacterial and neutrophil counts were digitized to characterize the kinetics of neutrophil‐mediated bacterial killing and inform on the immune systems' contribution to the clearance of bacterial infections. A mathematical model for the in vitro dynamics of bacteria and the kinetics of neutrophil‐mediated phagocytosis and digestion was developed, which was extended to in vivo studies in immune‐competent and immune‐compromised mice. Neutrophil‐mediated bacterial killing was described by two first‐order processes—phagocytosis and digestion—scaled by neutrophil concentration, where 50% of the maximum was achieved at neutrophil counts of 1.19 × 106 cells/mL (phagocytosis) and 6.55 × 106 cells/mL (digestion). The process efficiencies diminished as the phagocytosed bacteria to total neutrophils ratio increased (with 50% reduction at a ratio of 3.41). Neutrophil in vivo dynamics were captured through the characterization of myelosuppressive drug effects and postinoculation neutrophil influx into lungs and by system differences (27% bacterial growth and 9.3% maximum capacity, compared with in vitro estimates). Predictions showed how the therapeutically induced reduction of neutrophil counts enabled bacterial growth, especially when falling below 0.5 × 106 cells/mL, whereas control individuals could deal with all tested bacterial burdens (up to 109 colony forming units/g lung). The model‐based characterization of neutrophil‐mediated bacterial killing simultaneously predicted data across in vitro and in vivo studies and may be used to inform the capacity of host–response at the individual level. [ABSTRACT FROM AUTHOR]

Purpose: To investigate whether a more frequent monitoring of the absolute neutrophil counts (ANC) during myelosuppressive chemotherapy, together with model-based predictions, can improve therapy management, compared to the limited clinical monitoring typically applied today.Methods: Daily ANC in chemotherapy-treated cancer patients were simulated from a previously published population model describing docetaxel-induced myelosuppression. The simulated values were used to generate predictions of the individual ANC time-courses, given the myelosuppression model. The accuracy of the predicted ANC was evaluated under a range of conditions with reduced amount of ANC measurements.Results: The predictions were most accurate when more data were available for generating the predictions and when making short forecasts. The inaccuracy of ANC predictions was highest around nadir, although a high sensitivity (≥90%) was demonstrated to forecast Grade 4 neutropenia before it occurred. The time for a patient to recover to baseline could be well forecasted 6 days (±1 day) before the typical value occurred on day 17.Conclusions: Daily monitoring of the ANC, together with model-based predictions, could improve anticancer drug treatment by identifying patients at risk for severe neutropenia and predicting when the next cycle could be initiated. [ABSTRACT FROM AUTHOR]

Background:In view of the paucity of clinical evidence,in vitrostudies are needed to find antibiotic combinations effective against multidrug-resistant Gram-negative bacteria. Interpretation ofin vitroeffects is usually based on bacterial growth after 24 h in time-kill and checkerboard experiments. However, the clinical relevance of the effects observedin vitrois not established. In this study we explored alternative output parameters to assess the activities of colistin and meropenem againstPseudomonas aeruginosaandAcinetobacter baumannii. Methods:Four strains each ofP. aeruginosaandA. baumanniiwere exposed to colistin and meropenem, alone and in combination, in 8 h dynamic time-kill experiments. Initial (1 h), maximum and 8 h bacterial reductions and the area under the bacterial time-kill curve were evaluated. Checkerboards, interpreted based on fractional inhibitory concentration indices after 24 h, were performed for comparison. Results:In the time-kill experiments, the combination resulted in enhanced 1 h, maximum and 8 h bacterial reductions against 2, 3 and 5 of 8 strains, respectively, as compared to the single drugs. A statistically significant reduction in the area under the time-kill curve was observed for three strains. In contrast, the checkerboards did not identify synergy for any of the strains. Conclusions:Combination effects were frequently found with colistin and meropenem againstP. aeruginosaand A.baumanniiin time-kill experiments but were not detected with the checkerboard method. We propose that the early dynamics of bacterial killing and growth, which may be of great clinical importance, should be considered in futurein vitrocombination studies. [ABSTRACT FROM PUBLISHER]

Correction to: I Scientific Reports i https://doi.org/10.1038/s41598-022-08012-7, published online 10 March 2022 The original version of this Article contained errors in Table 1 where the data was listed incorrectly in the column "M I KRAS i patients". [Extracted from the article]

Objectives: For antibiotics, extensive animal PKPD studies are often performed to evaluate the PK/PD driver for subsequent use when recommending dosing regimens. The aim of this work was to evaluate a PKPD model, developed based on in vitro time-kill data for colistin, in predicting the relationships between PK/PD indices and the bacterial killing previously observed in mice.Methods: An in silico PKPD model for Pseudomonas aeruginosa exposed to colistin was previously developed based on static in vitro time-kill data. The model was here applied to perform an in silico replication of an in vivo study where the effect of colistin on P. aeruginosa was studied in the thigh infection model. Concentration-time profiles of unbound colistin were predicted and used as input to drive the bacterial killing in the PKPD model. The predicted bacterial count at 24 h was related to each of the PK/PD indices and the results were compared with reported observations in vivo.Results: The model was found to adequately predict in vivo results from mice; both in terms of which PK/PD index best correlates to effect (fAUC/MIC) as well as the magnitude needed for a 2 log kill. The fAUC/MIC needed to achieve a 2 log reduction in bacterial counts after 24 h was here predicted to be 9 compared with 31 previously reported in vivo.Conclusions: This study provides further support that PKPD models based on longitudinal data can be a useful tool to make drug development more efficient within the infectious diseases area. [ABSTRACT FROM AUTHOR]

Ibrutinib is a Bruton tyrosine kinase (Btk) inhibitor for treating chronic lymphocytic leukemia (CLL). It has also been associated with hypertension. The optimal dosing schedule for mitigating this adverse effect is currently under discussion. A quantification of relationships between systemic ibrutinib exposure and efficacy (i.e., leukocyte count and sum of the product of perpendicular diameters [SPD] of lymph nodes) and hypertension toxicity (i.e., blood pressure), and their association with overall survival is needed. Here, we present a semi‐mechanistic pharmacokinetic‐pharmacodynamic modeling framework to characterize such relationships and facilitate dose optimization. Data from a phase Ib/II study were used, including ibrutinib plasma concentrations to derive daily 0–24‐h area under the concentration‐time curve, leukocyte count, SPD, survival, and blood pressure measurements. A nonlinear mixed effects modeling approach was applied, considering ibrutinib's pharmacological action and CLL cell dynamics. The final framework included (i) an integrated model for SPD and leukocytes consisting of four CLL cell subpopulations with ibrutinib inhibiting phosphorylated Btk production, (ii) a turnover model in which ibrutinib stimulates an increase in blood pressure, and (iii) a competing risk model for dropout and death. Simulations predicted that the approved dosing schedule had a slightly higher efficacy (24‐month, progression‐free survival [PFS] 98%) than de‐escalation schedules (24‐month, average PFS ≈ 97%); the latter had, on average, ≈20% lower proportions of patients with hypertension. The developed modeling framework offers an improved understanding of the relationships among ibrutinib exposure, efficacy and toxicity biomarkers. This framework can serve as a platform to assess dosing schedules in a biologically plausible manner. [ABSTRACT FROM AUTHOR]