Saturable elimination of piperacillin in critically ill patients:implications for continuous infusion

The study aimed to evaluate saturation of piperacillin elimination in critically ill adult patients. Seventeen critically ill adult patients received continuous and intermittent infusion of piperacillin/tazobactam. Piperacillin plasma concentrations (n = 217) were analysed using population pharmacokinetic (PopPK) modelling. Post-hoc simulations were performed to evaluate the type I error rate associated with the study. Unseen data were used to validate the final model. The mean error (ME) and root mean square error (RMSE) were calculated as a measure of bias and imprecision, respectively. A PopPK model with parallel linear and non-linear elimination best fitted the data. The median and 95% confidence interval (CI) for the model parameters drug clearance (CL), volume of central compartment (V), volume of peripheral compartment (V-p) and intercompartmental clearance (Q) were 9 (7.69-11) L/h, 6.18 (4.93-11.2) L, 11.17 (7.26-12) L and 15.61 (12.66-23.8) L/h, respectively. The Michaelis-Menten constant (K-m) and the maximum elimination rate for Michaelis-Menten elimination (V-max) were estimated without population variability in the model to avoid overfitting and inflation of the type I error rate. The population estimates for K-m and V-max were 37.09 mg/L and 353.57 mg/h, respectively. The bias (ME) was -20.8 (95% CI -26.2 to -15.4) mg/L, whilst imprecision (RMSE) was 49.2 (95% CI 41.2-56) mg/L. In conclusion, piperacillin elimination is (partially) saturable. Moreover, the population estimate for K-m lies within the therapeutic window and therefore saturation of elimination should be accounted for when defining optimum dosing regimens for piperacillin in critically ill patients. (C) 2019 Elsevier B.V. and International Society of Chemotherapy. All rights reserved

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

Background: Beta-lactam antimicrobial concentrations are frequently suboptimal in critically ill patients. Population pharmacokinetic (PopPK) modeling is the golden standard to predict drug concentrations. However, currently available PopPK models often lack predictive accuracy, making them less suited to guide dosing regimen adaptations. Furthermore, many currently developed models for clinical applications often lack uncertainty quantification. We, therefore, aimed to develop machine learning (ML) models for the prediction of piperacillin plasma concentrations while also providing uncertainty quantification with the aim of clinical practice. Methods: Blood samples for piperacillin analysis were prospectively collected from critically ill patients receiving continuous infusion of piperacillin/tazobactam. Interpretable ML models for the prediction of piperacillin concentrations were designed using CatBoost and Gaussian processes. Distribution-based Uncertainty Quantification was added to the CatBoost model using a proposed Quantile Ensemble method, useable for any model optimizing a quantile function. These models are subsequently evaluated using the distribution coverage error, a proposed interpretable uncertainty quantification calibration metric. Development and internal evaluation of the ML models were performed on the Ghent University Hospital database (752 piperacillin concentrations from 282 patients). Ensuing, ML models were compared with a published PopPK model on a database from the University Medical Centre of Groningen where a different dosing regimen is used (46 piperacillin concentrations from 15 patients.). Results: The best performing model was the Catboost model with an RMSE and R-2 of 31.94-0.64 and 33.53-0.60 for internal evaluation with and without previous concentration. Furthermore, the results prove the added value of the proposed Quantile Ensemble model in providing clinically useful individualized uncertainty predictions and show the limits of homoscedastic methods like Gaussian Processes in clinical applications. Conclusions: Our results show that ML models can consistently estimate piperacillin concentrations with acceptable and high predictive accuracy when identical dosing regimens as in the training data are used while providing highly relevant uncertainty predictions. However, generalization capabilities to other dosing schemes are limited. Notwithstanding, incorporating ML models in therapeutic drug monitoring programs seems definitely promising and the current work provides a basis for validating the model in clinical practice

A simulation study reveals lack of pharmacokinetic/pharmacodynamic target attainment in de-escalated antibiotic therapy in critically ill patients

De-escalation of empirical antibiotic therapy is often included in antimicrobial stewardship programs in critically ill patients, but differences in target attainment when antibiotics are switched are rarely considered. The primary objective of this study was to compare the fractional target attainments of contemporary dosing of empirical broad-spectrum β-lactam antibiotics and narrower-spectrum antibiotics for a number pathogens for which de-escalation may be considered. The secondary objective was to determine whether alternative dosing strategies improve target attainment. We performed a simulation study using published population pharmacokinetic (PK) studies in critically ill patients for a number of broad-spectrum β-lactam antibiotics and narrower-spectrum antibiotics. Simulations were undertaken using a data set obtained from critically ill patients with sepsis without absolute renal failure (n = 49). The probability of target attainment of antibiotic therapy for different microorganisms for which de-escalation was applied was analyzed. EUCAST MIC distribution data were used to calculate fractional target attainment. The probability that therapeutic exposure will be achieved was lower for the narrower-spectrum antibiotics with conventional dosing than for the broad-spectrum alternatives and could drastically be improved with higher dosages and different modes of administrations. For a selection of microorganisms, the probability that therapeutic exposure will be achieved was overall lower for the narrower-spectrum antibiotics using conventional dosing than for the broad-spectrum antibiotics

Drawing Boundaries

In “On Drawing Lines on a Map” (1995), I suggested that the different ways we have of drawing lines on maps open up a new perspective on ontology, resting on a distinction between two sorts of boundaries: fiat and bona fide. “Fiat” means, roughly: human-demarcation-induced. “Bona fide” means, again roughly: a boundary constituted by some real physical discontinuity. I presented a general typology of boundaries based on this opposition and showed how it generates a corresponding typology of the different sorts of objects which boundaries determine or demarcate. In this paper, I describe how the theory of fiat boundaries has evolved since 1995, how it has been applied in areas such as property law and political geography, and how it is being used in contemporary work in formal and applied ontology, especially within the framework of Basic Formal Ontology

Protective effects of antiâ C5a peptide antibodies in experimental sepsis

We evaluated antibodies to different peptide regions of rat C5a in the sepsis model of cecal ligation and puncture (CLP) for their protective effects in rats. Rabbit polyclonal antibodies were developed to the following peptide regions of rat C5a: aminoâ terminal region (A), residues 1â 16; middle region (M), residues 17â 36; and the carboxylâ terminal region (C), residues 58â 77. With rat neutrophils, the chemotactic activity of rat C5a was significantly inhibited by antibodies with the following rank order: antiâ C > antiâ M â « antiâ A. In vivo, antibodies to the M and C (but not A) regions of C5a were protective in experimental sepsis, as determined by survival over a 10â day period, in a doseâ dependent manner. The relative protective efficacies of antiâ C5a preparations (in descending order of efficacy) were antiâ C â ¥ antiâ M â « antiâ A. In CLP rats, a delay in infusion of antibodies, which were injected at 6 or 12 h after CLP, still resulted in significant improvement in survival rates. These in vivo and in vitro data suggest that there are optimal targets on C5a for blockade during sepsis and that delayed infusion of antiâ C5a antibody until after onset of clinical evidence of sepsis still provides protective effects.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154417/1/fsb2fj000653fje-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154417/2/fsb2fj000653fje.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154417/3/fsb2fj000653fje-sup-0002.pd

HER2 therapy. HER2 (ERBB2): functional diversity from structurally conserved building blocks

EGFR-type receptor tyrosine kinases achieve a broad spectrum of cellular responses by utilizing a set of structurally conserved building blocks. Based on available crystal structures and biochemical information, significant new insights have emerged into modes of receptor control, its deregulation in cancer, and the nuances that differentiate the four human receptors. This review gives an overview of current models of the control of receptor activity with a special emphasis on HER2 and HER3

Plasma Biomarkers of Brain Atrophy in Alzheimer's Disease

Peripheral biomarkers of Alzheimer's disease (AD) reflecting early neuropathological change are critical to the development of treatments for this condition. The most widely used indicator of AD pathology in life at present is neuroimaging evidence of brain atrophy. We therefore performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD. Using gel based proteomics we previously identified seven plasma proteins that were significantly associated with hippocampal volume in a combined cohort of subjects with AD (N = 27) and MCI (N = 17). In the current report, we validated this finding in a large independent cohort of AD (N = 79), MCI (N = 88) and control (N = 95) subjects using alternative complementary methods—quantitative immunoassays for protein concentrations and estimation of pathology by whole brain volume. We confirmed that plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients. These proteins are complement components C3 and C3a, complement factor-I, γ-fibrinogen and alpha-1-microglobulin. Our findings suggest that these plasma proteins are strong predictors of in vivo AD pathology. Moreover, these proteins are involved in complement activation and coagulation, providing further evidence for an intrinsic role of these pathways in AD pathogenesis

Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure “just-in-time” assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract “single-cell”-like information from population-level time-series expression data. This method removes the effects of 1) variance in growth rate and 2) variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell

Proceedings of the International Cancer Imaging Society (ICIS) 16th Annual Teaching Course

Table of contents O1 Tumour heterogeneity: what does it mean? Dow-Mu Koh O2 Skeletal sequelae in adult survivors of childhood cancer Sue Creviston Kaste O3 Locoregional effects of breast cancer treatment Sarah J Vinnicombe O4 Imaging of cancer therapy-induced CNS toxicity Giovanni Morana, Andrea Rossi O5 Screening for lung cancer Christian J. Herold O6Risk stratification of lung nodules Theresa C. McLoud O7 PET imaging of pulmonary nodules Kirk A Frey O8 Transarterial tumour therapy Bernhard Gebauer O9 Interventional radiology in paediatric oncology Derek Roebuck O10 Image guided prostate interventions Jurgen J. Fütterer O11 Imaging cancer predisposition syndromes Alexander J. Towbin O12Chest and chest wall masses Thierry AG Huisman O13 Abdominal masses: good or bad? Anne MJB Smets O14 Hepatobiliary MR contrast: enhanced liver MRI for HCC diagnosis and management Giovanni Morana O15 Role of US elastography and multimodality fusion for managing patients with chronic liver disease and HCC Jeong Min Lee O16 Opportunities and challenges in imaging metastatic disease Hersh Chandarana O17 Diagnosis, treatment monitoring, and follow-up of lymphoma Marius E. Mayerhoefer, Markus Raderer, Alexander Haug O18 Managing high-risk and advanced prostate cancer Matthias Eiber O19 Immunotherapy: imaging challenges Bernhard Gebauer O20 RECIST and RECIST 1.1 Andrea Rockall O21 Challenges of RECIST in oncology imaging basics for the trainee and novice Aslam Sohaib O22 Lymphoma: PET for interim and end of treatment response assessment: a users’ guide to the Deauville Score Victoria S Warbey O23 Available resources Hebert Alberto Vargas O24 ICIS e-portal and the online learning community Dow-Mu Koh O25 Benign lesions that mimic pancreatic cancer Jay P Heiken O26 Staging and reporting pancreatic malignancies Isaac R Francis, Mahmoud, M Al-Hawary, Ravi K Kaza O27 Intraductal papillary mucinous neoplasm Giovanni Morana O28 Cystic pancreatic tumours Mirko D’Onofrio O29 Diffusion-weighted imaging of head and neck tumours Harriet C. Thoeny O30 Radiation injury in the head and neck Ann D King O31 PET/MR of paediatric brain tumours Giovanni Morana, Arnoldo Piccardo, Maria Luisa Garrè, Andrea Rossi O32 Structured reporting and beyond Hebert Alberto Vargas O33 Massachusetts General Hospital experience with structured reporting Theresa C. McLoud O34 The oncologist’s perspective: what the oncologist needs to know Nick Reed O35 Towards the cure of all children with cancer: global initiatives in pediatric oncology Carlos Rodriguez-Galindo O36 Multiparametric imaging of renal cancers Hersh Chandarana O37 Linking imaging features of renal disease and their impact on management strategies Hebert Alberto Vargas O38 Adrenals, retroperitoneum and peritoneum Isaac R Francis, Ashish P Wasnik O39 Lung and pleura Stefan Diederich O40 Advances in MRI Jurgen J. Fütterer O41 Advances in molecular imaging Wim J.G. Oyen O42 Incorporating advanced imaging, impact on treatment selection and patient outcome Cheng Lee Chaw, Nicholas van As S1 Combining ADC-histogram features improves performance of MR diffusion-weighted imaging for Lymph node characterisation in cervical cancer Igor Vieira, Frederik De Keyzer, Elleke Dresen, Sileny Han, Ignace Vergote, Philippe Moerman, Frederic Amant, Michel Koole, Vincent Vandecaveye S2 Whole-body diffusion-weighted MRI for surgical planning in patients with colorectal cancer and peritoneal metastases R Dresen, S De Vuysere, F De Keyzer, E Van Cutsem, A D’Hoore, A Wolthuis, V Vandecaveye S3 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extra capsular extension of prostate cancer. P. Pricolo ([email protected]), S. Alessi, P. Summers, E. Tagliabue, G. Petralia S4 Generating evidence for clinical benefit of PET/CT – are management studies sufficient as surrogate for patient outcome? C. Pfannenberg, B. Gückel, SC Schüle, AC Müller, S. Kaufmann, N. Schwenzer, M. Reimold,C. la Fougere, K. Nikolaou, P. Martus S5 Heterogeneity of treatment response in skeletal metastases from breast cancer with 18F-fluoride and 18F-FDG PET GJ Cook, GK Azad, BP Taylor, M Siddique, J John, J Mansi, M Harries, V Goh S6 Accuracy of suspicious breast imaging—can we tell the patient? S Seth, R Burgul, A Seth S7 Measurement method of tumour volume changes during neoadjuvant chemotherapy affects ability to predict pathological response S Waugh, N Muhammad Gowdh, C Purdie, A Evans, E Crowe, A Thompson, S Vinnicombe S8 Diagnostic yield of CT IVU in haematuria screening F. Arfeen, T. Campion, E. Goldstraw S9 Percutaneous radiofrequency ablation of unresectable locally advanced pancreatic cancer: preliminary results D’Onofrio M, Ciaravino V, Crosara S, De Robertis R, Pozzi Mucelli R S10 Iodine maps from dual energy CT improve detection of metastases in staging examinations of melanoma patients M. Uhrig, D. Simons, H. Schlemmer S11Can contrast enhanced CT predict pelvic nodal status in malignant melanoma of the lower limb? Kate Downey S12 Current practice in the investigation for suspected Paraneoplastic Neurological Syndromes (PNS) and positive malignancy yield. S Murdoch, AS Al-adhami, S Viswanathan P1 Technical success and efficacy of Pulmonary Radiofrequency ablation: an analysis of 207 ablations S Smith, P Jennings, D Bowers, R Soomal P2 Lesion control and patient outcome: prospective analysis of radiofrequency abaltion in pulmonary colorectal cancer metastatic disease S Smith, P Jennings, D Bowers, R Soomal P3 Hepatocellular carcinoma in a post-TB patient: case of tropical infections and oncologic imaging challenges TM Mutala, AO Odhiambo, N Harish P4 Role of apparent diffusion coefficient (ADC) diffusion-weighted MRI for predicting extracapsular extension of prostate cancer P. Pricolo, S. Alessi, P. Summers, E. Tagliabue, G. Petralia P5 What a difference a decade makes; comparison of lung biopsies in Glasgow 2005 and 2015 M. Hall, M. Sproule, S. Sheridan P6 Solid pseudopapillary tumour of pancreas: imaging features of a rare neoplasm KY Thein, CH Tan, YL Thian, CM Ho P7 MDCT - pathological correlation in colon adenocarcinoma staging: preliminary experience S De Luca, C Carrera, V Blanchet, L Alarcón, E Eyheremnedy P8 Image guided biopsy of thoracic masses and reduction of pneumothorax risk: 25 years experience B K Choudhury, K Bujarbarua, G Barman P9 Tumour heterogeneity analysis of 18F-FDG-PET for characterisation of malignant peripheral nerve sheath tumours in neurofibromatosis-1 GJ Cook, E Lovat, M Siddique, V Goh, R Ferner, VS Warbey P10 Impact of introduction of vacuum assisted excision (VAE) on screen detected high risk breast lesions L Potti, B Kaye, A Beattie, K Dutton P11 Can we reduce prevalent recall rate in breast screening? AA Seth, F Constantinidis, H Dobson P12 How to reduce prevalent recall rate? Identifying mammographic lesions with low Positive Predictive Value (PPV) AA Seth ([email protected]), F Constantinidis, H Dobson P13 Behaviour of untreated pulmonary thrombus in oncology patients diagnosed with incidental pulmonary embolism on CT R. Bradley, G. Bozas, G. Avery, A. Stephens, A. Maraveyas P14 A one-stop lymphoma biopsy service – is it possible? S Bhuva, CA Johnson, M Subesinghe, N Taylor P15 Changes in the new TNM classification for lung cancer (8th edition, effective January 2017) LE Quint, RM Reddy, GP Kalemkerian P16 Cancer immunotherapy: a review of adequate imaging assessment G González Zapico, E Gainza Jauregui, R Álvarez Francisco, S Ibáñez Alonso, I Tavera Bahillo, L Múgica Álvarez P17 Succinate dehydrogenase mutations and their associated tumours O Francies, R Wheeler, L Childs, A Adams, A Sahdev P18 Initial experience in the usefulness of dual energy technique in the abdomen SE De Luca, ME Casalini Vañek, MD Pascuzzi, T Gillanders, PM Ramos, EP Eyheremendy P19 Recognising the serious complication of Richter’s transformation in CLL patients C Stove, M Digby P20 Body diffusion-weighted MRI in oncologic practice: truths, tricks and tips M. Nazar, M. Wirtz, MD. Pascuzzi, F. Troncoso, F. Saguier, EP. Eyheremendy P21 Methotrexate-induced leukoencephalopathy in paediatric ALL Patients D.J. Quint, L. Dang, M. Carlson, S. Leber, F. Silverstein P22 Pitfalls in oncology CT reporting. A pictorial review R Rueben, S Viswanathan P23 Imaging of perineural extension in head and neck tumours B Nazir, TH Teo, JB Khoo P24 MRI findings of molecular subtypes of breast cancer: a pictorial primer K Sharma, N Gupta, B Mathew, T Jeyakumar, K Harkins P25 When cancer can’t wait! A pictorial review of oncological emergencies K Sharma, B Mathew, N Gupta, T Jeyakumar, S Joshua P26 MRI of pancreatic neuroendocrine tumours: an approach to interpretation D Christodoulou, S Gourtsoyianni, A Jacques, N Griffin, V Goh P27 Gynaecological cancers in pregnancy: a review of imaging CA Johnson, J Lee P28 Suspected paraneoplastic neurological syndromes - review of published recommendations to date, with proposed guideline/flowchart JA Goodfellow, AS Al-adhami, S Viswanathan P29 Multi-parametric MRI of the pelvis for suspected local recurrence of prostate cancer after radical prostatectomy R Bradley P30 Utilisation of PI-RADS version 2 in multi-parametric MRI of the prostate; 12-months experience R Bradley P31 Radiological assessment of the post-chemotherapy liver A Yong, S Jenkins, G Joseph P32 Skeletal staging with MRI in breast cancer – what the radiologist needs to know S Bhuva, K Partington P33 Perineural spread of lympoma: an educational review of an unusual distribution of disease CA Johnson, S Bhuva, M Subesinghe, N Taylor P34 Visually isoattenuating pancreatic adenocarcinoma. Diagnostic imaging tools. C Carrera, A Zanfardini, S De Luca, L Alarcón, V Blanchet, EP Eyheremendy P35 Imaging of larynx cancer: when is CT, MRI or FDG PET/CT the best test? K Cavanagh, E Lauhttp://deepblue.lib.umich.edu/bitstream/2027.42/134651/1/40644_2016_Article_79.pd