Comparison of efficacy from two different dosing regimens of bortezomib: an exposure–response analysis

Bortezomib is a first-in-class proteasome inhibitor, approved for the treatment of multiple myeloma. The originally approved dosing schedule of bortezomib results in significant toxicities that require dose interruptions and discontinuations. Consequentially, less frequent dosing has been explored to optimise bortezomib’s benefit–risk profile. Here, we performed exposure–response analysis to compare the efficacy of the original bortezomib dosing regimen with less frequent dosing of bortezomib over nine 6-week treatment cycles using data from the VISTA clinical trial and the control arm of the ALCYONE clinical trial. The relationship between cumulative bortezomib dose and clinical response was evaluated with a univariate logit model. The median cumulative bortezomib dose was higher in ALCYONE versus VISTA (42·2 vs. 38·5 mg/m²) and ALCYONE patients stayed on treatment longer (mean: 7·2 vs. 5·8 cycles). For all endpoints and regimens, probability of clinical response correlated with cumulative bortezomib dose. Similar to results observed for VISTA, overall survival was longer in ALCYONE patients with ≥ 39·0 versus < 39·0 mg/m² cumulative dose (hazard ratio, 0·119; P < 0·0001). Less frequent bortezomib dosing results in comparable efficacy, and a higher cumulative dose than the originally approved bortezomib dosing schedule, which may be in part be due to reduced toxicity and fewer dose reductions/interruptions.     

Potential Impact of Initial Clinical Data on Adjustment of Pediatric Readmission Rates

ObjectiveComparison of readmission rates requires adjustment for case-mix (ie, differences in patient populations), but previously only claims data were available for this purpose. We examined whether incorporation of relatively readily available clinical data improves prediction of pediatric readmissions and thus might enhance case-mix adjustment.MethodsWe examined 30-day readmissions using claims and electronic health record data for patients ≤18 years and 29 days of age who were admitted to 3 children's hospitals from February 2011 to February 2014. Using the Pediatric All-Condition Readmission Measure and starting with a model including age, gender, chronic conditions, and primary diagnosis, we examined whether the addition of initial vital sign and laboratory data improved model performance. We employed machine learning to evaluate the same variables, using the L2-regularized logistic regression with cost-sensitive learning and convolutional neural network.ResultsControlling for the core model variables, low red blood cell count and mean corpuscular hemoglobin concentration and high red cell distribution width were associated with greater readmission risk, as were certain interactions between laboratory and chronic condition variables. However, the C-statistic (0.722 vs 0.713) and McFadden's pseudo R² (0.085 vs 0.076) for this and the core model were similar, suggesting minimal improvement in performance. In machine learning analyses, the F-measure (harmonic mean of sensitivity and positive predictive value) was similar for the best-performing model (containing all variables) and core model (0.250 vs 0.243).ConclusionsReadily available clinical variables do not meaningfully improve the prediction of pediatric readmissions and would be unlikely to enhance case-mix adjustment unless their distributions varied widely across hospitals.     

Drug utilization evaluation of albumin in a teaching hospital of Mashhad,Iran: an interventional pre–post design study

Background Albumin is a protein colloidal solution with limited availability and high cost. It should be used in such approved indications as paracentesis, extensive burn, spontaneous bacterial peritonitis, and nephrotic syndrome. Objectives The aim of this study was to evaluate and compare the appropriateness of albumin usage before and after an evidence-based guideline. Setting Four wards of Imam Reza Hospital, Mashhad, Iran. Method An interventional pre–post design study was performed on 2 groups of patients; in gGroup 1 as a preparation phase group in 6 months from February 2015 to July 2015 and Group 2 as an interventional group from September 2015 to February 2016. A guideline for proper indications of albumin, designed and finalized based on the physicians’ comments, was implemented in Group 2. Main outcome measure The pattern of albumin consumption. Results Fifty patients were evaluated in each group. The implementation of the guideline resulted in reduction of improper albumin use from 62 to 57.5%, which was not statistically significant; however., it reduced inappropriate dose and duration of albumin therapy (55.5–16.7%), the number of consumed albumin vial, and the average cost for each patient (317.78 ± 3.15–149.81 ± 1.91 USD) significantly, as well. Conclusion This study illustrated that in this hospital in most cases, albumin was used inappropriately and at an alarming rate. This improved after the introduction of an evidence-based guideline. Moreover, guideline implementation resulted in significant cost reduction.     

Longitudinal Positron Emission Tomography in Preventive Alzheimer's Disease Drug Trials,Critical Barriers from Imaging Science Perspective

Recent Alzheimer's trials have recruited cognitively normal people at risk for Alzheimer's dementia. Due to the lack of clinical symptoms in normal population, conventional clinical outcome measures are not suitable for these early trials. While several groups are developing new composite cognitive tests that could serve as potential outcome measures by detecting subtle cognitive changes in normal people, there is a need for longitudinal brain imaging techniques that can correlate with temporal changes in these new tests and provide additional objective measures of neuropathological changes in brain. Positron emission tomography (PET) is a nuclear medicine imaging procedure based on the measurement of annihilation photons after positron emission from radiolabeled molecules that allow tracking of biological processes in body, including the brain. PET is a well‐established in vivo imaging modality in Alzheimer's disease diagnosis and research due to its capability of detecting abnormalities in three major hallmarks of this disease. These include (1) amyloid beta plaques; (2) neurofibrillary tau tangles and (3) decrease in neuronal activity due to loss of nerve cell connection and death. While semiquantitative PET imaging techniques are commonly used to set discrete cut‐points to stratify abnormal levels of amyloid accumulation and neurodegeneration, they are suboptimal for detecting subtle longitudinal changes. In this study, we have identified and discussed four critical barriers in conventional longitudinal PET imaging that may be particularly relevant for early Alzheimer's disease studies. These include within and across subject heterogeneity of AD‐affected brain regions, PET intensity normalization, neuronal compensations in early disease stages and cerebrovascular amyloid deposition.     

Mechanism and Factors Influencing Formation and Stability of Chitosan/Lignosulfonate Nanoparticles

A set of new nanoparticles are synthesized in this work at room temperature by combining two oppositely charged non‐toxic biopolymer polyelectrolytes in the form of chitosan and lignosulfonate. The effects of intensity of mixing, solid content, and reactant ratio on nanoparticle size and composition are investigated using turbidity measurements, dynamic light scattering data, zeta potential values, surface tension data, and electron microscopy. The data support nanoparticle structures with a dense hydrophobic core surrounded by a positively charged hydrophilic shell. The chitosan and lignosulfonate domains are held in these nanoparticles primarily by the electrostatic force while hydrogen bonding plays a minor role. The particle size increases with an increase of the total solid content, while the ratio of the two reactants determines the number of particles.     

Familial form of Hirschsprung disease: Nucleotide sequence studies reveal point mutations in the RET proto‐oncogene in two of six families but not in other candidate genes

Hirschsprung disease (HSCR; McKusick 142623) or aganglionic megacolon is a frequent (1 in 5,000 live births) heritable disorder of the enteric nervous system. By haplotyping with a variety of microsatellite markers, by amplifying all 20 exons of the RET proto‐oncogene and by applying a direct DNA sequencing protocol, we have analyzed the DNA from HSCR patients in 6 different families. In one family with a joint occurrence of HSCR and FMTC (follicular medullary thyroid carcinoma), we have identified a mutation in codon 609 in one out of 6 cysteine residues encoded in exon 10 of the RET gene. This C609R point mutation has not previously been reported to cause HSCR. In 2 of the HSCR patients described here from different families, we have found a mutation in exon 2 (R77C) and a silent mutation in exon 3 (Y204Y), respectively, in the extracellular part of the RET proto‐oncogene. In introns 2 and 17 of the RET proto‐oncogene in 2 families, we have detected single nucleotide exchanges that are probably polymorphisms with unknown, if any, relations to HSCR. The DNA sequences of 5 further genes (GDNF, GDNFRα, EDN3, EDNRB, and NTN), that may contribute to the development of HSCR, have not shown mutations in the patients analyzed so far. In 2 of the reported families with several affected children and one grandchild, sequence analyses revealed no mutations in the coding regions of any of the candidate genes analyzed. Am. J. Med. Genet. 94:19–27, 2000. © 2000 Wiley‐Liss, Inc.     

Segregation analysis of Parkinson disease

Parkinson disease (PD) is a prevalent movement disorder of unknown cause whose incidence rises with increasing age. Nearly 20% of PD is familial, a small subset of which exhibits autosomal dominant transmission. However, in most families, the inheritance is not clear. To determine the most likely mode of inheritance of PD, we performed complex segregation analyses using kindreds of 136 PD patients randomly ascertained from a clinic population. The hypotheses of a nontransmissible environmental factor, no major gene or type (sporadic), and all Mendelian inheritance (dominant, recessive, additive, decreasing) were rejected (P <0.001). Familial clustering of PD in this data set is best explained by a rare familial factor which a) is transmitted in a non-Mendelian fashion, and b) influences the age at onset of PD. If confirmed, our results have immediate implications in gene-mapping studies which often search for genes that behave in a Mendelian fashion that affect susceptibility rather than age at onset and long term implications in understanding the pathogenesis of PD. Am. J. Med. Genet. 80:410–417, 1998. © 1998 Wiley-Liss, Inc.     

Simultaneous spectrophotometric determination of chlordiazepoxide and clidinium using multivariate calibration techniques

Three multivariate modelling approaches including partial least squares regression (PLS), genetic algorithm‐partial least squares regression (GA‐PLS), and principal components‐artificial neural network (PC‐ANN) analysis were investigated for their application to the simultaneous determination of chlordiazepoxide and clidinium levels in pharmaceuticals. A set of synthetic mixtures of drugs in ethanol and 0.1 M HCL was made, and the prediction abilities of the aforementioned methods were examined using RSE% (relative standard error of the prediction). The PLS and PC‐ANN methods were found to be comparable, and GA‐PLS produced slightly better results. The predictive models that we built were successfully applied to simultaneously determine the levels of chlordiazepoxide and clidinium in coated tablets. Copyright © 2010 John Wiley & Sons, Ltd.