We developed and used an innovative approach to compare MELD to six proposed alternatives with respect to waiting list mortality. Our analysis was based on United Network for Organ Sharing data of patients with ESLD on the waiting list between January 2006 and June 2009. We compared six allocation models to MELD. Two models were based on Nutlin-3a reweighting the variables used by MELD: an updated MELD, and ReFit MELD. Four models also included serum sodium: MESO, MeldNa, UKELD, and ReFit MELDNa. We estimated that UKELD and the

updated MELD would result in significantly fewer lives saved. There were no significant differences between the other models. Our new approach can supplement standard methods to provide insight into the relative performance of liver allocation models in reducing waiting list mortality. Our analysis suggests that UKELD and the updated MELD score would not be optimal for reducing waiting list mortality in the United States.”
“Aims: We conducted a population-based study of practice patterns and outcome PCI-34051 cost across

the regional cancer centres providing care to patients with laryngeal cancer in the Province of Ontario, Canada.

Materials and methods: : This was a retrospective cohort study of 1547 patients with cancers of the glottic or supraglottic larynx diagnosed between 1982 and 1995. Data were collected via chart review, including: patient and disease characteristics, treatment, waiting times and treatment volumes. Vital status was obtained from the Ontario Cancer Registry. Variations across the nine regional cancer centres are described and their effect on outcome explored. All analyses were stratified Veliparib by stage I and II separately from stage III and IV.

Results: Treatments differed across centres (P < 0.0001): for instance, in the stage I and II group, use of a daily close of > 2.54 Gy varied from 0 to 87.6% and in the stage III and IV group, total laryngectomy rates varied from a low of 6% to a high of 53%. The percentage of patients waiting more than 6 weeks from diagnosis to first treatment varied from 17

to 49% (P < 0.0001). Multivariate analysis revealed cause-specific survival differences that were not explained by control for case mix, treatment or waiting times. Differences ranged from an 82% risk reduction in one centre compared with the reference (stage I and II group, P= 0.008) to a 153% increase in risk (stage Ill and IV group, P= 0.02). Centre case volumes were not associated with cause-specific survival.

Conclusions: This study quantifies the degree of variation that can occur in the treatment and outcome of people with cancer. We cannot properly assess whether care delivery is of high quality until we have a better understanding of the factors that drive such variations. (C) 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.