Huntington's disease (HD) is an autosomal dominant neurodegenerative disease caused by a triplet (CAG) expansion mutation. The length of the triplet repeat is the most important factor in determining age of onset of HD, although substantial variability remains after controlling for repeat length. The Venezuelan HD kindreds encompass 18,149 individuals spanning 10 generations, 15,409 of whom are living. Of the 4,384 immortalized lymphocyte lines collected, 3,989 DNAs were genotyped for their HD alleles, representing a subset of the population at greatest genetic risk. There are 938 heterozygotes, 80 people with variably penetrant alleles, and 18 homozygotes. Analysis of the 83 kindreds that comprise the Venezuelan HD kindreds demonstrates that residual variability in age of onset has both genetic and environmental components. We created a residual age of onset phenotype from a regression analysis of the log of age of onset on repeat length. Familial correlations (correlation +/- SE) were estimated for sibling (0.40 +/- 0.09), parent-offspring (0.10 +/- 0.11), avuncular (0.07 +/- 0.11), and cousin (0.15 +/- 0.10) pairs, suggesting a familial origin for the residual variance in onset. By using a variance-components approach with all available familial relationships, the additive genetic heritability of this residual age of onset trait is 38%. A model, including shared sibling environmental effects, estimated the components of additive genetic (0.37), shared environment (0.22), and nonshared environment (0.41) variances, confirming that approximately 40% of the variance remaining in onset age is attributable to genes other than the HD gene and 60% is environmental.

SummaryAge of onset for Huntington's disease (HD) varies inversely with the length of the disease-causing CAG repeat expansion in the HD gene. A simple exponential regression model yielded adjusted R-squared values of 0.728 in a large set of Venezuelan kindreds and 0.642 in a North American, European, and Australian sample (the HD MAPS cohort). We present evidence that a two-segment exponential regression curve provides a significantly better fit than the simple exponential regression. A plot of natural log-transformed age of onset against CAG repeat length reveals this segmental relationship. This two-segment exponential regression on age of onset data increases the adjusted R-squared values by 0.012 in the Venezuelan kindreds and by 0.035 in the HD MAPS cohort. Although the amount of additional variance explained by the segmental regression approach is modest, the two slopes of the two-segment regression are significantly different from each other in both the Venezuelan kindreds [F(2, 439) = 11.13, P = 2 × 10 − 5 ] and in the HD MAPS cohort [F(2, 688) = 38.27, P = 2 × 10 − 16 ]. In both populations, the influence of each CAG repeat on age of onset appears to be stronger in the adult-onset range of CAG repeats than in the juvenile-onset range.

No abstract

Objective The National Comprehensive Cancer Network guidelines recommend an interval between surgery and adjuvant radiation therapy of less than 6 weeks, but only 44% of patients meet this metric nationally. We sought to identify key components of an improvement process focused on starting adjuvant radiation therapy within 6 weeks of surgery. Methods This project used an A3 model to improve a defined process measure. We studied a consecutive sample of 56 patients with oral cavity carcinoma who were treated at our institution with upfront surgical resection followed by adjuvant radiation therapy. Twelve proposed interventions tested during the study period focused on 3 key drivers of delays: delayed dental evaluation and teeth extraction, delayed radiation oncology consults, and inadequate patient engagement. The primary outcome measure was the number of days from surgery to the start of radiation therapy. Results Prior to the intervention, 62% of patients received adjuvant radiation within 6 weeks of surgery. Following the intervention, 73% of patients achieved this metric. The percentage of patients with avoidable delays decreased from 24% to 9%. The percentage of patients with unavoidable delays was relatively constant before and after the intervention (15% and 18%, respectively). Discussion Defining disease-specific metrics is critical to improving care in our head and neck cancer patient population. We demonstrate several key components to develop and improve self-defined metrics. Implications for Practice As we transition to a system of value-based care, structured quality improvement projects can have a measurable impact on cancer patient process measures.