Association of genetic and sulcal traits with executive function in congenital heart disease.

OBJECTIVE: Persons with congenital heart disease (CHD) are at increased risk of neurodevelopmental disabilities, including impairments to executive function. Sulcal pattern features correlate with executive function in adolescents with single-ventricle heart disease and tetralogy of Fallot. However, the interaction of sulcal pattern features with genetic and participant factors in predicting executive dysfunction is unknown. METHODS: We studied sulcal pattern features, participant factors, and genetic risk for executive function impairment in a cohort with multiple CHD types using stepwise linear regression and machine learning. RESULTS: Genetic factors, including predicted damaging de novo or rare inherited variants in neurodevelopmental disabilities risk genes, apolipoprotein E genotype, and principal components of sulcal pattern features were associated with executive function measures after adjusting for age at testing, sex, mother's education, and biventricular versus single-ventricle CHD in a linear regression model. Using regression trees and bootstrap validation, younger participant age and larger alterations in sulcal pattern features were consistently identified as important predictors of decreased cognitive flexibility with left hemisphere graph topology often selected as the most important predictor. Inclusion of both sulcal pattern and genetic factors improved model fit compared to either alone. INTERPRETATION: We conclude that sulcal measures remain important predictors of cognitive flexibility, and the model predicting executive outcomes is improved by inclusion of potential genetic sources of neurodevelopmental risk. If confirmed, measures of sulcal patterning may serve as early imaging biomarkers to identify those at heightened risk for future neurodevelopmental disabilities.

Sample size requirements for testing treatment effect heterogeneity in cluster randomized trials with binary outcomes.

Cluster randomized trials (CRTs) refer to a popular class of experiments in which randomization is carried out at the group level. While methods have been developed for planning CRTs to study the average treatment effect, and more recently, to study the heterogeneous treatment effect, the development for the latter objective has currently been limited to a continuous outcome. Despite the prevalence of binary outcomes in CRTs, determining the necessary sample size and statistical power for detecting differential treatment effects in CRTs with a binary outcome remain unclear. To address this methodological gap, we develop sample size procedures for testing treatment effect heterogeneity in two-level CRTs under a generalized linear mixed model. Closed-form sample size expressions are derived for a binary effect modifier, and in addition, a computationally efficient Monte Carlo approach is developed for a continuous effect modifier. Extensions to multiple effect modifiers are also discussed. We conduct simulations to examine the accuracy of the proposed sample size methods. We present several numerical illustrations to elucidate features of the proposed formulas and to compare our method to the approximate sample size calculation under a linear mixed model. Finally, we use data from the Strategies and Opportunities to Stop Colon Cancer in Priority Populations (STOP CRC) CRT to illustrate the proposed sample size procedure for testing treatment effect heterogeneity.

Assessing exposure-time treatment effect heterogeneity in stepped-wedge cluster randomized trials.

A stepped-wedge cluster randomized trial (CRT) is a unidirectional crossover study in which timings of treatment initiation for clusters are randomized. Because the timing of treatment initiation is different for each cluster, an emerging question is whether the treatment effect depends on the exposure time, namely, the time duration since the initiation of treatment. Existing approaches for assessing exposure-time treatment effect heterogeneity either assume a parametric functional form of exposure time or model the exposure time as a categorical variable, in which case the number of parameters increases with the number of exposure-time periods, leading to a potential loss in efficiency. In this article, we propose a new model formulation for assessing treatment effect heterogeneity over exposure time. Rather than a categorical term for each level of exposure time, the proposed model includes a random effect to represent varying treatment effects by exposure time. This allows for pooling information across exposure-time periods and may result in more precise average and exposure-time-specific treatment effect estimates. In addition, we develop an accompanying permutation test for the variance component of the heterogeneous treatment effect parameters. We conduct simulation studies to compare the proposed model and permutation test to alternative methods to elucidate their finite-sample operating characteristics, and to generate practical guidance on model choices for assessing exposure-time treatment effect heterogeneity in stepped-wedge CRTs.

Abnormal Right-Hemispheric Sulcal Patterns Correlate with Executive Function in Adolescents with Tetralogy of Fallot.

Neurodevelopmental disabilities are the most common noncardiac conditions in patients with congenital heart disease (CHD). Executive function skills have been frequently observed to be decreased among children and adults with CHD compared with peers, but a neuroanatomical basis for the association is yet to be identified. In this study, we quantified sulcal pattern features from brain magnetic resonance imaging data obtained during adolescence among 41 participants with tetralogy of Fallot (ToF) and 49 control participants using a graph-based pattern analysis technique. Among patients with ToF, right-hemispheric sulcal pattern similarity to the control group was decreased (0.7514 vs. 0.7553, P = 0.01) and positively correlated with neuropsychological testing values including executive function (r = 0.48, P < 0.001). Together these findings suggest that sulcal pattern analysis may be a useful marker of neurodevelopmental risk in patients with CHD. Further studies may elucidate the mechanisms leading to different alterations in sulcal patterning.

Abnormal Left-Hemispheric Sulcal Patterns Correlate with Neurodevelopmental Outcomes in Subjects with Single Ventricular Congenital Heart Disease.

Neurodevelopmental abnormalities are the most common noncardiac complications in patients with congenital heart disease (CHD). Prenatal brain abnormalities may be due to reduced oxygenation, genetic factors, or less commonly, teratogens. Understanding the contribution of these factors is essential to improve outcomes. Because primary sulcal patterns are prenatally determined and under strong genetic control, we hypothesized that they are influenced by genetic variants in CHD. In this study, we reveal significant alterations in sulcal patterns among subjects with single ventricle CHD (n = 115, 14.7 ± 2.9 years [mean ± standard deviation]) compared with controls (n = 45, 15.5 ± 2.4 years) using a graph-based pattern-analysis technique. Among patients with CHD, the left hemisphere demonstrated decreased sulcal pattern similarity to controls in the left temporal and parietal lobes, as well as the bilateral frontal lobes. Temporal and parietal lobes demonstrated an abnormally asymmetric left-right pattern of sulcal basin area in CHD subjects. Sulcal pattern similarity to control was positively correlated with working memory, processing speed, and executive function. Exome analysis identified damaging de novo variants only in CHD subjects with more atypical sulcal patterns. Together, these findings suggest that sulcal pattern analysis may be useful in characterizing genetically influenced, atypical early brain development and neurodevelopmental risk in subjects with CHD.

Health and Economic Impact of Intensive Surveillance for Distant Recurrence After Curative Treatment of Colon Cancer: A Mathematical Modeling Study.

BACKGROUND: Intensive surveillance strategies are currently recommended for patients after curative treatment of colon cancer, with the aim of secondary prevention of recurrence. Yet, intensive surveillance has not yielded improvements in overall patient survival compared with minimal follow-up, and more intensive surveillance may be costlier. OBJECTIVE: The purpose of this study was to estimate the quality-adjusted life-years, economic costs, and cost-effectiveness of various surveillance strategies after curative treatment of colon cancer. DESIGN: A Markov model was calibrated to reflect the natural history of colon cancer recurrence and used to estimate surveillance costs and outcomes. SETTINGS: This was a decision-analytic model. PATIENTS: Individuals entered the model at age 60 years after curative treatment for stage I, II, or III colon cancer. Other initial age groups were assessed in secondary analyses. MAIN OUTCOME MEASURES: We estimated the gains in quality-adjusted life-years achieved by early detection and treatment of recurrence, as well as the economic costs of surveillance under various strategies. RESULTS: Cost-effective strategies for patients with stage I colon cancer improved quality-adjusted life-expectancy by 0.02 to 0.06 quality-adjusted life-years at an incremental cost of $1702 to $13,019. For stage II, they improved quality-adjusted life expectancy by 0.03 to 0.09 quality-adjusted life-years at a cost of $2300 to $14,363. For stage III, they improved quality-adjusted life expectancy by 0.03 to 0.17 quality-adjusted life-years for a cost of $1416 to $17,631. At a commonly cited willingness-to-pay threshold of $100,000 per quality-adjusted life-year, the most cost-effective strategy for patients with a history of stage I or II colon cancer was liver ultrasound and chest x-ray annually. For those with a history of stage III colon cancer, the optimal strategy was liver ultrasound and chest x-ray every 6 months with CEA measurement every 6 months. LIMITATIONS: The study was limited by model structure assumptions and uncertainty around the values of the model's parameters. CONCLUSIONS: Given currently available data and within the limitations of a model-based decision-analytic approach, the effectiveness of routine intensive surveillance for patients after treatment of colon cancer appears, on average, to be small. Compared with testing using lower cost imaging, currently recommended strategies are associated with cost-effectiveness ratios that indicate low value according to well-accepted willingness-to-pay thresholds in the United States. See Video Abstract at http://links.lww.com/DCR/A921.