A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data

We propose a matrix factorization technique that decomposes the resting state fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set of representative subnetworks, as modeled by rank one outer products. The subnetworks are combined using patient specific non-negative coefficients; these coefficients are also used to model, and subsequently predict the clinical severity of a given patient via a linear regression. Our generative-discriminative framework is able to exploit the structure of rs-fMRI correlation matrices to capture group level effects, while simultaneously accounting for patient variability. We employ ten fold cross validation to demonstrate the predictive power of our model on a cohort of fifty eight patients diagnosed with Autism Spectrum Disorder. Our method outperforms classical semi-supervised frameworks, which perform dimensionality reduction on the correlation features followed by non-linear regression to predict the clinical scores

Sleep problems for children with autism and caregiver spillover effects

Sleep problems in children with autism spectrum disorders (ASD) are under-recognized and under-treated. Identifying treatment value accounting for health effects on family members (spillovers) could improve the perceived cost-effectiveness of interventions to improve child sleep habits. A prospective cohort study (N = 224) was conducted with registry and postal survey data completed by the primary caregiver.Wecalculated quality of life outcomes for the child and the primary caregiver associated with treatments to improve sleep in the child based on prior clinical trials. Predicted treatment effects for melatonin and behavioral interventions were similar in magnitude for the child and for the caregiver. Accounting for caregiver spillover effects associated with treatments for the child with ASD increases treatment benefits and improves cost-effectiveness profiles

Preferred reporting items for studies mapping onto preference-based outcome measures: The MAPS statement

'Mapping' onto generic preference-based outcome measures is increasingly being used as a means of generating health utilities for use within health economic evaluations. Despite publication of technical guides for the conduct of mapping research, guidance for the reporting of mapping studies is currently lacking. The MAPS (MApping onto Preference-based measures reporting Standards) statement is a new checklist, which aims to promote complete and transparent reporting of mapping studies. The primary audiences for the MAPS statement are researchers reporting mapping studies, the funders of the research, and peer reviewers and editors involved in assessing mapping studies for publication. A de novo list of 29 candidate reporting items and accompanying explanations was created by a working group comprised of six health economists and one Delphi methodologist. Following a two-round, modified Delphi survey with representatives from academia, consultancy, health technology assessment agencies and the biomedical journal editorial community, a final set of 23 items deemed essential for transparent reporting, and accompanying explanations, was developed. The items are contained in a user friendly 23 item checklist. They are presented numerically and categorised within six sections, namely: (i) title and abstract; (ii) introduction; (iii) methods; (iv) results; (v) discussion; and (vi) other. The MAPS statement is best applied in conjunction with the accompanying MAPS explanation and elaboration document. It is anticipated that the MAPS statement will improve the clarity, transparency and completeness of reporting of mapping studies. To facilitate dissemination and uptake, the MAPS statement is being co-published by eight health economics and quality of life journals, and broader endorsement is encouraged. The MAPS working group plans to assess the need for an update of the reporting checklist in five years' time. This statement was published jointly in Applied Health Economics and Health Policy, Health and Quality of Life Outcomes, International Journal of Technology Assessment in Health Care, Journal of Medical Economics, Medical Decision Making, PharmacoEconomics, and Quality of Life Research

From KIDSCREEN-10 to CHU9D: creating a unique mapping algorithm for application in economic evaluation

Background: The KIDSCREEN-10 index and the Child Health Utility 9D (CHU9D) are two recently developed generic instruments for the measurement of health-related quality of life in children and adolescents. Whilst the CHU9D is a preference based instrument developed specifically for application in cost-utility analyses, the KIDSCREEN-10 is not currently suitable for application in this context. This paper provides an algorithm for mapping the KIDSCREEN-10 index onto the CHU9D utility scores. Methods: A sample of 590 Australian adolescents (aged 11–17) completed both the KIDSCREEN-10 and the CHU9D. Several econometric models were estimated, including ordinary least squares estimator, censored least absolute deviations estimator, robust MM-estimator and generalised linear model, using a range of explanatory variables with KIDSCREEN-10 items scores as key predictors. The predictive performance of each model was judged using mean absolute error (MAE) and root mean squared error (RMSE). Results: The MM-estimator with stepwise-selected KIDSCREEN-10 items scores as explanatory variables had the best predictive accuracy using MAE, whilst the equivalent ordinary least squares model had the best predictive accuracy using RMSE. Conclusions: The preferred mapping algorithm (i.e. the MM-estimate with stepwise selected KIDSCREEN-10 item scores as the predictors) can be used to predict CHU9D utility from KIDSCREEN-10 index with a high degree of accuracy. The algorithm may be usefully applied within cost-utility analyses to generate cost per quality adjusted life year estimates where KIDSCREEN-10 data only are available

A comparison of the sensitivity of EQ-5D, SF-6D and TTO utility values to changes in vision and perceived visual function in patients with primary open-angle glaucoma

Background: Economic viability of treatments for primary open-angle glaucoma (POAG) should be assessed objectively to prioritise health care interventions. This study aims to identify the methods for eliciting utility values (UVs) most sensitive to differences in visual field and visual functioning in patients with POAG. As a secondary objective, the dimensions of generic health-related and vision-related quality of life most affected by progressive vision loss will be identified. Methods: A total of 132 POAG patients were recruited. Three sets of utility values (EuroQoL EQ-5D, Short Form SF-6D, Time Trade Off) and a measure of perceived visual functioning from the National Eye Institute Visual Function Questionnaire (VFQ-25) were elicited during face-to-face interviews. The sensitivity of UVs to differences in the binocular visual field, visual acuity and visual functioning measures was analysed using non-parametric statistical methods. Results: Median utilities were similar across Integrated Visual Field score quartiles for EQ-5D (P = 0.08) whereas SF-6D and Time-Trade-Off UVs significantly decreased (p = 0.01 and p = 0.001, respectively). The VFQ-25 score varied across Integrated Visual Field and binocular visual acuity groups and was associated with all three UVs (P ≤ 0.001); most of its vision-specific sub-scales were associated with the vision markers. The most affected dimension was driving. A relationship with vision markers was found for the physical component of SF-36 and not for any dimension of EQ-5D. Conclusions: The Time-Trade-Off was more sensitive than EQ-5D and SF-6D to changes in vision and visual functioning associated with glaucoma progression but could not measure quality of life changes in the mildest disease stages

Neurocognition and quality of life after reinitiating antiretroviral therapy in children randomized to planned treatment interruption

Objective: Understanding the effects of antiretroviral treatment (ART) interruption on neurocognition and quality of life (QoL) are important for managing unplanned interruptions and planned interruptions in HIV cure research. Design: Children previously randomized to continuous (continuous ART, n=41) vs. planned treatment interruption (PTI, n=47) in the Pediatric European Network for Treatment of AIDS (PENTA) 11 study were enrolled. At study end, PTI children resumed ART. At 1 and 2 years following study end, children were assessed by the coding, symbol search and digit span subtests of Wechsler Intelligence Scale for Children (6-16 years old) or Wechsler Adult Intelligence Scale ( 6517 years old) and by Pediatrics QoL questionnaires for physical and psychological QoL. Transformed scaled scores for neurocognition and mean standardized scores for QoL were compared between arms by t-test and Mann-Whitney U test, respectively. Scores indicating clinical concern were compared (<7 for neurocognition and <70 for QoL tests). Results: Characteristics were similar between arms with a median age of 12.6 years, CD4 + of 830 cells/\u3bcl and HIV RNA of 1.7 log 10 copies/ml. The median cumulative ART exposure was 9.6 in continuous ART vs. 7.7 years in PTI (P=0.02). PTI children had a median of 12 months off ART and had resumed ART for 25.2 months at time of first assessment. Neurocognitive scores were similar between arms for all tests. Physical and psychological QoL scores were no different. About 40% had low neurocognitive and QoL scores indicating clinical concern. Conclusion: No differences in information processing speed, sustained attention, short-term memory and QoL functioning were observed between children previously randomized to continuous ART vs. PTI in the PENTA 11 trial

EQ-5D in Central and Eastern Europe : 2000-2015

Objective: Cost per quality-adjusted life year data are required for reimbursement decisions in many Central and Eastern European (CEE) countries. EQ-5D is by far the most commonly used instrument to generate utility values in CEE. This study aims to systematically review the literature on EQ-5D from eight CEE countries. Methods: An electronic database search was performed up to July 1, 2015 to identify original EQ-5D studies from the countries of interest. We analysed the use of EQ-5D with respect to clinical areas, methodological rigor, population norms and value sets. Results: We identified 143 studies providing 152 country-specific results with a total sample size of 81,619: Austria (n=11), Bulgaria (n=6), Czech Republic (n=18), Hungary (n=47), Poland (n=51), Romania (n=2), Slovakia (n=3) and Slovenia (n=14). Cardiovascular (20%), neurologic (16%), musculoskeletal (15%) and endocrine/nutritional/metabolic diseases (14%) were the most frequently studied clinical areas. Overall 112 (78%) of the studies reported EQ VAS results and 86 (60%) EQ-5D index scores, of which 27 (31%) did not specify the applied tariff. Hungary, Poland and Slovenia have population norms. Poland and Slovenia also have a national value set. Conclusions: Increasing use of EQ-5D is observed throughout CEE. The spread of health technology assessment activities in countries seems to be reflected in the number of EQ-5D studies. However, improvement in informed use and methodological quality of reporting is needed. In jurisdictions where no national value set is available, in order to ensure comparability we recommend to apply the most frequently used UK tariff. Regional collaboration between CEE countries should be strengthened