Predicting preference-based utility values using partial proportional odds models.

BACKGROUND: The majority of analyses on utility data have used ordinary least square (OLS) regressions to explore potential relationships. The aim of this paper is to explore the benefits of response mapping onto health dimension profiles to generate preference-based utility scores using partial proportional odds models (PPOM). METHODS: Models are estimated using EQ-5D data collected in the Health Survey for England and the predicted utility scores are compared with those obtained using OLS regressions. Explanatory variables include age, acute illness, educational level, general health, deprivation and survey year. The expected EQ-5D scores for the PPOMs are obtained by weighting the predicted probabilities of scoring one, two or three for the five health dimensions by the corresponding preference-weights. RESULTS: The EQ-5D scores obtained using the probabilities from the PPOMs characterise the actual distribution of EQ-5D preference-based utility scores more accurately than those obtained from the linear model. The mean absolute and mean squared errors in the individual predicted values are also reduced for the PPOM models. CONCLUSIONS: The PPOM models characterise the underlying distributions of the EQ-5D data better than models obtained using OLS regressions. Additional research exploring the effect of modelling conditional responses and two part models could potentially improve the results further

Case-mix methodology for the NHS outcomes framework GP Patient Survey Questionnaire Data

The objective of the research described in the current report was to explore alternative methodologies which could be used to determine whether the health status of people living with long- term conditions in England is changing over time, all other factors being equal. Data from the Health Survey for England (HSE) were used in the analyses and EQ-5D was used to represent health related quality of life (HRQoL). The proposed case mix ratio approach which utilised ordinary least square regressions (with the EQ-5D preference - based score as the dependent variable) was replicated and alternatives using logistic regressions and two part models (both using the responses to the EQ-5D health dimensions as the dependent variables) were explored. An alternative method using the HSE year as a performance indicator (PI) was explored and results presented for the four most prevalent health conditions. Results were compared in terms of errors in predicted scores and the ability to capture changes in the distributions of the preference-based scores. Both expected and simulated values were compared

Examining productivity losses associated with health related quality of life using patient and general population data

The work described in this report was commissioned by the Department of Health to inform its work on Value-Based-Pricing (VBP), which is due to replace the current Pharmaceutical Pricing Regulation Scheme (PPS) in January 2014 for pricing medicines in the UK. VBP will include additional payments to interventions that are deemed to provide benefit that is of greater social value instead of the current narrow focus on outcomes relevant to the NHS and Personal Social Services (PSS). This requires taking into account wider societal benefits of medicines beyond the health of the patient including productivity. The objective of the analyses was to provide a model to predict productivity losses associated with paid work that were representative of all patients that are likely to be seen in the NHS

Loneliness, social relations and health and wellbeing in deprived communities

There is growing policy concern about the extent of loneliness in advanced societies, and its prevalence among various social groups. This study looks at loneliness among people living in deprived communities, where there may be additional barriers to social engagement including low incomes, fear of crime, poor services and transient populations. The aim was to examine the prevalence of loneliness, and also its associations with different types of social contacts and forms of social support, and its links to self-reported health and wellbeing in the population group. The method involved a cross-sectional survey of 4,302 adults across 15 communities, with the data analysed using multinomial logistic regression controlling for sociodemographics, then for all other predictors within each domain of interest. Frequent feelings of loneliness were more common among those who: had contact with family monthly or less; had contact with neighbours weekly or less; rarely talked to people in the neighbourhood; and who had no available sources of practical or emotional support. Feelings of loneliness were most strongly associated with poor mental health, but were also associated with long-term problems of stress, anxiety and depression, and with low mental wellbeing, though to a lesser degree. The findings are consistent with a view that situational loneliness may be the product of residential structures and resources in deprived areas. The findings also show that neighbourly behaviours of different kinds are important for protecting against loneliness in deprived communities. Familiarity within the neighbourhood, as active acquaintance rather than merely recognition, is also important. The findings are indicative of several mechanisms that may link loneliness to health and wellbeing in our study group: loneliness itself as a stressor; lonely people not responding well to the many other stressors in deprived areas; and loneliness as the product of weak social buffering to protect against stressors

The cost-effectiveness of changes to the care pathway used to identify depression and provide treatment amongst people with diabetes in England: a model-based economic evaluation.

BACKGROUND: Diabetes is associated with premature death and a number of serious complications. The presence of comorbid depression makes these outcomes more likely and results in increased healthcare costs. The aim of this work was to assess the health economic outcomes associated with having both diabetes and depression, and assess the cost-effectiveness of potential policy changes to improve the care pathway: improved opportunistic screening for depression, collaborative care for depression treatment, and the combination of both. METHODS: A mathematical model of the care pathways experienced by people diagnosed with type-2 diabetes in England was developed. Both an NHS perspective and wider social benefits were considered. Evidence was taken from the published literature, identified via scoping and targeted searches. RESULTS: Compared with current practice, all three policies reduced both the time spent with depression and the number of diabetes-related complications experienced. The policies were associated with an improvement in quality of life, but with an increase in health care costs. In an incremental analysis, collaborative care dominated improved opportunistic screening. The incremental cost-effectiveness ratio (ICER) for collaborative care compared with current practice was £10,798 per QALY. Compared to collaborative care, the combined policy had an ICER of £68,017 per QALY. CONCLUSIONS: Policies targeted at identifying and treating depression early in patients with diabetes may lead to reductions in diabetes related complications and depression, which in turn increase life expectancy and improve health-related quality of life. Implementing collaborative care was cost-effective based on current national guidance in England

Search for Neutral Q-balls in Super-Kamiokande II

A search for Q-balls induced groups of successive contained events has been carried out in Super-Kamiokande II with 541.7 days of live time. Neutral Q-balls would emit pions when colliding with nuclei, generating a signal of successive contained pion events along a track. No candidate for successive contained event groups has been found in Super-Kamiokande II, so upper limits on the possible flux of such Q-balls have been obtained.Comment: 5 pages, 5 figures, Submitted to Phys. Lett.

Diagnostic yield of candidate genes in an Australian corneal dystrophy cohort

First published: 19 August 2022Corneal dystrophies describe a clinically and genetically heterogeneous group of inherited disorders. The International Classification of Corneal Dystrophies (IC3D) lists 22 types of corneal dystrophy, 17 of which have been demonstrated to result from pathogenic variants in 19 identified genes. In this study, we investigated the diagnostic yield of genetic testing in a well-characterised cohort of 58 individuals from 44 families with different types of corneal dystrophy. Individuals diagnosed solely with Fuchs endothelial corneal dystrophy were excluded. Clinical details were obtained from the treating ophthalmologist. Participants and their family members were tested using a gene candidate and exome sequencing approach. We identified a likely molecular diagnosis in 70.5% families (31/44). The detection rate was significantly higher among probands with a family history of corneal dystrophy (15/16, 93.8%) than those without (16/28, 57.1%, p = .015), and among those who had undergone corneal graft surgery (9/9, 100.0%) compared to those who had not (22/35, 62.9%, p = .041). We identified eight novel variants in five genes and identified five families with syndromes associated with corneal dystrophies. Our findings highlight the genetic heterogeneity of corneal dystrophies and the clinical utility of genetic testing in reaching an accurate clinical diagnosis.Emmanuelle Souzeau, Owen M. Siggs, Sean Mullany, Joshua M. Schmidt, Mark M. Hassall, Andrew Dubowsky, Angela Chappell, James Breen, Haae Bae, Jillian Nicholl, Johanna Hadler, Lisa S. Kearns, Sandra E. Staffieri, Alex W. Hewitt, David A. Mackey, Aanchal Gupta, Kathryn P. Burdon, Sonja Klebe, Jamie E. Craig, Richard A. Mill

Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation