NIHRDataInsights/HRCSData huggingface dataset:
Title: Cellular and Pathological Responses to Chromosome DNA Single-Strand Breaks
Funder: Medical Research Council

Abstract: My laboratory is focused on understanding the molecular mechanism/s of DNA strand break repair and their links to human disease. The proposed work will address exciting new hypotheses that have arisen during my current research Programme concerning both the mechanism/s by which DNA single-strand breaks are repaired and the link between this process and neurological disease. Whilst we are focusing on experimental model systems in which single-strand break repair is defective to address these questions, the relevance of this work may extend to neurodegenerative disease in the normal ageing population. This is because single-strand breaks are the commonest DNA lesions arising in cells and are induced by oxidative stress; an etiological factor implicated in normal human ageing. In summary, our recent work has identified novel components of single-strand break sensing by by poly(ADP-ribose) polymerase enzymes. We have also identified new and unexpected putative roles for the single-strand break repair pathway beyond its canonical role in global genome repair that are linked to transcription and/or RNA splicing. In addition, we have identified novel gene mutations associated with single-strand break repair-defective neurodegenerative disease and uncovered a molecular mechanism by which unrepaired single-strand breaks trigger neurodegeneration; providing not only the first molecular explanation of this pathological event but also raising exciting possibilities concerning therapeutic intervention. We will now pursue the new questions and hypotheses arising from our recent work in the research Programme described here, using a combination of biochemical, cellular, and physiological model systems.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Making health financing work for the poor: An evaluation of equity in health systems financing in Indonesia
Funder: Medical Research Council

Abstract: Over the next 3 years the government of Indonesia will be initiating and strengthening a number of important reforms to achieve Universal Health Coverage (UHC) by 2019. This study will undertake pre and post comparative assessment of this reform package. Using before and after design, comparisons will be made of: (i) the distribution of the burden of paying for health care across SEGs; (ii) the distribution of health care benefits across socioeconomic groups (SEGs); and (iii) self-reported health outcomes across SEGs. Financing and benefit incidence analysis will be used to measure (i) and (ii) respectively. For the financing incidence analysis (FIA), secondary data derived from the Indonesian National Health Accounts (2014) and the National Socioeconomic Survey (2015) will be used to estimate the healthcare financing mix and household contributions to health financing through direct and indirect taxation and out-of-pocket payments. The benefit incidence analysis (BIA) requires the collection of primary data on health service utilization, the cost of accessing healthcare and socioeconomic status. A cross-sectional household survey will be conducted at baseline (2017) and 2 years into implementation (2019). Self-reported health indicators will also be measured as part of the household survey. These quantitative analyses will be complemented by detailed documentation of the context pre and post-intervention, and the process of implementing the latest UHC reforms. Our qualitative analysis will also provide insight into the relationships between components of the package and outcomes which in turn will facilitate an understanding of the process by which change has occurred. This qualitative information will also help to identify other factors that could have contributed to any observed changes in the study outcomes.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES;8.2 HEALTH AND WELFARE ECONOMICS;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE
Title: Predicting parental investment and child outcomes in transitioning populations: An application of the evolutionary theory of risk to public health
Funder: Medical Research Council

Abstract: AIMS: This research aims to create knowledge about predictors of parental investment and child outcomes relevant to public health interventions, by combining public health and evolutionary anthropology. It will examine the influence of risk exposure by asking (i) how does parental investment respond to different risks; (ii) how do these dynamics influence child outcomes; and (iii) what application does this have to public health interventions? DATA & METHODOLOGY: The Agta (Philippines, n = 900) dataset contains measures of child wellbeing (height, weight and medical histories), parental investment (childcare activities) across a population who experience variable risk exposure and resource availability (e.g. pathogen loads, accidental deaths, no medical access). The Young Lives (YLS) and the Indonesian Family Life Surveys (IFLS) contain datasets for five low and middle income countries (Ethiopia, India, Peru, Vietnam and Indonesia) which include longitudinal demographic, socioeconomic and child outcome data on 7,224 households (IFLS) and 12,000 children (YLS). These provide measures of household (livelihood loss) and community (crime and safety, disasters) risks as well as measures of parental investment (expenditure, child feeding) and child outcomes (height, weight and school attainment). Causal mediation analysis will be used to explore direct and indirect influences of risk on parental investment and child outcomes. Multilevel techniques will be deployed to examine individual, household and community-level predictors of parental investment and child outcomes. Time series regressions will explore the effect of risk exposure on parental investment. SCIENTIFIC OPPORTUNITIES: This research will generate policy relevant knowledge about how an understanding of parental investment and risk can influence child wellbeing policies and programmes. This research will theoretically develop both disciplines by integrating public health with evolutionary theory.


Research activity codes: 1.2 PSYCHOLOGICAL AND SOCIOECONOMIC PROCESSES
Health categories: GENERIC HEALTH RELEVANCE
Title: Improving evidence for economic evaluation and healthcare policy in relation to long term conditions using Mendelian Randomization on large cohorts
Funder: Medical Research Council

Abstract: Background: Accurate measurement of the effects of health conditions on healthcare cost and quality of life is important in the pragmatic evaluation of interventions and for healthcare policy more generally. However, most existing evidence is based either on short-term effect estimates from RCTs, or observational methods prone to bias. The proposed work will produce new and robust evidence of the causal effect of prevalent health conditions on cost and quality of life. Objectives: To apply the techniques of Mendelian Randomization in order to produce robust causal estimates of the effects of two exemplar, prevalent and complex conditions (obesity and coronary artery disease) on healthcare cost and on quality of life. To improve population health by generating more robust evidence for the evaluation of interventions, and to increase awareness of the proposed methods. Methods: The causal effects of obesity and coronary artery disease on healthcare cost and quality of life will be estimated by using data on genetic variants (single nucleotide polymorphisms) as proxy or instrumental variables, since appropriately selected genetic variants will be approximately randomly allocated to individuals (no confounding), at the time of conception (no reverse causality), and with can be measured with high precision (little measurement error). Data: I will use data from well-conducted genome-wide association studies to obtain robust evidence of the associations of genetic variants and health conditions (e.g. the CARDIOGRAM consortium for coronary artery disease). I will obtain data on the association of variants and costs from the UK Biobank. I will obtain information on the association between variants and quality of life from the Wisconsin Longitudinal Study, the Health and Retirement Study, and the English Longitudinal Study of ageing. Outputs: Research papers, methodological expositions and other dissemination outputs including conference presentations and public engagement


Research activity codes: 1.2 PSYCHOLOGICAL AND SOCIOECONOMIC PROCESSES
Health categories: GENERIC HEALTH RELEVANCE
Title: Improving the statistical efficiency of randomised controlled trials through their design
Funder: Medical Research Council

Abstract: Randomised controlled trials (RCTs) are an important tool for assessing the effectiveness of medical interventions. RCTs are expensive and time consuming, and designing more statistically efficient trials is therefore crucial. The primary objectives of this research are to develop and extend existing methodologies to assess the statistical efficiency of RCT designs, and compare the efficiency of different design features. This will be achieved through addressing the following questions: 1. How do design features, such as the number of interim visits, length of follow-up, and use of complex designs such as run-in periods, affect the statistical efficiency of an RCT? 2. What effect does missing data and/or non-compliance have on the optimal choice of such design features? 3. Is it possible to use routinely collected data such as electronic health records and disease registries to inform the optimal design of RCTs? These questions will be addressed by developing and extending methods for assessing the statistical efficiency of RCTs, including existing methodology based on linear mixed models. The methods will be explored using both simulation and application to case-studies, including RCT data from multiple sclerosis patients and a series of N-of-1 trials, and observational data from patients with Huntington's disease. This research will focus on two types of RCT: those which have an outcome that is a rate, and series of N-of-1 trials. These types of design are of particular interest since they can offer greatly improved statistical efficiency compared with standard alternatives. Due to the complexity of these designs, there are many choices to be made about the design features. Developing methods that allow the optimal design features to be chosen offers the opportunity to maximise the efficiency of these designs. The proposed research will provide information and methodologies that can be used to design statistically efficient RCTs.


Research activity codes: 6.9 RESOURCES AND INFRASTRUCTURE (TREATMENT EVALUATION);7.4 RESOURCES AND INFRASTRUCTURE (DISEASE MANAGEMENT)
Health categories: GENERIC HEALTH RELEVANCE
Title: Strengthening health system delivery and quality: Mechanisms and Effects of Performance Based Financing in the Sub-Saharan context
Funder: Medical Research Council

Abstract: This project aims to understand to what extent incentive payments to health care providers (performance based financing) contribute to improved service delivery (increased coverage of quality health services) and health and behavioural outcomes through health system strengthening, or enhancements to health system inputs in Sub-Saharan African settings. Specific attention will be given to understanding how PBF works in low and middle income countries (LMICs) over time, by extending evaluations of PBF schemes in Mozambique and Zimbabwe, and exploring the contextual factors that shape this. The research has six specific objectives. 1. To map key differences in PBF scheme design and context in each of the two countries and develop a theory of change for how PBF affects service delivery and health outcomes through changes to health system inputs; 2. To evaluate the short and longer term impact of PBF on health system inputs in each of the countries. 3. To evaluate the short and longer term impact of PBF on service delivery and health outcomes in each of the two countries. 4. To identify the specific causal pathway(s) through which performance based financing results in service delivery and health outcome effects; 5. To evaluate whether PBF effects on health system inputs, service delivery and health outcomes differ according to: scheme design; contextual factors; population characteristics; concurrent interventions, and the extent to which the design process projected and integrated measures to manage effects. 6. To develop a framework of conceptual links between PBF design, its effects on the health system, and ultimately on health outcomes that can be adapted to other countries as well as inform regional and global policy.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES;8.2 HEALTH AND WELFARE ECONOMICS
Health categories: GENERIC HEALTH RELEVANCE
Title: Impact of Rapid Expansion of the Estratégia de Saúde da Familia in Rio de Janeiro: Mixed Methods Evaluation
Funder: Medical Research Council

Abstract: Primary health care strengthening has been insufficiently prioritised in Universal Health Coverage proposals. This may be partly due to lack of evidence from middle-income countries. This project will use mixed methods to evaluate the impact of recent expansion of the Estratégia de Saúde da Familia (ESF) in Rio de Janeiro (RJ). The project has three interlinked work packages: WP1 An individual-level dataset linking PHC, hospital, mortality and welfare recipient data will be created. We will examine impacts of the ESF on a variety of outcome indicators and whether ESF benefits are similar across key patient characteristics (race/ethnicity, socio-economic status, literacy). We will explore potential synergistic health benefits from ESF and enrolment in a national conditional cash transfer programme (Bolsa Familia). Analytic approaches of the longitudinal dataset will include difference-in-difference analyses with propensity score matching, in addition to individual-level multi-level regression modelling. WP2 Micro-simulation modelling will exploit the large amount of estimates and parameters obtained from WP1 to model the effectiveness and cost-effectiveness of a variety of ESF coverage scenarios in RJ, and additionally in 16 Brazilian cities with more than 1 million population (where ESF coverage is low and 45 million (22%) of the population live). WP3: Our qualitative research component will focus on understanding patient and provider perspectives on the introduction of ESF, PHC processes (including comprehensiveness, coordination, and continuity), and health outcomes. Special attention will be given to potential barriers and facilitators to the implementation of the new care model. Data will be collected through three mutually complimentary methods: i) participant observation in family clinics, ii) semi-structured interviews with patients and health care workers iii) focus group interviews of community health workers.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE
Title: The dynamics of drug resistance within hospital populations of Gram-negative bacteria
Funder: Medical Research Council

Abstract: Mathematical models of the spread of antibiotic resistant bacteria (ARB) in a hospital usually do not take into account individual hospital level data on antibiotic usage or resistance. Nor do they consider the full complexity of resistance mechanisms, usually considering only a binary state. In this project I will construct new frameworks for ARB spread in hospitals. Firstly, I will extend an existing deterministic mathematical model to take into account not only diversity in fitness (or transmissibility) between bacteria, but also diversity in ability to survive at different antibiotic concentrations (i.e. resistance level). Diversity will be incorporated through a weighted mean function and the model will be analysed using a new diversity metric function. This will provide a theoretical framework to determine how resistance within a bacterial population changes under constant and then changing selective pressure. This framework will be adapted to account for mobile genetic element movement within Gram-negative bacteria and to include a stochastic rate at which resistances appear. The second part of the project will utilise hierarchical statistical methods that I wish to gain knowledge of and will have training in during this fellowship. These will allow me to determine trends in antibiotic usage and resistance. I will use time series analysis and multivariate regression to link these two data. Multi-level modelling will then test the links between hospital and patient level factors in driving differences in resistance and antibiotic usage. The final part will bring together the information on the bacterial population and the input the data on clinical trends. An initial deterministic homogeneously mixing compartmental model will be extended to include further population stratification and stochastic transmission, to compare intervention impact. This will be fitted to clinical data using Bayesian and Markov Chain Monte Carlo methods.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Verbal Autopsy with Participatory Action Research (VAPAR): expanding the knowledge base through partnerships for action on health equity
Funder: Medical Research Council

Abstract: Health systems are increasingly considered in terms beyond 'building blocks' models, as complex, adaptive, human and relational. Despite the conceptual advances, people-centered health systems research methods remain underdeveloped. The proposed work will connect two issues: the lack of information on the health of people excluded from access to health systems, and the low utilisation of research evidence by health systems stakeholders. The proposal is to institutionalise a process to strengthen data on mortality registration, combine with local knowledge, and interpret, plan and act on this basis in the health system at different levels. The method combines Verbal Autopsy (VA) with Participatory Action Research (PAR). VA is a method to determine levels, causes and circumstances of deaths. In PAR, communities organise evidence for action. 3 phases are proposed. In Phase 1, a series of 3 reflection and action cycles will be conducted to generate evidence, analyse, plan and act. Data will be generated on levels, causes and circumstances of deaths (using VA) and on health needs and priorities for action (using PAR) with communities. Data will be analysed with provincial level policy makers, action plans will be developed and implemented by district-level practitioners, and progress will be re-assessed in subsequent cycles. In Phase 2, participants and researchers will evaluate the process using realist and political economy methods to understand changes in care, outcomes and progress towards health equity. In Phase 3, sustainability and transferability will be developed with authorities, research and technical groups, health systems stakeholders and communities in the study site, and to the public. The output will be a process based on international standards, that is contextually relevant in health systems at different levels, and capable of translating local priorities into actionable agendas for health systems strengthening as a means towards health equity.


Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE
Title: Guidance on sample size when using observational data to develop and validate risk prediction models in health research
Funder: Medical Research Council

Abstract: Risk prediction models are used to make predictions regarding a patient's (current or future) health based on their clinical and demographic characteristics. An example of such a model is QRISK2 which is routinely used to estimate the risk of having a heart attack or stroke in the next 10 years. Risk models are typically developed using statistical models such as logistic or Cox regression and sample size plays a major role in ensuring that risk models are developed and validated correctly. There has been some work in this area but there are several remaining issues. It has been suggested through simulation that having an EPV (events per variable) ratio of least 10 results in unbiased estimates of the regression coefficients which should increase the chance that the resulting risk model can make reliable predictions. We intend to take a more focused approach that will also consider the accuracy of the individual predictions. We will also consider other very important risk model scenarios that include the development and validation of risk models for clustered data, the use of variable selection to develop models, and both internal and external validation. To date, there has been only limited work on sample size in these scenarios. Most of this work will be carried out using simulation based on real clinical datasets. Datasets with different characteristics (e.g. EPV, censoring, clustering) will be generated and various risk models (e.g. using variable selection, lasso) fitted to them. The performance of these risk models will be quantified in validation data using performance measures that consider the calibration and discrimination of the risk model. Analytical work will also be carried out where feasible. The primary objective of this research proposal is to develop comprehensive sample size guidance for researchers who develop and validate clinical risk models.


Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: Calibration of multiple treatment comparisons using individual patient data
Funder: Medical Research Council

Abstract: The integrity of conclusions drawn from indirect comparisons and network meta-analysis depend on the assumption that there is no imbalance in effect modifiers across the evidence on the different contrasts. Recently, new methods have been proposed which use IPD from a single (AB) trial (typically a manufacturer's trial) to generate an comparison that is supposed to be "adjusted" for imbalance in "baseline variables" between the AB and competitor AC trials These methods are appearing with increasing frequency in the literature and in submissions to NICE, although their reliability remains untested. Of some concern, they are also used to derive treatment effects from one arm studies, which implausibly assumes all prognostic factors affecting absolute outcomes are accounted for. We have developed new calibration-based methods which can be used to adjust for imbalances in effect modifiers in an entire connected network of treatment comparison, based on whatever IPD trial evidence is available, to generate a coherent set of treatment comparisons in any population with a known distribution of covariates. The methods make strong assumptions (specifically that all effect modifiers are included in the IPD data), but these are still far weaker than the assumptions made by standard network meta-analysis. We will compare the proposed calibration methods with other methods in a series of simulation studies. We will conduct empirical studies using data provided by project partners to: study the performance of adjustment and calibration methods applied to one-arm studies, to assess the assumption that all effect modifiers are accounted for, and to study the differences between methods in a number of real life examples.


Research activity codes: 6.1 PHARMACEUTICALS;8.3 POLICY, ETHICS AND RESEARCH GOVERNANCE
Health categories: GENERIC HEALTH RELEVANCE