ORCID Profile
0000-0002-8594-3061
Current Organisation
University of Cambridge
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Sociology | Consumption and Everyday Life | Environmental Sociology | Sociology and Social Studies of Science and Technology
Expanding Knowledge through Studies of Human Society | Residential Energy Conservation and Efficiency |
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 08-2023
Abstract: The aim of this study was to provide quantitative evidence of the use of polygenic risk scores for systematically identifying in iduals for invitation for full formal cardiovascular disease (CVD) risk assessment. A total of 108 685 participants aged 40 to 69 years, with measured biomarkers, linked primary care records, and genetic data in UK Biobank were used for model derivation and population health modeling. Prioritization tools using age, polygenic risk scores for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex‐specific Cox models. We modeled the implications of initiating guideline‐recommended statin therapy after prioritizing in iduals for invitation to a formal CVD risk assessment. If primary care records were used to prioritize in iduals for formal risk assessment using age‐ and sex‐specific thresholds corresponding to 5% false‐negative rates, then the numbers of men and women needed to be screened to prevent 1 CVD event are 149 and 280, respectively. In contrast, adding polygenic risk scores to both prioritization and formal assessments, and selecting thresholds to capture the same number of events, resulted in a number needed to screen of 116 for men and 180 for women. Using both polygenic risk scores and primary care records to prioritize in iduals at highest risk of a CVD event for a formal CVD risk assessment can efficiently prioritize those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of risk assessments in primary care while still preventing the same number of CVD events.
Publisher: Oxford University Press (OUP)
Date: 22-11-2018
Publisher: Cold Spring Harbor Laboratory
Date: 27-09-2021
DOI: 10.1101/2021.09.24.21264079
Abstract: Metabolic biomarker data quantified by nuclear magnetic resonance (NMR) spectroscopy has recently become available in UK Biobank. Here, we describe procedures for quality control and removal of technical variation for this biomarker data, comprising 249 circulating metabolites, lipids, and lipoprotein sub-fractions on approximately 121,000 participants. We identify and characterise technical and biological factors associated with in idual biomarkers and find that linear effects on in idual biomarkers can combine in a non-linear fashion for 61 composite biomarkers and 81 biomarker ratios. We create an R package, ukbnmr, for extracting and normalising the metabolic biomarker data, then use ukbnmr to remove unwanted variation from the UK Biobank data. We make available code for re-deriving the 61 composite biomarkers and 81 ratios, and for further derivation of 76 additional biomarker ratios of potential biological significance. Finally, we demonstrate that removal of technical variation leads to increased signal for genetic and epidemiological studies of the NMR metabolic biomarkers in UK Biobank.
Publisher: Elsevier BV
Date: 03-2011
Publisher: Springer Science and Business Media LLC
Date: 18-09-2007
DOI: 10.1007/S10654-007-9165-7
Abstract: Many long-term prospective studies have reported on associations of cardiovascular diseases with circulating lipid markers and/or inflammatory markers. Studies have not, however, generally been designed to provide reliable estimates under different circumstances and to correct for within-person variability. The Emerging Risk Factors Collaboration has established a central database on over 1.1 million participants from 104 prospective population-based studies, in which subsets have information on lipid and inflammatory markers, other characteristics, as well as major cardiovascular morbidity and cause-specific mortality. Information on repeat measurements on relevant characteristics has been collected in approximately 340,000 participants to enable estimation of and correction for within-person variability. Re-analysis of in idual data will yield up to approximately 69,000 incident fatal or nonfatal first ever major cardiovascular outcomes recorded during about 11.7 million person years at risk. The primary analyses will involve age-specific regression models in people without known baseline cardiovascular disease in relation to fatal or nonfatal first ever coronary heart disease outcomes. This initiative will characterize more precisely and in greater detail than has previously been possible the shape and strength of the age- and sex-specific associations of several lipid and inflammatory markers with incident coronary heart disease outcomes (and, secondarily, with other incident cardiovascular outcomes) under a wide range of circumstances. It will, therefore, help to determine to what extent such associations are independent from possible confounding factors and to what extent such markers (separately and in combination) provide incremental predictive value.
Publisher: Massachusetts Medical Society
Date: 04-10-2012
Publisher: Oxford University Press (OUP)
Date: 22-12-2013
DOI: 10.1093/AJE/KWT298
Publisher: Cold Spring Harbor Laboratory
Date: 22-10-2022
DOI: 10.1101/2022.10.20.22281120
Abstract: To provide quantitative evidence of the use of polygenic risk scores (PRS) for systematically identifying in iduals for invitation for full formal cardiovascular disease (CVD) risk assessment. 108,685 participants aged 40-69, with measured biomarkers, linked primary care records and genetic data in UK Biobank were used for model derivation and population health modelling. Prioritisation tools using age, PRS for coronary artery disease and stroke, and conventional risk factors for CVD available within longitudinal primary care records were derived using sex-specific Cox models. Rescaling to account for the healthy cohort effect, we modelled the implications of initiating guideline-recommended statin therapy after prioritising in iduals for invitation to a formal CVD risk assessment. 1,838 CVD events were observed over median follow up of 8.2 years. If primary care records were used to prioritise in iduals for formal risk assessment using age- and sex-specific thresholds corresponding to 5% false negative rates then we would capture 65% and 43% events amongst men and women respectively. The numbers of men and women needed to be screened to prevent one CVD event (NNS) are 74 and 140 respectively. In contrast, adding PRS to both prioritisation and formal assessments, and selecting thresholds to capture the same number of events resulted in a NNS of 60 for men and 90 for women. The use of PRS together with primary care records to prioritise in iduals at highest risk of a CVD event for a formal CVD risk assessment can more efficiently prioritise those who need interventions the most than using primary care records alone. This could lead to better allocation of resources by reducing the number of formal risk assessments in primary care while still preventing the same number CVD events.
Publisher: Oxford University Press (OUP)
Date: 29-05-2023
DOI: 10.1093/EURHEARTJ/EHAD260
Abstract: To develop and validate a recalibrated prediction model (SCORE2-Diabetes) to estimate the 10-year risk of cardiovascular disease (CVD) in in iduals with type 2 diabetes in Europe. SCORE2-Diabetes was developed by extending SCORE2 algorithms using in idual-participant data from four large-scale datasets comprising 229 460 participants (43 706 CVD events) with type 2 diabetes and without previous CVD. Sex-specific competing risk-adjusted models were used including conventional risk factors (i.e. age, smoking, systolic blood pressure, total, and HDL-cholesterol), as well as diabetes-related variables (i.e. age at diabetes diagnosis, glycated haemoglobin [HbA1c] and creatinine-based estimated glomerular filtration rate [eGFR]). Models were recalibrated to CVD incidence in four European risk regions. External validation included 217 036 further in iduals (38 602 CVD events), and showed good discrimination, and improvement over SCORE2 (C-index change from 0.009 to 0.031). Regional calibration was satisfactory. SCORE2-Diabetes risk predictions varied several-fold, depending on in iduals’ levels of diabetes-related factors. For ex le, in the moderate-risk region, the estimated 10-year CVD risk was 11% for a 60-year-old man, non-smoker, with type 2 diabetes, average conventional risk factors, HbA1c of 50 mmol/mol, eGFR of 90 mL/min/1.73 m2, and age at diabetes diagnosis of 60 years. By contrast, the estimated risk was 17% in a similar man, with HbA1c of 70 mmol/mol, eGFR of 60 mL/min/1.73 m2, and age at diabetes diagnosis of 50 years. For a woman with the same characteristics, the risk was 8% and 13%, respectively. SCORE2-Diabetes, a new algorithm developed, calibrated, and validated to predict 10-year risk of CVD in in iduals with type 2 diabetes, enhances identification of in iduals at higher risk of developing CVD across Europe.
Publisher: Oxford University Press (OUP)
Date: 13-06-2021
DOI: 10.1093/EURHEARTJ/EHAB309
Abstract: The aim of this study was to develop, validate, and illustrate an updated prediction model (SCORE2) to estimate 10-year fatal and non-fatal cardiovascular disease (CVD) risk in in iduals without previous CVD or diabetes aged 40–69 years in Europe. We derived risk prediction models using in idual-participant data from 45 cohorts in 13 countries (677 684 in iduals, 30 121 CVD events). We used sex-specific and competing risk-adjusted models, including age, smoking status, systolic blood pressure, and total- and HDL-cholesterol. We defined four risk regions in Europe according to country-specific CVD mortality, recalibrating models to each region using expected incidences and risk factor distributions. Region-specific incidence was estimated using CVD mortality and incidence data on 10 776 466 in iduals. For external validation, we analysed data from 25 additional cohorts in 15 European countries (1 133 181 in iduals, 43 492 CVD events). After applying the derived risk prediction models to external validation cohorts, C-indices ranged from 0.67 (0.65–0.68) to 0.81 (0.76–0.86). Predicted CVD risk varied several-fold across European regions. For ex le, the estimated 10-year CVD risk for a 50-year-old smoker, with a systolic blood pressure of 140 mmHg, total cholesterol of 5.5 mmol/L, and HDL-cholesterol of 1.3 mmol/L, ranged from 5.9% for men in low-risk countries to 14.0% for men in very high-risk countries, and from 4.2% for women in low-risk countries to 13.7% for women in very high-risk countries. SCORE2—a new algorithm derived, calibrated, and validated to predict 10-year risk of first-onset CVD in European populations—enhances the identification of in iduals at higher risk of developing CVD across Europe.
Publisher: American Medical Association (AMA)
Date: 22-07-2009
Publisher: Elsevier BV
Date: 2010
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 15-11-2022
DOI: 10.1161/CIRCULATIONAHA.122.060700
Abstract: End-stage renal disease is associated with a high risk of cardiovascular events. It is unknown, however, whether mild-to-moderate kidney dysfunction is causally related to coronary heart disease (CHD) and stroke. Observational analyses were conducted using in idual-level data from 4 population data sources (Emerging Risk Factors Collaboration, EPIC-CVD [European Prospective Investigation into Cancer and Nutrition–Cardiovascular Disease Study], Million Veteran Program, and UK Biobank), comprising 648 135 participants with no history of cardiovascular disease or diabetes at baseline, yielding 42 858 and 15 693 incident CHD and stroke events, respectively, during 6.8 million person-years of follow-up. Using a genetic risk score of 218 variants for estimated glomerular filtration rate (eGFR), we conducted Mendelian randomization analyses involving 413 718 participants (25 917 CHD and 8622 strokes) in EPIC-CVD, Million Veteran Program, and UK Biobank. There were U-shaped observational associations of creatinine-based eGFR with CHD and stroke, with higher risk in participants with eGFR values or mL·min –1 ·1.73 m –2 , compared with those with eGFR between 60 and 105 mL·min –1 ·1.73 m –2 . Mendelian randomization analyses for CHD showed an association among participants with eGFR mL·min –1 ·1.73 m –2 , with a 14% (95% CI, 3%–27%) higher CHD risk per 5 mL·min –1 ·1.73 m –2 lower genetically predicted eGFR, but not for those with eGFR mL·min –1 ·1.73 m –2 . Results were not materially different after adjustment for factors associated with the eGFR genetic risk score, such as lipoprotein(a), triglycerides, hemoglobin A1c, and blood pressure. Mendelian randomization results for stroke were nonsignificant but broadly similar to those for CHD. In people without manifest cardiovascular disease or diabetes, mild-to-moderate kidney dysfunction is causally related to risk of CHD, highlighting the potential value of preventive approaches that preserve and modulate kidney function.
Publisher: Elsevier BV
Date: 10-2019
Publisher: Oxford University Press (OUP)
Date: 23-07-2012
DOI: 10.1093/IJE/DYS086
Publisher: Oxford University Press (OUP)
Date: 03-05-2010
DOI: 10.1093/IJE/DYQ063
Publisher: Public Library of Science (PLoS)
Date: 14-01-2021
DOI: 10.1371/JOURNAL.PMED.1003498
Abstract: Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. Using data from UK Biobank on 306,654 in iduals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years females: 57% median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million in iduals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 in iduals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to %) 10-year CVD risk could help prevent 1 additional CVD event for approximately every 340 in iduals screened. Such a targeted strategy could help prevent 7% more CVD events than conventional risk prediction alone. Potential gains afforded by assessment of PRSs on top of conventional risk factors would be about 1.5-fold greater than those provided by assessment of C-reactive protein, a plasma biomarker included in some risk prediction guidelines. Potential limitations of this study include its restriction to European ancestry participants and a lack of health economic evaluation. Our results suggest that addition of PRSs to conventional risk factors can modestly enhance prediction of first-onset CVD and could translate into population health benefits if used at scale.
Publisher: American Medical Association (AMA)
Date: 07-07-2015
Publisher: Wiley
Date: 20-12-2014
Publisher: American Medical Association (AMA)
Date: 11-11-2009
Publisher: American Medical Association (AMA)
Date: 20-06-2012
Publisher: Springer Science and Business Media LLC
Date: 05-2015
Publisher: Elsevier BV
Date: 06-2010
Publisher: Wiley
Date: 10-02-2009
DOI: 10.1002/SIM.3378
Abstract: Many measures have been proposed to summarize the prognostic ability of the Cox proportional hazards (CPH) survival model, although none is universally accepted for general use. By contrast, little work has been done to summarize the prognostic ability of the stratified CPH model such measures would be useful in analyses of in idual participant data from multiple studies, data from multi-centre studies, and in single study analysis where stratification is used to avoid making assumptions of proportional hazards. We have chosen three measures developed for the unstratified CPH model (Schemper and Henderson's V , Harrell's C-index and Royston and Sauerbrei's D), adapted them for use with the stratified CPH model and demonstrated how their values can be represented over time. Although each of these measures is promising in principle, we found the measure of explained variation V very difficult to apply when data are combined from several studies with differing durations of participant follow-up. The two other measures considered, D and the C-index, were more applicable under such circumstances. We illustrate the methods using in idual participant data from several prospective epidemiological studies of chronic disease outcomes.
Publisher: Cold Spring Harbor Laboratory
Date: 22-08-2019
DOI: 10.1101/744565
Abstract: There is debate about the value of adding information on genetic and other molecular markers to conventional cardiovascular disease (CVD) risk predictors. Using data on 306,654 in iduals without a history of CVD from UK Biobank, we calculated measures of risk-discrimination and reclassification upon addition of polygenic risk scores (PRS) and a panel of 27 clinical biochemistry markers to a conventional risk prediction model (i.e., including age, sex, systolic blood pressure, smoking status, history of diabetes, total cholesterol and HDL cholesterol). We then modelled implications of initiating guideline-recommended statin therapy after the assessment of molecular markers for a UK primary-care setting. The C-index was 0.710 (95% CI, 0.703-0.717) for a CVD prediction model containing conventional risk predictors alone. The C-index increased by similar amounts when adding information on PRS or biochemistry markers (0.011 and 0.014, respectively P .001), and it increased still further (0.022 P .001) when information on both was combined. Among cases and controls, continuous net reclassification improvements were about 12% and 19%, respectively, when both PRS and biochemistry markers were added. If PRS and biochemistry markers were to be assessed in the entire primary care population aged 40-75, then it could help prevent one additional CVD event for every 893 in iduals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5-10%) 10-year CVD risk could help prevent one additional CVD event for every 233 in iduals screened. This targeted strategy could help reclassify 16% of the intermediate-risk group to the high-risk (i.e., ≥10%) category, preventing 11% more CVD events than conventional risk prediction. Adding information on both PRS and selected biochemistry markers moderately enhanced CVD predictive accuracy and could improve primary prevention of CVD. However, our modelling suggested that targeted assessment of molecular markers among in iduals at intermediate-risk would be more efficient than blanket approaches.
Publisher: Wiley
Date: 09-09-2011
DOI: 10.1002/SIM.4362
Publisher: Oxford University Press (OUP)
Date: 13-06-2017
DOI: 10.1093/AJE/KWX149
Publisher: American Medical Association (AMA)
Date: 02-2019
Publisher: Massachusetts Medical Society
Date: 03-03-2011
Publisher: American Medical Association (AMA)
Date: 26-03-2014
Publisher: Oxford University Press (OUP)
Date: 13-06-2021
DOI: 10.1093/EURHEARTJ/EHAB312
Abstract: The aim of this study was to derive and validate the SCORE2-Older Persons (SCORE2-OP) risk model to estimate 5- and 10-year risk of cardiovascular disease (CVD) in in iduals aged over 70 years in four geographical risk regions. Sex-specific competing risk-adjusted models for estimating CVD risk (CVD mortality, myocardial infarction, or stroke) were derived in in iduals aged over 65 without pre-existing atherosclerotic CVD from the Cohort of Norway (28 503 in iduals, 10 089 CVD events). Models included age, smoking status, diabetes, systolic blood pressure, and total- and high-density lipoprotein cholesterol. Four geographical risk regions were defined based on country-specific CVD mortality rates. Models were recalibrated to each region using region-specific estimated CVD incidence rates and risk factor distributions. For external validation, we analysed data from 6 additional study populations {338 615 in iduals, 33 219 CVD validation cohorts, C-indices ranged between 0.63 [95% confidence interval (CI) 0.61–0.65] and 0.67 (0.64–0.69)}. Regional calibration of expected-vs.-observed risks was satisfactory. For given risk factor profiles, there was substantial variation across the four risk regions in the estimated 10-year CVD event risk. The competing risk-adjusted SCORE2-OP model was derived, recalibrated, and externally validated to estimate 5- and 10-year CVD risk in older adults (aged 70 years or older) in four geographical risk regions. These models can be used for communicating the risk of CVD and potential benefit from risk factor treatment and may facilitate shared decision-making between clinicians and patients in CVD risk management in older persons.
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 2015
End Date: 06-2018
Amount: $370,000.00
Funder: Australian Research Council
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