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We lead multidisciplinary applied research and training to rethink the way health care is delivered in general practice and across the community.
Determining the feasibility of calculating pancreatic cancer risk scores for people with new-onset diabetes in primary care (DEFEND PRIME): study protocol.
INTRODUCTION: Worldwide, pancreatic cancer has a poor prognosis. Early diagnosis may improve survival by enabling curative treatment. Statistical and machine learning diagnostic prediction models using risk factors such as patient demographics and blood tests are being developed for clinical use to improve early diagnosis. One example is the Enriching New-onset Diabetes for Pancreatic Cancer (ENDPAC) model, which employs patients' age, blood glucose and weight changes to provide pancreatic cancer risk scores. These values are routinely collected in primary care in the UK. Primary care's central role in cancer diagnosis makes it an ideal setting to implement ENDPAC but it has yet to be used in clinical settings. This study aims to determine the feasibility of applying ENDPAC to data held by UK primary care practices. METHODS AND ANALYSIS: This will be a multicentre observational study with a cohort design, determining the feasibility of applying ENDPAC in UK primary care. We will develop software to search, extract and process anonymised data from 20 primary care providers' electronic patient record management systems on participants aged 50+ years, with a glycated haemoglobin (HbA1c) test result of ≥48 mmol/mol (6.5%) and no previous abnormal HbA1c results. Software to calculate ENDPAC scores will be developed, and descriptive statistics used to summarise the cohort's demographics and assess data quality. Findings will inform the development of a future UK clinical trial to test ENDPAC's effectiveness for the early detection of pancreatic cancer. ETHICS AND DISSEMINATION: This project has been reviewed by the University of Surrey University Ethics Committee and received a favourable ethical opinion (FHMS 22-23151 EGA). Study findings will be presented at scientific meetings and published in international peer-reviewed journals. Participating primary care practices, clinical leads and policy makers will be provided with summaries of the findings.
Fracture prediction in rheumatoid arthritis: validation of FRAX with bone mineral density for incident major osteoporotic fractures.
OBJECTIVES: FRAX® uses clinical risk factors, with or without bone mineral density (BMD), to calculate 10-year fracture risk. Rheumatoid arthritis (RA) is a risk factor for osteoporotic fracture and a FRAX input variable. FRAX predates the current era of RA treatment. We examined how well FRAX predicts fracture in contemporary RA patients. METHODS: Administrative data from patients receiving BMD testing were linked to the Manitoba Population Health Research Data Repository. Observed cumulative 10-year Major Osteoporotic Fracture (MOF) probability was compared with FRAX-predicted 10-year MOF probability with BMD for assessing calibration. MOF risk stratification was assessed using Cox regression. RESULTS: RA patients (N = 2,099, 208 with incident MOF) and non-RA patients (N = 2,099, with 165 incident MOF) were identified. For RA patients, FRAX predicted 10-year risk was 13.2% and observed 10-year MOF risk was 13.2% (95% CI 11.6% to 15.1%). The slope of the calibration plot was 0.67 (95% CI 0.53-0. 81) in those with RA vs 0.98 (95% CI 0.61-1.34) in non-RA patients. Risk was overestimated in RA patients with high FRAX scores (>20%), but FRAX was well-calibrated in other groups. FRAX stratified risk in those with and without RA (hazard ratios 1.52, 95% 1.25-1.72 vs 2.00, 95% 1.73-2.31), with slightly better performance in the latter (p-interaction = 0.004). CONCLUSIONS: FRAX predicts fracture risk in contemporary RA patients but may slightly overestimate risk in those already at high predicted risk. Thus, the current FRAX tool continues to be appropriate for fracture risk assessment in RA patients.
Tobacco smoking and risks of more than 470 diseases in China: a prospective cohort study
Background: Tobacco smoking is estimated to account for more than 1 million annual deaths in China, and the epidemic continues to increase in men. Large nationwide prospective studies linked to different health records can help to periodically assess disease burden attributed to smoking. We aimed to examine associations of smoking with incidence of and mortality from an extensive range of diseases in China. Methods: We analysed data from the prospective China Kadoorie Biobank, which recruited 512 726 adults aged 30–79 years, of whom 210 201 were men and 302 525 were women. Participants who had no major disabilities were identified through local residential records in 100–150 administrative units, which were randomly selected by use of multistage cluster sampling, from each of the ten diverse study areas of China. They were invited and recruited between June 25, 2004, and July 15, 2008. Upon study entry, trained health workers administered a questionnaire assessing detailed smoking behaviours and other key characteristics (eg, sociodemographics, lifestyle, and medical history). Participants were followed up via electronic record linkages to death and disease registries and health insurance databases, from baseline to Jan 1, 2018. During a median 11-year follow-up (IQR 10–12), 285 542 (55·7%) participants were ever hospitalised, 48 869 (9·5%) died, and 5252 (1·0%) were lost to follow-up during the age-at-risk of 35–84 years. Cox regression yielded hazard ratios (HRs) associating smoking with disease incidence and mortality, adjusting for multiple testing. Findings: At baseline, 74·3% of men and 3·2% of women (overall 32·4%) ever smoked regularly. During follow-up, 1 137 603 International Classification of Diseases, 10th revision (ICD-10)-coded incident events occurred, involving 476 distinct conditions and 85 causes of death, each with at least 100 cases. Compared with never-regular smokers, ever-regular smokers had significantly higher risks for nine of 18 ICD-10 chapters examined at age-at-risk of 35–84 years. For individual conditions, smokers had significantly higher risks of 56 diseases (50 for men and 24 for women) and 22 causes of death (17 for men and nine for women). Among men, ever-regular smokers had an HR of 1·09 (95% CI 1·08–1·11) for any disease incidence when compared with never-regular smokers, and significantly more episodes and longer duration of hospitalisation, particularly those due to cancer and respiratory diseases. For overall mortality, the HRs were greater in men from urban areas than in men from rural areas (1·50 [1·42–1·58] vs 1·25 [1·20–1·30]). Among men from urban areas who began smoking at younger than 18 years, the HRs were 2·06 (1·89–2·24) for overall mortality and 1·32 (1·27–1·37) for any disease incidence. In this population, 19·6% of male (24·3% of men residing in urban settings and 16·2% of men residing in rural settings) and 2·8% of female deaths were attributed to ever-regular smoking. Interpretation: Among Chinese adults, smoking was associated with higher risks of morbidity and mortality from a wide range of diseases. Among men, the future smoking-attributed disease burden will increase further, highlighting a pressing need for reducing consumption through widespread cessation and uptake prevention. Funding: British Heart Foundation, Cancer Research UK, Chinese Ministry of Science and Technology, Kadoorie Charitable Foundation, UK Medical Research Council, National Natural Science Foundation of China, Wellcome Trust.
Utility of single versus sequential measurements of risk factors for prediction of stroke in Chinese adults
Absolute risks of stroke are typically estimated using measurements of cardiovascular disease risk factors recorded at a single visit. However, the comparative utility of single versus sequential risk factor measurements for stroke prediction is unclear. Risk factors were recorded on three separate visits on 13,753 individuals in the prospective China Kadoorie Biobank. All participants were stroke-free at baseline (2004–2008), first resurvey (2008), and second resurvey (2013–2014), and were followed-up for incident cases of first stroke in the 3 years following the second resurvey. To reflect the models currently used in clinical practice, sex-specific Cox models were developed to estimate 3-year risks of stroke using single measurements recorded at second resurvey and were retrospectively applied to risk factor data from previous visits. Temporal trends in the Cox-generated risk estimates from 2004 to 2014 were analyzed using linear mixed effects models. To assess the value of more flexible machine learning approaches and the incorporation of longitudinal data, we developed gradient boosted tree (GBT) models for 3-year prediction of stroke using both single measurements and sequential measurements of risk factor inputs. Overall, Cox-generated estimates for 3-year stroke risk increased by 0.3% per annum in men and 0.2% per annum in women, but varied substantially between individuals. The risk estimates at second resurvey were highly correlated with the annual increase of risk for each individual (men: r = 0.91, women: r = 0.89), and performance of the longitudinal GBT models was comparable with both Cox and GBT models that considered measurements from only a single visit (AUCs: 0.779–0.811 in men, 0.724–0.756 in women). These results provide support for current clinical guidelines, which recommend using risk factor measurements recorded at a single visit for stroke prediction.
WHO cardiovascular disease risk prediction model performance in 10 regions, China
Objective To validate the World Health Organization (WHO) non-laboratory-based cardiovascular disease risk prediction model in regions of China. Methods We performed an external validation of the WHO model for East Asia using the data set of China Kadoorie Biobank, an ongoing cohort study with 512 725 participants recruited from 10 regions of China from 2004–2008. We also recalculated the recalibration parameters for the WHO model in each region and evaluated the predictive performance of the model before and after recalibration. We assessed discrimination performance by Harrell’s C index. Findings We included 412 225 participants aged 40–79 years. During a median follow-up of 11 years, 58 035 and 41 262 incident cardiovascular disease cases were recorded in women and men, respectively. Harrell's C of the WHO model was 0.682 in women and 0.700 in men but varied among regions. The WHO model underestimated the 10-year cardiovascular disease risk in most regions. After recalibration in each region, discrimination and calibration were both improved in the overall population. Harrell’s C increased from 0.674 to 0.749 in women and from 0.698 to 0.753 in men. The ratios of predicted to observed cases before and after recalibration were 0.189 and 1.027 in women and 0.543 and 1.089 in men. Conclusion The WHO model for East Asia yielded moderate discrimination for cardiovascular disease in the Chinese population and had limited prediction for cardiovascular disease risk in different regions in China. Recalibration for diverse regions greatly improved discrimination and calibration in the overall population.
Modeling biological age using blood biomarkers and physical measurements in Chinese adults
Background: This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. Methods: The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004–08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). Findings: The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (−0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). Interpretation: In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. Funding: This work was supported by National Natural Science Foundation of China ( 82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust ( 212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants ( 2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China ( 81390540, 91846303), and Chinese Ministry of Science and Technology ( 2011BAI09B01).
Impacts of solid fuel use versus smoking on life expectancy at age 30 years in the rural and urban Chinese population: a prospective cohort study
Background: The impact of solid fuel use on life expectancy (LE) in less-developed countries remains unclear. We aimed to evaluate the potential impact of household solid fuel use on LE in the rural and urban Chinese population, with the effect of smoking as a reference. Methods: We used data from China Kadoorie Biobank (CKB) of 484,915 participants aged 30–79 free of coronary heart disease, stroke, or cancer at baseline. Analyses were performed separately for solid fuel use for cooking, solid fuel use for heating, and smoking, with participants exposed to the other two sources excluded. Solid fuels refer to coal and wood, and clean fuels refer to electricity, gas, and central heating. We used a flexible parametric Royston-Parmar model to estimate hazard ratios of all-cause mortality and predict LE at age 30. Findings: Totally, 185,077, 95,228, and 230,995 participants were included in cooking-, heating-, and smoking-related analyses, respectively. During a median follow-up of approximately 12.1 years, 12,725, 7,531, and 18,878 deaths were recorded in the respective analysis. Compared with clean fuel users who reported cooking with ventilation, participants who used solid fuels with ventilation and without ventilation had a difference in LE (95% confidence interval [CI]) at age 30 of −1.72 (−2.88, −0.57) and −2.62 (−4.16, −1.05) years for men and −1.33 (−1.85, −0.81) and −1.35 (−2.02, −0.67) years for women, respectively. The difference in LE (95% CI) for heating was −2.23 (−3.51, −0.95) years for men and −1.28 (−2.08, −0.48) years for women. In rural men, the LE reduction (95% CI) related to solid fuel use for cooking (−2.55; −4.51, −0.58) or heating (−3.26; −6.09, 0.44) was more than that related to smoking (−1.71; −2.54, −0.89). Conversely, in urban men, the LE reduction (95% CI) related to smoking (−3.06; −3.56, −2.56) was more than that related to solid fuel use for cooking (−1.28; −2.61, 0.05) and heating (−1.90; −3.16, −0.65). Similar results were observed in women but with a smaller magnitude. Interpretation: In this Chinese population, the harm to LE from household use of solid fuels was greater than that from smoking in rural residents. Conversely, the negative impact of smoking was greater than solid fuel use in urban residents. Our findings highlight the complexity and diversity of the factors affecting LE in less-developed populations. Funding: National Natural Science Foundation of China, National Key R&D Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.
Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study
Objective: To develop and externally validate the STRAtifying Treatments In the multi-morbid Frail elderlY (STRATIFY)-Falls clinical prediction model to identify the risk of hospital admission or death from a fall in patients with an indication for antihypertensive treatment. Design: Retrospective cohort study. Setting: Primary care data from electronic health records contained within the UK Clinical Practice Research Datalink (CPRD). Participants: Patients aged 40 years or older with at least one blood pressure measurement between 130 mm Hg and 179 mm Hg. Main outcome measure: First serious fall, defined as hospital admission or death with a primary diagnosis of a fall within 10 years of the index date (12 months after cohort entry). Model development was conducted using a Fine-Gray approach in data from CPRD GOLD, accounting for the competing risk of death from other causes, with subsequent recalibration at one, five, and 10 years using pseudo values. External validation was conducted using data from CPRD Aurum, with performance assessed through calibration curves and the observed to expected ratio, C statistic, and D statistic, pooled across general practices, and clinical utility using decision curve analysis at thresholds around 10%. Results: Analysis included 1 772 600 patients (experiencing 62 691 serious falls) from CPRD GOLD used in model development, and 3 805 366 (experiencing 206 956 serious falls) from CPRD Aurum in the external validation. The final model consisted of 24 predictors, including age, sex, ethnicity, alcohol consumption, living in an area of high social deprivation, a history of falls, multiple sclerosis, and prescriptions of antihypertensives, antidepressants, hypnotics, and anxiolytics. Upon external validation, the recalibrated model showed good discrimination, with pooled C statistics of 0.833 (95% confidence interval 0.831 to 0.835) and 0.843 (0.841 to 0.844) at five and 10 years, respectively. Original model calibration was poor on visual inspection and although this was improved with recalibration, under-prediction of risk remained (observed to expected ratio at 10 years 1.839, 95% confidence interval 1.811 to 1.865). Nevertheless, decision curve analysis suggests potential clinical utility, with net benefit larger than other strategies. Conclusions: This prediction model uses commonly recorded clinical characteristics and distinguishes well between patients at high and low risk of falls in the next 1-10 years. Although miscalibration was evident on external validation, the model still had potential clinical utility around risk thresholds of 10% and so could be useful in routine clinical practice to help identify those at high risk of falls who might benefit from closer monitoring or early intervention to prevent future falls. Further studies are needed to explore the appropriate thresholds that maximise the model's clinical utility and cost effectiveness.
Opt-in versus universal codeine provision for medical abortion up to 10 weeks of gestation at British Pregnancy Advisory Service: a cross-sectional evaluation
ObjectiveTo assess patient experiences of pain management during medical abortion up to 10 weeks’ gestation with opt-in versus universal codeine provision.MethodsWe invited patients who underwent medical abortion up to 10 weeks of gestation to participate in an online, anonymous, English-language survey from November 2021 to March 2022. We performed ordinal regression analyses to compare satisfaction with pain management (5-point Likert scale) and maximum abortion pain score (11-point numerical rating scale) in the opt-in versus universal codeine provision groups.ResultsOf 11 906 patients invited to participate, 1625 (13.6%) completed the survey. Participants reported a mean maximum pain score of 6.8±2.2. A total of 1149 participants (70.7%) reported using codeine for pain management during their abortion. Participants in the opt-in codeine provision group were significantly more likely to be satisfied with their pain management than those in the universal group (aOR 1.48, 95% CI 1.12 to 1.96, p<0.01). Maximum abortion pain scores were lower on average among the opt-in codeine provision group (OR 0.80, 95% CI 0.66 to 0.96, p=0.02); however, this association was not statistically significant in the model adjusted for covariates (aOR 0.85, 95% CI 0.70 to 1.03, p=0.09).ConclusionOur findings suggest that patients have a better experience with pain management during medical abortion when able to opt-in to codeine provision following counselling versus receiving this medication routinely.
Framework for understanding movement and physical activity in patients diagnosed with psychosis.
BACKGROUND: Patients diagnosed with psychosis often spend less time than others engaged in exercise and more time sitting down, which likely contributes to poorer physical and mental health. OBJECTIVE: The aim of this study was to develop a comprehensive framework from the perspective of patients, carers, and staff for understanding what promotes movement and physical activity. METHODS: A critical realist approach was taken to design the study. Interviews (n=23) and focus groups (n=12) were conducted with (1) outpatients aged 16 years or older diagnosed with psychosis, and under the care of a mental health team, (2) carers and (3) mental health staff working in the community. Purposive sampling was used to maximise variation in participant characteristics. Data were analysed using reflexive thematic analysis. FINDINGS: 19 patients (9 women and 10 men, mean age=45·0 (SD=12·2) years, 15 White British, 2 Black African, 1 Pakistani and 1 other ethnic group), 14 carers (11 women and 3 men, mean age=59·9 (SD=12·7) years, 13 White British and 1 Asian) and 18 staff (14 women and 4 men, mean age=38·7 (SD=12·3) years, 15 White British, 1 White other, 1 Asian Bangladeshi and 1 other Asian) participated in the study. Five factors were found to promote movement and physical activity. Patients must be able to find a purpose to moving which is meaningful to them (Factor 1: Purpose). Patients need to have an expectation of the positive consequences of movement and physical activity, which can be influenced by others' expectations (Factor 2: Predictions). A patient's current physical (eg, pain) and emotional state (eg, distress about voices) needs to be addressed to allow movement and physical activity (Factor 3: Present state). Movement and physical activity can also be encouraged by the availability of effective and tailored support, provided by engaged and supported people (Factor 4: Provision). Finally, through the identification and interruption of vicious cycles (eg, between inactivity and mood states) more positive cycles can be put in place (Factor 5: Process). CONCLUSIONS AND CLINICAL IMPLICATIONS: The 5 P (Purpose, Predictions, Present state, Provision and Process Physical Activity Framework) for understanding movement and physical activity for people diagnosed with psychosis has the potential to inform future research and guide interventions. A checklist is provided for clinicians to help foster change in activity levels.
Clinical and cost-effectiveness of DREAMS START (Dementia RElAted Manual for Sleep; STrAtegies for RelaTives) for people living with dementia and their carers: a study protocol for a parallel multicentre randomised controlled trial.
INTRODUCTION: Many people living with dementia experience sleep disturbance and there are no known effective treatments. Non-pharmacological treatment options should be the first-line sleep management. For family carers, relatives' sleep disturbance leads to interruption of their sleep, low mood and breakdown of care. Our team developed and delivered DREAMS START (Dementia RElAted Manual for Sleep; STrAtegies for RelaTives), a multimodal non-pharmacological intervention, showing it to be feasible and acceptable. The aim of this randomised controlled trial is to establish whether DREAMS START is clinically cost-effective in reducing sleep disturbances in people living with dementia living at home compared with usual care. METHODS AND ANALYSIS: We will recruit 370 participant dyads (people living with dementia and family carers) from memory services, community mental health teams and the Join Dementia Research Website in England. Those meeting inclusion criteria will be randomised (1:1) either to DREAMS START or to usual treatment. DREAMS START is a six-session (1 hour/session), manualised intervention delivered every 1-2 weeks by supervised, non-clinically trained graduates. Outcomes will be collected at baseline, 4 months and 8 months with the primary outcome being the Sleep Disorders Inventory score at 8 months. Secondary outcomes for the person with dementia (all proxy) include quality of life, daytime sleepiness, neuropsychiatric symptoms and cost-effectiveness. Secondary outcomes for the family carer include quality of life, sleep disturbance, mood, burden and service use and caring/work activity. Analyses will be intention-to-treat and we will conduct a process evaluation. ETHICS AND DISSEMINATION: London-Camden & Kings Cross Ethics Committee (20/LO/0894) approved the study. We will disseminate our findings in high-impact peer-reviewed journals and at national and international conferences. This research has the potential to improve sleep and quality of life for people living with dementia and their carers, in a feasible and scalable intervention. TRIAL REGISTRATION NUMBER: ISRCTN13072268.