Cardiovascular risk models for South Asian populations: a systematic review.

OBJECTIVES: To review existing cardiovascular risk models applicable to South Asian populations. METHODS: A systematic review of the literature using a combination of search terms for "South Asian", "cardiovascular", "risk"/"score" and existing risk models for inclusion. South Asian was defined as those residing in or with ancestry belonging to the Indian subcontinent. RESULTS: The literature search including MEDLINE and EMBASE identified 7560 papers. After full-text review, 4 papers met the inclusion criteria. Only 1 reported formal measures of model performance. In that study, both a modified Framingham model and QRISK2 showed similar good discrimination with AUROCs of 0.73-0.77 with calibration also reasonable in men (0.71-0.93) but poor in women (0.43-0.52). CONCLUSIONS: Considering the number of South Asians and prevalence of cardiovascular disease, very few studies have reported performance of risk scores in South Asian populations. Furthermore, it was difficult to make comparisons, as many did not provide measures of discrimination, accuracy and calibration. There is a need for further research to evaluate risk models in South Asians, and ideally derive and validate cardiovascular risk models within South Asian populations.JUS is supported by a National Institute of Health Research (NIHR) Clinical Lectureship.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00038-015-0733-

The spectrum effect in tests for risk prediction, screening, and diagnosis.

The spectrum effect describes the variation between settings in performance of tests used to predict, screen for, and diagnose disease. In particular, the predictive use of a test may be different when it is applied in a general population rather than in the study sample in which it was first developed. This article discusses the impact of the spectrum effect on measures of test performance, and its implications for the development, evaluation, application, and implementation of such tests.JUS is supported by a National Institute of Health Research (NIHR) Clinical Lectureship. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. SJS is supported by the Medical Research Council www.mrc.ac.uk [Unit Programme number MC_UU_12015/1].This is the final version of the article. It first appeared from the BMJ Group via https://doi.org/10.1136/bmj.i313

Development and usability testing of a very brief intervention for personalised cancer risk assessment to promote behaviour change in primary care using normalisation process theory.

BACKGROUND: Cancer is the second leading cause of death worldwide. Lifestyle choices play an important role in the aetiology of cancer with up to 4 in 10 cases potentially preventable. Interventions delivered by healthcare professionals (HCPs) that incorporate risk information have the potential to promote behaviour change. Our aim was to develop a very brief intervention incorporating cancer risk, which could be implemented within primary care. METHODS: Guided by normalisation process theory (NPT), we developed a prototype intervention using literature reviews, consultation with patient and public representatives and pilot work with patients and HCPs. We conducted focus groups and interviews with 65 HCPs involved in delivering prevention activities. Findings were used to refine the intervention before 22 HCPs completed an online usability test and provided further feedback via a questionnaire incorporating a modified version of the NoMAD checklist. RESULTS: The intervention included a website where individuals could provide information on lifestyle risk factors view their estimated 10-year risk of developing one or more of the five most common preventable cancers and access lifestyle advice incorporating behaviour change techniques. Changes incorporated from feedback from the focus groups and interviews included signposting to local services and websites, simplified wording and labelling of risk information. In the usability testing, all participants felt it would be easy to collect the risk information. Ninety-one percent felt the intervention would enable discussion about cancer risk and believed it had potential to be easily integrated into National Health Service (NHS) Health Checks. However, only 36% agreed it could be delivered within 5 min. CONCLUSIONS: With the use of NPT, we developed a very brief intervention that is acceptable to HCPs in primary care and could be potentially integrated into NHS Health Checks. However, further work is needed to assess its feasibility and potential effectiveness

Risk prediction models for melanoma: a systematic review.

Melanoma incidence is increasing rapidly worldwide among white-skinned populations. Earlier diagnosis is the principal factor that can improve prognosis. Defining high-risk populations using risk prediction models may help targeted screening and early detection approaches. In this systematic review, we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict risk of developing cutaneous melanoma. A total of 4,141 articles were identified from the literature search and six through citation searching. Twenty-five risk models were included. Between them, the models considered 144 possible risk factors, including 18 measures of number of nevi and 26 of sun/UV exposure. Those most frequently included in final risk models were number of nevi, presence of freckles, history of sunburn, hair color, and skin color. Despite the different factors included and different cutoff values for sensitivity and specificity, almost all models yielded sensitivities and specificities that fit along a summary ROC with area under the ROC (AUROC) of 0.755, suggesting that most models had similar discrimination. Only two models have been validated in separate populations and both also showed good discrimination with AUROC values of 0.79 (0.70-0.86) and 0.70 (0.64-0.77). Further research should focus on validating existing models rather than developing new ones.This report is independent research arising from a Clinician Scientist award supported by the National Institute for Health Research (RG 68235) and J Usher-Smith is funded by a National Institute for Health Research Clinical LectureshipThis is the author accepted manuscript. The advanced access published version can be found on the publisher's website at: http://cebp.aacrjournals.org/content/early/2014/06/03/1055-9965.EPI-14-0295.abstrac

Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.

BACKGROUND: Most risk models for cancer are either specific to individual cancers or include complex or predominantly non-modifiable risk factors. METHODS: We developed lifestyle-based models for the five cancers for which the most cases are potentially preventable through lifestyle change in the UK (lung, colorectal, bladder, kidney, and esophageal for men and breast, lung, colorectal, endometrial, and kidney for women). We selected lifestyle risk factors from the European Code against Cancer and obtained estimates of relative risks from meta-analyses of observational studies. We used mean values for risk factors from nationally representative samples and mean 10-year estimated absolute risks from routinely available sources. We then assessed the performance of the models in 23,768 participants in the EPIC-Norfolk cohort who had no history of the five selected cancers at baseline. RESULTS: In men, the combined risk model showed good discrimination [AUC, 0.71; 95% confidence interval (CI), 0.69-0.73] and calibration. Discrimination was lower in women (AUC, 0.59; 95% CI, 0.57-0.61), but calibration was good. In both sexes, the individual models for lung cancer had the highest AUCs (0.83; 95% CI, 0.80-0.85 for men and 0.82; 95% CI, 0.76-0.87 for women). The lowest AUCs were for breast cancer in women and kidney cancer in men. CONCLUSIONS: The discrimination and calibration of the models are both reasonable, with the discrimination for individual cancers comparable or better than many other published risk models. IMPACT: These models could be used to demonstrate the potential impact of lifestyle change on risk of cancer to promote behavior change

Factors associated with the presence of diabetic ketoacidosis at diagnosis of diabetes in children and young adults: a systematic review

Objective To identify the factors associated with diabetic ketoacidosis at diagnosis of type 1 diabetes in children and young adults

Analysis of the components of cancer risk perception and links with intention and behaviour: A UK-based study.

Funder: NIHR Academic Clinical FellowshipRisk perception refers to how individuals interpret their susceptibility to threats, and has been hypothesised as an important predictor of intentions and behaviour in many theories of health behaviour change. However, its components, optimal measurement, and effects are not yet fully understood. The TRIRISK model, developed in the US, conceptualises risk perception as deliberative, affective and experiential components. In this study, we aimed to assess the replicability of the TRIRISK model in a UK sample by confirmatory factor analysis (CFA), explore the inherent factor structure of risk perception in the UK sample by exploratory factor analysis (EFA), and assess the associations of EFA-based factors with intentions to change behaviour and subsequent behaviour change. Data were derived from an online randomised controlled trial assessing cancer risk perception using the TRIRISK instrument and intention and lifestyle measures before and after communication of cancer risk. In the CFA analysis, the TRIRISK model of risk perception did not provide a good fit for the UK data. A revised model developed using EFA consisted of two separate "numerical" and "self-reflective" factors of deliberative risk perception, and a third factor combining affective with a subset of experiential items. This model provided a better fit to the data when cross-validated. Using multivariable regression analysis, we found that the self-reflective and affective-experiential factors of the model identified in this study were reliable predictors of intentions to prevent cancer. There were no associations of any of the risk perception factors with behaviour change. This study confirms that risk perception is clearly a multidimensional construct, having identified self-reflective risk perception as a new distinct component with predictive validity for intention. Furthermore, we highlight the practical implications of our findings for the design of interventions incorporating risk perception aimed at behaviour change in the context of cancer prevention.This study was funded by the Cancer Research UK Prevention Fellowship (C55650/A21464). CR was supported by an NIHR Academic Clinical Fellowship. JC, WMPK and RAF received no specific funding for this project. JAUS was funded by the Cancer Research UK Prevention Fellowship (C55650/A21464)

Impact of provision of cardiovascular disease risk estimates to healthcare professionals and patients: a systematic review.

OBJECTIVE: To systematically review whether the provision of information on cardiovascular disease (CVD) risk to healthcare professionals and patients impacts their decision-making, behaviour and ultimately patient health. DESIGN: A systematic review. DATA SOURCES: An electronic literature search of MEDLINE and PubMed from 01/01/2004 to 01/06/2013 with no language restriction and manual screening of reference lists of systematic reviews on similar topics and all included papers. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: (1) Primary research published in a peer-reviewed journal; (2) inclusion of participants with no history of CVD; (3) intervention strategy consisted of provision of a CVD risk model estimate to either professionals or patients; and (4) the only difference between the intervention group and control group (or the only intervention in the case of before-after studies) was the provision of a CVD risk model estimate. RESULTS: After duplicates were removed, the initial electronic search identified 9671 papers. We screened 196 papers at title and abstract level and included 17 studies. The heterogeneity of the studies limited the analysis, but together they showed that provision of risk information to patients improved the accuracy of risk perception without decreasing quality of life or increasing anxiety, but had little effect on lifestyle. Providing risk information to physicians increased prescribing of lipid-lowering and blood pressure medication, with greatest effects in those with CVD risk >20% (relative risk for change in prescribing 2.13 (1.02 to 4.63) and 2.38 (1.11 to 5.10) respectively). Overall, there was a trend towards reductions in cholesterol and blood pressure and a statistically significant reduction in modelled CVD risk (-0.39% (-0.71 to -0.07)) after, on average, 12 months. CONCLUSIONS: There seems evidence that providing CVD risk model estimates to professionals and patients improves perceived CVD risk and medical prescribing, with little evidence of harm on psychological well-being.BS was supported by the European Commission Framework 7, EPIC-CVD: Individualised CVD risk assessment: tailoring targeted and cost-effective approaches to Europe's diverse populations, Grant agreement no: 279233. JUS was supported by a National Institute of Health Research (NIHR) Clinical Lectureship.This is the final version of the article. It first appeared from BMJ via http://dx.doi.org/10.1136/bmjopen-2015-00871

The pathway to diagnosis of type 1 diabetes in children: a questionnaire study.

OBJECTIVE: To explore the pathway to diagnosis of type 1 diabetes (T1D) in children. DESIGN: Questionnaire completed by parents. PARTICIPANTS: Parents of children aged 1 month to 16 years diagnosed with T1D within the previous 3 months. SETTING: Children and parents from 11 hospitals within the East of England. RESULTS: 88/164 (54%) invited families returned the questionnaire. Children had mean±SD age of 9.41±4.5 years. 35 (39.8%) presented with diabetic ketoacidosis at diagnosis. The most common symptoms were polydipsia (97.7%), polyuria (83.9%), tiredness (75.9%), nocturia (73.6%) and weight loss (64.4%) and all children presented with at least one of those symptoms. The time from symptom onset to diagnosis ranged from 2 to 315 days (median 25 days). Most of this was the appraisal interval from symptom onset until perceiving the need to seek medical advice. Access to healthcare was good but one in five children presenting to primary care were not diagnosed at first encounter, most commonly due to waiting for fasting blood tests or alternative diagnoses. Children diagnosed at first consultation had a shorter duration of symptoms (p=0.022) and children whose parents suspected the diagnosis were 1.3 times more likely (relative risk (RR) 1.3, 95% CI 1.02 to 1.67) to be diagnosed at first consultation. CONCLUSIONS: Children present with the known symptoms of T1D but there is considerable scope to improve the diagnostic pathway. Future interventions targeted at parents need to address the tendency of parents to find alternative explanations for symptoms and the perceived barriers to access, in addition to symptom awareness.The study was funded by the Royal College of General Practitioners Scientific Foundation Board (SFB-2011-15). JUS was supported by a National Institute of Health Research (NIHR) Academic Clinical Fellowship and subsequently Clinical Lectureship, and FMW by an NIHR Clinician Scientist award. SJS was supported by the Medical Research Council www.mrc.ac.uk [Unit Programme number MC_UU_12015/1]. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.This is the final version of the article. It was first published by BMJ Group at http://bmjopen.bmj.com/content/5/3/e006470.ful

Risk prediction models for colorectal cancer in people with symptoms: a systematic review

Abstract Background Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals. Methods We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers. Results Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen. Conclusions Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice