External Validation of a Tool Predicting 7-Year Risk of Developing Cardiovascular Disease, Type 2 Diabetes or Chronic Kidney Disease

Understanding the risk of developing weight-related complications associated with different body mass index categories: a systematic review

BACKGROUND

Obesity and overweight are major risk factors for several chronic diseases. There is limited systematic evaluation of risk equations that predict the likelihood of developing an obesity or overweight associated complication. Predicting future risk is essential for health economic modelling. Availability of future treatments rests upon a model's ability to inform clinical and decision-making bodies.  This systematic literature review aimed to identify studies reporting (1) equations that calculate the risk for individuals with obesity, or overweight with a weight-related complication (OWRC), of developing additional complications, namely T2D, cardiovascular (CV) disease (CVD), acute coronary syndrome, stroke, musculoskeletal disorders, knee replacement/arthroplasty, or obstructive sleep apnea; (2) absolute or proportional risk for individuals with severe obesity, obesity or OWRC developing T2D, a CV event or mortality from knee surgery, stroke, or an acute CV event.

METHODS

Databases (MEDLINE and Embase) were searched for English language reports of population-based cohort analyses or large-scale studies in Australia, Canada, Europe, the UK, and the USA between January 1, 2011, and March 29, 2021. Included reports were quality assessed using an adapted version of the Newcastle Ottawa Scale.

RESULTS

Of the 60 included studies, the majority used European cohorts. Twenty-nine reported a risk prediction equation for developing an additional complication. The most common risk prediction equations were logistic regression models that did not differentiate between body mass index (BMI) groups (particularly above 40 kg/m²) and lacked external validation. The remaining included studies (31 studies) reported the absolute or proportional risk of mortality (29 studies), or the risk of developing T2D in a population with obesity and with prediabetes or normal glucose tolerance (NGT) (three studies), or a CV event in populations with severe obesity with NGT or T2D (three studies). Most reported proportional risk, predominantly a hazard ratio.

CONCLUSION

More work is needed to develop and validate these risk equations, specifically in non-European cohorts and that distinguish between BMI class II and III obesity. New data or adjustment of the current risk equations by calibration would allow for more accurate decision making at an individual and population level.

A systematic review of diabetes risk assessment tools in sub-Saharan Africa

Objectives

To systematically review all current studies on diabetes risk assessment tools used in SSA to diagnose diabetes in symptomatic and asymptomatic patients.

Methods

Tools were identified through a systematic search of PubMed, Ovid, Google Scholar, and the Cochrane Library for articles published from January 2010 to January 2020. The search included articles reporting the use of diabetes risk assessment tool to detect individuals with type 2 diabetes in SSA. A standardized protocol was used for data extraction (registry #177726).

Results

Of the 825 articles identified, 39 articles met the inclusion criteria, and three articles reported tools used in SSA population but developed for the Western population. None was validated in SSA population. All but three articles were observational studies (136 and 58,657 study participants aged between the ages of 15 and 85 years). The Finnish Medical Association risk tool, World Health Organization (WHO) STEPS instrument, General Practice Physical Activity Questionnaire (GPPAQ), Rapid Eating and Activity Assessment for Patients (REAP), and an anthropometric tool were the most frequently used non-invasive tools in SSA. The accuracy of the tools was measured using sensitivity, specificity, or area under the receiver operating curve. The anthropometric predictor variables identified included age, body mass index, waist circumference, positive family of diabetes, and activity levels.

Conclusions

This systematic review demonstrated a paucity of validated diabetes risk assessment tools for SSA. There remains a need for the development and validation of a tool for the rapid identification of diabetes for targeted interventions.

A newly developed and externally validated non-clinical score accurately predicts 10-year cardiovascular disease risk in the general adult population

Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C-indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C-indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.

Cost-effectiveness of a stepwise cardiometabolic disease prevention program: results of a randomized controlled trial in primary care

BACKGROUND

Cardiometabolic diseases (CMD) are the major cause of death worldwide and are associated with a lower quality of life and high healthcare costs. To prevent a further rise in CMD and related healthcare costs, early detection and adequate management of individuals at risk could be an effective preventive strategy. The objective of this study was to determine long-term cost-effectiveness of stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. A computer-based simulation model was used to project long-term health benefits and cost-effectiveness, assuming the prevention program was implemented in Dutch primary care.

METHODS

A randomized controlled trial in a primary care setting in which 1934 participants aged 45-70 years without recorded CMD or CMD risk factors participated. The intervention group was invited for stepwise CMD risk assessment through a risk score (step 1), additional risk assessment at the practice in case of increased risk (step 2) and individualized follow-up treatment if indicated (step 3). The control group was not invited for risk assessment, but completed a health questionnaire. Results of the effectiveness analysis on systolic blood pressure (- 2.26 mmHg; 95% CI - 4.01: - 0.51) and total cholesterol (- 0.15 mmol/l; 95% CI - 0.23: - 0.07) were used in this analysis. Outcome measures were the costs and benefits after 1-year follow-up and long-term (60 years) cost-effectiveness of stepwise CMD risk assessment compared to no assessment. A computer-based simulation model was used that included data on disability weights associated with age and disease outcomes related to CMD. Analyses were performed taking a healthcare perspective.

RESULTS

After 1 year, the average costs in the intervention group were 260 Euro higher than in the control group and differences were mainly driven by healthcare costs. No meaningful change was found in EQ 5D-based quality of life between the intervention and control groups after 1-year follow-up (- 0.0154; 95% CI - 0.029: 0.004). After 60 years, cumulative costs of the intervention were 41.4 million Euro and 135 quality-adjusted life years (QALY) were gained. Despite improvements in blood pressure and cholesterol, the intervention was not cost-effective (ICER of 306,000 Euro/QALY after 60 years). Scenario analyses did not allow for a change in conclusions with regard to cost-effectiveness of the intervention.

CONCLUSIONS

Implementation of this primary care-based CMD prevention program is not cost-effective in the long term. Implementation of this program in primary care cannot be recommended.

TRIAL REGISTRATION

Dutch Trial Register NTR4277 , registered on 26 November 2013.

The association between GP organisational factors and the effectiveness of a prevention programme for cardiometabolic diseases: a prospective intervention study

Background

Owing to the rising disease burden of cardiometabolic diseases (CMD), prevention programmes for CMD are increasingly implemented in primary care. Organisational practice characteristics and availability of preventive services may be associated with a more effective programme.

Aim

To identify possible organisational success factors from general practices related to an effective primary prevention programme for CMD.

Design & setting

A prospective intervention study involving 37 Dutch general practices was undertaken.

Method

Patients aged 45–70 years without known CMD, hypertension, or hypercholesterolemia were invited for the prevention programme. The outcome measures were an improvement (yes/no) in four different CMD risk factors between baseline and 1-year follow-up on an individual level (body mass index [BMI], smoking, systolic blood pressure, and cholesterol ratio). Multivariate logistic regression analysis was used for assessing associations between practice organisational characteristics and outcomes.

Results

Just over half of the participants showed an improvement on one or more risk factors. Marginal differences were found in the four different outcomes between the practices with different organisational characteristics. None of the practice characteristics that were tested showed a significant association with an improvement in one of the outcome measures.

Conclusion

In this study, general practice organisational and preventive service characteristics showed no impact on the effectiveness of a CMD prevention programme. Possible explanations could be the effectiveness of protocolised pharmaceutical treatment and only limited contribution of lifestyle programmes on the improvement of CMD risk factors.

External validation of the European risk assessment tool for chronic cardio-metabolic disorders in a Middle Eastern population

BACKGROUND

High burden of chronic cardio-metabolic disorders including type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD) have been reported in the Middle East and North Africa region. We aimed to externally validate a non-laboratory risk assessment tool for the prediction of the chronic cardio-metabolic disorders in the Iranian population.

METHODS

The predictors included age, body mass index, waist circumference, use of antihypertensive medications, current smoking, and family history of cardiovascular disease and/or diabetes. For external validation of the model in the Tehran lipids and glucose study (TLGS), the Area under the curve (AUC) and the Hosmer-Lemeshow (HL) goodness of fit test were performed for discrimination and calibration, respectively.

RESULTS

Among 1310 men and 1960 women aged 28-85 years, 29.5% and 47.4% experienced chronic cardio-metabolic disorders during the 6 and 9-year follow-up, respectively. The model showed acceptable discrimination, with an AUC of 0.72 (95% CI 0.69-0.75) for men and 0.73 (95% CI 0.71-0.76) for women. The calibration of the model was good for both genders (min HL P = 0.5). Considering separate outcomes, AUC was highest for CKD (0.76 (95% CI 0.72-0.79)) and lowest for T2DM (0.65 (95% CI 0.61-0.69)), in men. As for women, AUC was highest for CVD (0.82 (95% CI 0.78-0.86)) and lowest for T2DM (0.69 (95% CI 0.66-0.73)). The 9-year follow-up demonstrated almost similar performances compared to the 6-year follow-up. Using Cox regression in place of logistic multivariable analysis, model's discrimination and calibration were reduced for prediction of chronic cardio-metabolic disorders; the issue which had more effect on the prediction of incident CKD among women. Moreover, adding data of educational levels and marital status did not improve, the discrimination and calibration in the enhanced model.

CONCLUSION

This model showed acceptable discrimination and good calibration for risk prediction of chronic cardio-metabolic disorders in short and long-term follow-up in the Iranian population.

Uptake and detection rate of a stepwise cardiometabolic disease detection program in primary care-a cohort study

Background

Early detection and treatment of cardiometabolic diseases (CMD) in high-risk patients is a promising preventive strategy to anticipate the increasing burden of CMD. The Dutch guideline ‘the prevention consultation’ provides a framework for stepwise CMD risk assessment and detection in primary care. The aim of this study was to assess the outcome of this program in terms of newly diagnosed CMD.

Methods

A cohort study among 30 934 patients, aged 45–70 years without known CMD or CMD risk factors, who were invited for the CMD detection program within 37 general practices. Patients filled out a CMD risk score (step 1), were referred for additional risk profiling in case of high risk (step 2) and received lifestyle advice and (pharmacological) treatment if indicated (step 3). During 1-year follow-up newly diagnosed CMD, prescriptions and abnormal diagnostic tests were assessed.

Results

Twelve thousand seven hundred and thirty-eight patients filled out the risk score of which 865, 6665 and 5208 had a low, intermediate and high CMD risk, respectively. One thousand seven hundred and fifty-five high-risk patients consulted the general practitioner, in 346 of whom a new CMD was diagnosed. In an additional 422 patients a new prescription and/or abnormal diagnostic test were found.

Conclusions

Implementation of the CMD detection program resulted in a new CMD diagnosis in one-fifth of high-risk patients who attended the practice for completion of their risk profile. However, the potential yield of the program could be higher given the considerable number of additional risk factors—such as elevated glucose, blood pressure and cholesterol levels—found, requiring active follow-up and presumably treatment in the future.

Mismatch between self-perceived and calculated cardiometabolic disease risk among participants in a prevention program for cardiometabolic disease: a cross-sectional study

Background

The rising prevalence of cardiometabolic diseases (CMD) calls for effective prevention programs. Self-assessment of CMD risk, for example through an online risk score (ORS), might induce risk reducing behavior. However, the concept of disease risk is often difficult for people to understand. Therefore, the study objective was to assess the impact of communicating an individualized CMD risk score through an ORS on perceived risk and to identify risk factors and demographic characteristics associated with risk perception among high-risk participants of a prevention program for CMD.

Methods

A cross-sectional analysis of baseline data from a randomized controlled trial conducted in a primary care setting. Seven thousand five hundred forty-seven individuals aged 45–70 years without recorded CMD, hypertension or hypercholesterolemia participated. The main outcome measures were: 1) differences in cognitive and affective risk perception between the intervention group - who used an ORS and received an individualized CMD risk score- and the control group who answered questions about CMD risk, but did not receive an individualized CMD risk score; 2) risk factors and demographic characteristics associated with risk perception.

Results

No differences were found in cognitive and affective risk perception between the intervention and control group and risk perception was on average low, even among high-risk participants. A positive family history for diabetes type 2 (β0.56, CI95% 0.39–0.73) and cardiovascular disease (β0.28, CI95% 0.13–0.43), BMI ≥25 (β0.27, CI95% 0.12–0.43), high waist circumference (β0.25, CI95% 0.02–0.48) and physical inactivity (β0.30, CI95% 0.16–0.45) were positively associated with cognitive CMD risk perception in high-risk participants. No other risk factors or demographic characteristics were associated with risk perception.

Conclusions

Communicating an individualized CMD risk score did not affect risk perception. A mismatch was found between calculated risk and self-perceived risk in high-risk participants. Family history and BMI seem to affect the level of CMD risk perception more than risk factors such as sex, age and smoking. A dialogue about personal CMD risk between patients and health care professionals might optimize the effect of the provided risk information.

Trial registration

Dutch trial Register number NTR4277, registered 26th Nov 2013.

Effectiveness of a stepwise cardiometabolic disease prevention program: Results of a randomized controlled trial in primary care

Effective preventive strategies for cardiometabolic disease (CMD) are needed. We aim to establish the effectiveness of a stepwise CMD risk assessment followed by individualized treatment if indicated compared to care as usual. We conducted a RCT between 2014 and 2017. Individuals (45-70 years) without CMD or CMD risk factors were invited for stepwise CMD risk assessment through a risk score (step1), additional risk assessment at the practice in case of high-risk (step2) and individualized follow-up treatment if indicated (step3). We compared newly detected CMD and newly prescribed drugs during one-year follow-up, and change in CMD risk profile between baseline and one-year follow-up among participants who completed step2 to matched controls. A CMD was diagnosed almost three times more often (OR 2.90, 95% CI 2.25: 3.72) in the intervention compared to the control group, in parallel with newly prescribed antihypertensive and lipid lowering drugs (OR 2.85, 95% CI 1.96: 4.15 and 3.23, 95% CI 2.03: 5.14 respectively). Waist circumference significantly decreased between the intervention compared to the control group (mean -3.08 cm, 95% CI -3.73: -2.43). No differences were observed for changes in BMI and smoking. Systolic blood pressure (mean -2.26 mmHg, 95% CI -4.01: -0.51) and cholesterol ratio (mean -0.11, 95% CI -0.19: -0.02) significantly decreased within intervention participants between baseline and one-year follow-up. In conclusion, implementation of the CMD prevention program resulted in the detection of two- to threefold more patients with CMD. A significant drop in systolic blood pressure and cholesterol levels was found after one year of treatment. Modelling of these results should confirm the effect on long term endpoints. Trial registration: Dutch trial Register number NTR4277.