Estimating the potential population impact of stepwise screening strategies for identifying and treating individuals at high risk of Type 2 diabetes: a modelling study

Performance and costs of multiple screening strategies for type 2 diabetes: two population-based studies in Shanghai, China

INTRODUCTION

To compare the performance and the costs of various assumed screening strategies for type 2 diabetes mellitus (T2DM) among Chinese adults, and identify an optimal one for the population.

RESEARCH DESIGN AND METHODS

Two multistage-sampling surveys were conducted in Shanghai, China, in 2009 and 2017. All participants were interviewed, had anthropometry, measured fasting plasma glucose (FPG), hemoglobin A1c (A1c) and/or postprandial glucose. The 1999 WHO diagnostic criteria was used to identify undiagnosed T2DM. A previously developed Chinese risk assessment system and a specific risk assessment system developed in this study were applied to calculate diabetes risk score (DRS) 1 and 2. Optimal screening strategies were selected based on the sensitivity, Youden index and the costs using the 2009 survey data as the training set and the 2017 survey data as the validation set. A twofold cross-validation was also performed.

RESULTS

Of numerous assumed strategies, FPG ≥5.6 mmol/L alone performed well (Youden index of 71.8%) and cost least (US$18.4 for each case detected), followed by the strategy of DRS2 ≥8 combining with FPG ≥5.6 mmol/L (Youden index of 71.7% and US$20.2 per case detected) and the strategy of DRS1 ≥17 combining with FPG ≥5.6 mmol/L (Youden index of 72.0% and US$21.6 per case detected). However, FPG alone resulted in more subjects requiring oral glucose tolerance test (OGTT) than did combining with DRS. The strategy of FPG ≥5.6 mmol/L combining with A1c ≥4.7% achieved a Youden index of 72.1%, but had a cost as high as US$48.8 for each case identified. Twofold cross-validation also supported the use of FPG alone, but with an optimal cut-off of 6.1 mmol/L.

CONCLUSIONS

Our results support the use of FPG alone in T2DM screening in Chinese adults. DRS may be used combining with FPG in populations with available electronic health records to reduce the number of OGTT and save costs of screening.

Validation of Seven Type 2 Diabetes Mellitus Risk Scores in a Population-Based Cohort: The CoLaus Study

AIM

To assess the validity of seven type 2 diabetes mellitus (T2DM) risk scores in predicting the 10-year incidence of T2DM in a Swiss population-based study.

METHODS

The prospective study included 5131 participants (55% women, age range 35 to 75 years) living in Lausanne, Switzerland. The baseline survey was conducted between 2003 and 2006, and the average follow-up was 10.9 years. Five clinically-based scores (the Balkau, Kahn clinical, Griffin, Swiss Diabetes Association [SDAS], and Finnish Diabetes Risk Score [FINDRISC]) and two clinically and biologically based scores (the Kahn CB and Wilson) were tested.

RESULTS

405 (7.9%) participants developed T2DM. The overall prevalence of participants at high risk ranged from 13.7% for the Griffin score to 43.3% for the Balkau score. The prevalence of participants at high risk among those who developed T2DM ranged from 34.6% for the Griffin score to 82.0% for the Kahn CB score. The Kahn CB score had the highest area under the ROC (value and 95% confidence interval: 0.866 [0.849-0.883]), followed by the FINDRISC (0.818 [0.798-0.838]), while the Griffin score had the lowest (0.740 [0.718-0.762]). Sensitivities and specificities were above 70%, except for the Griffin and the Kahn C scores (for sensitivity) and the Balkau score (for specificity). The numbers needed to screen ranged from 15.5 for the Kahn CB score to 36.7 for the Griffin score.

CONCLUSION

The Kahn CB and the FINDRISC scores performed the best out of all the scores. The FINDRISC score could be used in an epidemiological setting, while the need for blood sampling for the Kahn CB score restricts its use to a more clinical setting.

Current stepwise recommendations for hypogonadism screening in erectile dysfunction are not cost-effective

Hypogonadism is a prevalent comorbidity with erectile disfunction (ED) and current guidelines recommend screening for hypogonadism with total testosterone (TT). If low TT is detected, further assessment with LH and SHBG plus albumin are needed to establish an etiology and treatment. Our primary objective was to determine the cost benefit of current stepwise approach versus ad initium full hormonal assessment. Two hundred consecutive male patients referred for ED were screened after consent and 81 were included and assessed for hypogonadism according to the current stepwise approach with TT, and only if TT was less than 345 ng/mL, a full hormonal assessment with TT, LH, and SHBG plus albumin to calculate free testosterone was performed. Direct costs were calculated using the national public healthcare system reimbursement tables and were compared with a hypothetical initial full hormonal assessment. Screening TT was less than 345 ng/mL in 34.6% patients leading to a full hormonal assessment on these. Using a stepwise approach there was a direct cost increase of 5.82 € per patient. Moreover, one out of every three patients had two extra venipunctures and an additional follow-up appointment. Current stepwise recommendations may prove costly in high prevalence scenarios such as the ED subpopulation as a direct cost increase was observed.

Cost-Effectiveness of Cardiovascular Screening in Patients With Rheumatoid Arthritis

OBJECTIVE

Early detection and preemptive treatment of patients at risk is of great importance in reducing the excess risk of cardiovascular (CV) disease in rheumatoid arthritis (RA). However, it is unclear how much screening is cost-effective in RA. The objective is to assess whether CV screening in RA proves to be cost-effective from a medical perspective, using different scenarios based on different guidelines.

METHODS

A Markov chain model was used with a time horizon of 10 years. Parameter values were mainly obtained from literature and from RA patients screened for CV diseases at the Radboud University Medical Centre, Nijmegen, The Netherlands. The primary outcome was incremental cost-effectiveness expressed as costs per quality-adjusted life year (QALY) gained. Probabilistic sensitivity analysis was performed and described in willingness-to-pay curves; several scenarios were built.

RESULTS

In the base case scenario, in 82% of the simulations, screening proved to be dominant compared to no screening. The mean QALY gain was 0.09 (95% percentile -0.07, 0.27), and the mean cost savings were €-1,057 (95% percentile -€2,825, €333). Different scenarios showed small differences in cost-effectiveness; the probability that screening is dominant remained high with the lowest probability being 50% for a very conservative scenario.

CONCLUSION

Screening for CV events in RA patients was estimated to be cost-effective with high chances of being less expensive and more effective. These results support endorsement of screening for CV risk in patients with RA.

Modeling the costs and long-term health benefits of screening the general population for risks of cardiovascular disease: a review of methods used in the literature

BACKGROUND

Strategies for screening and intervening to reduce the risk of cardiovascular disease (CVD) in primary care settings need to be assessed in terms of both their costs and long-term health effects. We undertook a literature review to investigate the methodologies used.

METHODS

In a framework of developing a new health-economic model for evaluating different screening strategies for primary prevention of CVD in Europe (EPIC-CVD project), we identified seven key modeling issues and reviewed papers published between 2000 and 2013 to assess how they were addressed.

RESULTS

We found 13 relevant health-economic modeling studies of screening to prevent CVD in primary care. The models varied in their degree of complexity, with between two and 33 health states. Programmes that screen the whole population by a fixed cut-off (e.g., predicted 10-year CVD risk >20 %) identify predominantly elderly people, who may not be those most likely to benefit from long-term treatment. Uncertainty and model validation were generally poorly addressed. Few studies considered the disutility of taking drugs in otherwise healthy individuals or the budget impact of the programme.

CONCLUSIONS

Model validation, incorporation of parameter uncertainty, and sensitivity analyses for assumptions made are all important components of model building and reporting, and deserve more attention. Complex models may not necessarily give more accurate predictions. Availability of a large enough source dataset to reliably estimate all relevant input parameters is crucial for achieving credible results. Decision criteria should consider budget impact and the medicalization of the population as well as cost-effectiveness thresholds.

Which Measures of Health Status Assessment are the Most Significant in Organized Cohorts with Low Current Cardiovascular Risk? The Screening Study of Penitentiary Staff in Saratov Region, Russia

OBJECTIVE

The aim of the present study was to compare different methods of health status assessment in organized cohort of penitentiary employees in Saratov Region, Russian Federation.

MATERIALS AND METHODS

1,014 penitentiary employees (81.8% male) aged 33.4±6.8 years were included in the cohort study. All participants underwent an annual preventive health examination in the Center of Medical and Social Rehabilitation of Russian Federal Penitentiary Service in Saratov Region. The prevalence of common cardiovascular risk factors was assessed. Risk Score and the number of fulfilled health metrics proposed by American Heart Association (AHA) were calculated for each participant.

RESULTS

It is shown that penitentiary staff in Saratov Region is characterized by low current risk score (1.2±0.8%), but high prevalence of such risk factors as increased body weight and obesity (51%), tobacco use or passive smoking (81%), and unhealthy diet (55%). 98.4% of participants had the Score level of ≤5%, but only 4.5% of penitentiary staff met the ideal cardiovascular health (they met all seven AHA health metrics). One fifth of the participants met three or less AHA health metrics. A statistically significant correlation between the risk Score and the number of fulfilled AHA health metrics is revealed (Chi-square = 5.1, p=0.024). The probability of fulfilment of less than 5 AHA health metrics in subjects with medium risk score is shown to be almost twofold greater than in subjects with low risk Score. However, there are a lot of differences in the assessment of cardiovascular health by risk Score and AHA health metrics.

CONCLUSION

AHA health metrics are more preferable than the risk Score or assessment of separate cardiovascular risk factors for preventive management in organized cohorts with low current cardiovascular risk such as penitentiary staff in Saratov Region.

Screening for Type 2 Diabetes and Dysglycemia in Saudi Arabia: Development and Validation of Risk Scores

OBJECTIVE

The prevalence of type 2 diabetes in Saudi Arabia is the highest worldwide after excluding small island nations. We developed and validated a noninvasive screening test based on demographic and clinical data for identifying adults with undiagnosed diabetes and dysglycemia in Saudi Arabia.

RESEARCH DESIGN AND METHODS

Data from 1,485 nonpregnant Saudi adults ≥20 years of age without a current diagnosis of diabetes were obtained from urban and rural primary healthcare centers in 2009. Clinical and demographic data were obtained through physician-administered interviews. Oral glucose tolerance test data were used to define diabetes (fasting plasma glucose ≥7.0 mmol/L or 2-h post-load glucose ≥11.1 mmol/L) and dysglycemia (fasting plasma glucose ≥5.6 mmol/L or 2-h post-load glucose ≥7.8 mmol/L). Predictive models were developed using data from 1,435 individuals. Multivariable logistic regression and receiver operating characteristic curves were used to develop and evaluate a separate risk score for both diabetes and dysglycemia. Scores were validated on a hold-out sample of 50 individuals.

RESULTS

The risk score for undiagnosed diabetes contained age, history of gestational diabetes, smoking, family history of diabetes, and central obesity with a sensitivity of 76.6% and a specificity of 52.1%. The dysglycemia risk score contained age, gestational diabetes, hypertension, and central obesity with a sensitivity of 71.2% and a specificity of 54.0%. All performed equally well, if not better, in the hold-out sample.

CONCLUSIONS

These risk scores can identify Saudi adults with undiagnosed diabetes or dysglycemia and should be validated in prospective studies.

Mixed Influence of Electronic Health Record Implementation on Diabetes Order Patterns for Michigan Medicaid Adults

BACKGROUND

These 2011-2013 analyses examined the authors' hypothesis that relative diabetes care order changes would be measured after electronic health record (EHR) implementation for 291 Medicaid adults who received all of their office-based care at one midwestern federally qualified health center (FQHC) over a 24-month period (n = 2727 encounters, 2489 claims).

METHOD

Beneficiary sociodemographic, clinical, and claims data were validated with clinic EHR and state Medicaid claims linked to providers' national identifier numbers. Overall pre-post order rate comparisons, and a series of controlled within group binary logistic models were conducted under penalized maximum likelihood estimation terms.

RESULTS

After EHR implementation, both the overall order rates and odds ratios of per beneficiary hemoglobin A1C (HbA1C) orders increased significantly (ie, from mean of 0.65 [SD = 1.19] annual tests to 0.96 tests [SD = 1.24] [P < .001]). Although the overall post-EHR order rates of dilated eye exams and microalbumin urine tests appeared fairly stable, the odds of eye exam orders being placed at the claims level decreased significantly (OR = 0.774, P = .0030).

CONCLUSIONS

These mixed results provide evidence of the varied diabetes care ordering patterns likely seen from increased office use of EHR technologies. The authors attempt to explain these post-EHR differences (or lack of) that generally resemble some of the authors' results from another funded project. Ideally, these findings provide Medicaid and health care officials with a more realistic indication of how EHRs may, or may not, influence diabetes care ordering patterns for vulnerable lower-income primary health care consumers.

A novel model enhances HbA1c-based diabetes screening using simple anthropometric, anamnestic, and demographic information

BACKGROUND

The sensitivity of HbA1c is not optimal for the screening of patients with latent diabetes. We hypothesize that simple healthcare information could improve accuracy.

METHODS

We retrospectively analyzed data, including HbA1c, from multiple years from the National Health and Nutrition Examination Survey (NHANES) database (2005-2010). The data were used to create a logistic regression classification model for screening purposes.

RESULTS

The study evaluated data for 5381 participants, including 404 with undiagnosed diabetes. The HbA1c screening data were supplemented with information about age, waist circumference, and physical activity in the HbA1c+ model. Alone, HbA1c alone had a receiver operating characteristics (ROC) curve for the area under the curve (AUC) of 0.808 (95% confidence interval [CI] 0.792-0.834). The HbA1c+ model had an ROC AUC of 0.851 (95% CI 0.843-0.872). There was a significant difference in the AUC between our model and using HbA1c without supplementary information (P < 0.05).

CONCLUSIONS

We have developed a novel screening model that could help improve screening for type 2 diabetes with HbA1c. It seems beneficial to systematically add additional patient healthcare information in the process of screening with HbA1c.

Risk distribution and its influence on the population targets for diabetes prevention

OBJECTIVE

To quantify the influence of type 2 diabetes risk distribution on prevention benefit and apply a method to optimally identify population targets.

METHODS

We used data from the 2011 Canadian Community Health Survey (N=45,040) and the validated Diabetes Population Risk Tool to calculate 10-year diabetes risk. We calculated the Gini coefficient as a measure of risk dispersion. Intervention benefit was estimated using absolute risk reduction (ARR), number-needed-to-treat (NNT), and number of cases prevented.

RESULTS

There is a wide variation of diabetes risk in Canada (Gini=0.48) and with an inverse relation to risk (r=-0.99). Risk dispersion is lower among individuals meeting an empirically derived risk cut-off (Gini=0.18). Targeting prevention based on a risk cut-off (10-year risk ≥ 16.5%) resulted in a greater number of cases prevented (340 thousand), higher ARR (7.7%) and lower NNT (13) compared to targeting individuals based on risk factor targets.

CONCLUSIONS

This study provides empirical evidence to demonstrate that risk variability is an important consideration for estimating the prevention benefit. Prioritizing target populations using an empirically derived cut-off based on a multivariate risk score will result in greater benefit and efficiency compared to risk factor targets.

The development and validation of the Portuguese risk score for detecting type 2 diabetes and impaired fasting glucose

AIMS

To develop and validate a non-invasive score for detecting undiagnosed impaired fasting glucose (IFG) and type 2 diabetes (T2DM) in a Portuguese population.

METHODS

We used data from 3,374 individuals aged 18-94 years from a Portuguese cross-sectional study. We developed a logistic regression model for predicting IFG/T2DM (diagnosed using fasting glucose). We externally validated the score using data from two cohorts of the EPI-Porto study, cross-sectional (n = 2,131) and data from the 5 year follow-up (n = 1,304).

RESULTS

The final model included age, sex, BMI and hypertension with an area under the ROC curve of 70.1 (95%CI 68.4, 71.7). Using a cut-point which classifies 50% of the EPI-Porto cross-sectional data as high-risk gave sensitivity 73.2% (95%CI 68.5%, 77.6%), specificity 55.5% (53.1%, 57.8%), positive predictive value (PPV) 27.0% (24.3%, 29.8%) and negative predictive value (NPV) 90.2% (88.3%, 92.0%) for IFG/T2DM. Using the same cut-point on the prospective data classified 45% as high-risk; sensitivity 69.1% (63.4%, 74.4%), specificity 63.3% (60.0%, 66.5%), PPV 38.0% (33.9%, 42.4%), and NPV 86.2% (83.3%, 88.8%).

CONCLUSION

The Portuguese risk score can be used to identify those at high risk of both prevalent undiagnosed and incident IFG/T2DM.

Shifting from glucose diagnosis to the new HbA1c diagnosis reduces the capability of the Finnish Diabetes Risk Score (FINDRISC) to screen for glucose abnormalities within a real-life primary healthcare preventive strategy

BACKGROUND

To investigate differences in the performance of the Finnish Diabetes Risk Score (FINDRISC) as a screening tool for glucose abnormalities after shifting from glucose-based diagnostic criteria to the proposed new hemoglobin (Hb)A1c-based criteria.

METHODS

A cross-sectional primary-care study was conducted as the first part of an active real-life lifestyle intervention to prevent type 2 diabetes within a high-risk Spanish Mediterranean population. Individuals without diabetes aged 45-75 years (n = 3,120) were screened using the FINDRISC. Where feasible, a subsequent 2-hour oral glucose tolerance test and HbA1c test were also carried out (n = 1,712). The performance of the risk score was calculated by applying the area under the curve (AUC) for the receiver operating characteristic, using three sets of criteria (2-hour glucose, fasting glucose, HbA1c) and three diagnostic categories (normal, pre-diabetes, diabetes).

RESULTS

Defining diabetes by a single HbA1c measurement resulted in a significantly lower diabetes prevalence (3.6%) compared with diabetes defined by 2-hour plasma glucose (9.2%), but was not significantly lower than that obtained using fasting plasma glucose (3.1%). The FINDRISC at a cut-off of 14 had a reasonably high ability to predict diabetes using the diagnostic criteria of 2-hour or fasting glucose (AUC = 0.71) or all glucose abnormalities (AUC = 0.67 and 0.69, respectively). When HbA1c was used as the primary diagnostic criterion, the AUC for diabetes detection dropped to 0.67 (5.6% reduction in comparison with either 2-hour or fasting glucose) and fell to 0.55 for detection of all glucose abnormalities (17.9% and 20.3% reduction, respectively), with a relevant decrease in sensitivity of the risk score.

CONCLUSIONS

A shift from glucose-based diagnosis to HbA1c-based diagnosis substantially reduces the ability of the FINDRISC to screen for glucose abnormalities when applied in this real-life primary-care preventive strategy.

Screening for type 2 diabetes in a high-risk population: study design and feasibility of a population-based randomized controlled trial

BACKGROUND

We describe the design and present the results of the first year of a population-based study of screening for type 2 diabetes in individuals at high risk of developing the disease. High risk is defined as having abdominal obesity.

METHODS

Between 2006 and 2007, 79,142 inhabitants of two Dutch municipalities aged 40-74 years were approached to participate in screening. Eligible participants had a self-reported waist circumference of ≥ 80 cm for women and ≥ 94 cm for men, and no known pre-existing diabetes. Of the respondents (n = 20,578; response rate 26%), 16,135 were abdominally obese. In total, 10,609 individuals gave written informed consent for participation and were randomized into either the screening (n = 5305) or the control arm (n = 5304). Participants in the screening arm were invited to have their fasting plasma glucose (FPG) measured and were referred to their general practitioner (GP) if it was ≥ 6.1 mmol/L. In addition, blood lipids were determined in the screening arm, because abdominal obesity is often associated with cardiovascular risk factors. Participants in both arms received written healthy lifestyle information. Between-group differences were analyzed with Chi-square tests and logistic regression (categorical variables) and unpaired t-tests (continuous variables).

RESULTS

The screening attendance rate was 84.1%. Attending screening was associated with age at randomization (OR = 1.03, 95% CI 1.02-1.04), being married (OR = 1.57, 95% CI 1.33-1.83) and not-smoking currently (OR = 0.52, 95% CI 0.44-0.62). Of the individuals screened, 5.6% had hyperglycemia, and a further 11.6% had an estimated absolute cardiovascular disease risk of 5% or higher, according to the Systematic Coronary Risk Evaluation risk model. These participants were referred to their GP.

CONCLUSIONS

Self-reported home-assessed waist circumference could feasibly detect persons at high risk of hyperglycemia or cardiovascular disease. Continuation of the large-scale RCT is warranted to test the hypothesis that targeted population-based screening for type 2 diabetes leads to a significant reduction in cardiovascular morbidity and mortality.

TRIAL REGISTRATION

ISRCTN75983009.