How can we identify candidates at highest risk – to screen or not to screen?

Diagnostic accuracy of tests for type 2 diabetes and prediabetes: A systematic review and meta-analysis

AIM

This systematic review aimed to ascertain the diagnostic accuracy (sensitivity and specificity) of screening tests for early detection of type 2 diabetes and prediabetes in previously undiagnosed adults.

METHODS

This systematic review included published studies that included one or more index tests (random and fasting tests, HbA1c) for glucose detection, with 75-gram Oral Glucose Tolerance Test (or 2-hour post load glucose) as a reference standard (PROSPERO ID CRD42018102477). Seven databases were searched electronically (from their inception up to March 9, 2020) accompanied with bibliographic and website searches. Records were manually screened and full text were selected based on inclusion and exclusion criteria. Subsequently, data extraction was done using standardized form and quality assessment of studies using QUADAS-2 tool. Meta-analysis was done using bivariate model using Stata 14.0. Optimal cut offs in terms of sensitivity and specificity for the tests were analysed using R software.

RESULTS

Of 7,151 records assessed by title and abstract, a total of 37 peer reviewed articles were included in this systematic review. The pooled sensitivity, specificity, positive (LR+) and negative likelihood ratio (LR-) for diagnosing diabetes with HbA1c (6.5%; venous sample; n = 17 studies) were 50% (95% CI: 42-59%), 97.3% (95% CI: 95.3-98.4), 18.32 (95% CI: 11.06-30.53) and 0.51 (95% CI: 0.43-0.60), respectively. However, the optimal cut-off for diagnosing diabetes in previously undiagnosed adults with HbA1c was estimated as 6.03% with pooled sensitivity of 73.9% (95% CI: 68-79.1%) and specificity of 87.2% (95% CI: 82-91%). The optimal cut-off for Fasting Plasma Glucose (FPG) was estimated as 104 milligram/dL (mg/dL) with a sensitivity of 82.3% (95% CI: 74.6-88.1%) and specificity of 89.4% (95% CI: 85.2-92.5%).

CONCLUSION

Our findings suggest that at present recommended threshold of 6.5%, HbA1c is more specific and less sensitive in diagnosing the newly detected diabetes in undiagnosed population from community settings. Lowering of thresholds for HbA1c and FPG to 6.03% and 104 mg/dL for early detection in previously undiagnosed persons for screening purposes may be considered.

The prevalence of pre-diabetes and diabetes in the Kuwaiti adult population in 2014

BACKGROUND

Kuwait ranks among the top 20 countries worldwide in diabetes prevalence. This study's objectives were to assess the prevalence of pre-diabetes and diabetes in Kuwaiti adults.

METHODS

Kuwaiti citizens aged 18-69 years (n = 3915) were studied using the WHO's STEPwise survey methodology, including its Instrument for Chronic Disease Risk Factor Surveillance. Participants' demographics, medical history, physical measurements and blood biochemistry were assessed. A subset of 2561 individuals completed all three survey steps, including fasting plasma glucose (FPG) and HbA1c assays. The study assessed the prevalence of pre-diabetes (FPG 6.1-6.9 mmol/L or HbA1c level 5.7-6.4%) and diabetes (self-reported history of diabetes with prescription of diabetes medications or FPG ≥ 7 mmol/L or HbA1c level ≥6.5%).

RESULTS

The prevalence of pre-diabetes was 19.4% [95% CI: 17.9-21.0%] (By sex: Men, 19.3%; Women, 19.5%; p = 0.92; By age (years): 18-29 y, 13.9%; 30-44 y, 22.6%; 45-59 y, 25.8%; 60-69 y, 16.4%; p < 0.001). The prevalence of diabetes was 18.8% [17.3-20.4%] (By sex: Men, 20.4%; Women, 17.4%; p = 0.055; By age: 18-29 y, 6.6%; 30-44 y, 14.0%; 45-59 y, 36.7%; 60-69 y, 62.8%; p < 0.001), of whom 41.5% were previously undiagnosed. Diabetes prevalence was 27.4% among those with body mass index (BMI) ≥ 30 kg/m², 29% among those with elevated waist-hip ratio and 36% among those with hypertension. Diabetes was positively associated with BMI, waist-hip ratio and blood pressure level. Pre-diabetes was positively associated with BMI and waist-hip ratio, but not blood pressure level.

CONCLUSIONS

Almost 40% of Kuwaiti citizens had pre-diabetes or diabetes. Urgent public health action is needed to decrease diabetes prevalence and thus avoid associated morbidity and mortality.

Development of a screening tool using electronic health records for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose detection in the Slovenian population

AIM

To develop and validate a simplified screening test for undiagnosed Type 2 diabetes mellitus and impaired fasting glucose for the Slovenian population (SloRisk) to be used in the general population.

METHODS

Data on 11 391 people were collected from the electronic health records of comprehensive medical examinations in five Slovenian healthcare centres. Fasting plasma glucose as well as information related to the Finnish Diabetes Risk Score questionnaire, FINDRISC, were collected for 2073 people to build predictive models. Bootstrapping-based evaluation was used to estimate the area under the receiver-operating characteristic curve performance metric of two proposed logistic regression models as well as the Finnish Diabetes Risk Score model both at recommended and at alternative cut-off values.

RESULTS

The final model contained five questions for undiagnosed Type 2 diabetes prediction and achieved an area under the receiver-operating characteristic curve of 0.851 (95% CI 0.850-0.853). The impaired fasting glucose prediction model included six questions and achieved an area under the receiver-operating characteristic curve of 0.840 (95% CI 0.839-0.840). There were four questions that were included in both models (age, sex, waist circumference and blood sugar history), with physical activity selected only for undiagnosed Type 2 diabetes and questions on family history and hypertension drug use selected only for the impaired fasting glucose prediction model.

CONCLUSIONS

This study proposes two simplified models based on FINDRISC questions for screening of undiagnosed Type 2 diabetes and impaired fasting glucose in the Slovenian population. A significant improvement in performance was achieved compared with the original FINDRISC questionnaire. Both models include waist circumference instead of BMI.