Reducing analytical variation between point-of-care and laboratory HbA1c testing

Assessment of Two Diabetes Point-of-care Analyzers Measuring Hemoglobin A1c in the Peruvian Amazon

Background:

With an estimated 174 million undiagnosed cases of diabetes mellitus worldwide and 80% of them occurring in low- and middle-income countries an effective point-of-care diagnostic tool is key to fighting this global epidemic. Glycated hemoglobin has become a reliable biomarker for the diagnosis and prognosis of diabetes.

Objective:

We assessed two point-of-care (POC) analyzers in multi-ethnic communities of the Amazon Rainforest in Peru where laboratory-based glycated hemoglobin (HbA1c) testing is not available.

Methods:

203 venous blood samples were tested for HbA1c by Afinion and DCA Vantage analyzers as well as a Premier Hb9210 high-performance liquid chromatography (HPLC) method as the reference standard. The coefficient of variation (CV) of each device was calculated to assess assay imprecision. Bland-Altman plots were used to assess bias. Ambient temperature, humidity, and barometric pressure were also evaluated for their effect on HbA1c results using multivariate regression.

Findings:

There was a wide range of HbA1c for participants based on the HPLC test: 4.4–9.0% (25–75 mmol/mol). The CV for the Afinion was 1.75%, and 4.01% for Vantage. The Afinion generated higher HbA1c results than the HPLC (mean difference = +0.56% [+6 mmol/mol]; p < 0.001), as did the DCA Vantage (mean difference = +0.32% [4 mmol/mol] p < 0.001). Temperature and humidity were not related to HbA1c; however, barometric pressure was associated with HPLC HbA1c results for the Afinion.

Conclusions:

Imprecision and bias were not low enough to recommend either POC analyzer for HbA1c determinations in this setting.

Assessment of Two Diabetes Point-of-care Analyzers Measuring Hemoglobin A1c in the Peruvian Amazon

BACKGROUND

With an estimated 174 million undiagnosed cases of diabetes mellitus worldwide and 80% of them occurring in low- and middle-income countries an effective point-of-care diagnostic tool is key to fighting this global epidemic. Glycated hemoglobin has become a reliable biomarker for the diagnosis and prognosis of diabetes.

OBJECTIVE

We assessed two point-of-care (POC) analyzers in multi-ethnic communities of the Amazon Rainforest in Peru where laboratory-based glycated hemoglobin (HbA1c) testing is not available.

METHODS

203 venous blood samples were tested for HbA1c by Afinion and DCA Vantage analyzers as well as a Premier Hb9210 high-performance liquid chromatography (HPLC) method as the reference standard. The coefficient of variation (CV) of each device was calculated to assess assay imprecision. Bland-Altman plots were used to assess bias. Ambient temperature, humidity, and barometric pressure were also evaluated for their effect on HbA1c results using multivariate regression.

FINDINGS

There was a wide range of HbA1c for participants based on the HPLC test: 4.4-9.0% (25-75 mmol/mol). The CV for the Afinion was 1.75%, and 4.01% for Vantage. The Afinion generated higher HbA1c results than the HPLC (mean difference = +0.56% [+6 mmol/mol]; p &lt; 0.001), as did the DCA Vantage (mean difference = +0.32% [4 mmol/mol] p &lt; 0.001). Temperature and humidity were not related to HbA1c; however, barometric pressure was associated with HPLC HbA1c results for the Afinion.

CONCLUSIONS

Imprecision and bias were not low enough to recommend either POC analyzer for HbA1c determinations in this setting.

Variation in Point-of-Care Testing of HbA1c in Diabetes Care in General Practice

Background: Point-of-care testing (POCT) of HbA1c may result in improved diabetic control, better patient outcomes, and enhanced clinical efficiency with fewer patient visits and subsequent reductions in costs. In 2008, the Danish regulators created a framework agreement regarding a new fee-for-service fee for the remuneration of POCT of HbA1c in general practice. According to secondary research, only the Capital Region of Denmark has allowed GPs to use this new incentive for POCT. The aim of this study is to use patient data to characterize patients with diabetes who have received POCT of HbA1c and analyze the variation in the use of POCT of HbA1c among patients with diabetes in Danish general practice. Methods: We use register data from the Danish Drug Register, the Danish Health Service Register and the National Patient Register from the year 2011 to define a population of 44,981 patients with diabetes (type 1 and type 2 but not patients with gestational diabetes) from the Capital Region. The POCT fee is used to measure the amount of POCT of HbA1c among patients with diabetes. Next, we apply descriptive statistics and multilevel logistic regression to analyze variation in the prevalence of POCT at the patient and clinic level. We include patient characteristics such as gender, age, socioeconomic markers, health care utilization, case mix markers, and municipality classifications. Results: The proportion of patients who received POCT was 14.1% and the proportion of clinics which were “POCT clinics” was 26.9%. There were variations in the use of POCT across clinics and patients. A part of the described variation can be explained by patient characteristics. Male gender, age differences (older age), short education, and other ethnicity imply significantly higher odds for POCT. High patient costs in general practice and other parts of primary care also imply higher odds for POCT. In contrast, high patient costs for drugs and/or morbidity in terms of the Charlson Comorbidity index mean lower odds for POCT. The frequency of patients with diabetes per 1000 patients was larger in POCT clinics than Non-POCT clinics. A total of 22.5% of the unexplained variability was related to GP clinics. Conclusions: This study demonstrates variation in the use of POCT which can be explained by patient characteristics such as demographic, socioeconomic, and case mix markers. However, it appears relevant to reassess the system for POCT. Further studies are warranted in order to assess the impacts of POCT of HbA1c on health care outcomes.

Performance of point-of-care HbA1c test devices: implications for use in clinical practice - a systematic review and meta-analysis

BACKGROUND

Point-of-care (POC) devices could be used to measure hemoglobin A1c (HbA1c) in the doctors' office, allowing immediate feedback of results to patients. Reports have raised concerns about the analytical performance of some of these devices. We carried out a systematic review and meta-analysis using a novel approach to compare the accuracy and precision of POC HbA1c devices.

METHODS

Medline, Embase and Web of Science databases were searched in June 2015 for published reports comparing POC HbA1c devices with laboratory methods. Two reviewers screened articles and extracted data on bias, precision and diagnostic accuracy. Mean bias and variability between the POC and laboratory test were combined in a meta-analysis. Study quality was assessed using the QUADAS2 tool.

RESULTS

Two researchers independently reviewed 1739 records for eligibility. Sixty-one studies were included in the meta-analysis of mean bias. Devices evaluated were A1cgear, A1cNow, Afinion, B-analyst, Clover, Cobas b101, DCA 2000/Vantage, HemoCue, Innovastar, Nycocard, Quo-Lab, Quo-Test and SDA1cCare. Nine devices had a negative mean bias which was significant for three devices. There was substantial variability in bias within devices. There was no difference in bias between clinical or laboratory operators in two devices.

CONCLUSIONS

This is the first meta-analysis to directly compare performance of POC HbA1c devices. Use of a device with a mean negative bias compared to a laboratory method may lead to higher levels of glycemia and a lower risk of hypoglycaemia. The implications of this on clinical decision-making and patient outcomes now need to be tested in a randomized trial.

Long-Term Performance of Point-of-Care Hemoglobin A1c Assays

BACKGROUND

Point-of-care (POC) testing of HbA1c is used as a time-efficient tool to improve treatment and management planning for diabetes in the clinic setting. HbA1c values are the basis for monitoring ongoing response to treatment and to make adjustments to diabetes therapy. Yet, there is ongoing controversy as to the accuracy of POC assays. Diabetes is a lifelong disease, so comparability of results over a long period of time is needed to follow the response to treatment.

METHODS

We compared the Afinion™ automated boronate affinity assay and the DCA Vantage immunoassay-based POC techniques to the Tosoh G8 and Bio-Rad Variant II ion-exchange high-performance liquid chromatography (HPLC) central laboratory methods in a study lasting 3 years. College of American Pathology Survey results and American Proficiency testing were utilized to assess the external validity of the POC techniques.

RESULTS

Despite high correlations among the 4 techniques, there were significant and variable differences obtained over time. The Biorad values varied from 0.1 to 0.4% higher than the Afinion values. The DCA results were usually higher than the Afinion values, but fell below the Afinion results in the last 6 months of our study. Both POC techniques gave systematically lower values than the Tosoh measurements, and both the POC and the central laboratory measurements showed variable differences from the National Glycohemoglobin Standardization Program values over the duration of this study.

CONCLUSIONS

All who rely on POC methods as well as on central laboratory measurement of HbA1c must understand the potential limitations of these assays. The assessment of diabetes blood sugar control should proceed from the evaluation of HbA1c combined with review of plasma glucose and of self-monitored blood glucose values.