Evaluation of biological variations in glucose and glycated hemoglobin levels in healthy individuals

Introduction

Most clinical laboratory tests are commonly requested by clinicians for various clinical situations, including diagnosis, monitoring, assessment of risk factors and screening [1]. Glucose and glycated hemoglobin (HbA_1c) levels are also assessed for similar purposes. In this context, plasma glucose criteria, either the fasting plasma glucose (FPG) levels or the 2-h value in the 75-g oral glucose tolerance test have been used to diagnose diabetes mellitus (DM) for several years. An International Expert Committee that included representatives of the American Diabetes Association (ADA), the International Diabetes Federation (IDF), and the European Association for the Study of Diabetes (EASD) recommended that both the glucose test and the HbA_1c test should be used to diagnose DM, and the ADA adopted this criterion in 2010 [2], [3], [4]. Moreover, numerous diabetes organizations have defined the range of HbA_1c levels and FPG levels to predict the progression to DM [5].

Techniques used to monitor glucose and HbA_1c levels are important tools in assessing DM management, since poor glycemic control over time has been specifically linked to the development and progression of microvascular DM complications [6]. But, it sometimes is really difficult for clinicians to decide upon in some cases, although most tests have various clinical decision limits. Alterations observed in consecutive test results may be clinically significant, even if these results are within their reference intervals. This condition may also related to inherent variation [expressed as the coefficient of variation (CV)], which consist of the variations in pre-analytical (CV_P), analytical (CV_A) and within-subject biological variation (CV_I).

Between-subject biological variation (CV_G) defined as the differences between the set points of different individuals is another component of biological variation (BV) as well as CV_I. The CV_I/CV_G ratio is also used to calculate the index of individuality (II) which determines whether population-based reference interval for any analyte are useful. Moreover, the reference change value (RCV) derived from BV data (BVD) is also particularly helpful for the clinician to decide whether the changes in values for any analyte between consecutive tests are significant for patient health [7].

However, in the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference, doubts about the quality of BVD in current clinical use were raised, and its utility was suggested to be limited [8]. Indeed, existing BVD exhibit marked heterogeneity in terms of study design, as well as uncertainty in the calculations [9]. In particular, the EFLM has continued to work to overcome the challenges in these issues and endeavor to expand reliable BVD through the Working Group on BV (WG-BV) [10], [11]. In this context, the BV database (BV-DB) that were previously prepared by Ricos and colleagues [12] were recently updated by gathering data from new publications that have been continuously expanded, updated and published online. In addition, analytical performance specifications (APS) for imprecision (I%), bias (B%) and total error (TE%) of various analytes calculated from BVD were also published on the same website [13]. Moreover, Bartlett and colleagues [9] have recently published a critical appraisal checklist to enable the standardized assessment of papers on BV in the name of the EFLM WG-BV. Perich and colleagues [14] have also reported criteria used to evaluate the reliability of the BV-DB.

Consequently, our initial goal was to estimate BVD for both analytes in detail based on the guidance of relevant organizations and experts. The other goal was to guide to the clinician to make decision about reference interval or RCV should be used for both analytes while managing the DM process.

Materials and methods

Results

The data from 33 subjects were statistically evaluation after three subjects with IFG were excluded from the study. Glucose levels were normally distributed, according to the results of the normality test (p=0.063). After outlier tests, one dataset from five subjects (together with repeated measurements) was removed the study and we then confirmed whether the data were normally distributed by performing the normality test again (p=0.069).

It was applied In transformation to all HbA_1c data because they did not exhibit a normal distribution (p=0.001). After transformation, the data exhibited a normal distribution (p=0.053), and we then removed one dataset from four subjects (including repeated measurements) and all data for one subject from the study after performing the outlier test. Finally, we performed a statistical evaluation on HbA_1c data from 32 subjects.

We graphically presented the glucose and HbA_1c data obtained after completing all statistical procedures below (Figures 1 and 2).

Figure 1:

Error bar graph of glucose levels in 33 subjects.

Green bars represent female subjects and blue bars show male subjects.

Figure 2:

Error bar graph of logHbA_1c% in 32 subjects.

The colors used for logHbA_1c% in each gender are the same as the glucose levels. All data for one subject were excluded from the study.

We calculated all SD values for both analytes using a nested ANOVA design after testing the homogeneity of variances in glucose (p=0.945) and HbA_1c levels (p=0.226). In addition, we calculated RCV and II for glucose and HbA_1c levels (Table 1).

Finally, we obtained desirable APS for I%, B% and TE% for both analytes and compared these values with the desirable specifications reported in an online database (Table 2) [23].

Discussion

In this study, we firstly analyzed each sample in duplicate to estimate analytic variation for both analytes, since this procedure was reported as the best approach in studies by some experts [15], [24]. The CV_A value for glucose was 1.1%. This result was slightly lower than the results from other studies [21], [25]. We used the reference method approved by IFCC and reference material supplied by manufacturers; in addition, we clearly defined the analytical system used to measure glucose levels in this study. In contrast, previous studies did not completely explain which methods and analytical systems were used to measure glucose levels, and the reference materials used to calibration the glucose measurement methods were not defined [12], [21], [25]. However, notations of the use of commercial methods with validated calibrators are important, since some commercial systems used for glucose measurements may produce non-traceable values because of a lack of validated calibrations [20]. The CV_A for HbA_1c was 1.3%. This value was similar to the values reported in studies that used the ion exchange method to measure HbA_1c levels [17], [26], [27], [28], but was also less than the values reported in several studies that used different methods [29], [30].

Moreover, within-subject and between subject variations calculated for glucose in this study were also a slightly lower than the values reported in the study by Ricos et al. [12], [23] and published online on the Westgard website, whereas they were fairly consistent with the results presented in another study of Ricos et al. [21] and a study by Fraser et al. [25]. Moreover, we observed that components of biological variation regarding HbA_1c calculated by ours were consistent with the results reported in some studies [17], [30], [31], but were different from the results obtained other studies [28], [32].

We observed that between-subject variation in HbA_1c was much more higher than within-subject variation in HbA_1c. Therefore, the II value of HbA_1c were more less than 0.6. Whereas II value of glucose was higher than this value. There are serious similarities between reference interval and RCV in terms of those of production and use even though the requirements for delivery and characterisation of the latter have been clearly identified by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) and more recently in guidance issued by the Clinical and Laboratory Standards Institute (CLSI) [9]. As a consequence, it may be thought that reference interval for HbA_1c are also not useful in evaluating HbA_1c results and therefore the RCV for HbA_1c may be used to assess meaningful difference in HbA_1c levels from consecutive tests in the clinic. As mentioned previous studies, we also thought that it may be required very different HbA_1c target values to obtain the same overall glycemic status while management of patient with DM accordìng to glucose [32]. On the other hand, it should be also considered the current clinical practice guidelines for the DM management as well as our suggestions in this issue.

We also determined that the desirable analytical performance specification obtained in this study for both analytes were fairly consistent with the desirable specifications reported in an online database [23], with the exception that I% for HbA_1c shows minimum analytical performance (CV_A<0.75 CV_I), as reported in other studies [26], [27]. However, several studies using the same methodology achieved desirable performance [28], [33]. The studies that used a different methodology to measure HbA_1c levels generally displayed a worse analytical performance than our methodology [17], [29], [30], [31], [34]. On the other hand, according to the study by Braga and colleagues [35], HPLC systems with ion-exchange columns has more specificity for HbA_1c than many methodologies, but still did not exhibit good performance in terms of analytical specificity, according to the IFCC reference measurement procedure.

Previous studies had various levels of quality in terms of study design and substantial uncertainty in terms of estimating BVD, because accepted international standards for these issues have not been available. However, some international organizations, such as the IFCC, EFLM and CLSI have made an effort to standardize the BVD studies [9]. As a result, we performed this study according to the recommendations of these organizations as well as relevant experts.

Regarding the limitations of our work, we could have collected more than four samples for both analytes because their consecutive measurements obtained samples which were collected over a longer period time interval may better reflects variables in their blood levels.

Conclusion

We thought that the guidelines of some relevant international organizations, such as the EFLM, should be published to standardize the study design used in BV studies and to calculate BVD using an appropriate method. In addition, we suggested that the RCV should be used to assess meaningful difference in consecutive results of HbA_1c instead of reference interval.