The findings presented here depict a detailed investigation of the performance of two tests widely used for assessment of dysglycemia among PWTB from Brazil and Peru. The studied countries represent an expressive portion of TB cases and around of 50% of Latin American cases in the world, with also elevated prevalence of DM and PDM [1, 8, 22]. As discussed, PWTB with concurrent uncontrolled glycemic status have an increased risk of increased morbidity and poor treatment outcomes [25, 26]. Therefore, there is an urgent need for systematic screening of dysglycemia in PWTB, in order to reach those at highest risk of disease complications. Understanding the peculiarities of diagnosing dysglycemia in TB cases in different populations is key to develop focused control strategies adapted to local epidemiological trends.
Our analyses revealed that the accuracy of HbA1c and FPG to diagnose dysglycemia in PWTB differs between Brazil and Peru, with a better performance of HbA1c in Brazil and FPG in Peru. Findings from studies in other countries reinforce the idea that there is heterogeneity in performance of DM screening tests in PWTB. A study from India has demonstrated that HbA1c performed better than FPG with an AUC of 0.754 (0.682–0.828) for newly diagnosed DM among subjects with TB [13]. Furthermore, a Pakistan study showed that the proportion of participants falsely classified as positive was higher for FPG, although the performance of HbA1c and FPG had no differences in terms of diagnosing new DM cases [17]. In a recent study, FPG levels were able to detect more cases of PDM in PWTB from Peru than HbA1c [2]. In a Chinese study, FPG performed better than HbA1c in identifying newly diagnosed DM and PDM [27]. Such peculiarities in test performance to diagnose dysglycemia reported in different countries may be determined by genetics, environmental factors or a combination of both and should be explored in future mechanistic studies.
Previous studies have shown that HbA1c values vary according to ethnicity, even in individuals without dysglycemia [28, 29]. Moreover, abnormalities of erythrocyte indices are considerable confounders in the analysis of HbA1c [30]. Possible explanations for this could be hemoglobin-related factors such as red cell turnover, variations in hemoglobin glycation, differences in the passage of glucose mediated by GLUT1 transporter into the erythrocyte, higher prevalence of hemolytic conditions such as glucose-6-phosphate dehydrogenase deficiency or sickle cell trait, among others [29, 31]. Genetic factors can also modulate HbA1c levels with heritability of 47–59% [32]. Interestingly, a genetic risk score, based on the 14 single nucleotide polymorphisms (SNPs) found that some people had a higher genetic risk of higher levels of fasting plasma glucose [33]. Regarding DM in PWTB, a multicentric prospective study compared the accuracy of random plasma glucose, point-of-care HbA1c, FPG, urine dipstick, risk scores and anthropometric measurements, using HbA1C as a golden standard. They also found heterogeneous performance of laboratory markers to diagnose DM across countries [12].
More than identifying the reasons for HbA1c variation among populations, it is essential to know what the clinical importance of these findings is. It is still under discussion how this variation in test performance can affect DM outcomes, but some studies have found no difference in long term risk for cardiovascular disease, final-stage renal disease and retinopathy [29, 34, 35]. To our knowledge, no studies to date have evaluated the influence of HbA1c accuracy variation in TB outcomes. A previous study reported higher HbA1c values being predictive of unfavorable outcomes in PWTB [36], but there was no comparison between populations with distinct genetic backgrounds.
The ADA guidelines for DM recommends that any of three diagnostic test mentioned in this study can be used to diagnose DM [19]. The Brazilian guidelines use the same criteria as ADA and the Peruvian guidelines have not included HbA1c as a diagnostic tool because of its low availability in the public health system and lack of standardization in the country [37, 38]. Our findings suggest that the use of HbA1c should be used with caution in the diagnosis, as the cutoff is still inconsistent and may vary in dissimilar populations. It is possible that different thresholds need to be used in different populations.
More research needs to be done in evaluating the impact of variability in DM screening test accuracy in TB treatment outcome. Moreover, additional studies are required to define the most reliable screening methods for each population. As an example, Grint D, et al tested a combination of two tests that increased DM diagnosis accuracy in PWTB from Peru and Indonesia, but not in other countries [12]. Meanwhile, standard diagnostic thresholds should be used with caution, particularly in the population with greater variability of tests results. Clinicians should also be attentive for factors that are predictors of high glycemia, such as older age, hypertension, and increased body mass index [28] and repeat or associate a different method when there is high pre-test probability of dysglycemia.
Common limitations of retrospective investigations should be acknowledged in our study. Our investigations could not determine the major factors responsible for the heterogeneity observed between countries, concerning ethnicity, severe anemia, and genetic variations in hemoglobin. Additionally, the dissonances found regarding the distinct glycemic status on each group analyzed may have affected the accuracy of our findings in terms of confidence intervals. Finally, there was not a gold standard such as OGTT test used for the evaluation of accuracy. Nevertheless, given our diversified and well characterized cohorts, our conclusions do extend the current knowledge in the field by demonstrating a significant variability in accuracy of FPG and HbA1c to diagnose dysglycemia in TB patients across countries.