The effect of a structured clinical algorithm on glycemic control in patients with combined tuberculosis and diabetes in Indonesia: A randomized trial

Glycemic control during TB treatment among Filipinos: The Starting Anti-Tuberculosis Treatment Cohort Study

Poor TB treatment outcomes are observed in patients with type 2 diabetes mellitus (DM) comorbidity and glycemic control throughout treatment may play a role. The objective of this study was to investigate glycemic control longitudinally among Filipino adults undergoing TB treatment using mixed-effects linear and logistic regression. Analyses were conducted in 188 DM-TB patients out of 901 enrolled in the Starting Anti-TB Treatment (St-ATT) cohort, with a median baseline glycosylated hemoglobin (HbA1c) of 8.2% (range 4.5-13.3%). Previous versus new DM diagnosis was associated with higher mean HbA1c (worse glycemic control) during treatment, with a smaller effect amongst those with central obesity (coefficient 0.80, 95% confidence interval [CI] 0.26, 1.57, P = 0.043) than amongst those without central obesity (coefficient 3.48, 95% CI 2.16, 4.80, P<0.001). In those with a new DM diagnosis, central obesity was associated with higher blood glucose (coefficient 1.62, 95% CI 0.72, 2.53, P = 0.009). Of 177 participants with ≥2 HbA1c results, 40% had uncontrolled glycemia (≥2 HbA1c results ≥8%). Of 165 participants with ≥3 HbA1c results, 29.9% had consistently-controlled glycemia, 15.3% had initially-uncontrolled glycemia, and 18.6% had consistently-uncontrolled glycemia. Previous versus new DM diagnosis and glucose-lowering medication use versus no use were associated with having uncontrolled versus controlled glycemia (adjusted odds ratio [aOR] 2.50 95%CI 1.61, 6.05, P = 0.042; aOR 4.78 95% CI 1.61,14.23, P<0.001) and more likely to have consistently-uncontrolled versus consistently-controlled glycemia (adjusted relative risk ratio [aRRR] 5.14 95% CI 1.37, 19.20, P = 0.015; aRRR 10.24 95% CI 0.07, 0.95, P = 0.003). Relapse cases of TB were less likely than new cases to have uncontrolled (aOR 0.20 95%CI 0.06, 0.63, P = 0.031) or consistently-uncontrolled (aRRR 0.25 95%CI 0.07, 0.95, P = 0.042) versus controlled glycemia. Those with long-term DM, suggested by previous diagnosis, glucose-lowering medication use and possibly central obesity, may require additional support to manage blood glucose during TB treatment.

Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity

BACKGROUND

People with diabetes are more likely to develop tuberculosis (TB) and to have poor TB-treatment outcomes than those without. We previously showed that blood transcriptomes in people with TB-diabetes (TB-DM) co-morbidity have excessive inflammatory and reduced interferon responses at diagnosis. It is unknown whether this persists through treatment and contributes to the adverse outcomes.

METHODS

Pulmonary TB patients recruited in South Africa, Indonesia and Romania were classified as having TB-DM, TB with prediabetes, TB-related hyperglycaemia or TB-only, based on glycated haemoglobin concentration at TB diagnosis and after 6 months of TB treatment. Gene expression in blood at diagnosis and intervals throughout treatment was measured by unbiased RNA-Seq and targeted Multiplex Ligation-dependent Probe Amplification. Transcriptomic data were analysed by longitudinal mixed-model regression to identify whether genes were differentially expressed between clinical groups through time. Predictive models of TB-treatment response across groups were developed and cross-tested.

RESULTS

Gene expression differed between TB and TB-DM patients at diagnosis and was modulated by TB treatment in all clinical groups but to different extents, such that differences remained in TB-DM relative to TB-only throughout. Expression of some genes increased through TB treatment, whereas others decreased: some were persistently more highly expressed in TB-DM and others in TB-only patients. Genes involved in innate immune responses, anti-microbial immunity and inflammation were significantly upregulated in people with TB-DM throughout treatment. The overall pattern of change was similar across clinical groups irrespective of diabetes status, permitting models predictive of TB treatment to be developed.

CONCLUSIONS

Exacerbated transcriptome changes in TB-DM take longer to resolve during TB treatment, meaning they remain different from those in uncomplicated TB after treatment completion. This may indicate a prolonged inflammatory response in TB-DM, requiring prolonged treatment or host-directed therapy for complete cure. Development of transcriptome-based biomarker signatures of TB-treatment response should include people with diabetes for use across populations.

Effect of Tuberculosis (TB) and Diabetes mellitus (DM) integrated healthcare on bidirectional screening and treatment outcomes among TB patients and people living with DM in developing countries: a systematic review

A systematic review (Prospero CRD42017075562) including articles published between 1 January 1990 and 31 October 2021 was performed to synthesize evidence on the effect of integrating tuberculosis (TB) and diabetes mellitus (DM) healthcare on screening coverage and treatment loss to follow-up as compared to non-integrated care services for TB and DM in low- to middle-income countries (LMICs). Searches were performed in PubMed, Web of Science, WHO Global Index Medicus, and Cochrane Central Library. This review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and we adopted Cochrane data collection form for Randomized Controlled Trials (RCTs) and non-RCTs. Due to heterogeneity and limited data of studies included, meta-analysis was not performed. Of 6902 abstracts, 10 studies from South America, Asia, and Africa were included. One study from Zimbabwe showed 57% increase in DM screening among TB patients in integrated care as compared to non-integrated care; 95% CI: 54.1, 59.8. Seven studies with before-after comparison groups reported increased screening coverage during implementation of integrated healthcare that ranged from 10.1% in Mexico to 99.1% in China. Three studies reported reduction in loss to follow-up among TB patients in integrated care; two in China showed 9.2%, 95% CI: -16.7, -1.7, and -9.5%, 95% CI: -18.4, -0.7 differences, while a study from Mexico showed -5.3% reduction, 95% CI: -9.8, -0.9.With few and heterogenous included studies, the synthesized evidence is weak to establish effect of TB/DM integrated care. Therefore, further robust studies such as randomized clinical trials and well-designed observational studies are needed.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment

BACKGROUND

Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control.

METHODS

Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n  =  94) and Indonesia (n  =  81), who had concomitant DM (n  =  59), intermediate hyperglycaemia (n  =  79) or normal glycaemia/no DM (n  =  37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA.

FINDINGS

We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749).

INTERPRETATION

These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM.

FUNDING

The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).

Educational counselling of patients with combined TB and diabetes mellitus: a randomised trial

SETTING

Newly diagnosed pulmonary TB with diabetes mellitus (DM) comorbidity attending clinics in Bandung City, Indonesia.

OBJECTIVE

To describe the effect of educational counselling on patients' knowledge about TB (transmission, treatment, risk factors) and DM (symptoms, treatment, complications, healthy lifestyle), adherence to medication, and to assess characteristics associated with knowledge.

DESIGN

All patients received counselling and were then randomised to either structured education on TB-DM, combined with clinical monitoring and medication adjustment (intervention arm), or routine care (control arm). Knowledge and adherence were assessed using a questionnaire.

RESULTS

Baseline and 6-month questionnaires were available for 108 of 150 patients randomised (60/76 in the intervention arm and 48/74 in the control arm). Patients knew less about DM than about TB. There was no significant difference in the proportion with knowledge improvement at 6 months, both for TB (difference of differences 14%; P = 0.20) or for DM (10%; P = 0.39) between arms. Intervention arm patients were more likely to adhere to taking DM medication, with fewer patients reporting ever missing oral DM drugs than those in the control arm (23% vs. 48%; P = 0.03). Higher education level was associated with good knowledge of both TB and DM.

CONCLUSIONS

Structured education did not clearly improve patients' knowledge. It was associated with better adherence to DM medication, but this could not be attributed to education alone. More efforts are needed to improve patients' knowledge, especially regarding DM.