Diabetes mellitus affects the treatment outcomes of drug-resistant tuberculosis: A systematic review and meta-analysis

doi:10.21203/rs.3.rs-2251001/v2

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Research Article

Diabetes mellitus affects the treatment outcomes of drug-resistant tuberculosis: A systematic review and meta-analysis

https://doi.org/10.21203/rs.3.rs-2251001/v2

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published 20 Nov, 2023

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Background

Both tuberculosis (TB) and diabetes mellitus (DM) are major public health problems threatening global health. Drug-resistant TB (DR-TB) and impaired immunity caused by DM make controlling TB more difficult.

Methods

We searched PubMed, Excerpta Medica Database (EMBASE), Web of Science, ScienceDirect and Cochrance Library for literature published in English until July 2022. Papers were limited to those reporting the association between DM and treatment outcomes among DR-TB and multidrug-resistant TB (MDR-TB) patients. The strength of association was presented as odds ratios (ORs) and their 95% confidence intervals (CIs) using the fixed-effects or random-effects models. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were followed for the analysis.

Results

A total of twenty-five studies involving 16,905 DR-TB patients were included in the meta-analysis, of which 10,124 (59.88%) participants were MDR-TB patients, and 1,952 (11.54%) had DM history. In DR-TB patients, the pooled OR was 1.56 (95% Cl: 1.24–1.96) for unsuccessful outcomes, 0.64 (95% Cl: 0.44–0.94) for cured treatment outcomes, 0.63 (95% Cl: 0.46–0.86) for completed treatment, and 1.28 (95% Cl: 1.03–1.58) for treatment failure. Among MDR-TB patients, the pooled OR was 1.57 (95% Cl: 1.20–2.04) for unsuccessful treatment outcomes, 0.55 (95% Cl: 0.35–0.87) for cured treatment outcomes, 0.66 (95% Cl: 0.46–0.93) for completed treatment and 1.37 (95% Cl: 1.08–1.75) for treatment failure.

Conclusion

DM is a risk factor for adverse outcomes of DR-TB or MDR-TB patients. Controlling hyperglycemia may contribute to the favourable prognosis of TB.

Drug-resistant tuberculosis

Multidrug-resistant tuberculosis

Diabetes mellitus

Treatment outcomes

Tuberculosis (TB) is a major public health issue that threatens global health, which caused 1.3 million deaths in 2020. The burden of TB is further aggravated by the growing prevalence of acquired immunodeficiency syndrome (AIDS), diabetes mellitus (DM) and kidney disease[1–3], as they may contribute to the TB risk and affect treatment outcomes[4–6]. With the changes in people's lifestyles, the global burden of DM is continuously increasing. It is estimated that 693 million people worldwide will suffer from DM by 2045[7]. The epidemic of DM will further aggravate the burden of TB, especially in low- and middle-income countries[8, 9].

The World Health Organization (WHO) estimated that there were 157,903 multidrug-resistant (MDR) TB cases reported in 2020[10]. Drug-resistant TB (DR-TB) and MDR-TB make controlling TB more challenging[11]. Patients afflicted with both DR-TB and DM will face worse treatment outcomes[12, 13]. However, there were few systematic analyses to clarify and quantify the association between DM and DR/MDR-TB outcomes. Given the increasing burden of TB among people with DM, we performed a meta-analysis to systematically assess the association between DM and the treatment outcomes of DR/MDR-TB.

Search strategy and study selection

This systematic review has been registered with the International Prospective Register of Systematic Reviews (PROSPERO) (https://www.crd.york.ac.uk/prospero/ ID=CRD42022350214; registration number: CRD42022350214). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were followed for the analysis. We systematically searched the electronic database, including PubMed, Excerpta Medica Database (EMBASE), Web of Science, ScienceDirect and Cochrance Library, by July 2022. We used the following search terms: (“Tuberculosis” or “Drug-resistant tuberculosis” or “Multidrug-resistant tuberculosis”) AND (“diabetes mellitus” or “diabetes”) AND (“Treatment(s) outcome(s)”or “treatment(s)”). The EndNote X9.0 software was used to manage records, screen, and exclude duplicates. The inclusion criteria were as follows: (1) The study was designed as a cohort, case-control or cross-sectional study; (2) TB cases could provide whether there was a history of DM; (3) TB cases were diagnosed as DR/MDR-TB; (4) Treatment outcomes of TB cases were recorded.

Data extraction

Two reviewers extracted data independently and subsequently met to resolve discrepancies. In case of continued disagreement, a third reviewer made the final disposition. We extracted data on demographic characteristics, study design, location of the population, number of participants in each study, drug-resistant type, type of DM, adjusted odds ratio (OR) and relevant covariates (Table 1).

Treatment outcomes definitions

Treatment outcomes were divided into six categories, namely cured, treatment completed, treatment failed, death, lost to follow-up, and not evaluated. Cured and completed treatment were considered successful, and the rest were deemed unsuccessful in accordance with the WHO guidelines [14] (Table2).

Quality assessment

The quality of the included studies were evaluated using a modified version of the Newcastle-Ottawa Scale for cohort and case-control studies[15]. Studies were classified as having low (≥7 stars), moderate (5-6 stars), and high risk of bias (≤4 stars) with an overall quality score of 9 stars [16]. For cross-sectional studies, we assigned each item of the AHRQ checklist a score of 1 (answered “yes”) or 0 (answered “no” or “unclear”). The high, moderate, and low risk of bias were identified as having a score of 0-3, 4-7, and 8-11, respectively.

Statistical analysis

Data was extracted using the Excel 2019 software, and further analysed by Stata/se17.0. Heterogeneity between studies was assessed using the I² statistic described by Higgins et al[17]. The pooled effects were estimated with fixed or random effect models: I² ≤50% and P >0.10 representing insignificant heterogeneity, using fixed-effects models; I² ≥50% and P <0.10 representing significant heterogeneity, using random-effects models.

The pooled effects of DM on DR/MDR-TB treatment outcomes were described by forest plots, quantified by OR (besides case-control studies, cross-sectional studies and cohort studies were also estimated by OR) and the corresponding 95% confidence interval (CI). P <0.05 was considered statistically significant. The publication bias was assessed through a funnel plot and Egger’s test. All analyses were performed using the STATA 17.0 software (Texas, USA).

Study selection and characteristics

We searched 9,918 papers by titles, abstracts and keywords and then excluded 9,416 papers without TB treatment outcomes. Among 502 articles under full-text reading, 477 articles were excluded for lacking targeted data or imperfect data (Figure 1). Finally, we involved twenty-five eligible studies in the meta-analysis (Table 1)[12, 13, 18-40], including nine cohort studies, fourteen case-control studies and two cross-sectional studies. These studies were published from 2005 to 2022. Eleven studies were identified as having a low risk of bias, and fourteen studies had a moderate risk of bias. The total sample size of subjects was 16,905 DR-TB patients, of which 10,124 (59.89%) participants were MDR and 1,952 (11.54%) had DM (DM+).

Unsuccessful treatment outcomes

Twenty-three studies analyzed the risk of DM on unsuccessful treatment outcomes in patients with DR-TB and twenty studies analyzed the risk of DM on unsuccessful treatment outcomes in patients with MDR-TB. DM patients were more likely to have unsuccessful treatment outcomes in DR-TB (OR =1.56, 95% Cl: 1.24-1.96) and MDR-TB patients (OR =1.57, 95% Cl: 1.20-2.04) (Table 3, Figure 2). Sensitivity analysis showed that four studies contributed to the primary heterogeneity [18, 24, 29, 32]， which might be attributed to the inclusion of extensively drug-resistant (XDR-TB) [29, 32]. Figure 3 illustrates the funnel plots of the detailed studies (Figures 2 and 3). We did not find evidence for publication bias in DR-TB treatment outcomes (P =0.086) and MDR-TB treatment outcomes (P =0.365) by Egger’s test (Table 3).

Death

We further compared the risk of death for patients with and without DM. The random-effects model was used to estimate the pooled effects, as there was significant heterogeneity for DR-TB studies (I² =53.3%, P =0.029) and MDR-TB studies (I² =59.2%, P =0.016) (Table 3). The pooled OR was 1.32 (95% CI: 0.97-1.82) and 1.33 (95% CI: 0.85-2.07), respectively (Table 3, Figure 2). There was no evidence for publication bias by Egger’s test (P =0.929 in DR-TB; P =0.940 in MDR-TB) (Table 3).

Cured

Patients without DM were more likely to be cured (DR-TB: OR =0.64, 95% Cl: 0.44-0.94; MDR-TB: OR =0.55, 95% Cl: 0.35-0.87) (Table 3, Figure 2). The random-effects model was used as there was significant heterogeneity (DR-TB: I² =75.7%, P =0.001; MDR-TB: I² =66.5%, P =0.018). The Egger's test suggested no publication bias (P =0.062 in DR-TB and P =0.263 in MDR-TB).

Treatment completed

Patients without DM were more likely to complete treatment (DR-TB: OR =0.63, 95% Cl: 0.46-0.86; MDR-TB: OR =0.66, 95% Cl: 0.46-0.93) (Table 3, Figure 2). There was no evidence for heterogeneity (DR-TB: I² =0.00%, P =0.660; MDR-TB: I² =0.00%, P =0.559) . There was no evidence for publication bias by Egger’s test (P =0.221 in DR-TB and P =0.192 in MDR-TB).

Treatment failure

Patients with DM were more likely to have treatment failure outcomes (DR-TB: OR =1.28, 95% Cl: 1.03-1.58; MDR-TB: OR =1.37, 95% Cl: 1.08-1.75) (Table 3, Figure 2). There was no evidence for heterogeneity (DR-TB: I² =22.7%, P =0.256; MDR-TB: I² = 19.7%, P =0.284). There was no publication bias by Egger’s test (P =0.263 in DR-TB and P =0.275 in MDR-TB).

This study systematically reviewed the impact of DM on the treatment outcomes of DR/MDR-TB patients. We demonstrated the negative effect of DM on the prognosis of TB, which was consistent with the findings by Meghan and Sanju et al. [41, 42].

This study analyzed twenty-five studies, including nine cohort studies, fourteen case-control studies, and two cross-sectional studies. Twenty studies were conducted in Asian populations, four were in Europe populations, three were in African people, and one was in American populations. The prevalence of DM in TB patients was 11.54% (95% Cl: 11.06–11.93) in this study, which was lower than the global level (15.4%, 95% Cl: 14.1–16.6) and marginally higher as compared to the prevalence in Africa (9%, 95% Cl: 6.0–12.0)[43, 44].

DM can induce abnormalities in innate and adaptive immune responses, increasing the risk of the activation, complication, and outcomes of TB[45]. TB patients with DM have a rapidly progressive infection and a higher bacterial burden[46]. Coincident DM modulates Th1, Th2, and Th17 cell responses in latent TB in an IL-10- and TGF-β-dependent manner [47]. TB patients with DM had an increased risk of death and late culture transformation[48, 49].

The possible hypothesis of delay in the time of clearance and treatment failure of TB among DM patients is related to higher bacterial burden at diagnosis, which could be related to slower kinetics in the immune response in DM patients and altered pharmacokinetics of anti-TB drugs[49–52]. A pharmacokinetic study noted that plasma levels of rifampicin were 53% lower in TB patients with DM[53]. Depressed production of IFN-γ in DM patients is related to a decreased immune response to TB infection. The reduced IL-12 response to mycobacterial stimulation in leukocytes from TB with DM suggests a compromise of the innate immune response[54]. Roger et al. showed that TB patients with prediabetes or DM were more likely to have unsuccessful treatment outcomes in Peru, with an OR of 6.1 (95% Cl: 1.9–19.6)[17]. Siti et al. reported that TB patients with DM were three times more likely to have an unsuccessful treatment outcome than those without DM in Kelantan state, Malaysia[55].

In conclusion, DM is a risk factor for adverse outcomes in DR-TB or MDR-TB patients. Controlling hyperglycemia may contribute to a favorable prognosis of TB.

tuberculosis

diabetes mellitus

DR-TB

Drug-resistant tuberculosis

MDR-TB

Multidrug-resistant tuberculosis

EMBASE

Excerpta Medica Database

ORs

odds ratios

CIs

confidence intervals

AIDS

acquired immunodeficiency syndrome

WHO

The World Health Organization

PROSPERO

Prospective Register of Systematic Reviews

AHRQ

Healthcare Research and Quality.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that there is no conflict of interest.

Funding

This work was supported by Scientific Research Project of Jiangsu Health Vocational College-General Project (JKC201940), Jiangsu University Philosophy and Social Science Research Project-General Project (2020SJA0844) and Scientific Research Project of Jiangsu Provincial Health Commission (Z2019009).

Authors' contributions

Guisheng Xu and Xiaojiang Hu conceived the study, participated in literature search and review, data extraction, study design and coordination, performed the statistical analysis, and helped draft the manuscript. Yanshu Lian and Xiuting Li contributed to collect and analyze the data. All authors read and approved the fnal manuscript.

Acknowledgements

We thank all the people who participated in the primary studies and the teams who did them.

Author details

¹Department of Preventive Medicine and Health Management, Health Management and Foundation College, Jiangsu Health Vocational College, 69 Huangshanling Road, Pukou District, Nanjing City, Jiangsu Province, 211800, China.

²Nanjing Luhe District Center for Disease Control and Prevention, 8 Meteorological Road, Luhe District, Nanjing City, Jiangsu Province, 211500, China.

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Table1 Characteristics of the studies included for meta-analysis

Author and year	Country	Population	Study type	Sample size	Unsuccessful Outcomes (DM+)	Successful Outcomes (DM-)	Unsuccessful Outcomes (DM+)	Successful Outcome (DM-)	The type of DR-TB	The type of DM	Odds ratio (95%Confidence Interval)
July Mary Johnson (2022)	India (Asian)	In-patients and out-patients	Case-control study	462	93	5	336	28	DR-TB	DM	1.55（0.58,4.13）
Daniel Bekele Ketema (2019)	Ethiopia (Africa)	In-patients and out-patients	Cohort study	508	7	9	79	413	DR-TB	DM	4.07(1.47,11.24)
A. Latif (2018)	Pakistan (Asian)	Community population	Cross-sectional study	5811	171	338	1631	3671	DR-TB	Type 2 DM	1.14(0.94,1.38)
Li Shi (2021)	China (Asian)	Hospital patients	Case-control study	214	10	97	7	100	MDR-TB	Type 2 DM	1.47(0.54,4.03)
Khasan Safaev (2021)	Uzbekistan (Asian)	Community population	Cohort study	545	13	7	229	296	MDR-TB	DM	2.40(0.94,6.11)
Subhakar Kandi (2021)	India (Asian)	In-patients and out-patients	Case-control study	377	11	20	151	195	MDR-TB	DM	0.71(0.33,1.53)
Wang Jianjie (2019)*	China (Asian)	In-patients and out-patients	Cohort study	552	60	89	97	306	MDR-TB	DM	2.13(1.43,3.17)
A K JanmeJa (2018)	India (Asian)	Community population	Case-control study	231	17	9	92	113	MDR-TB	DM	2.32(0.99,5.45)
Tariq Mahmood (2018)	India (Asian)	Hospital patients	Cross-sectional study	141	9	4	71	57	MDR-TB	DM	1.81(0.53,6.17)
Muñoz-Torrico (2017)	Mexico (America)	In-patients	Case-control study	77	25	18	15	19	MDR-TB	DM	1.76(0.71,4.36)
Baodong Yuan (2017)	China (Asian)	Hospital patients	Case-control study	359	32	42	59	226	MDR-TB	Type 2 DM	2.92(1.70,5.02)
Mohsen A. Gadallah (2015)	Egypt (Africa)	In-patients	Cohort study	228	17	19	53	139	MDR-TB	DM	2.35(1.13,4.85)
N. Kwak（2015）	Korea (Asian)	Hospital patients	Case-control study	123	0	10	20	93	MDR-TB	DM	0.22(0.01,3.86)
J.Peter Cegielsk (2015)	Estonia, Latvia, Philippines, Peru, Russia, South Africa, Korea, Taiwan and Thailand (Europe, Asian and African)	Community population	Cohort study	973	25	107	226	615	MDR-TB	DM	0.64(0.40,1.01)
Matthew J. Magee (2014)	Georgia (Asian)	Community population	Cohort study	1421	36	36	666	683	MDR-TB	DM	1.03(0.64,1.65)
Young Ae Kang (2013)	Korea (Asian)	Hospital patients	Case-control study	1407	153	86	617	551	MDR-TB	DM	1.59(1.19,2.12)
Ma Tarcela Gler (2013)	Philippines (Asian)	Hospital patients	Cohort study	439	34	83	95	227	MDR-TB	DM	0.98(0.61,1.56)
L F Anderson (2013)	England, Wales and Northern Ireland（Europe）	Hospital patients	Cohort study	191	6	4	41	140	MDR-TB	DM	5.12(1.38,19.02)
Shenjie Tang (2013)	China (Asian)	In-patients and out-patients	Case-control study	586	65	15	281	225	MDR-TB	DM	3.47(1.93,6.25)
Ekaterina V. Kurbatova (2012)	Russia, Latvia, Estonia, Peru and Philippines (Europe and Asian)	Out-patients	Case- control study	1401	23	45	395	938	MDR-TB	DM	1.21(0.72,2.03)
Medea Gegia (2012)	Georgian (Asian)	the National TB Reference Laboratory	Cohort study	380	16	19	163	182	MDR-TB	DM	0.94(0.47,1.89)
D.Bendayan (2010)*	Israel (Asian)	In-patients and out-patients	Case- control study	132	6	11	34	81	MDR-TB	DM	1.3(0.44,3.80)
D.S.Jeon (2008)	Korea (Asian)	Hospital patients	Case- control study	142	17	3	97	25	MDR-TB	DM	1.46(0.40,5.38)
T Yoshiyama (2005)	Japan (Asian)	In-patients and out-patients	Case-control study	74	7	14	5	48	MDR-TB	DM	4.80(1.32,17.49)
Vaira Leimane (2005)	Latvia (Europe)	Hospital Patients, prisoners patients, Community population	Case-control study	131	3	6	21	101	MDR-TB	DM	2.40(0.56,10.39)
DM(+), With diabetes mellitus; DM(-),Without diabetes mellitus; DR-TB, Drug-resistant tuberculosis; MDR-TB, Multidrug-resistant tuberculosis; * Number were for death treatment outcomes data

Table 2 Definitions of treatment outcomes for drug-resistant tuberculosis patients[14]

Treatment outcome	Definition
Cured	Treatment completed as recommended by the national policy without evidence of failure AND three or more consecutive cultures taken at least 30 days apart are negative after the intensive phase.^a
Treatment completed	Treatment completed as recommended by the national policy without evidence of failure BUT no record that three or more consecutive cultures taken at least 30 days apart are negative after the intensive phase.^a
Treatment failed	Treatment terminated or need for permanent regimen change of at least two anti-TB drugs because of: -Lack of conversion^b by the end of the intensive phase^a, or -Bacteriological reversion in the continuation phase after conversion to negative, or -Evidence of additional acquired resistance to fluoroquinolones or second-line injectable drugs, or -Adverse drug reactions (ADRs).
Died	A patient who dies for any reason during the course of treatment.
Lost to follow-up	A patient whose treatment was interrupted for 2 consecutive months or more.
Not evaluated	A patient for whom no treatment outcome is assigned. (This includes cases “transferred out” to another treatment unit and whose treatment outcome is unknown)
Treatment success	The sum of cured and treatment completed.

^aFor Treatment failed, lack of conversion by the end of the intensive phase implies that the patient does not convert within the maximum duration of intensive phase applied by the programme. If no maximumduration is defined, an 8-month cut-off is proposed. For regimens without a clear distinction between intensive and continuation phases, a cut-off 8 months after the start of treatment is suggested to determine when the criteria for Cured, Treatment completed and Treatment failed start to apply.

^bThe terms “conversion” and “reversion” of culture as used here are defined as follows:Conversion (to negative): culture is considered to have converted to negative when two consecutive

cultures, taken at least 30 days apart, are found to be negative. In such a case, the specimen collection date of the first negative culture is used as the date of conversion.

Reversion (to positive): culture is considered to have reverted to positive when, after an initial conversion, two consecutive cultures, taken at least 30 days apart, are found to be positive. For the purpose of defining Treatment failed, reversion is considered only when it occurs in the continuation phase.

Table3 Pooled effects odds ratio (95% confidence interval), Heterogeneity test and Egger's test for publication bias

DR-TB						MDR-TB
Treatment outcomes	Odds ratio (95% CI)	I² (%)	P-value for Heterogeneity	Z-value for Egger’s test	P- value for Egger’s test	Odds ratio (95% CI)	I² (%)	P-value for Heterogeneity	Z-value for Egger’s test	P- value for Egger’s test
Unsuccessful outcomes	1.56(1.24,1.96)	62.9	<0.001	1.35	0.086	1.57(1.20,2.04)	62.6	<0.001	0.91	0.365
Death	1.32(0.97,1.82)	53.3	0.029	0.42	0.929	1.33(0.85,2.07)	59.2	0.016	0.25	0.940
Cured outcomes	0.64(0.44,0.94)	75.7	0.001	-1.69	0.062	0.55(0.35,0.87)	66.5	0.018	-0.98	0.263
Treatment completed outcomes	0.63（0.46,0.86）	0	0.660	0.98	0.221	0.66(0.46,0.93)	0	0.559	1.36	0.192
Treatment failed outcomes	1.28(1.03,1.58)	22.7	0.256	1.05	0.263	1.37(1.08,1.75)	19.7	0.284	0.94	0.275

No competing interests reported.

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Diabetes mellitus affects the treatment outcomes of drug-resistant tuberculosis: A systematic review and meta-analysis

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