The influence of comorbidities on treatment outcomes in patients with tuberculosis

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Abstract

Aim. To study the association of comorbidities and treatment outcomes in tuberculosis (TB) patients.

Materials and methods. A retrospective study includes all TB patients aged 18 years and older registered for treatment in Moscow in period 2021 the end of the 3rd quarter of 2022 using data of regional epidemiological TB monitoring system, a total of 3039 patients. The frequency and spectrum of comorbidities, its impact on the risk of adverse treatment outcome (ATO) and mortality using univariate and regression analysis were assessed.

Results. Comorbidities were identified in 1528 (50.3%) patients (95% confidence interval – CI 48.5–52.1); HIV infection (18.0%), chronic nonspecific lung disease (9.6%) and cardiovascular disease (8.2%) were predominant. The presence of comorbid pathology increased the odds of uneffective treatment (odds ratio – OR 2.56, 95% CI 2.22–3.03) and death (OR 2.45, 95% СI 1.67–3.59). Independent risk factors for ATO were HIV infection (OR 4.10, 95% CI 3.36–5.10), substance use (OR 2.57, 95% CI 1.70–3.66), chronic nonspecific lung disease (OR 1.39, 95% CI 1.04–1.88), diabetes mellitus (OR 1.69, 95% CI 1.15–2.48), liver pathology (OR 2.10, 95% CI 1.46–3.03), mental illness (OR 2.01, 95% CI 1.32–3.06). The death rate was 13.4%; the most significant predictors of mortality were HIV infection (OR 3.89, 95% CI 2.42–6.22) and liver disease (OR 1.90, 95% CI 1.27–2.82). A comorbidome model was constructed to assess the importance of different comorbidities for patient prognosis.

Conclusion. The presence of comorbidity (predominantly HIV infection and liver disease) is a significant risk factor for ATO and mortality in TB patients, which should be taken into account when organizing and providing TB care to comorbid patients.

About the authors

Diana A. Ivanova

Moscow Research and Clinical Center for Tuberculosis Control; Russian Medical Academy of Continuous Professional Education

Author for correspondence.
Email: d-ivanova@list.ru
ORCID iD: 0000-0001-5686-536X

д-р мед. наук, ученый секретарь, проф. каф. фтизиатрии

Russian Federation, Moscow; Moscow

Evgeny M. Belilovskiy

Moscow Research and Clinical Center for Tuberculosis Control

Email: d-ivanova@list.ru
ORCID iD: 0000-0002-3456-3069

канд. биол. наук, зав. отд. эпидемиологического мониторинга туберкулеза

Russian Federation, Moscow

Elena M. Bogorodskaya

Moscow Research and Clinical Center for Tuberculosis Control; Russian Medical Academy of Continuous Professional Education

Email: d-ivanova@list.ru
ORCID iD: 0000-0003-4552-5022

д-р мед. наук, проф., дир., зав. каф. фтизиатрии

Russian Federation, Moscow; Moscow

Mikhail N. Reshetnikov

Moscow Research and Clinical Center for Tuberculosis Control; Russian Medical Academy of Continuous Professional Education

Email: d-ivanova@list.ru
ORCID iD: 0000-0002-4418-4601

канд. мед. наук, врач-хирург, вед. науч. сотр., доц. каф. фтизиатрии

Russian Federation, Moscow; Moscow

Dmitriy V. Plotkin

Moscow Research and Clinical Center for Tuberculosis Control; Pirogov Russian National Research Medical University

Email: d-ivanova@list.ru
ORCID iD: 0000-0002-6659-7888

д-р мед. наук, доц., врач-хирург, вед. науч. сотр., доц. каф. общей хирургии

Russian Federation, Moscow; Moscow

Viktoria B. Avdentova

Moscow Research and Clinical Center for Tuberculosis Control; Russian Medical Academy of Continuous Professional Education

Email: d-ivanova@list.ru
ORCID iD: 0009-0009-9971-5885

науч. сотр. отд. эпидемиологического мониторинга туберкулеза, ассистент каф. фтизиатрии

Russian Federation, Moscow; Moscow

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Supplementary files

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2. Fig. 1. The detection frequency of concomitant pathology depending on age, %.

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3. Fig. 2. The spectrum of concomitant pathology in the general sample, % (n=3039).

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4. Fig. 3. Treatment outcomes of TB patients depending on the presence of comorbidities, %: a – in the whole sample (n=3039); b – in HIV-uninfected patients (n=2491); *using χ2 test.

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5. Fig. 4. Diseases that caused the death of TB patients who died from other causes, % (n=268).

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6. Fig. 5. Survival rate of TB patients depending on the presence of any of the registered concomitant diseases (Kaplan–Mayer curves).

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7. Fig. 6. A comorbidoma model for assessing the prognostic role of concomitant diseases in TB patients.

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