Outcome of patients with and poor prognostic factors for Mycobacterium kansasii-pulmonary disease

Liu, Chia-Jung; Huang, Hsien‐Cheng; Cheng, Meng-Hsuan; Lu, Po‐Liang; Wang, Jann‐Yuan; Chong, Inn‐Wen

doi:10.1016/j.rmed.2019.03.015

Cited by 11 publications

(8 citation statements)

References 26 publications

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“…The overall rate of radiographic progressive disease was 43% (95% CI 31%–55%, I 2 = 95.1%). In single studies, increasing age (adjusted OR = 1.120; 95% CI 1.038–1.209) 49 and being elderly (adjusted OR = 2.980; 95% CI 1.041–8.534) 48 was significantly associated with increased radiographic progression after adjusting for covariates.…”

Section: Resultsmentioning

confidence: 97%

The factors associated with mortality and progressive disease of nontuberculous mycobacterial lung disease: a systematic review and meta-analysis

Hwang

Lee

Heo

et al. 2023

Sci Rep

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This systematic review and meta-analysis aimed to comprehensively evaluate the factors associated with mortality and progressive disease in NTM-LD patients. We conducted a literature search to identify the eligible studies, dated between January 1, 2007, and April 12, 2021. Forty-one studies with total 10,452 patients were included. The overall all-cause mortality rate was 20% (95% CI 17–24%). The overall rates of clinical and radiographic progressive disease were 46% (95% CI 39–53%) and 43% (95% CI 31–55%), respectively. Older age, male sex, history of TB, diabetes, chronic heart disease, malignancy, systemic immunosuppression, chronic liver disease, presence of cavity, consolidative radiologic features, acid-fast bacillus (AFB) smear positivity, hypoalbuminemia, anemia, increasing platelet count, high CRP, and high ESR were significantly associated with increased all-cause mortality, whereas increasing body mass index (BMI), hemoptysis, and treatment with rifamycin regimen (in M. xenopi) were significantly associated with decreased all-cause mortality in multivariable analysis. History of TB, Aspergillus co-infection, cough, increased sputum, weight loss, presence of cavity, and AFB smear positivity were significantly associated with increased clinical progression with treatment, while older age and low BMI were significantly associated with decreased clinical progression in multivariable analysis. Older age, interstitial lung disease, presence of cavity, consolidative radiologic feature, anemia, high CRP, and leukocytosis were significantly associated with increased radiographic progression after adjusting for covariates. Older age, history of tuberculosis, presence of cavity, consolidative radiologic features, AFB smear positivity, anemia, and high C-reactive protein were common significant factors associated with the all-cause mortality and clinical or radiographic progressive disease of NTM-LD. These factors are thought to directly affect NTM-LD related mortality. The future prediction models for the prognosis of NTM-LD should be established considering these factors.

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Section: Resultsmentioning

confidence: 97%

The factors associated with mortality and progressive disease of nontuberculous mycobacterial lung disease: a systematic review and meta-analysis

Hwang

Lee

Heo

et al. 2023

Sci Rep

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“…MK was highly associated with previous PTB, COPD, and other structural lung diseases ( Maliwan and Zvetina, 2005 ). Notably, MK was reported as a virulent NTM species, and it might cause significant short-term mortality ( Huang et al, 2018 ; Liu et al, 2019 ). Therefore, it is plausible that MK-LD may have the highest mortality rates for all-cause mortality and chronic airway disease mortality.…”

Section: Discussionmentioning

confidence: 99%

“…A study in Canada reported various hazard ratios (HR) of all-cause mortality rates among different NTM species to the general population but provided no details on causes of death ( Marras et al, 2017 ). Some studies have reported the specific mortality causes of certain NTM-LDs, but those studies lacked comparisons of the relationship between mortality and NTM species ( Hwang et al, 2017 ; Liu et al, 2019 ). A population-based study in Korea reported the distribution of mortality causes in NTM-LD mortality in a 15-year follow-up study, but they focused on only Mycobacterium avium complex (MAC) and M. abscessus complex (MABC) ( Lee et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

The Impact of Nontuberculous Mycobacteria Species on Mortality in Patients With Nontuberculous Mycobacterial Lung Disease

et al. 2022

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Patients with nontuberculous mycobacterial lung disease (NTM-LD) have increased mortality. The impact of NTM species on the risk of mortality remains unclear, especially that of death by non-cancer causes. We conducted a retrospective cohort study from 2006 to 2018 in a tertiary-care hospital in Taiwan. We enrolled patients who fulfilled the microbiological diagnostic criteria of NTM-LD. The mortality causes within 8 years after diagnosis were identified, and the Cox proportional hazard regression was performed for risk factors of mortality. A total of 1,652 subjects with NTM-LD were included. Among them, 723 (43.8%) were infected by Mycobacterium avium complex (MAC), 408 (24.7%) by M. abscessus complex (MABC), 120 (7.3%) by Mycobacterium kansasii (MK), 304 (18.4%) by other rapid-growing mycobacteria (RGM), and 97 (5.9%) by other slow-growing mycobacteria (SGM) groups. The 8-year all-cause mortality was 45.2% for all and the highest in the MK-LD group (59.2%), followed by the MABC-LD and MAC-LD groups. The adjusted hazard ratios were 2.20 (95% confidence interval: 1.40–3.46) in the MK-LD, 1.85 (1.54–2.22) in the MABC-LD, and 1.65 (1.12–2.41) in the MAC-LD groups for all-cause mortality, compared with the SGM group. Kaplan–Meier survival curves showed that all-cause mortality, non-cancer mortality, and mortality due to chronic airway diseases were significantly correlated with NTM species (log-rank p = 0.0031, < 0.001, and 0.001, respectively). High 8-year mortality rates were found in patients with NTM-LDs according to different NTM species. Notably, the difference was significant in non-cancer mortality causes, especially in chronic airway diseases.

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“…The CXRs with anteroposterior views or visible medical devices were excluded. Two experienced pulmonologists, who were blinded to the clinical information, evaluated the characteristics of each CXR respectively, including the pattern (consolidation, cavitation, pleural effusion or others) and extent (multifocal or focal) according to standard protocol [ 14 ]. In cases of discrepancy, a final decision was achieved through consensus.…”

Section: Methodsmentioning

confidence: 99%

A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional study

et al. 2023

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Background Timely differentiating between pulmonary tuberculosis (TB) and nontuberculous mycobacterial lung disease (NTM-LD), which are radiographically similar, is important because infectiousness and treatment differ. This study aimed to evaluate whether artificial intelligence could distinguish between TB or NTM-LD patients by chest X-rays (CXRs) from suspects of mycobacterial lung disease. Methods A total of 1500 CXRs, including 500 each from patients with pulmonary TB, NTM-LD, and patients with clinical suspicion but negative mycobacterial culture (Imitator) from two hospitals, were retrospectively collected and evaluated in this study. We developed a deep neural network (DNN) and evaluated model performance using the area under the receiver operating characteristic curves (AUC) in both internal and external test sets. Furthermore, we conducted a reader study and tested our model under three scenarios of different mycobacteria prevalence. Results Among the internal and external test sets, the AUCs of our DNN model were 0.83 ± 0.005 and 0.76 ± 0.006 for pulmonary TB, 0.86 ± 0.006 and 0.64 ± 0.017 for NTM-LD, and 0.77 ± 0.007 and 0.74 ± 0.005 for Imitator. The DNN model showed higher performance on the internal test set in classification accuracy (66.5 ± 2.5%) than senior (50.8 ± 3.0%, p < 0.001) and junior pulmonologists (47.5 ± 2.8%, p < 0.001). Among different prevalence scenarios, the DNN model has stable performance in terms of AUC to detect TB and mycobacterial lung disease. Conclusion DNN model had satisfactory performance and a higher accuracy than pulmonologists on classifying patients with presumptive mycobacterial lung diseases. DNN model could be a complementary first-line screening tool.

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Outcome of patients with and poor prognostic factors for Mycobacterium kansasii-pulmonary disease

Cited by 11 publications

References 26 publications

The factors associated with mortality and progressive disease of nontuberculous mycobacterial lung disease: a systematic review and meta-analysis

The factors associated with mortality and progressive disease of nontuberculous mycobacterial lung disease: a systematic review and meta-analysis

The Impact of Nontuberculous Mycobacteria Species on Mortality in Patients With Nontuberculous Mycobacterial Lung Disease

A deep learning model using chest X-ray for identifying TB and NTM-LD patients: a cross-sectional study

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