Clinical Impact of Rapid Drug Susceptibility Testing to Accompany Fluoroquinolone-Containing Universal Tuberculosis Regimens: A Markov Model

Mathematical models of drug-resistant tuberculosis lack bacterial heterogeneity: A systematic review

Drug-resistant tuberculosis (DR-TB) threatens progress in the control of TB. Mathematical models are increasingly being used to guide public health decisions on managing both antimicrobial resistance (AMR) and TB. It is important to consider bacterial heterogeneity in models as it can have consequences for predictions of resistance prevalence, which may affect decision-making. We conducted a systematic review of published mathematical models to determine the modelling landscape and to explore methods for including bacterial heterogeneity. Our first objective was to identify and analyse the general characteristics of mathematical models of DR-mycobacteria, including M. tuberculosis. The second objective was to analyse methods of including bacterial heterogeneity in these models. We had different definitions of heterogeneity depending on the model level. For between-host models of mycobacterium, heterogeneity was defined as any model where bacteria of the same resistance level were further differentiated. For bacterial population models, heterogeneity was defined as having multiple distinct resistant populations. The search was conducted following PRISMA guidelines in five databases, with studies included if they were mechanistic or simulation models of DR-mycobacteria. We identified 195 studies modelling DR-mycobacteria, with most being dynamic transmission models of non-treatment intervention impact in M. tuberculosis (n = 58). Studies were set in a limited number of specific countries, and 44% of models (n = 85) included only a single level of "multidrug-resistance (MDR)". Only 23 models (8 between-host) included any bacterial heterogeneity. Most of these also captured multiple antibiotic-resistant classes (n = 17), but six models included heterogeneity in bacterial populations resistant to a single antibiotic. Heterogeneity was usually represented by different fitness values for bacteria resistant to the same antibiotic (61%, n = 14). A large and growing body of mathematical models of DR-mycobacterium is being used to explore intervention impact to support policy as well as theoretical explorations of resistance dynamics. However, the majority lack bacterial heterogeneity, suggesting that important evolutionary effects may be missed.

Epidermal growth factor receptor-mutant pulmonary adenocarcinoma coexisting with tuberculosis: A case report

RATIONALE

Lung cancer and pulmonary infections can have similar clinical and radiographic manifestations. Treatment for the coexistence of epidermal growth factor receptor (EGFR)-mutant pulmonary adenocarcinoma and tuberculosis remains unclear.

PATIENT CONCERNS

We reported a case of EGFR-mutant lung adenocarcinoma (mimicking pulmonary infections) that coexisted with pulmonary tuberculosis during the course of the disease.

DIAGNOSES

The patient was initially diagnosed with pneumonia-like pulmonary adenocarcinoma with EGFR exon 19 deletions based on computed tomography scan, fiberoptic bronchoscopy, pathology, and genetic analysis, and then coexistence with active tuberculosis (TB) was confirmed via laboratory examinations and TB-DNA polymerase chain reaction.

INTERVENTIONS

Antibiotics and gefitinib were administered initially. A combination of gefitinib and anti-TB treatment was then administered when active TB was confirmed, and osimertinib was then prescribed because the disease was progressive and EGFR T790 M mutation was detected.

OUTCOMES

The patient has survived with a stable disease status to date.

LESSONS

Exploring and ruling out differential diagnoses between pulmonary malignancies and infectious diseases is vital for treatment decisions and outcomes. The combined gefitinib-anti-TB regimen was safe, though it needed modification.