Pirfenidone is a recently approved antifibrotic drug for the treatment of idiopathic pulmonary fibrosis (IPF). Because tuberculosis (TB) is characterized by granulomatous inflammation in conjunction with parenchymal destruction and replacement fibrosis, we sought to determine whether the addition of pirfenidone as an adjunctive, host-directed therapy provides a beneficial effect during antimicrobial treatment of TB. We hypothesized that pirfenidone’s antiinflammatory and antifibrotic properties would reduce inflammatory lung damage and increase antimicrobial drug penetration in granulomas to accelerate treatment response. The effectiveness of adjunctive pirfenidone during TB drug therapy was evaluated using a murine model of chronic TB. Mice treated with standard therapy 2HRZ/4HR (H, isoniazid; R, rifampin; and Z, pyrazinamide) were compared with 2 alternative regimens containing pirfenidone (Pf) (2HRZPf/4HRPf and 2HRZPf/4HR). Contrary to our hypothesis, adjunctive pirfenidone use leads to reduced bacterial clearance and increased relapse rates. This treatment failure is closely associated with the emergence of isoniazid monoresistant bacilli, increased cavitation, and significant lung pathology. While antifibrotic agents may eventually be used as part of adjunctive host-directed therapy of TB, this study clearly demonstrates that caution must be exercised. Moreover, as pirfenidone becomes more widely used in clinical practice, increased patient monitoring would be required in endemic TB settings.
Bintou A. Ahidjo, Mariama C. Maiga, Elizabeth A. Ihms, Mamoudou Maiga, Alvaro A. Ordonez, Laurene S. Cheung, Sarah Beck, Bruno B. Andrade, Sanjay Jain, William R. Bishai
Usage data is cumulative from February 2023 through February 2024.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.