Application of a stochastic modeling to assess the evolution of tuberculous and non-tuberculous mycobacterial infection in patients treated with tumor necrosis factor inhibitors.

Elena Agliari,Guido Valesini,Lorenzo Asti,Adriano Barra,Robert S Wallis,Rossana Scrivo,Pere-Joan Cardona

doi:10.1371/journal.pone.0055017

Abstract

In this manuscript we apply stochastic modeling to investigate the risk of reactivation of latent mycobacterial infections in patients undergoing treatment with tumor necrosis factor inhibitors. First, we review the perspective proposed by one of the authors in a previous work and which consists in predicting the occurrence of reactivation of latent tuberculosis infection or newly acquired tuberculosis during treatment; this is based on variational procedures on a simple set of parameters (e.g. rate of reactivation of a latent infection). Then, we develop a full analytical study of this approach through a Markov chain analysis and we find an exact solution for the temporal evolution of the number of cases of tuberculosis infection (re)activation. The analytical solution is compared with Monte Carlo simulations and with experimental data, showing overall excellent agreement. The generality of this theoretical framework allows to investigate also the case of non-tuberculous mycobacteria infections; in particular, we show that reactivation in that context plays a minor role. This may suggest that, while the screening for tuberculous is necessary prior to initiating biologics, when considering non-tuberculous mycobacteria only a watchful monitoring during the treatment is recommended. The framework outlined in this paper is quite general and could be extremely promising in further researches on drug-related adverse events.

Highlights

Over the last decades the improved understanding of the pathogenesis of chronic inflammatory diseases, together with a major advance in biotechnology, have accelerated the development of biological therapies, designed to neutralize specific targets that mediate and sustain the clinical manifestations of diseases
Much has been speculated about the structure of granuloma which should contain Mycobacteria, since murine models indicated that tumor necrosis factor (TNF) was necessary for both formation and maintenance of granulomas [11]
The TB-infection Case Having obtained the complete solution of the model and exploiting the available information on parameters, we look for proper approximations able to highlight the effective behavior of c(t) in cases of practical interest, starting with the TB scenario

Summary

Introduction

Over the last decades the improved understanding of the pathogenesis of chronic inflammatory diseases, together with a major advance in biotechnology, have accelerated the development of biological therapies, designed to neutralize specific targets that mediate and sustain the clinical manifestations of diseases These compounds, mainly monoclonal antibodies (mAb) and fusion proteins, introduced a breakthrough in the management of different conditions including inflammatory rheumatologic disorders [1]. Studies on the pathogenic mechanisms of RA have revealed that tumor necrosis factor (TNF) is a cytokine playing a critical role in the inflammatory cascade that results in the irreversible joint damage typical of the disease [3] Following these discoveries, a series of clinical trials in patients with RA showed the therapeutic benefit of TNF blockade [4]. The reactivation of latent TB infection has been associated with all TNF inhibitors, pre-initiation screening procedures have been recommended, which have successfully reduced the number of reported cases [18], current screening tools lack sensitivity and specificity [19,20]

Methods

Results

Conclusion