Application of a Stochastic Modeling to Assess the Evolution of Tuberculous and Non-Tuberculous Mycobacterial Infection in Patients Treated with Tumor Necrosis Factor Inhibitors
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{"title"=>"Application of a Stochastic Modeling to Assess the Evolution of Tuberculous and Non-Tuberculous Mycobacterial Infection in Patients Treated with Tumor Necrosis Factor Inhibitors", "type"=>"journal", "authors"=>[{"first_name"=>"Elena", "last_name"=>"Agliari", "scopus_author_id"=>"8706062300"}, {"first_name"=>"Lorenzo", "last_name"=>"Asti", "scopus_author_id"=>"55243802800"}, {"first_name"=>"Adriano", "last_name"=>"Barra", "scopus_author_id"=>"14071060500"}, {"first_name"=>"Rossana", "last_name"=>"Scrivo", "scopus_author_id"=>"6508085749"}, {"first_name"=>"Guido", "last_name"=>"Valesini", "scopus_author_id"=>"7005133584"}, {"first_name"=>"Robert S.", "last_name"=>"Wallis", "scopus_author_id"=>"7102604862"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84873839636", "issn"=>"19326203", "scopus"=>"2-s2.0-84873839636", "pmid"=>"23383039", "pui"=>"368226764", "isbn"=>"1932-6203", "doi"=>"10.1371/journal.pone.0055017"}, "id"=>"dd5cd520-2c40-3167-ad24-9ae5e563ff9d", "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.", "link"=>"http://www.mendeley.com/research/application-stochastic-modeling-assess-evolution-tuberculous-nontuberculous-mycobacterial-infection-1", "reader_count"=>12, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Researcher"=>3, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Researcher"=>3, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>2, "Agricultural and Biological Sciences"=>3, "Medicine and Dentistry"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>2}, "Unspecified"=>{"Unspecified"=>3}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499681/Figure_1.tif"], "description"=>"<p>States are represented as circles and numbered from to according to the scheme outlined in the Materials and Methods section. The arrows represent the transition probabilities connecting two different states, while and represent the initial conditions on the states .</p>", "links"=>[], "tags"=>["markov"], "article_id"=>170191, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Symbolic_representation_of_the_Markov_chain_under_investigation_/170191", "title"=>"Symbolic representation of the Markov chain under investigation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:21:25"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499720/Figure_2.tif"], "description"=>"<p>From the state there is a potential flux of probability at rate toward the state , hence we expect that, after a proper amount of time, a fraction of the probability will be drained from to . The same holds for the situation linking to . After an infinite time the probability of having the patient in the state is one, while it is zero for the states .</p>", "links"=>[], "tags"=>["markov"], "article_id"=>170237, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Toy_Markov_chain_/170237", "title"=>"Toy Markov chain.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:21:44"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499767/Figure_3.tif"], "description"=>"<p>Cumulative number of patients undergoing active TB-infection. Experimental data from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055017#pone.0055017-Wallis3\" target=\"_blank\">[9]</a> ( for infliximab-treated patients and for etanercept-treated patients) are compared with the approximated analytical solution (see Eq. 15 and Eq. 16, respectively, solid curves) and with data from numerical simulation (dashed curves). The parameters used to draw the analytical curves correspond to the best-fit coefficients and are reported in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055017#pone-0055017-t001\" target=\"_blank\">Table 1</a>. Notice that here we consider the extensive number of patients affected by TB over a population of treated patients, according to experimental results.</p>", "links"=>[], "tags"=>["analytical", "numerical", "tb-infection"], "article_id"=>170280, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Comparison_between_experimental_analytical_and_numerical_results_for_the_TB_infection_case_/170280", "title"=>"Comparison between experimental, analytical and numerical results for the TB-infection case.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:21:57"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499828/Figure_4.tif"], "description"=>"<p>Absolute difference between experimental data and theoretical data reported in Fig. 3; the same legend holds.</p>", "links"=>[], "tags"=>["analytical", "numerical", "tb-infection"], "article_id"=>170343, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Deviations_between_experimental_analytical_and_numerical_results_for_the_TB_infection_case_/170343", "title"=>"Deviations between experimental, analytical and numerical results for the TB-infection case.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:22:17"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499877/Figure_5.tif"], "description"=>"<p>The probability of being in state (TB reactivation) and of being in state (Post TB) are calculated from Eq. 7, using the parameters of Table . In the main plot we compare the ratio obtained from infliximab () and etanercept () parameters. In the inset, we depict each single probability, namely for infliximab (dark ) and for etanercept (dark ), for infliximab (bright ) and for etanercept (bright ); notice that the two sets of data for are partially overlapped. Lines are guide for the eye.</p>", "links"=>[], "tags"=>["tb-infection"], "article_id"=>170400, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Probabilities_and_versus_time_for_the_TB_infection_case_/170400", "title"=>"Probabilities and versus time for the TB-infection case.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:22:35"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499933/Figure_6.tif"], "description"=>"<p>Cumulative number of patients undergoing active NTM-infection. Experimental data from <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055017#pone.0055017-Winthrop1\" target=\"_blank\">[23]</a> ( for infliximab-treated patients and for etanercept-treated patients) are compared with the approximated analytical solution (see Eq. , solid curves) and with data from numerical simulation (dashed curves). The parameters used to draw the analytical curves correspond to the best-fit coefficient and are reported in Table . Notice that here we consider the extensive number of patients affected by NTM over the whole population of treated patients, according to experimental results.</p>", "links"=>[], "tags"=>["analytical", "numerical", "ntm-infection"], "article_id"=>170447, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Comparison_between_experimental_analytical_and_numerical_results_for_the_NTM_infection_case_/170447", "title"=>"Comparison between experimental, analytical and numerical results for the NTM-infection case.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:22:51"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/499986/Figure_7.tif"], "description"=>"<p>Absolute difference between experimental data and theoretical data reported in Fig. 5; the same legend holds.</p>", "links"=>[], "tags"=>["analytical", "numerical", "ntm-infection"], "article_id"=>170505, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_Deviations_between_experimental_analytical_and_numerical_results_for_the_NTM_infection_case_/170505", "title"=>"Deviations between experimental, analytical and numerical results for the NTM-infection case.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-19 16:23:07"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/500034/Table_2.xls"], "description"=>"<p>Best fit parameters obtained through the maximum likelihood method (see Eq. 19). Here we used , consistently with clinical data. Notice that here parameters only count through the combination , and, again, was thought as drug-independent. Moreover, in this case available data are extensive, so that the explicit number of overall treated patients has been introduced. The average relative error on these parameters is .</p>", "links"=>[], "tags"=>["best-fit"], "article_id"=>170550, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_NTM_infection_case_Best_fit_coefficients_/170550", "title"=>"NTM-infection case: Best-fit coefficients.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-19 16:23:23"}
  • {"files"=>["https://s3-eu-west-1.amazonaws.com/pstorage-plos-3567654/500060/Table_1.xls"], "description"=>"<p>Best fit parameters obtained through the maximum likelihood method (see Eqs. 15, 16, respectively). Here we used , consistently with clinical data. The fit was accomplished with the constraint that the parameters and are the same for both therapies, as they are drug-independent. The average relative error on these parameters is .</p>", "links"=>[], "tags"=>["best-fit"], "article_id"=>170582, "categories"=>["Physics", "Mathematics", "Ecology", "Infectious Diseases", "Immunology"], "users"=>["Elena Agliari", "Lorenzo Asti", "Adriano Barra", "Rossana Scrivo", "Guido Valesini", "Robert S. Wallis"], "doi"=>["http://dx.doi.org/10.1371/journal.pone.0055017.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"http://figshare.com/articles/_TB_infection_case_Best_fit_coefficients_/170582", "title"=>"TB-infection case: Best-fit coefficients.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-19 16:23:33"}

PMC Usage Stats | Further Information

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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences/Mycology", "average_usage"=>[318, 546, 681, 824, 962, 1073, 1181, 1310, 1465, 1570, 1678, 1771, 1864]}, {"subject_area"=>"/Medicine and health sciences/Infectious diseases", "average_usage"=>[297, 523, 655, 765, 866, 971, 1070, 1159, 1256, 1337, 1424, 1496, 1568]}, {"subject_area"=>"/Medicine and health sciences/Tropical diseases", "average_usage"=>[327, 579, 720, 841, 955, 1064, 1151, 1250, 1336, 1437, 1514, 1586, 1677]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[254, 431, 547, 651, 748, 842, 932, 1017, 1098, 1178, 1259, 1336, 1404]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[259, 431, 541, 639, 727, 816, 898, 980, 1061, 1136, 1214, 1294, 1356]}]}
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