Literature DB >> 15525559

Statistical limitations to the Cornell model of latent tuberculosis infection for the study of relapse rates.

Anne J Lenaerts1, Phillip L Chapman, Ian M Orme.   

Abstract

The Cornell model has been extensively used as a mouse model for studying the latent stage of Mycobacterium tuberculosis infection. In this model mice are infected and then given a course of chemotherapy prior to reactivation of infection. We discuss here the importance of using adequate mouse numbers in a Cornell model for the study of relapse rates in order to obtain sufficient statistical power to confirm a hypothesis. Experiments with small sample sizes are useful for 'screening' experiments, but will have very little value in 'confirming' the objective. When the objective of the experiment is confirmation of an effect through establishment of statistical significance, power calculations are critical in order to assure that the sample size will be sufficient to meet that objective.

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Year:  2004        PMID: 15525559     DOI: 10.1016/j.tube.2004.03.002

Source DB:  PubMed          Journal:  Tuberculosis (Edinb)        ISSN: 1472-9792            Impact factor:   3.131


  14 in total

1.  In vivo adaptation of the Wayne model of latent tuberculosis.

Authors:  Lisa Woolhiser; Marcela Henao Tamayo; Baolin Wang; Veronica Gruppo; John T Belisle; Anne J Lenaerts; Randall J Basaraba; Ian M Orme
Journal:  Infect Immun       Date:  2007-02-05       Impact factor: 3.441

2.  Testing of experimental compounds in a relapse model of tuberculosis using granulocyte-macrophage colony-stimulating factor gene-disrupted mice.

Authors:  Lisa K Woolhiser; Donald R Hoff; Karen S Marietta; Ian M Orme; Anne J Lenaerts
Journal:  Antimicrob Agents Chemother       Date:  2008-10-13       Impact factor: 5.191

Review 3.  Animal Models for Tuberculosis in Translational and Precision Medicine.

Authors:  Lingjun Zhan; Jun Tang; Mengmeng Sun; Chuan Qin
Journal:  Front Microbiol       Date:  2017-05-04       Impact factor: 5.640

4.  Unique model of dormant infection for tuberculosis vaccine development.

Authors:  Suely S Kashino; Pamela Ovendale; Angelo Izzo; Antonio Campos-Neto
Journal:  Clin Vaccine Immunol       Date:  2006-09

5.  Comparative studies evaluating mouse models used for efficacy testing of experimental drugs against Mycobacterium tuberculosis.

Authors:  Mary A De Groote; Janet C Gilliland; Colby L Wells; Elizabeth J Brooks; Lisa K Woolhiser; Veronica Gruppo; Charles A Peloquin; Ian M Orme; Anne J Lenaerts
Journal:  Antimicrob Agents Chemother       Date:  2010-12-06       Impact factor: 5.191

6.  Evaluation of standard chemotherapy in the guinea pig model of tuberculosis.

Authors:  Diane J Ordway; Crystal A Shanley; Megan L Caraway; Eileen A Orme; Daniel S Bucy; Laurel Hascall-Dove; Marcela Henao-Tamayo; Marisa R Harton; Shaobin Shang; David Ackart; Susan L Kraft; Anne J Lenaerts; Randall J Basaraba; Ian M Orme
Journal:  Antimicrob Agents Chemother       Date:  2010-02-16       Impact factor: 5.191

7.  Characterization of a novel necrotic granuloma model of latent tuberculosis infection and reactivation in mice.

Authors:  Noton K Dutta; Peter B Illei; Sanjay K Jain; Petros C Karakousis
Journal:  Am J Pathol       Date:  2014-05-09       Impact factor: 4.307

8.  Short-course therapy with daily rifapentine in a murine model of latent tuberculosis infection.

Authors:  Tianyu Zhang; Ming Zhang; Ian M Rosenthal; Jacques H Grosset; Eric L Nuermberger
Journal:  Am J Respir Crit Care Med       Date:  2009-09-03       Impact factor: 21.405

Review 9.  Current and novel approaches to vaccine development against tuberculosis.

Authors:  Mark J Cayabyab; Lilia Macovei; Antonio Campos-Neto
Journal:  Front Cell Infect Microbiol       Date:  2012-12-06       Impact factor: 5.293

10.  Genetic models of latent tuberculosis in mice reveal differential influence of adaptive immunity.

Authors:  Hongwei Su; Kan Lin; Divya Tiwari; Claire Healy; Carolina Trujillo; Yao Liu; Thomas R Ioerger; Dirk Schnappinger; Sabine Ehrt
Journal:  J Exp Med       Date:  2021-07-16       Impact factor: 14.307

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