Literature DB >> 18028573

Evaluation of data quality in a laboratory-based surveillance of M. tuberculosis drug resistance and impact on the prevalence of resistance: France, 2004.

P M Khuê1, A Mallet, N Veziris, V Jarlier, J Robert.   

Abstract

In France, surveillance of anti-tuberculosis drug resistance is performed by the Azay-Mycobacteria network, representing 30% of all culture-positive cases. We sought to validate administrative and clinical data gathered by the network in 2004 and to produce corrected resistance rates accounting for the observed misclassification. We reviewed a 10% sample of patients' records diagnosed in 2004 and measured the agreement between controlled data and data collected by the network by using the kappa (kappa) statistic. A re-sampling bootstrap-based method was used to investigate the impact of bias found on resistance rates. Most of data collected by the network, such as demographic data, and country of birth had an excellent agreement (kappa>0.8) with controlled data. The concordance was good (kappa>0.6) for HIV status and tuberculosis site. The only variable slightly discordant with controlled data was prior history of treatment (kappa=0.52). However, after correcting crude resistance rates for the observed misclassification, all estimated rates were within confidence intervals based on reported rates. This validation study is in favour of a good quality of data produced by the network, even though corrected rates are slightly different from observed rates. Therefore, data collected through the network may be used for policy making and tuberculosis programme evaluation. However, improvement in data collection regarding prior history of treatment should be considered.

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Year:  2007        PMID: 18028573      PMCID: PMC2870927          DOI: 10.1017/S0950268807009867

Source DB:  PubMed          Journal:  Epidemiol Infect        ISSN: 0950-2688            Impact factor:   2.451


  8 in total

1.  Training, quality assurance, and assessment of medical record abstraction in a multisite study.

Authors:  Lisa M Reisch; Jessica Scura Fosse; Kevin Beverly; Onchee Yu; William E Barlow; Emily L Harris; Sharon Rolnick; Mary B Barton; Ann M Geiger; Lisa J Herrinton; Sarah M Greene; Suzanne W Fletcher; Joann G Elmore
Journal:  Am J Epidemiol       Date:  2003-03-15       Impact factor: 4.897

2.  European recommendations for antimicrobial resistance surveillance.

Authors:  G Cornaglia; W Hryniewicz; V Jarlier; G Kahlmeter; H Mittermayer; L Stratchounski; F Baquero
Journal:  Clin Microbiol Infect       Date:  2004-04       Impact factor: 8.067

3.  An evaluation of data quality in a network for surveillance of Mycobacterium tuberculosis resistance to antituberculosis drugs in Ile-de-France region-2001-2002.

Authors:  E Guerrin-Tran; J-M Thiolet; C Rousseau; S Henry; C Poirier; D Che; J-M Vinas; V Jarlier; J Robert
Journal:  Eur J Epidemiol       Date:  2006-11-15       Impact factor: 8.082

4.  Epidemiology of antituberculosis drug resistance (the Global Project on Anti-tuberculosis Drug Resistance Surveillance): an updated analysis.

Authors:  Mohamed Abdel Aziz; Abigail Wright; Adalbert Laszlo; Aimé De Muynck; Françoise Portaels; Armand Van Deun; Charles Wells; Paul Nunn; Leopold Blanc; Mario Raviglione
Journal:  Lancet       Date:  2006-12-16       Impact factor: 79.321

5.  Surveillance of Mycobacterium tuberculosis drug resistance in France, 1995-1997. AZAY Mycobacteria Study Group.

Authors:  J Robert; D Trystram; C Truffot-Pernot; B Carbonnelle; J Grosset
Journal:  Int J Tuberc Lung Dis       Date:  2000-07       Impact factor: 2.373

6.  The accuracy and completeness of data collected by prospective and retrospective methods.

Authors:  J Tobias Nagurney; David F M Brown; Swati Sane; Justin B Weiner; Andrew C Wang; Yuchiao Chang
Journal:  Acad Emerg Med       Date:  2005-09       Impact factor: 3.451

7.  The measurement of observer agreement for categorical data.

Authors:  J R Landis; G G Koch
Journal:  Biometrics       Date:  1977-03       Impact factor: 2.571

8.  Using probabilistic corrections to account for abstractor agreement in medical record reviews.

Authors:  Timothy L Lash; Matthew P Fox; Soe Soe Thwin; Ann M Geiger; Diana S M Buist; Feifei Wei; Terry S Field; Marianne Ulcickas Yood; Floyd J Frost; Virginia P Quinn; Marianne N Prout; Rebecca A Silliman
Journal:  Am J Epidemiol       Date:  2007-04-03       Impact factor: 4.897

  8 in total
  1 in total

Review 1.  Quality and Utility of Information Captured by Surveillance Systems Relevant to Antimicrobial Resistance (AMR): A Systematic Review.

Authors:  Mustafa Al-Haboubi; Rebecca E Glover; Elizabeth Eastmure; Mark Petticrew; Nick Black; Nicholas Mays
Journal:  Antibiotics (Basel)       Date:  2021-04-13
  1 in total

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