Use of spatial information to predict multidrug resistance in tuberculosis patients, Peru

Emerging Infectious Diseases

Volumn 18, Issue 5, 2012, Pages 811-813

  Lin, Hsien Ho ^a,b,c   Shin, Sonya S ^a,d   Contreras, Carmen ^e   Asencios, Luis ^f   Paciorek, Christopher J ^g,h   Cohen, Ted ^a,g  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b Mennonite Christian Hospital   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^d PARTNERS IN HEALTH   (United States)

^e SOCIOS EN SALUD   (Peru)

^f INSTITUTO NACIONAL DE SALUD   (Peru)

^g HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^h UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE; AREA UNDER THE CURVE; ARTICLE; DIAGNOSTIC TEST ACCURACY STUDY; DRUG SENSITIVITY; GENDER; GEOGRAPHIC DISTRIBUTION; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; INFORMATION PROCESSING; MAJOR CLINICAL STUDY; MULTIDRUG RESISTANT TUBERCULOSIS; PERU; PREDICTION; RECEIVER OPERATING CHARACTERISTIC; RISK FACTOR; SPUTUM SMEAR; STATISTICAL MODEL;

ANTITUBERCULAR AGENTS; DEMOGRAPHY; DRUG RESISTANCE, MULTIPLE, BACTERIAL; HUMANS; LOGISTIC MODELS; PERU; PROGNOSIS; RISK FACTORS; ROC CURVE; TUBERCULOSIS, MULTIDRUG-RESISTANT;

EID: 84859830830     PISSN: 10806040     EISSN: 10806059     Source Type: Journal    
DOI: 10.3201/eid1805.111467     Document Type: Article

References (11)

1. Boehme CC, Nicol MP, Nabeta P, Michael JS, Gotuzzo E, Tahirli R, et al. Feasibility, diagnostic accuracy, and effectiveness of de use of the Xpert MTB/RIF test for diagnosis of tuberculosis and multidrug resistance: a multicentre implementation study. Lancet. 2011;377:1495-505. http://dx.doi.org/10.1016/S01406736(11)60438-8
2. Andrews JR, Shah NS, Weissman D, Moll AP, Friedland G, Gandhi NR. Predictors of multidrugand extensively drug-resistant tuberculosis in a high HIV prevalence community. PLoS ONE. 2010;5:e15735. http://dx.doi.org/10.1371/journal.pone.0015735
3. Faustini A, Hall AJ, Perucci CA. Risk factors for multidrug resistant tuberculosis in Europe: a systematic review. Thorax. 2006;61:158-63. http://dx.doi.org/10.1136/thx.2005.045963
4. Gardy JL, Johnston JC, Ho Sui SJ, Cook VJ, Shah L, Brodkin E, et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med. 2011;364:730-9. http://dx.doi. org/10.1056/NEJMoa1003176
5. Munch Z, Van Lill SW, Booysen CN, Zietsman HL, Enarson DA, Beyers N. Tuberculosis transmission patterns in a high-incidence area: a spatial analysis. Int J Tuberc Lung Dis. 2003;7:271-7.
6. National Health Strategy on Prevention and Control of Tuberculosis. Technical health standards for the control of tuberculosis [in Spanish]. Lima (Peru): Ministry of Health; 2006.
7. Lin H, Shin S, Blaya JA, Zhang Z, Cegielski P, Contreras C, et al. Assessing spatiotemporal patterns of multidrug-resistant and drugsensitive tuberculosis in a South American setting. Epidemiol Infect. 2010;1-10.
8. Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. Hoboken (NJ): Wiley-Interscience; 2004.
9. Wood SN. Thin plate regression splines. J R Stat Soc Series B Stat Methodol. 2003;65:95-114. http://dx.doi.org/10.1111/1467-9868.00374
10. Wood SN. Generalized additive models: an introduction with R. Boca Raton (FL): Chapman & Hall/CRC; 2006.
11. Geisser S, Eddy WF. A predictive approach to model selection. J Am Stat Assoc. 1979;74:153-60. http://dx.doi.org/10.2307/2286745