Incidence of and factors for non-compliance to antituberculous treatment
Keywords:
Mycobacterium tuberculosis, tuberculosis/therapy, drug therapy, directly observed therapy, treatment refusal, incidence
Abstract
Introduction. Tuberculosis is a public health problem. Non-compliance with treatment regimes increases morbidity-mortality, perpetuates transmission and generates bacterial resistance. It is necessary to know incidence and associated factors to non-compliance for performance interventions.Objective. The incidence of and associated factors associated with non-compliance to antituberculous treatment were investigated.
Materials and methods. A follow-up study was conducted in an adult cohort with tuberculosis, living in an urban area. Non-compliance was defined as treatment default of 30 days or more. Patients were interviewed at the initiation of treatment and and re-interviewed in subsequent intervals. Outcome was defined as the period of time until treatment abandonment. Noncompliance rates were calculated, as well as survival curves; the Cox regression model was used to adjust for associated variables.
Results. Of the 261 patients who were interviewed, 39 (14.9%) had abandoned treatment (rate 0.4 episodes/1,000 days-person, 95%CI 0.2-0.8). Factors associated with compliance were family support (HR=0.4, 95%CI 0.2-0.9), secondary drug effects (HR=0.2, 95%CI 0.1-0.6) and opportunity to receive treatment at the clinic where tuberculosis was diagnosed (HR=0.3, 95%CI 0.1-0.6). Risk factors for non-compliance were as follows: treatment requiring >2 months (HR=14.3, 95%CI 1.8-112.7), low socioeconomic status (HR=3.90, 95%CI 2.1-9.3), age between 21-30 years (HR=20.6, 95%CI 2.4-175.4), history of incarceration (HR=2.2, 95%CI 1.0-5.4), skipping treatments more that twice (HR=6.6, 95%CI 2.8-15.6) and co-infection with HIV/AIDS (HR=2.9, 95%CI 1.6-5.4).
Conclusion. Non-compliance rate is higher than previously reported. The data recommend the following strategies for improving compliance with antituberculosis treatment: (1) early diagnosis, (2) opportune treatment, (3) improved family support and (4) immediate intervention if a treatment is missed -especially in patients with HIV/AIDS, from low socioeconomic strata, or with record of incarceration.
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References
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27. Carvajal R, Cabrera GA, Mateus JC. Efectos de la reforma en salud en las acciones de control de tuberculosis en el Valle del Cauca, Colombia. Biomédica. 2004;24(Suppl.1):138-48.
28. Moro ML, Resi D, Lelli B, Nicoli A, Gaglioti C, Falcone F. Barriers to effective tuberculosis control: a qualitative study. Int J Tuberc Lung Dis. 2005;9:1355-60.
29. Ferrer X, Kirschbaum A, Toro J, Jadue J, Muñoz M, Espinoza A. Caracterización del paciente tuberculoso que abandona el tratamiento, Santiago de Chile. Bol Oficina Sanit Panam. 1991;111:423-31.
30. Kimerling ME, Petri L. Tracing as part of tuberculosis control in a rural Cambodian district during 1992. Tuberc Lung Dis. 1995;76:156-9.
31. North American Nursing Diagnosis Association (NANDA). Nursing diagnoses: definitions and classification 2001-2002. Barcelona: Ediciones Harcourt; 2001.
2. Ministerio de Salud. Dirección General de Promoción y Prevención. Guía de atención de la tuberculosis pulmonar y extrapulmonar. Bogotá: Ministerio de Salud; 2001. p.1-47.
3. Pablos-Méndez A, Cnirsch CA, Barr RG, Lerner BH, Frieden TR. Nonadherence in tuberculosis treatment: Predictors and consequences in New York City. Am J Med. 1997;102:164-70.
4. World Health Organization Global. TB Programme. Report of the Ad Hoc Committee on the Tuberculosis Epidemic. WHO/TB/98.245. Geneva: World Health Organization; 1998.
5. Chaparro PE, García I, Guerrero MI, León CI. Situación de la tuberculosis en Colombia, 2002. Biomédica. 2004;24(Suppl.1):102-14.
6. Cáceres FM, Flórez NS, García ME, Ortega N, Téllez LE. Características epidemiológicas de los pacientes con tuberculosis en Bucaramanga, 1990 a 1999.Médicas UIS. 2001;15:89-98.
7. Homedes N, Ugalde A. ¿Qué sabemos del cumplimiento de los tratamientos médicos en el tercer mundo? Bol Of Sanit Panam. 1994;116:491-517.
8. Jaramillo E. Pulmonary tuberculosis and healthseeking behavior: How to get a delayed diagnosis in Cali, Colombia. Trop Med Int Health. 1998; 3:138-44.
9. Pozsik C. Compliance with tuberculosis therapy. Med Clin North Am. 1993;77:1289-301.
10. Eraker SA, Kirscht JP, Becker MH. Understanding and improving patient compliance. Ann Intern Med. 1984;100:258-68.
11. Singh M. Adherence to anti-tuberculosis treatment. Indian Pediatr. 1999;36:1285-6
12. Orozco LC, Hernández R, de Usta CY, Cerra M, Camargo D. Factores de riesgo para el abandono (no adherencia) del tratamiento antituberculoso. Médicas UIS. 1998;12:169-72.
13. Dean J, Dean DA, Coloumbier D, Brebdel KA, Smith DC, Burton AH, et al . Epi Info 6.04c. A word processing, database, and statistic program for public health. Atlanta: Center for Disease Control and Prevention, World Health Organization; 1997
14. STATA Corporation Inc. STATA 8.0. College Station. Texas: STATA Corporation Inc; 2003.
15. Matthews DE, Farawell VT. Curvas de sobrevida. En: Estadística médica: aplicación e interpretación. 2 edición. Barcelona: Editorial Salvat; 1990.p.132-48.
16. Green MS, Symons MJ. A comparison of the logistic risk function and the proportional hazards model in prospective epidemiologic studies. J Chronic Dis. 1983;36:715-24
17. Greenland S. Modeling and variable selection in epidemiologic analysis. Am J Public Health. 1989;79:340-9.
18. Christensen E. Multivariate survival analysis using Cox´s regression model. Hepatology. 1987;7:136-58.
19. Grambsch PM, Therneau TM. Proportional hazard test and diagnostics based on weighted residuals. Biometrika. 1994;81:515-26.
20. Cox DR. Regression models and life-tables (with discussion) J R Stat Soc. 1972;34B:187-220.
21. Cleves MA, Gould WW, Gutiérrez RG. An Introduction to survival analysis using stata. Texas: Stata Press; 2002.
22. Cox DR, Snell EJ. A general definition of residuals (with discussion). J R Stat Soc. 1968;30B:248-75.
23. May S, Hosmer DW. A simplified method for calculating a goodness-of-fit test for the proportional hazard model. Lifetime Data Anal. 1998;4:109-20.
24. Vittinghoff E, McCulloch CE. Relaxing the ruler of ten events per variable in logistic and Cox regression. Am J Epidemiol. 2007;165:710-8.
25. Stare J, O‘Quigley J. Fit and frailties in proportional hazard regression. Biometrical J. 2004;46:157-64.
26. Arbeláez MP, Gaviria MB, Franco A, Restrepo R, Hincapié D, Blas E. Tuberculosis control and managed competition in Colombia. Int J Health Plann Manage. 2004;19(Suppl.1):S25-43.
27. Carvajal R, Cabrera GA, Mateus JC. Efectos de la reforma en salud en las acciones de control de tuberculosis en el Valle del Cauca, Colombia. Biomédica. 2004;24(Suppl.1):138-48.
28. Moro ML, Resi D, Lelli B, Nicoli A, Gaglioti C, Falcone F. Barriers to effective tuberculosis control: a qualitative study. Int J Tuberc Lung Dis. 2005;9:1355-60.
29. Ferrer X, Kirschbaum A, Toro J, Jadue J, Muñoz M, Espinoza A. Caracterización del paciente tuberculoso que abandona el tratamiento, Santiago de Chile. Bol Oficina Sanit Panam. 1991;111:423-31.
30. Kimerling ME, Petri L. Tracing as part of tuberculosis control in a rural Cambodian district during 1992. Tuberc Lung Dis. 1995;76:156-9.
31. North American Nursing Diagnosis Association (NANDA). Nursing diagnoses: definitions and classification 2001-2002. Barcelona: Ediciones Harcourt; 2001.
How to Cite
1.
Cáceres F de M, Orozco LC. Incidence of and factors for non-compliance to antituberculous treatment. biomedica [Internet]. 2007 Dec. 1 [cited 2024 May 18];27(4):498-504. Available from: https://revistabiomedica.org/index.php/biomedica/article/view/170
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Published
2007-12-01
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