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Masters Project: Logistic Regression Analysis, Comparing the Completion of Latent Tuberculosis Therapy of HIV-Coinfected Individuals and Other Chronic High Risk Groups

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Masters Degree Final Project (MAY 2016):

Logistic Regression Analysis, Comparing the Completion of Latent Tuberculosis Infection (LTBI) Therapy of HIV-Coinfected Individuals and Other Chronic High Risk Groups.

  • All statistical analyses were done using the SAS 9.4 (SAS Institute Inc, Cary, NC) version.
  • Data: 38,906 de-identified demographic and clinical data on LTBI cases reported in Florida from January 1, 2009 to January 29, 2016

Outcome variable:

  • Completed therapy

Main predictor variable:

  • HIV positive

Other predictor variables: (Other chronic high risk factors)

  • Chronic corticosteroid
  • Chronic immunosuppression
  • Chronic renal failure
  • Chronic diabetes
  • Chronic hematologic disorders
  • Other significant malignancies

 

ABSTRACT

Background

As the most common infectious disease worldwide, tuberculosis (TB) remains a significant public health issue. In areas of low prevalence, such as the United States, many cases of TB are as a result of the reactivation of latent tuberculosis infection (LTBI) acquired prior to the TB diagnosis. Combined with HIV co-infection or other high risk factors, the rate of progressing into active TB disease greatly increases among LTBI persons. Therefore improving adherence to completion of LTBI treatment is very critical especially among high risk groups in order to eliminate TB.

 

Objective

To analyze the LTBI therapy rates among HIV co-infected persons compared to others with high risk chronic factors in the state of Florida. This analysis will help identify some of the gaps in the cascade of care during LTBI treatment among high risk groups. The main hypothesis is that among LTBI patients, HIV co-infected patients will have equal completion rates of LTBI therapy as other high risk chronic groups. Understanding the gaps in the continuum of care for high risk LTBI patients would help bring about interventions that could be used in the TB prevention cascade of care approach for better delivery services for TB control program and adherence to treatment completion amongst LTBI patients.

HIV positive status was the main predictor and the other predictor variable was other chronic high risk groups which included chronic renal failure, diabetes, hematologic disorders, other specific malignancies, chronic immunosuppression treatment and chronic corticosteroid treatment.

 

Methods

A retrospective analysis was conducted on a surveillance data reported to the Florida Department of Health (FDOH) of patients referred for LTBI testing from 67 Florida counties. The data was collected over a span of seven years from January 1, 2009 to January 29, 2016 and it contained 38,906 de-identified demographic cases however, 23,279 met the study criteria for analysis. The primary hypothesis was that HIV co-infected cases and cases with other high risk chronic factors will have a high rate of completing LTBI therapy. The secondary hypothesis was that when both groups are compared (HIV versus other high risk chronic factors), an equal rate of completion of therapy should be seen. Logistic regression analysis was used to compare the completion of therapy rates among the groups and describe associations found.

 

Results

  • Analysis 1: Out of 23,279 cases, 12,632 (54.26%) completed LTBI therapy. Of these, 509 (4.03%) were HIV positive. The results supported the hypothesis that HIV co-infected persons will have a higher rate of completion of therapy (127.2%) than HIV un-infected persons (Odds Ratio (OR) =2.423, Confidence Interval (CI): 2.036-2.883).

  • Analysis 2: Out of 22,577 cases (HIV infected persons excluded), 12,123 (53.70%) completed LTBI therapy. Of these, 363 (2.99%) had other high risk chronic factors. The results supported the hypothesis that those with other high risk chronic factors will have a higher rate of completion of LITBI therapy (54.3%) compared to those not in the high risk chronic factors group (OR= 1.543, CI: 1.298 -1.8352).

  • Analysis 3: Out of 1,219 cases with HIV and other high risk chronic factors, 835 (68.50%) completed therapy. Of these, 472 (56.54%) had HIV and 363 (43.47%) had other high risk chronic factors. Our hypothesis was not supported in this analysis because we found that those with other high risk chronic factors had a 33.9% lower rate of completing LTBI therapy compared to those with HIV (OR=1.543, CI: 1.298 -1.8352).

 

Conclusion

In this retrospective study analysis, having HIV co-infection and other high risk chronic factors predicted higher rates of completion of LTBI therapy with HIV twice as much completion rates compared to those with other high risk chronic factors. This study suggests that changes need to be made to increase adherence of completion of LTBI therapy among those with other high risk chronic factors since they also have a high risk of progressing into active TB without LTBI treatment.

 

Keywords: Latent Tuberculosis; LTBI treatment; HIV; systematic review.*

 

References:

  • WHO. (n.d.). Latent Tuberculosis Infection (LTBI). Retrieved February 05, 2016, from http://www.who.int/tb/challenges/ltbi/en/
  • CDC. (2014). Fact Sheets: The Difference Between Latent TB Infection and TB Disease. Retrieved February 05, 2016, from http://www.cdc.gov/tb/publications/factsheets/general/ltbiandactivetb.htm
  • Dearborn Edwards and Charles H. Kirkpatrick "The Immunology of Mycobacterial Diseases",American Review of Respiratory Disease, Vol. 134, No. 5 (1986), pp. 1062-1071.
  • doi: 10.1164/arrd.1986.134.5.1062
  • CDC. (2015). Latent TB Infection: A Guide for Primary Health Care Providers. Retrieved from http://www.cdc.gov/tb/publications/ltbi/pdf/targetedltbi.pdf
  • Geneva: World Health Organization (WHO). (2015). Guidelines on the management of latent tuberculosis infection. WHO (The End TB Strategy), 1-38. Retrieved from http://apps.who.int/iris/bitstream/10665/136471/1/9789241548908_eng.pdf?ua=1&ua=1
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  • CDC. (2016). TBESC-II Task order 1 Sub-Study Part B: Strengthening Public Health Surveillance For Latent Tuberculosis Infection.
  • CDC. (2010). Tuberculosis Epidemiologic Studies Consortium (TBESC). Retrieved February 05, 2016, from http://www.cdc.gov/TB/topic/research/TBESC/default.htm
  • ATS/CDC. Targeted tuberculin testing and treatment of latent TB infection. MMWR 2000;49 (No. RR- 6) Retrieved February 26, 2016, from http://www.cdc.gov/mmwr/preview/mmwrhtml/rr4906a1.htm
  • WHO. (n.d.). Tuberculosis: Key Facts. Retrieved February 05, 2016, from http://www.who.int/mediacentre/factsheets/fs104/en/
  • WHO. (n.d.). Global tuberculosis report 2015. Retrieved February 05, 2016, from http://www.who.int/tb/publications/global_report/en/
  • Stop TB Partnership. (n.d.). Tuberculosis Profiles by Country. Retrieved February 05, 2016, from http://www.stoptb.org/countries/tbdata.asp
  • CDC. (2015). Tuberculosis in the United States: National Tuberculosis Surveillance System Highlights from 2014. Retrieved February 05, 2016, from http://www.cdc.gov/tb/statistics/surv/surv2014/default.htm
  • CDC. Reported Tuberculosis in the United States, 2014. Atlanta, GA: U.S. Department of Health and Human Services, CDC, October 2015.from http://www.cdc.gov/tb/statistics/reports/2014/pdfs/tb-surveillance-2014-report.pdf
  • Hirsch-Moverman Y, Colson P, Bethel J, Franks J, El-Sadr W. Can a peer-based intervention impact adherence to the treatment of latent tuberculous infection? Int J Tuberc Lung Dis.2013;17:1178–85.
  • Nyamathi A, Christiani A, Nahid P, Gregerson P, Leake B. A randomized controlled trial of two treatment programs for homeless adults with latent tuberculosis infection. Int J Tuberc Lung Dis. 2006;10:775–82.
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