16,000 healthcare workers who were tested serially with an IGRA at 19 hospitals (3). Choosing one test method over another is not a hedge against unreliability: ...
LETTERS 16,000 healthcare workers who were tested serially with an IGRA at 19 hospitals (3). Choosing one test method over another is not a hedge against unreliability: Dorman and colleagues described unstable conversions, with site-to-site variability, with Tubersol TST and both IGRA methods (4). We speculate that the disproportionate rate of unstable IGRA conversions could be attributed to overrepresentation of healthcare workers with prior negative TST results in the samples tested by Dorman and Gamsky. Overall, the findings should discourage annual testing of health care workers at low risk for exposure (5). How much of an occupational hazard is exposure to M. tuberculosis for emergency responders? They might encounter patients who have unrecognized tuberculosis, but the exposure times would be brief, and any such events are unlikely because the disease is uncommon in the United States. Although the data about occupational tuberculosis risk for emergency responders are sparse, the findings have been similar to Gamsky’s: the infection rate is low, approaching undetectable. Prezant and colleagues described 6 years of annual TST surveillance of emergency responders in New York City during the tuberculosis resurgence in the early 1990s (6). The citywide tuberculosis incidence during the period of observation was four to five times the incidence in Gamsky’s community, yet conversions, defined by Prezant as a change from any negative TST result to greater than 10 mm induration, averaged 0.5% per year, similar to the 0.9% overall reported by Dorman for apparently unexposed health care workers who were tested every 6 months over the course of 18 months (4). The American Thoracic Society defines TST conversion as a 10 mm or more increase over the baseline reaction, which helps to counteract TST variability. The U.S. definition for a conversion of IGRA results is less strict: a change from a negative to a positive (5, 7). The accuracy might be enhanced by locally determined test values for defining “positive” or “conversion” (8). Even after refinements, all the methods tend to be problematic for serial testing of health care workers because of the unavoidable trade-off between sensitivity and specificity. For low-risk healthcare workers, obtaining a baseline result followed by selective testing after tuberculosis exposures (5) will be more efficient than comparing test methods and trying to refine a method for annual testing.
Author disclosures are available with the text of this letter at www.atsjournals.org.
Reply
Dr. Thanassi and Dr. Kawamura and colleagues have incorrectly calculated the rates of positive QuantiFERON-TB test results based on data that are presented as the number of new individuals with initial positive QuantiFERON-TB results, and not the total number of positive results. The latter are needed to calculate prevalence rates. The data they cite do not include results from individuals who had more than one positive test and cannot be used to support their conclusion that the test is reliable. Dr. Kawamura and Dr. Hudson allege bias based on our inclusion of data collected in 2007, at a time when some QuantiFERON-TB collection tubes were endotoxin contaminated (2). There is no definitive evidence that contamination found in some tubes used in 2007 caused our false-positive results, as these tubes were not tested for endotoxin contamination. There are many documented causes of false-positive QuantiFERON-TB results, apart from endotoxin contamination (3). All tests were performed in accordance with the manufacturer’s
From the Authors: We welcome the correspondents’ support for our conclusion that QuantiFERON-TB (tuberculosis) testing should not be used in low-risk populations. We agree that policies governing screening for latent tuberculosis infection in low-risk populations need to be reexamined and changed. The central finding of our longitudinal study is that false-positive QuantiFERON-TB results predominantly occurred in different individuals in each of the 7 years of the study (1). These false-positive results accumulated under conditions of standard clinical practice, resulting in unacceptably high false-positive rates. Conclusions that accumulation of false-positive results is mathematically predictable further supports discontinuing the use of the QuantiFERON-TB test in low-risk populations.
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John A. Jereb, M.D. Centers for Disease Control and Prevention Atlanta, Georgia
References 1 Gamsky TE, Lum T, Hung-Fan M, Green JA. Cumulative false positive QuantiFERON-TB interferon-gamma release assay results. Ann Am Thorac Soc 2016;13:660–665. 2 Gamsky TE, Alexander RC. QuantiFERON-TB blood testing in the occupational setting. J Occup Environ Med 2008;50:3–4. 3 King TC, Upfal M, Gottlieb A, Adamo P, Bernacki E, Kadlecek CP, Jones JG, Humphrey-Carothers F, Rielly AF, Drewry P, et al. T-SPOT. TB interferon-g release assay performance in healthcare worker screening at nineteen US hospitals. Am J Respir Crit Care Med 2015; 192:367–373. 4 Dorman SE, Belknap R, Graviss EA, Reves R, Schluger N, Weinfurter P, Wang Y, Cronin W, Hirsch-Moverman Y, Teeter LD, et al.; Tuberculosis Epidemiologic Studies Consortium. Interferon-g release assays and tuberculin skin testing for diagnosis of latent tuberculosis infection in healthcare workers in the United States. Am J Respir Crit Care Med 2014;189:77–87. 5 Jensen PA, Lambert LA, Iademarco MF, Ridzon R; CDC. Guidelines for preventing the transmission of Mycobacterium tuberculosis in health-care settings, 2005. MMWR Recomm Rep 2005;54:1–141. 6 Prezant DJ, Kelly KJ, Mineo FP, Janus D, Karwa ML, Futterman N, Nolte C. Tuberculin skin test conversion rates in New York City Emergency Medical Service health care workers. Ann Emerg Med 1998;32:208–213. 7 Mazurek GH, Jereb J, Vernon A, LoBue P, Goldberg S, Castro K; IGRA Expert Committee; Centers for Disease Control and Prevention (CDC). Updated guidelines for using interferongamma release assays for detecting Mycobacterium tuberculosis infection. United States. MMWR Recomm Rep 2010; 59:1–25. 8 Thanassi W, Noda A, Hernandez B, Newell J, Terpeluk P, Marder D, Yesavage JA. Delineating a retesting zone using receiver operating characteristic analysis on serial QuantiFERON tuberculosis test results in US healthcare workers. Pulm Med 2012;2012:291294. Copyright © 2016 by the American Thoracic Society
AnnalsATS Volume 13 Number 7 | July 2016
LETTERS recommendations and are valid for inclusion. In addition, Dr. Kawamura and Dr. Hudson’s assertion that our study was further biased because we only included persons with negative skin test results is unfounded. It is a widely accepted statistical premise that false-positive results are best identified by studying very low risk populations (4). The QuantiFERON-TB test manufacturer Cellestis Limited (Carnegie, Victoria, Australia) (currently Qiagen, Hilden, Germany) has had multiple quality assurance issues and almost yearly revisions. The premise that each revision should be evaluated separately would effectively preclude comparative longitudinal analyses. The letters also raise methodologic points. Some centers are noted to have a quantitative retesting zone that identifies individuals whose QuantiFERON-TB test is likely to revert (5). However, these suggested alterations in the test metrics have not been widely adopted. Also, as pointed out by Dr. Jereb, changes in normative test values risk reducing test sensitivity. Oddly, Dr. Thanassi and Dr. Buchta offer a solution our paper explicitly refutes when they posit that repeating the QuantiFERON-TB can confirm an initial positive result in low-risk individuals. If their assumptions were applied to our cohort, we could have needlessly treated 100% of low-risk people with two sequentially positive QuantiFERON-TB test results and no other evidence of latent TB infection. We await studies that evaluate the cumulative false-positive rate of the QuantiFERON-TB test as a potential confounding factor when the test is used in higher-risk populations. Author disclosures are available with the text of this letter at www.atsjournals.org.
Asthma/COPD Overlap Syndrome and Medicare 30-Day Readmissions To the Editor: Kumbhare and colleagues report that patients enrolled in a U.S. national health surveillance telephone survey with asthma/chronic obstructive pulmonary disease (COPD) overlap (ACOS) had more comorbidities and hospitalizations than patients who had COPD alone (1). To extend their observations, we examined the effect of a diagnosis of ACOS on 30-day readmission rates after an index admission for three diseases featured in the Medicare Hospital Readmission Reduction Program: heart failure, pneumonia, and acute myocardial infarction (2). For this analysis, we examined data derived from the fiscal year 2015 and 2016 Hospital-Specific Reports for 11 hospitals in Northwell Health (New York), using methods we have described previously (3, 4). Each HospitalSpecific Report included coding data from the time of discharge for each index admission, including a diagnosis of COPD or asthma. We defined the ACOS group to include any patient who was coded with both COPD and asthma. Patients with ACOS and an index admission for heart failure had a higher rate of readmission within 30 days than patients without ACOS (250 [29.1%] of 858 vs. 2,032 [22.3%] of 9,100; P , 0.0001 by two-tailed Chi square with Yate’s correlation). There was a trend toward higher 30-day readmission rates for this cohort of patients compared with patients admitted because of Letters
Thomas E. Gamsky, M.D., M.P.H. Melody Hung-Fan, M.P.H. Contra Costa County Hospital Martinez, California Thomas Lum, B.S. East Bay Institute for Research and Education Martinez, California Jon A. Green, M.D., Ph.D. VA Northern California Health Care System Martinez, California
References 1 Gamsky TE, Lum T, Hung-Fan M, Green JA. Cumulative false positive quantiFERON-TB interferon-gamma. Ann Am Thorac Soc 2016;13: 660–665. 2 Gamsky TE, Alexander RC. QuantiFERON-TB blood testing in the occupational setting. J Occup Environ Med 2008;50:3–4. 3 Pai M, Denkinger CM, Kik SV, Rangaka MX, Zwerling A, Oxlade O, Metcalfe JZ, Cattamanchi A, Dowdy DW, Dheda K, et al. Gamma interferon release assays for detection of Mycobacterium tuberculosis infection. Clin Microbiol Rev 2014; 27:3–20. 4 Burke DS, Brundage JF, Redfield RR, Damato JJ, Schable CA, Putman P, Visintine R, Kim HI. Measurement of the false positive rate in a screening program for human immunodeficiency virus infections. N Engl J Med 1988;319:961–964. 5 Thanassi W, Noda A, Hernandez B, Newell J, Terpeluk P, Marder D, Yesavage JA. Delineating a retesting zone using receiver operating characteristic analysis on serial QuantiFERON tuberculosis test results in US healthcare workers. Pulm Med 2012;2012:291294. Copyright © 2016 by the American Thoracic Society
heart failure who had COPD (P = 0.087). Patients with ACOS who were admitted for pneumonia also had a higher rate of 30-day readmission than patients who did not have ACOS (166 [25.2%] of 660 vs. 1,252 [18.9%] of 6,618; P = 0.0006). Patients with ACOS who were admitted for acute myocardial infarction did not have a higher readmission rate within 30 days than patients who did not have ACOS. For index admissions resulting from heart failure, readmission within 30 days with an asthma exacerbation (International Statistical Classification of Diseases and Related Health Problems, Ninth Revision, codes 49322 and 49392) occurred more frequently for patients who also had ACOS compared with those who also had COPD (10 [1.17%] of 858 vs. 3 [0.09%] of 3,325; P , 0.0001 by two-tailed Fisher’s exact test). The same held true after an index admission for pneumonia (11 [1.67%] of 660 vs. 3 [0.12%] of 2,525; P , 0.0001). Logistic regression using SigmaXL7 software confirmed that ACOS was a risk predictor for 30-day readmissions resulting from asthma exacerbation (but not COPD exacerbation) after either a heart failure (odds ratio [OR], 32.91; P = 0.0000) or pneumonia (OR, 16.55; P = 0.0000) admission. We found that 30-day readmission with diastolic heart failure after an index admission for heart failure or pneumonia was higher for patients with ACOS than for patients with COPD (44 [2.90%] of 1,518 vs. 110 [1.88%] of 5,850; P = 0.018 by two-tailed Chi squared with Yate’s correlation). Logistic regression confirmed that ACOS was a risk predictor for 30-day readmission resulting from diastolic heart failure after either a heart failure (OR, 1.429; 1191
