Supplemental Digital Content 1.
This supplement provides additional details regarding the creation of a limited data set, the subsequent linkage of data to publically available data bases for geographic analysis, and a summary of characteristics of specimens excluded from analysis.
Creation of a Limited Data Set: Oxford Diagnostic Laboratories, a division of Oxford
Immunotec, is a CLIA-certified, CAP-accredited laboratory offering testing services within the US. Oxford Immunotec queried the laboratory’s test databases for T-SPOT.TB tests collected from patients under the age of 17 between June 29, 2010 and June 29, 2015. Test record
information, including city, state and zip code and category of the sample collection facility (e.g., hospital, public health, HIV clinic), were extracted from the databases. Samples identified as meeting laboratory rejection criteria due to courier failure (e.g., weather-delayed deliveries) or errors in sample collection or handling at the collection facility were excluded from the dataset.
To identify patients with multiple test results and ensure that only the initial result was included in the dataset, Oxford Immunotec matched laboratory records against patient first and last name or unique alphanumeric identifier, sample collection state and date of birth. Oxford Immunotec removed direct patient identifiers for purposes of producing a limited data set, as defined by US privacy rules and in accordance with the Institutional Review Board (IRB) at Baylor College of Medicine. Oxford Immunotec generated a random and unique patient identifier for each patient and removed the name of each patient and ordering provider from the dataset. The resulting limited dataset included the following data fields: unique patient ID, gender, date of birth, date of sample collection, reported test results, test report comments, city, state, and zip code of the collection facility and categorical description of the collection facility.
Reported test results were provided qualitatively as negative, positive, borderline, invalid and quantitatively as individual spot counts for the Nil (Negative) Control, Panel A (ESAT-6), Panel B (CFP10) and Positive Control (Mitogen). The laboratory interprets the qualitative test result based on the spot count in accordance with the manufacturer’s instruction. (Table 1 available in manuscript)
The Use of T-Cell Xtend®: The laboratory's procedures specify that samples greater than 32 hours old are not suitable for processing and are rejected. The T-Cell Xtend® reagent was added to all samples in this dataset, as it has been routinely used in all T-SPOT.TB specimens since 2010. Samples received prior to 2012 were processed by Oxford Immunotec's Marlborough, Massachusetts laboratory. In January of 2012, Oxford Immunotec opened a second laboratory located in Memphis, Tennessee. Samples were processed by either laboratory until the
Marlborough laboratory was closed in the fall of 2012. All subsequent samples were processed by the Memphis laboratory.
Zip Code Data Retrieval to Support Geographic analysis: Draw location and zip code were recorded for each individual sample obtained. Zip code information was extracted for each
individual and used as a surrogate marker to calculate TB rates at a county and state level within the cohort and compare to published estimates of state and county TB rates.
Unique zip codes were first identified from within the entire dataset. Using an open online zip code database, each individual zip code was tagged to its appropriate county (1). Estimated county level TB incidence rates from 2006-2010 were obtained from Scales et al. who acquired TB county rates from state health departments websites and upon request from various state TB programs (2, 3). As the Centers for Disease Control and Prevention (CDC) does not release county level TB data to the public, this is the only available comprehensive public dataset that provides county level TB rates for all 50 states. As there was no county level TB data publicly available for Puerto Rico, the overall incidence within the territory for year 2014 was extracted from the CDC Online Tuberculosis Information System (OTIS)(4). Estimates of state level TB rates were obtained from the CDC through OTIS from years 2010-2014.
Zip codes were also categorized by population density in accordance with 2010 classifications of the US Office of Management and Budget that are used by Federal statistical agencies in
collecting, tabulating, and publishing Federal statistics (5). A metropolitan area contains a core urban area of 50,000 or more population, and a micropolitan area contains an urban core of at least 10,000 (but less than 50,000) population. Each metro or micro area consists of one or more counties and includes the counties containing the core urban area, as well as any adjacent
counties that have a high degree of social and economic integration (as measured by commuting to work) with the urban core. Zip codes not linked to a micropolitan or metropolitan areas were classified as rural.
Data Excluded from Primary Analysis: In accordance with the laboratory’s standard operating procedures, 592 samples out of 44,289 (1.3%) did not undergo testing due to the following reasons: a laboratory technical error, insufficient blood volume received, insufficient PBMCs isolated, high background staining, or the blood samples was clotted. Characteristics of these samples that were not tested are summarized in Supplemental Table 1. On univariate analysis, there was no association between samples not tested and age, sex, or draw site. Among this subset of 592 samples, testing was not completed on 252 (0.6%) due to insufficient blood
volume, emphasizing the need to ensure that the proper blood volume is obtained. In this subset of 592 samples, testing was not completed on 176 samples (0.4% of the total 44,289 samples) specifically due to insufficient PBMCs. As testing of these samples would have likely produced a low mitogen (positive control) response or a false negative response, univariate analysis was completed in this subgroup to determine if there were associations with important host
characteristics. This subgroup analysis demonstrated that samples with insufficient PBMC were received from younger children (median: 8.9 years (IQR: 5.0, 13.8) vs. median: 12.5 years (IQR:
7.7, 15.5)) compared to those in which testing was completed (p<0.0001). (Supplemental Figure 1). There was no difference in sex.
While controlling for the effect of age, samples received from hospital draw sites were more likely to have insufficient PBMCs compared to samples received from public health clinics (p<0.0001) (see table, SDC 2). There was no difference in the prevalence of insufficient PBMCs in samples received from public health, HIV and all other draw sites. These findings suggest that some younger children and others requiring hospital services may lack immunologic capacity to complete IGRA testing.
REFERENCES
1. ZIP Code Software - Complete List of American Zip Codes - 5-Digit ZIP Code Database Downloads [Internet]. 2016. Available from: http://www.zipcodestogo.com/.
2. Scales D, Brownstein JS, Khan K, Cetron MS. Toward a county-level map of
tuberculosis rates in the U.S. American journal of preventive medicine. 2014 May;46(5):e49-51.
PubMed PMID: 24745646. Pubmed Central PMCID: 4474181.
3. Tuberculosis in the U.S [Internet]. Available from: http://www.healthmap.org/tb/.
4. Online Tuberculosis Information System (OTIS), National Tuberculosis Surveillance System, United States, 1993-2014. [Internet]. [cited April 4, 2016]. Available from:
http://wonder.cdc.gov/tb-v2014.html
5. Office of Management and Budget. 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas; Notice. In: Office of Information and Regulatory Affairs OoMaBO, Executive Office of the President., editor. Washington, DC: National Archives and Records Administration; 2010. p. 37245-52.
