FOURTH EDITION

Tuberculosis Laboratory 

Aggregate Report
ii

Suggested Citation: CDC. Fourth Edition of the Tuberculosis Laboratory Aggregate Report, Atlanta, Georgia: 

U.S. Department of Health and Human Services, CDC; 2017

Use of trade names and commercial sources is for identification only and does not imply endorsement by 

Centers for Disease Control and Prevention or U.S. Department of Health and Human Services.
1

Inside This Report

Introduction......................................... 1

How to Get the Most

from this Report.................................. 1

Glossary ............................................. 2

Technical Notes .................................. 3

Laboratory Workload .......................... 4

MTBC Culture Positivity...................... 6

Trends in Nucleic Acid 

Amplification Testing (NAAT).............. 8

Turnaround Times .............................. 9

Comparisons to Surveillance Data ... 12

Methods............................................ 13

References ....................................... 15

Resources ........................................ 15

Journal Articles of Interest ................ 16

LCT Contact Details

Stephanie Johnston, MS

sjohnston@cdc.gov

(404) 639-5019

Cortney Stafford, MPH 

cstafford@cdc.gov

(404) 639-3420

Frances Tyrrell, MPH 

ftyrrell@cdc.gov

(404) 639-5451

Mitchell Yakrus, MS, MPH 

myakrus@cdc.gov

(404) 639-1288

Monica Youngblood, MPH

myoungblood@cdc.gov

(404) 718-2079

Introduction 

The Laboratory Capacity Team (LCT) in the Laboratory Branch 

(LB) of the Division of Tuberculosis Elimination (DTBE) at 

the U.S. Centers for Disease Control and Prevention (CDC) 

is pleased to present the “Fourth Edition of the Tuberculosis 

Laboratory Aggregate Report.” This report includes a 

comparison of aggregate workload data for calendar years 

2012, 2013, 2014, and 2015, and six-year trends (2010–2015) 

for turnaround time (TAT). Current public health laboratory 

(PHL) testing methods and practices for tuberculosis (TB) 

are also included in this report. Data are self-reported by PHL 

supported, in part, by the CDC TB Elimination Cooperative 

Agreement. Data serve as a tool to assess benchmarks and 

provide peer comparisons. Providing self-reported data back to 

grantees in a meaningful format is an important mission of LCT.

How to Get the Most from this Report

A key aspect of a quality assurance program is to monitor 

workload and TAT indicators within a laboratory. By assessing 

these indicators internally over time, as well as externally against 

peer data, laboratories can track progress and set realistic goals. 

The Fourth Edition of the Tuberculosis Laboratory Aggregate 

Report provides peer data for comparison and serves as a guide 

to define a laboratory’s TAT goals using national averages and 

trends. For example, if your laboratory is above the national 

average, continue those efforts. However, if your laboratory is 

below the national average, focus on efforts for improvement. 

The Aggregate Report also contains data that is stratified by 

laboratory volume for a more specific comparison among 

laboratories. Testing volume and courier service availability are 

stratified for direct comparison with similar laboratories. 

Use the data in this Aggregate Report to your advantage. 

Information from this report can be used to either document 

your program’s accomplishments or provide evidence 

to substantiate change within your laboratory, such as 

methodologies, protocols, or staffing. 

Please contact your LCT consultant with any questions 

regarding data requirements for the CDC TB Cooperative 

Agreement or your laboratory’s specific data. In addition, any 

recommendations concerning the Aggregate Report and its 

content are welcome.
2

Glossary

AFB: Acid-fast bacilli

AP: Agar proportion

CDC: United States Centers for Disease Control and Prevention

DST: Drug susceptibility testing

DTBE: Division of Tuberculosis Elimination

Hain LPA: Hain Lifescience. Commercial line probe assays that identify MTBC and can detect mutations 

associated with both rifampicin and isoniazid resistance.

HP 2020: Healthy People 2020 

HPLC: High Performance Liquid Chromatography

ID: Identification

IGRA: Interferon-Gamma Release Assay

INNO-LiPA®: Fujirebio. Commercial line probe assays that identify MTBC and can detect mutations 

associated with rifampin resistance.

LB: Laboratory Branch

LCT: Laboratory Capacity Team

MALDI-TOF: Matrix-assisted Laser Desorption Ionization Time of Flight. A mass-spectrometry-based assay 

for bacterial identification. 

BacTec MGITTM: Mycobacterium Growth Indicator Tube, Becton Dickinson and Co. A commercial 

non-radiometric broth-based mycobacterial culture system.

MTBC: Mycobacterium tuberculosis complex

MTDTM: Mycobacterium Direct Test, Gen Probe, Inc. A commercial molecular assay for direct detection of 

MTBC in clinical specimens.

NAAT: Nucleic acid amplification test. Generic terminology for molecular method used for direct detection of 

MTBC in clinical specimens.

PCR: Polymerase chain reaction

PHL: Public health laboratory

PRA: PCR restriction analysis

Quantiferon®: Qiagen. A commercial blood test used to aid in diagnosis of TB infection. (IGRA)

Trek Sensititre: ThermoScientific. A commercial microtiter plate for minimum inhibitory concentration (MIC) 

testing of 12 antituberculosis drugs simultaneously.

TAT: Turnaround time

TB: Tuberculosis

T-SPOT®: Oxford ImmunoTec. A commercial blood test used to aid in diagnosis of TB infection. (IGRA)

XpertTM MTB/RIF: Cepheid, Inc. A commercial molecular assay for direct detection of MTBC and mutations 

associated with rifampin resistance in clinical specimens.
3

Technical Notes

1. Unless otherwise specified, the source of all data and information for the tables and figures in this report 

originates from Annual Performance Reports of the TB Elimination and Laboratory Cooperative Agreement 

submitted to CDC by US Public Health Laboratories that receive Cooperative Agreement funding. 

2. For Figure 3, public health laboratories were required to report data for each category for inclusion in 

the analysis.

3. For Figure 5, data for courier service were interpreted as accurately as possible from project narratives of 

Cooperative Agreement Annual Performance Reports.

4. For Figures 6–9, data for test methods were interpreted as accurately as possible from project narratives 

of Cooperative Agreement Annual Performance Reports.
4

Laboratory Workload 

Changes in laboratory workload reported by PHL from 2012 through 2015 are listed by key variables in Table 1. While 

some variations in volume were noticed annually for this four year period, PHL reported a decrease in the number of 

clinical specimens received, patients for whom a specimen was submitted, patients culture positive for MTBC, patients 

for whom a reference isolate was submitted, and patients for whom a DST was performed. However, the number 

of patients tested by NAAT or other rapid test increased 39.5% while patients NAAT-positive for MTBC increased 

6.5%, providing evidence that PHL have increased use of molecular methods for detection of MTBC. In 2013, PHL 

began reporting use of IGRA for detection of TB infection as part of the Cooperative Agreement. A comparison of data 

collected in 2013 and 2015 showed a 6.5% increase in the number of IGRA tests performed in PHL.

Table 1. National Workload Data, 2012–2015.

Total No.

(Range among individual laboratories)

Four Year 

Change

2012 2013 2014 2015 No. (% change)

Clinical specimensa

received

237,761

(273—21,082)

223,363

(239—19,275)

222,660

(200—21,592)

207,018

(251—21,071)

-30,743 

(-12.9)

Patients for whom 

a specimen was 

submittedb

103,475

(152—10,695)

97,632

(107—11,487)

100,197

(104—11,311)

92,169

(130—10,017) -11,306 (-10.9)

Patients culture 

positive for MTBC

4,270 

(1—560)

4,210

(1—584)

3,748

(0—639)

3,868

(2—663) -402 (-9.4)

Patients for whom 

a reference isolate 

was submittedc

17,945

(0—2,242)

17,433

(0–2,175)

15,696

(0—1,958)

15,766

(0—2,313) -2,179 (-12.1)

Patients with a 

reference isolate 

identified as MTBC

2,984

(0—304)

3,084

(0—308)

3,073

(0—448)

3,307

(0—592) 323 (10.8)

Patients for whom 

DST was performed

6,854

(1—685)

6,429

(0—752)

5,929

(0—762)

6,006

(2—834) -848 (-12.4)

Patients tested 

by NAAT or other 

rapid test

14,720

(2—5,599)

16,610

(1—5,197)

19,011

(0—5,466)

20,053

(0—5,101) 5,813 (39.5)

Patients NAAT 

positive for MTBC

3,045

(0—706)

2,918

(1—382)

2,631

(0—345)

3,244

(1—485) 199 (6.5)

IGRA Not available 85,968

(0—16,718)

112,384

(0—26,702)

91,519

(0—23,709) 5,551 (6.5)d

a

Processed and cultured, not including isolates referred from other laboratories, bProcessed and culture inoculated, cReceived to either rule

 out or confirm the identification MTBC, d2015 compared to 2013
5

1-500

501-1000

1,001-2,000

2,001-3,000

3,001-4,000

5,001-8,000

8,001-15,000

>15,000

0

2

4

6

8

10

12

14

N

o. of P

H

L

CO

D.C.*

DE

VT

WY

NH

NM

NYS

OH

OR

Philadelphia

WV

CA

HI*

ID

IN

MO

NV

PA

RI

San Diego

UT

WA

AR

AZ

CT

IA

IL

KY

LA*

ME

MN

MT

ND

NE

San Francisco

AK

Houston

KS

MS

NC

NYC

OK

SD

TN

VA

WS

GA

MD

MI

PR

SC

AL

Los Angeles

FL

MA

TX

Diagnostic clinical specimens received, 2015

Figure 1. Distribution of PHL Testing Volumes Measured by Total Number of 

Clinical Specimens Received, 2015.

*These jurisdictions referred all TB testing to another laboratory. 

Note: D.C. = Washington, D.C., NYS = New York State, NYC = New York City, PR = Puerto Rico. All others are US Postal Service state abbreviations or cities.

The volume of public health diagnostic testing for TB is variable, as evidenced by widely distributed measurements of 

clinical specimens received. In 2015, 11 PHL received 1,000 or fewer specimens for AFB smear and culture, while 3 

PHL processed more than 15,000 specimens. Most PHL (n = 36) processed between 1,001 and 5,000 specimens. 

Some PHL process few clinical specimens, but may serve primarily as reference laboratories. These PHL may receive 

isolates and inoculated media from other laboratories within their jurisdictions. CDC and APHL recommend processing a 

minimum of 20 specimens per week1 (approximately 1,000 specimens per year) to maintain proficiency and recommend 

that laboratories with insufficient specimen volumes or those unable to provide accurate results in a timely manner 

consider sending specimens or cultures to qualified full service laboratories. Testing volume is only one potential 

indicator of proficiency. Many other factors contribute to the decision for a laboratory to continue mycobacteriology 

services, including staff expertise, dedicated quality assurance programs, and regional assessments of the need for 

essential services2. 

1-500

501-1000

1,001-2,000

2,001-3,000

3,001-4,000

5,001-8,000

8,001-15,000

>15,000

0

2

4

6

8

10

12

14

N

o. of P

H

L

CO

D.C.*

DE

VT

WY

NH

NM

NYS

OH

OR

Philadelphia

WV

CA

HI*

ID

IN

MO

NV

PA

RI

San Diego

UT

WA

AR

AZ

CT

IA

IL

KY

LA*

ME

MN

MT

ND

NE

San Francisco

AK

Houston

KS

MS

NC

NYC

OK

SD

TN

VA

WS

GA

MD

MI

PR

SC

AL

Los Angeles

FL

MA

TX

Diagnostic clinical specimens received, 2015
6

MTBC Culture Positivity 

Figure 2. Positivity of Cultures by Cooperative Agreement Site, 2015. 

0.1 (2/1,422)

0.4 (5/ 1,354)

0.4 (8/2,042)

0.6 (6/1,021)

0.6 (22/3,625)

0.8 (12/1,598)

0.8 (13/1,613)

0.9 (91/9,989)

1.0 (56/5,856)

1.0 (5/483)

1.1 (33/3,063)

1.3 (16/1,253)

1.3 (38/2,970)

1.3 (32/2,494)

1.5 (21/1,389)

1.6 (35/2,177)

1.7 (14/843)

1.7 (7/406)

1.8 (54/2,990)

1.9 (26/1,393)

1.9 (25/1,293)

2.2 (3/136)

2.3 3/130)

2.5 (42/1,693)

2.9 (52/1,798)

3.1 (15/486)

4.2 (3,868/92,169)

4.3 (8/186)

4.3 (32/738)

4.4 (49/1,121)

4.5 (453/10,017)

5.0 (36/723)

5.0 (65/1,300)

5.2 (111/2,131)

5.4 (41/760)

6.1 (143/2,352)

6.5 (12/185)

6.6 (11/166)

6.7 (19/282)

7.2 (21/290)

7.7 (10/130)

8.1 (40/492)

8.5 (69/816)

8.7 (65/751)

9.9 (306/3096)

10.7 (105/984)

11.8 (72/611)

11.9 (28/236)

12.2 (115/944)

12.4 (663/5,337)

12.7 (31/245)

12.9 (48/410)

12.9 (53/371)

13.2 (49/372)

14.4 (214/1481)

15.2 (73/479)

17.2 (79/459)

17.4 (95/546)

18.1 (116/641)

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0

North Dakota

Montana

Maine

Idaho

Michigan

South Dakota

Nebraska

Massachusetts

Alabama

West Virginia

Mississippi

Connecticut

Oklahoma

Puerto Rico

Kentucky

Kansas

Rhode Island

New Hampshire

South Carolina

Iowa

Minnesota

Wyoming

Vermont

Wisconsin

Alaska

Utah

National percent

Delaware

California

Arkansas

Florida

San Francisco

Houston

Maryland

Virginia

Georgia

Philadelphia

Colorado

New Mexico

Ohio

D.C.

Missouri

Nevada

Tennessee

Los Angeles

Arizona

San Diego

Oregon

North Carolina

Texas

New Jersey

Pennsylvania

Indiana

Washington

New York City

New York State

Louisiana

Illinois

Hawaii

Percent patient specimens received that were culture positive for MTBC
7

The wide range of MTBC culture positivity (percent of individual patients’ specimens that were positive for MTBC 

in culture) observed among PHL is shown in Figure 2. This range may be indicative of differences in incidence 

of TB disease among patient populations served by PHL or may reflect the widely variable roles that PHL serve 

within their jurisdictions. For instance, in some areas, the state PHL may be the sole facility processing AFB 

specimens and therefore, may see a lower percent of cultures positive for MTBC; but in other areas, the PHL 

may function primarily in a reference laboratory capacity by receiving follow-up specimens after diagnosis and 

therefore, might encounter a relatively higher MTBC culture positivity. A number of other factors may influence 

MTBC culture positivity, including the nature of the patient population served by PHL, differences in clinicians’ 

practices in evaluating patients, or local incidence of nontuberculous mycobacteria (NTM) disease. The national 

culture positivity displayed is not indicative of a nationwide goal, but rather reflects the percent of all specimens 

received in PHL in 2015 that were positive for MTBC in culture, measured on a per-patient basis. It is important 

for individual laboratories to determine baseline MTBC culture positivity and monitor this percentage over time 

to detect fluctuations. While some variation might indicate change in disease incidence or patient population 

changes, significant incremental deviations in this indicator could also indicate potential laboratory issues such 

as false-positive cultures. Laboratories may wish to use the information in this graph to compare culture positivity 

among their peers in terms of similar testing volumes or geographic location. 
8

Trends in Nucleic Acid Amplification Testing (NAAT)

Figure 3. Trends in NAAT, 2012–2015.

13%

18%

39%

16%

18%

43%

18%

14%

43%

22%

16%

46%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

% patient specimens processed

that also had NAAT performed

% NAAT positivity % Culture (+) TB confirmed

in 48 hrs.*

2012 2013 2014 2015

n=56 n=57 n=57 n=55 n=57 n=58 n=58 n=57 n=47 n=54 n=50 n=54

Note: n = number of laboratories reporting data. % NAAT positivity = percent of nucleic acid amplification tests performed that were positive 

for MTBC. 

*Beginning in 2013, clarification was provided to indicate only those patients with culture-positive TB should be counted. In 2014, 

2 laboratories had 0 patients with culture-positive TB; these were excluded from analysis. 

The use of NAAT as part of a laboratory’s testing algorithm is essential for rapid detection of patients with TB. From 

2012 to 2015, while the percent of NAAT positivity decreased, expanded use of NAAT in PHL increased, as did 

improvement towards achievement of the HP 2020 goal of 77% of culture-confirmed TB detected by NAAT within 

48 hours. Since 2012, NAAT algorithms have evolved and consequently, the percent of patient specimens tested 

by NAAT has increased. PHL should consider examining local data to determine characteristics of MTBC culture 

positive patients, adjust their NAAT algorithm accordingly to detect more cases, and work with their TB Control 

Program to ensure testing of appropriate patients. Please see Technical Note #2 for explanation of how the number 

of laboratories was derived.

13%

18%

39%

16%

18%

43%

18%

14%

43%

22%

16%

46%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

% patient specimens processed

that also had NAAT performed

% NAAT positivity % Culture (+) TB confirmed

in 48 hrs.*

2012 2013 2014 2015

n=56 n=57 n=57 n=55 n=57 n=58 n=58 n=57 n=47 n=54 n=50 n=54
9

New DST TAT Benchmark

DST TAT is dependent on growth of MTBC in culture, as evidenced by the strong correlation between 

ID of MTBC and DST TATs (p < .05 for 2010 – 2013) reported in the Third Edition of the Aggregate 

Report3. To more accurately assess DST TAT measurement independent of growth of MTBC in culture 

prior to ID of MTBC, the benchmark was changed in 2014 to percent of DST results within 17 days of 

ID of MTBC, rather than the previous measurement of 28 days from specimen receipt. Specific national 

targets for each benchmark were set4. Analysis of 2014 TAT data supports this change, as no correlation 

between ID of MTBC and DST TAT was observed (correlation analysis, SPSS version 21). 

DST Reference Center

Beginning in 2015, DTBE in collaboration with APHL, established the National TB DST Reference 

Center at the California Microbial Diseases Laboratory. Among other services, the reference center 

performs first-line DST for those laboratories performing fewer than 50 DSTs per year. Currently, 10 

PHL use the Reference Center for first-line DST. Those laboratories are excluded from analysis of the 

DST TAT for 2015.

Turnaround Times

Table 2. Turnaround Time Indicators, 2015.

Benchmark

Specimen receipt within 1 

day of 

collection

AFB smear 

result within 1 

day of receipt

ID of MTBC 

within 21 days 

of receipt

DST within 

17 days of ID 

of MTBC

National Target

(% of specimens that 

should meet benchmark)

67% 92% 74% 69%

No. laboratories meeting 

or exceeding National 

Target*

12 31 25 20†

National average* 

(% of specimens meeting 

benchmark)

48% 90% 69% 61%

No. laboratories meeting or exceeding national 

average*

31 33 29 26†

*Number of laboratories reporting = 57. †10 PHL referring isolates to the DST Reference Center 

for first-line DST are excluded from analysis of the DST TAT for 2015.
10

Figure 4. Trends in Turnaround Times, 2010–2015.

*

In 2014, the DST benchmark was changed to reflect the new recommendation of DST results within 17 days of ID of MTBC.

†

10 PHL referring isolates to the DST Reference Center for first-line DST are excluded from analysis of the DST TAT for 2015.
11

31%

52%

65%

44%

65%

80%

89%

95%

98%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 day 2 days 3 days

% specimensreceived within theti

me frame

State PHL with no or limited

courier service (n = 23)

State PHL with statewide courier (n = 27)

City or County PHL (n = 6)

Received in PHL from date of collection

State PHL that had availability of a statewide courier service achieved TAT for specimen delivery at higher levels 

than did those with no or limited courier service. While city and county PHL achieved this benchmark at higher 

levels, rapid specimen delivery remains challenging for state laboratories: many of which are located in large 

geographical areas and depend on a patchwork of delivery services, including U.S. Postal Service, commercial 

couriers, and other transportation methods. Please see Technical Note #3 for explanation of how courier 

availability was determined.

Figure 5. Specimen Receipt TAT Comparisons by Courier Availability, 2015. 
12

Comparison of PHL Testing to Surveillance Reports

Table 3. Comparison of National TB Surveillance Data and PHL Self-Reported Data, 2012–2015.

Year

2012 2013 2014 2015

National TB 

Surveillance 

data

Total no. TB cases 9,945 9,565 9,421 9,557

No. culture-confirmed 

TB cases 7,598 7,358 7,226 7,410

No. culture-confirmed TB 

cases with DST reported 7,250 7,108 6,949 7,209

Self-reported 

PHL data 

(n=58 PHL 

reporting)

No. NAAT positive 

MTBC patients (% of 

culture-confirmed TB 

cases as reported for 

national surveillance)

3,045

(40%)

2,918

(40%)

2,631

(36%)

3,244

(44%)

No. MTBC 

culture-positive patients 

(% of culture-confirmed 

TB cases as reported for 

national surveillance)

4,270

(56%)

4,201

(57%)

3,748

(52%)

3,868

(52%)

No. patient DST 

performed (% of 

culture-confirmed TB 

cases as reported for 

national surveillance)

6,854

(95%)

6,434

(91%)

5,929

(85%)

6,006

(83%)

In Table 3, self-reported Cooperative Agreement data are compared to National TB surveillance data5 for 

2012–2015. In this analysis, PHL appeared to have identified approximately half of the reported culture 

confirmed TB cases and detected 36–44% of MTBC by direct detection (NAAT). PHL also appeared to have 

performed a greater percentage of more complex testing such as DST for culture confirmed cases. Because 

these data are drawn from different sources and may not reflect redundant testing, this comparison represents 

an estimation of the contribution of PHL services to overall TB testing in the United States
13

Methods in Public Health Laboratories

Figure 6. NAAT Methods, 2016.

Figure 7. Primary ID Methods, 2016.

Methods used by PHL supported, in part, by the TB Cooperative Agreement for NAAT, ID, DST, and IGRA, are 

displayed in Figures 6–9. For each figure, total number of PHL equals 58. As new technology emerges and 

laboratories adjust testing algorithms, methods used will continue to evolve. Please see Technical Note #4 for 

explanation of how methods were determined. 

Xpert MTB/RIF, 27

Real-time PCR, 17

MTD, 6

Referred, 6

Hain LPA, 1 Pyrosequencing, 1

Accuprobe, 33

HPLC, 9

Real-time PCR, 5

Referred, 3

INNO-LiPA, 2

MALDI-TOF, 2

Sequencing, 2 Xpert MTB/RIF, 1 PRA, 1

XpertTM MTB/RIF, real-time PCR, and MTDTM assays make up 86% of NAAT methods used.

Although many PHL utilize more than one method within their ID algorithm, the primary 

method described from report narratives is included for each laboratory. 
14

Bactec MGIT, 41

Referred - DST

Reference Center, 10

Referred - Other, 5

Indirect AP, 1 Trek Sensititre, 1

None, 32

Quantiferon in other

section of PHL, 14

Quantiferon in

Mycobacteriology

section of PHL, 10

T-Spot, 2

Figure 8. First-line DST Methods, 2016.

Figure 9. IGRA Methods, 2016.

The majority of PHL continue to perform first-line DST via the Bactec MGITTM system. 

Over the past year, 10 laboratories performing less than 50 DST per year have utilized 

the APHL/CDC National TB DST Reference Center for susceptibility testing. 

As use of IGRA expands throughout public health laboratories, 24 laboratories performed 

Quantiferon®, with 10 of these performing testing within the Mycobacteriology section 

and 14 testing within another section of the PHL. Two laboratories utilized T-Spot® by 

referring specimens to a national testing center. The majority of PHL, however, are not 

currently performing IGRA testing. 
15

References

1. Beavis K, Bernardo J, Blank E, Desmond E, 

Harris R, Humes R, et al. The Future of TB 

laboratory services; a framework for integration, 

collaboration, leadership: a report from an APHL 

task force. Silver Spring, MD: 2004.

2. Livingston KA, Lobato MN, Sosa LE, Budnick 

GE, Bernardo J. Mycobacterium tuberculosis 

testing practices in hospital, commercial and 

state laboratories in the New England states. 

IJTLD, the official journal of the International 

Union against Tuberculosis and Lung Disease. 

2011;15(9):1218-22, 

3. CDC. Tuberculosis Laboratory Aggregate 

Report. Atlanta, GA: U.S. Department of Health 

Services, CDC; 2014. http://www.cdc.gov/tb/

publications/reportsarticles/labreports.htm

4. APHL. TB Cooperative Agreement Toolkit. 

Silver Spring, MD; 2016. https://www.aphl.

org/programs/infectious_disease/tuberculosis/

Pages/TB-Cooperative-Agreement.aspx

5. CDC. Reported tuberculosis in the United States, 

2014. Atlanta, GA: US Department of Health and 

Human Services, CDC; 2015. http://www.cdc.

gov/tb/statistics/reports/2014/default.htm

Resources

APHL Resources

APHL TB Web page https://www.aphl.org/programs/

infectious_disease/tuberculosis/Pages/default.aspx 

APHL White Paper on PZA (2016) http://www.aphl.

org/AboutAPHL/publications/Documents/ID-PZA_

WhitePaper_0216.pdf#search=PZA 

APHL White Paper on Ethambutol (2016) 

https://www.aphl.org/aboutAPHL/publications/

Documents/ID-MTBC_DrugSusceptibility_0216.

pdf#search=ethambutol

CDC Resources

CDC TB Website http://www.cdc.gov/tb/

CDC Molecular Detection of Drug Resistance 

(MDDR) Service http://www.cdc.gov/tb/topic/

laboratory/default.htm

MMWR on use of Xpert http://www.cdc.

gov/mmwr/preview/mmwrhtml/mm6241a1.

htm?s_cid=mm6241a1_e

MMWR on use of Xpert for removal of patients 

from respiratory isolation http://www.cdc.

gov/mmwr/preview/mmwrhtml/mm6407a8.

htm?s_cid=mm6407a8_w

Regional Training and Medical Consultation Centers 

http://www.cdc.gov/tb/education/rtmc/default.htm

Report of Expert Consultations on Rapid Molecular 

Testing to Detect Drug-Resistant Tuberculosis in the 

United States http://www.cdc.gov/tb/topic/laboratory/

rapidmoleculartesting/default.htm

Updated Guidelines for Using Interferon Gamma 

Release Assays to Detect Mycobacterium 

tuberculosis Infection—United States, 2010: http://

www.cdc.gov/mmwr/preview/mmwrhtml/rr5905a1.

htm?s_cid=rr5905a1_w

Guide to the Application of Genotyping to Tuberculosis 

Prevention and Control http://www.cdc.gov/tb/

programs/genotyping/manual.htm

TB Notes Newsletter http://www.cdc.gov/tb/

publications/newsletters/default.htm 

CDC Model Performance Evaluation Program http://

www.cdc.gov/tb/topic/laboratory/mpep/

Other Resources

TB Education and Training Resources 

http://www.findtbresources.org/ 
16

Journal Articles of Interest

Biosafety

Delaney J, Pentella M, Rodriguez J, et al. 2011. 

Guidelines for Biosafety Laboratory Competency. CDC 

and the Association of Public Health Laboratories. 

MMWR Supplements / 60(02);1-6. https://www.cdc.

gov/mmwr/preview/mmwrhtml/su6002a1.htm

Miller JM, Astles R, Baszler T, et al. 2012. Guidelines 

for Safe Work Practices in Human and Animal Medical 

Diagnostic Laboratories. MMWR Supplements / 

61(01);1-101. https://www.cdc.gov/Mmwr/preview/

mmwrhtml/su6101a1.htm

XpertTM MTB/RIF

Luetkemeyer AF, Firnhaber C, Kendall MA, et al. 

2016. Evaluation of Xpert MTB/RIF versus AFB 

Smear and Culture to Identify Pulmonary Tuberculosis 

in Patients with Suspected Tuberculosis from Low 

and Higher Prevalence Settings. Clin Infect Dis. 

62 (9): 1081-1088. https://www.ncbi.nlm.nih.gov/

pubmed/26839383

McAlister AJ, Driscoll J, Metchock B. 2015. DNA 

sequencing for confirmation of rifampin resistance 

detected by Cepheid Xpert MTB/RIF assay. J Clin 

Microbiol 53(5):1752-3. www.ncbi.nlm.nih.gov/

pubmed/25740782

Williamson DA, Basu I, Bower J, et al. 2012. 

An evaluation of the Xpert MTB/RIF assay and 

detection of false-positive rifampicin resistance in 

Mycobacterium tuberculosis. Diagnostic Microbiology 

and Infectious Disease 74(2):207-209. https://www.

ncbi.nlm.nih.gov/pubmed/22819240

Laboratory Practices

Han LL, Elvin P, Bernardo J. 2012. Nonclinical 

selection criteria for maximizing yield of nucleic acid 

amplification tests in tuberculosis diagnosis. J Clin 

Microbiol 50(8): 2592-2595. https://www.ncbi.nlm.nih.

gov/pmc/articles/PMC3421530/

Mitchell K, Halse T, Kohlerschmidt D, et al. 2015. A 

Model of Shared Mycobacteriology Testing Services: 

Lessons Learned. Public Health Rep 130(6):623-31. 

https://www.ncbi.nlm.nih.gov/pmc/articles/

PMC4612171/

Peralta G, Barry P, Pascopella L. 2016. Use of Nucleic 

Acid Amplification Tests in Tuberculosis Patients 

in California, 2010-2013. Open Forum Infect Dis. 

2016 https://www.ncbi.nlm.nih.gov/pmc/articles/

PMC5146759/

Pfyffer GE, Wittwer F. 2012. Incubation time of 

mycobacterial cultures: how long is long enough 

to issue a final negative report to the clinician? J 

Clin Microbiol 50(12):4188-9. http://jcm.asm.org/

content/50/12/4188

Tans-Kersten J, Grace Lin SY, Desmond E, et al. 

2016. Evaluating Shared Laboratory Services: 

Detecting Mycobacterium Tuberculosis Complex and 

Drug Resistance Using Molecular and Culture-Based 

Methods. Public Health Rep 131(1):117-25. https://

www.ncbi.nlm.nih.gov/pubmed/26843677

Tyrrell FC, Budnick GE, Elliott T, et al. 2012. 

Probability of negative Mycobacterium tuberculosis 

complex cultures based on time to detection 

of positive cultures: a multicenter evaluation of 

commercial-broth-based culture systems. J Clin 

Microbiol 50(10): 3275-3282. http://www.ncbi.nlm.nih.

gov/pubmed/22837326

Tyrrell F, Stafford C, Yakrus M, et al. 2016. Trends in 

Testing for Mycobacterium tuberculosis Complex From 

US Public Health Laboratories, 2009–2013. Public 

Health Reports: 132(1): 56-64. https://www.ncbi.nlm.

nih.gov/pubmed/28005481

Pyrazinamide

Piersimoni C, Mustazzolu A, et al. 2013. Prevention 

of False Resistance Results Obtained in Testing 

the Susceptibility of Mycobacterium tuberculosis to 

Pyrazinamide with the Bactec MGIT 960 System 

Using a Reduced Inoculum. J Clin Microbiol 51(1): 

291-294. https://www.ncbi.nlm.nih.gov/pmc/articles/

PMC3536208/

MALDI-TOF

Buckwalter SP, Olson SL, Connelly BJ, et al. 2016. 

Evaluation of Matrix-Assisted Laser Desorption 

Ionization-Time of Flight Mass Spectrometry for 

Identification of Mycobacterium species, Nocardia 

species, and Other Aerobic Actinomycetes. J Clin 

Microbiol; 54(2):376-84. https://www.ncbi.nlm.nih.gov/

pmc/articles/PMC4733196

Molecular Drug Resistance

Dominguez J, Boettger EC, Cirillo D, et al. 2016. 

Clinical implications of molecular drug resistance 

testing for Mycobacterium tuberculosis: a TBNET/

RESIST-TB consensus statement. Int J Tuberc 

Lung Dis 20(1):24-42. https://www.ncbi.nlm.nih.gov/

pubmed/26688526
17

Lin S-YG, Desmond EP. 2014. Molecular Diagnosis 

of Tuberculosis and Drug Resistance. Clinics in 

Laboratory Medicine 34(2):297-314 www.labmed.

theclinics.com/article/S0272-2712(14)00019-5/

references

Rigouts L, Gumusboga M, et al. 2013. Rifampin 

resistance missed in automated liquid culture system 

for Mycobacterium tuberculosis isolates with specific 

rpoB mutations. J Clin Microbiol; 51(8): 2641-2645. 

https://www.ncbi.nlm.nih.gov/pubmed/23761146 

Van Deun A, Aung KJ, Bola V, et al. 2013. Rifampin 

drug resistance tests for tuberculosis: challenging the 

gold standard. J Clin Microbiol 51(8):2633-40. https://

www.ncbi.nlm.nih.gov/pubmed/23761144

Yakrus MA, Metchock B, Starks AM. 2015. Evaluation 

of a U.S. Public Health Laboratory Service for the 

Molecular Detection of Drug Resistant Tuberculosis. 

Tuberculosis Research and Treatment 2015:7. https://

www.ncbi.nlm.nih.gov/pmc/articles/PMC4352467/

Zhang Y, Yew WW. 2015.Mechanisms of drug 

resistance in Mycobacterium tuberculosis: Int J 

Tuberc Lung Dis. 19 (11):1276-89. https://www.ncbi.

nlm.nih.gov/pubmed/19861002

Next Generation Sequencing

Denkinger CM, Kik SV, Cirillo DM, et al. 2015. 

Defining the needs for next generation assays for 

tuberculosis. J Infect Dis 211 Suppl 2:S29-38. https://

www.ncbi.nlm.nih.gov/pubmed/25765104

Köser CU, Bryant JM, Becq J, et al. 2013. 

Whole-Genome Sequencing for Rapid Susceptibility 

Testing of M. tuberculosis. New England Journal of 

Medicine 369 (3):290-292. https://www.ncbi.nlm.nih.

gov/pmc/articles/PMC3836233/

General

Salinas JL, Mindra G, Haddad MB, et al. 2016. 

Leveling of Tuberculosis Incidence — United 

States, 2013–2015. MMWR Morb Mortal Wkly Rep 

65:273–278. http://dx.doi.org/10.15585/mmwr.

mm6511a2

Updates

Official American Thoracic Society/Centers for 

Disease Control and Prevention/Infectious Diseases 

Society of America Clinical Practice Guidelines: 

Treatment of Drug-Susceptible Tuberculosis. 2016. 

Clin Infect Dis. 63(7):e147-95 https://www.ncbi.nlm.

nih.gov/pubmed/27516382

Official American Thoracic Society/Infectious Diseases 

Society of America/Centers for Disease Control and 

Prevention Clinical Practice Guidelines: Diagnosis 

of Tuberculosis in Adults and Children. 2017. Clin 

Infect Dis. 64(2):111-115 https://www.ncbi.nlm.nih.gov/

pubmed/28052967 

Screening for Latent Tuberculosis Infection in Adults: 

US Preventive Services Task Force Recommendation 

Statement. JAMA. 2016. 316(9):962-969. http://

jamanetwork.com/journals/jama/fullarticle/2547762
CS275045

U.S. Department of Health and Human Services

Centers for Disease Control and Prevention

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention

Division of Tuberculosis Elimination