Sensitive and Feasible Specimen Collection and Testing Strategies for Diagnosing Tuberculosis in Young Children | Infectious Diseases | JAMA Pediatrics | JAMA Network
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Figure 1.  Participant-Level Mycobacterial Results for 32 Children Tested for Tuberculosis Between October 2013 and August 2015 in Kisumu County, Kenya
Participant-Level Mycobacterial Results for 32 Children Tested for Tuberculosis Between October 2013 and August 2015 in Kisumu County, Kenya

Dot plot of participant-level results for fluorescence microscopy, Xpert MTB/RIF (Cepheid), and mycobacteria growth indicator tube (MGIT) by sample type and sample number. Up to 2 samples of each type were tested per participant. Black circles indicate a positive result, gray circles indicate an invalid (Xpert MTB/RIF) or contaminated (MGIT) result, and white circles indicate a negative result. The top 7 rows are results for participants with HIV. The column on the right shows the number of positive results by Xpert MTB/RIF or MGIT over the number of evaluable specimens. Participants are sorted vertically in descending order of number of testing results available. FNA indicates fine-needle aspiration; GA, gastric aspirate; IS, induced sputum; NPA, nasopharyngeal aspirate; ST, string test.

Figure 2.  Cumulative and Incremental Diagnostic Yield by Specimen Type Among 31 Children With Tuberculosis
Cumulative and Incremental Diagnostic Yield by Specimen Type Among 31 Children With Tuberculosis

The cumulative and incremental yield of each specimen type among 31 analyzable participants is depicted as 3 groups of 3 bars: yield of 1 specimen, yield of 2 specimens, and the incremental yield of the second specimen when added to the first; specimens were tested by Xpert MTB/RIF (Cepheid) alone, mycobacteria growth indicator tube (MGIT) alone, and both Xpert MTB/RIF and MGIT. The points depict average yield over the resampling distribution, black bars represent the interquartile range, and gray bars represent the interdecile range (10th to 90th centile). The specimen types are arranged in decreasing order of yield.

Figure 3.  Average Cumulative Yield of Confirmed Cases by Number of Specimen Samples Among 31 Children With Confirmed Tuberculosis
Average Cumulative Yield of Confirmed Cases by Number of Specimen Samples Among 31 Children With Confirmed Tuberculosis

The average yield for 31 analyzable participants over all combinations of specimens is depicted in groups of 3 for all combinations of each number of specimens from 1 to 12: yield for Xpert MTB/RIF (Cepheid) alone, yield for mycobacteria growth indicator tube (MGIT) alone, and yield for both Xpert MTB/RIF and MGIT. The points depict average yield over the resampling distribution, black bars represent the interquartile range, and gray bars represent the interdecile range (10th to 90th centile).

Figure 4.  Incremental Sequence of High-Yield Combinations and Highest-Diagnostic-Yield Combinations for Testing Minimally Invasive Specimen Types From Children for Tuberculosis
Incremental Sequence of High-Yield Combinations and Highest-Diagnostic-Yield Combinations for Testing Minimally Invasive Specimen Types From Children for Tuberculosis

Boxes show the average diagnostic yield on resampling participants bacteriologic test results (Xpert MTB/RIF [Cepheid] or mycobacteria growth indicator tube [MGIT]), with corresponding specimens and number of each specimen. The boxes on the left show results for single specimens with the highest yield. Connecting lines between boxes indicate which specimen type is added for the next box in the series. At each step, the specimen or specimens that contribute the greatest number of additional positive bacteriologic results is shown.

Table.  Characteristics of Children Tested for Tuberculosis Between October 2013 and August 2015 in Kisumu County, Kenya, by HIV Statusa
Characteristics of Children Tested for Tuberculosis Between October 2013 and August 2015 in Kisumu County, Kenya, by HIV Statusa
1.
World Health Organization. Global tuberculosis report 2020. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/336069/9789240013131-eng.pdf
2.
Graham  SM, Sismanidis  C, Menzies  HJ, Marais  BJ, Detjen  AK, Black  RE.  Importance of tuberculosis control to address child survival.   Lancet. 2014;383(9928):1605-1607. doi:10.1016/S0140-6736(14)60420-7PubMedGoogle ScholarCrossref
3.
Marais  BJ, Gie  RP, Schaaf  HS,  et al.  The natural history of childhood intra-thoracic tuberculosis: a critical review of literature from the pre-chemotherapy era.   Int J Tuberc Lung Dis. 2004;8(4):392-402.PubMedGoogle Scholar
4.
Dodd  PJ, Yuen  CM, Sismanidis  C, Seddon  JA, Jenkins  HE.  The global burden of tuberculosis mortality in children: a mathematical modelling study.   Lancet Glob Health. 2017;5(9):e898-e906. doi:10.1016/S2214-109X(17)30289-9PubMedGoogle ScholarCrossref
5.
Hanrahan  CF, Dansey  H, Mutunga  L,  et al.  Diagnostic strategies for childhood tuberculosis in the context of primary care in a high burden setting: the value of alternative sampling methods.   Paediatr Int Child Health. 2019;39(2):88-94. doi:10.1080/20469047.2018.1533321PubMedGoogle ScholarCrossref
6.
World Health Organization. Guidance for national tuberculosis programs on the management of tuberculosis in children: second edition. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/10665/112360/1/9789241548748_eng.pdf
7.
Zar  HJ, Hanslo  D, Apolles  P, Swingler  G, Hussey  G.  Induced sputum versus gastric lavage for microbiological confirmation of pulmonary tuberculosis in infants and young children: a prospective study.   Lancet. 2005;365(9454):130-134. doi:10.1016/S0140-6736(05)17702-2PubMedGoogle ScholarCrossref
8.
Perez-Velez  CM, Roya-Pabon  CL, Marais  BJ.  A systematic approach to diagnosing intra-thoracic tuberculosis in children.   J Infect. 2017;74(suppl 1):S74-S83. doi:10.1016/S0163-4453(17)30195-0PubMedGoogle ScholarCrossref
9.
Starke  JR, Taylor-Watts  KT.  Tuberculosis in the pediatric population of Houston, Texas.   Pediatrics. 1989;84(1):28-35.PubMedGoogle Scholar
10.
Cowger  TL, Wortham  JM, Burton  DC.  Epidemiology of tuberculosis among children and adolescents in the USA, 2007-17: an analysis of national surveillance data.   Lancet Public Health. 2019;4(10):e506-e516. doi:10.1016/S2468-2667(19)30134-3PubMedGoogle ScholarCrossref
11.
Cuevas  LE, Browning  R, Bossuyt  P,  et al.  Evaluation of tuberculosis diagnostics in children: 2. methodological issues for conducting and reporting research evaluations of tuberculosis diagnostics for intrathoracic tuberculosis in children. consensus from an expert panel.   J Infect Dis. 2012;205(suppl 2):S209-S215. doi:10.1093/infdis/jir879PubMedGoogle ScholarCrossref
12.
Mulenga  H, Tameris  MD, Luabeya  KK,  et al.  The role of clinical symptoms in the diagnosis of intrathoracic tuberculosis in young children.   Pediatr Infect Dis J. 2015;34(11):1157-1162. doi:10.1097/INF.0000000000000847PubMedGoogle ScholarCrossref
13.
Detjen  AK, DiNardo  AR, Leyden  J,  et al.  Xpert MTB/RIF assay for the diagnosis of pulmonary tuberculosis in children: a systematic review and meta-analysis.   Lancet Respir Med. 2015;3(6):451-461. doi:10.1016/S2213-2600(15)00095-8PubMedGoogle ScholarCrossref
14.
Raizada  N, Sachdeva  KS, Swaminathan  S,  et al.  Piloting upfront Xpert MTB/RIF testing on various specimens under programmatic conditions for diagnosis of TB & DR-TB in paediatric population.   PLoS One. 2015;10(10):e0140375. doi:10.1371/journal.pone.0140375PubMedGoogle Scholar
15.
World Health Organization. Automated real-time nucleic acid amplification technology for rapid and simultaneous detection of tuberculosis and rifampicin resistance: Xpert MTB/RIF assay for the diagnosis of pulmonary and extrapulmonary TB in adults and children: policy update. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/112472/9789241506335_eng.pdf
16.
Nansumba  M, Kumbakumba  E, Orikiriza  P,  et al.  Detection yield and tolerability of string test for diagnosis of childhood intrathoracic tuberculosis.   Pediatr Infect Dis J. 2016;35(2):146-151. doi:10.1097/INF.0000000000000956PubMedGoogle ScholarCrossref
17.
Atwebembeire  J, Orikiriza  P, Bonnet  M,  et al.  Xpert(®) MTB/RIF for detection of Mycobacterium tuberculosis from frozen string and induced sputum sediments.   Int J Tuberc Lung Dis. 2016;20(8):1113-1117. doi:10.5588/ijtld.15.0691PubMedGoogle ScholarCrossref
18.
Nicol  MP, Spiers  K, Workman  L,  et al.  Xpert MTB/RIF testing of stool samples for the diagnosis of pulmonary tuberculosis in children.   Clin Infect Dis. 2013;57(3):e18-e21. doi:10.1093/cid/cit230PubMedGoogle ScholarCrossref
19.
Marcy  O, Ung  V, Goyet  S,  et al.  Performance of Xpert MTB/RIF and alternative specimen collection methods for the diagnosis of tuberculosis in HIV-infected children.   Clin Infect Dis. 2016;62(9):1161-1168. doi:10.1093/cid/ciw036PubMedGoogle ScholarCrossref
20.
Oberhelman  RA, Soto-Castellares  G, Gilman  RH,  et al.  Diagnostic approaches for paediatric tuberculosis by use of different specimen types, culture methods, and PCR: a prospective case-control study.   Lancet Infect Dis. 2010;10(9):612-620. doi:10.1016/S1473-3099(10)70141-9PubMedGoogle ScholarCrossref
21.
Moussa  HS, Bayoumi  FS, Mohamed  AM.  Gene Xpert for direct detection of mycobacterium tuberculosis in stool specimens from children with presumptive pulmonary tuberculosis.   Ann Clin Lab Sci. 2016;46(2):198-203.PubMedGoogle Scholar
22.
Connor  RJ.  Sample size for testing differences in proportions for the paired-sample design.   Biometrics. 1987;43(1):207-211. doi:10.2307/2531961PubMedGoogle ScholarCrossref
23.
World Health Organization. WHO case definitions of HIV for surveillance and revised clinical staging and immunological classification of HIV-related disease in adults and children. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/43699/9789241595629_eng.pdf
24.
Walters  E, van der Zalm  MM, Palmer  M,  et al.  Xpert MTB/RIF on stool is useful for the rapid diagnosis of tuberculosis in young children with severe pulmonary disease.   Pediatr Infect Dis J. 2017;36(9):837-843. doi:10.1097/INF.0000000000001563PubMedGoogle ScholarCrossref
25.
LaCourse  SM, Pavlinac  PB, Cranmer  LM,  et al.  Stool Xpert MTB/RIF and urine lipoarabinomannan for the diagnosis of tuberculosis in hospitalized HIV-infected children.   AIDS. 2018;32(1):69-78. doi:10.1097/QAD.0000000000001662PubMedGoogle ScholarCrossref
26.
Hasan  Z, Shakoor  S, Arif  F,  et al.  Evaluation of Xpert MTB/RIF testing for rapid diagnosis of childhood pulmonary tuberculosis in children by Xpert MTB/RIF testing of stool samples in a low resource setting.   BMC Res Notes. 2017;10(1):473. doi:10.1186/s13104-017-2806-3PubMedGoogle ScholarCrossref
27.
MacLean  E, Sulis  G, Denkinger  CM, Johnston  JC, Pai  M, Ahmad Khan  F.  Diagnostic accuracy of stool Xpert MTB/RIF for detection of pulmonary tuberculosis in children: a systematic review and meta-analysis.   J Clin Microbiol. 2019;57(6):57. doi:10.1128/JCM.02057-18PubMedGoogle ScholarCrossref
28.
Andriyoko  B, Janiar  H, Kusumadewi  R, Klinkenberg  E, de Haas  P, Tiemersma  E.  Simple stool processing method for the diagnosis of pulmonary tuberculosis using GeneXpert MTB/RIF.   Eur Respir J. 2019;53(3):53. doi:10.1183/13993003.01832-2018PubMedGoogle ScholarCrossref
29.
Walters  E, Scott  L, Nabeta  P,  et al.  Molecular detection of Mycobacterium tuberculosis from stools in young children by use of a novel centrifugation-free processing method.   J Clin Microbiol. 2018;56(9):56. doi:10.1128/JCM.00781-18PubMedGoogle ScholarCrossref
30.
Coetzee  L, Nicol  MP, Jacobson  R,  et al.  Rapid diagnosis of pediatric mycobacterial lymphadenitis using fine needle aspiration biopsy.   Pediatr Infect Dis J. 2014;33(9):893-896. doi:10.1097/INF.0000000000000312PubMedGoogle ScholarCrossref
31.
Wright  CA, Hesseling  AC, Bamford  C, Burgess  SM, Warren  R, Marais  BJ.  Fine-needle aspiration biopsy: a first-line diagnostic procedure in paediatric tuberculosis suspects with peripheral lymphadenopathy?   Int J Tuberc Lung Dis. 2009;13(11):1373-1379.PubMedGoogle Scholar
32.
Boehme  CC, Nabeta  P, Hillemann  D,  et al.  Rapid molecular detection of tuberculosis and rifampin resistance.   N Engl J Med. 2010;363(11):1005-1015. doi:10.1056/NEJMoa0907847PubMedGoogle ScholarCrossref
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    Original Investigation
    February 22, 2021

    Sensitive and Feasible Specimen Collection and Testing Strategies for Diagnosing Tuberculosis in Young Children

    Author Affiliations
    • 1Division of Infectious Diseases, Boston Children’s Hospital, Boston, Massachusetts
    • 2Department of Pediatrics, Harvard Medical School, Boston, Massachusetts
    • 3Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom
    • 4US Centers for Disease Control and Prevention, Atlanta, Georgia
    • 5Kenya Medical Research Institute, Center for Global Health Research, Kisumu, Kenya
    • 6Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia
    • 7Northrop Grumman, Atlanta, Georgia
    • 8Tuberculosis Clinic, Pima County Health Department, Tucson, Arizona
    • 9Infectious Diseases, University of Arizona College of Medicine, Tucson
    • 10Division of Anatomical Pathology, University of Stellenbosch, Cape Town, South Africa
    • 11US Centers for Disease Control and Prevention, Kisumu, Kenya
    JAMA Pediatr. 2021;175(5):e206069. doi:10.1001/jamapediatrics.2020.6069
    Key Points

    Question  What combinations of specimens, ideally minimally invasive, provide the highest yield for bacteriologic diagnosis of tuberculosis in young children?

    Findings  In this diagnostic study of 300 children, the yield of 2 nasopharyngeal aspirate (NPA) samples (74%), of 1 NPA sample and 1 stool sample (71%), and of 1 NPA sample and 1 urine sample (69%) was similar to the reference-standard samples (up to 2 GA samples [77%] and up to 2 sputum induction samples [64%]), which are more difficult to collect.

    Meaning  These combinations of specimens could improve and facilitate tuberculosis diagnosis among children younger than 5 years in resource-limited settings.

    Abstract

    Importance  Criterion-standard specimens for tuberculosis diagnosis in young children, gastric aspirate (GA) and induced sputum, are invasive and rarely collected in resource-limited settings. A far less invasive approach to tuberculosis diagnostic testing in children younger than 5 years as sensitive as current reference standards is important to identify.

    Objective  To characterize the sensitivity of preferably minimally invasive specimen and assay combinations relative to maximum observed yield from all specimens and assays combined.

    Design, Setting, and Participants  In this prospective cross-sectional diagnostic study, the reference standard was a panel of up to 2 samples of each of 6 specimen types tested for Mycobacterium tuberculosis complex by Xpert MTB/RIF assay and mycobacteria growth indicator tube culture. Multiple different combinations of specimens and tests were evaluated as index tests. A consecutive series of children was recruited from inpatient and outpatient settings in Kisumu County, Kenya, between October 2013 and August 2015. Participants were children younger than 5 years who had symptoms of tuberculosis (unexplained cough, fever, malnutrition) and parenchymal abnormality on chest radiography or who had cervical lymphadenopathy. Children with 1 or more evaluable specimen for 4 or more primary study specimen types were included in the analysis. Data were analyzed from February 2015 to October 2020.

    Main Outcomes and Measures  Cumulative and incremental diagnostic yield of combinations of specimen types and tests relative to the maximum observed yield.

    Results  Of the 300 enrolled children, the median (interquartile range) age was 2.0 (1.0-3.6) years, and 151 (50.3%) were female. A total of 294 met criteria for analysis. Of 31 participants with confirmed tuberculosis (maximum observed yield), 24 (sensitivity, 77%; interdecile range, 68%-87%) had positive results on up to 2 GA samples and 20 (sensitivity, 64%; interdecile range, 53%-76%) had positive test results on up to 2 induced sputum samples. The yields of 2 nasopharyngeal aspirate (NPA) samples (23 of 31 [sensitivity, 74%; interdecile range, 64%-84%]), of 1 NPA sample and 1 stool sample (22 of 31 [sensitivity, 71%; interdecile range, 60%-81%]), or of 1 NPA sample and 1 urine sample (21.5 of 31 [sensitivity, 69%; interdecile range, 58%-80%]) were similar to reference-standard specimens. Combining up to 2 each of GA and NPA samples had an average yield of 90% (28 of 31).

    Conclusions and Relevance  NPA, in duplicate or in combination with stool or urine specimens, was readily obtainable and had diagnostic yield comparable with reference-standard specimens. This combination could improve tuberculosis diagnosis among children in resource-limited settings. Combining GA and NPA had greater yield than that of the current reference standards and may be useful in certain clinical and research settings.

    Introduction

    Tuberculosis is the leading infectious cause of death globally.1 The risk of tuberculosis infection progressing to disease and from disease to death is especially high for young children.2,3 The World Health Organization estimates that globally 230 000 children younger than 15 years died of tuberculosis in 2020.1,4 Tuberculosis-related mortality rates among infants and children younger than 5 years are approximately 9-fold higher than in children aged 5 to 15 years, and these younger children account for almost 80% of all tuberculosis-related deaths in children 15 years and younger.4 However, detecting tuberculosis among children is challenging, and the vast majority of these deaths (96%) are among children not receiving treatment.4 Reductions in child tuberculosis-related mortality may be feasible with improved diagnostic methods.

    Pediatric tuberculosis is often paucibacillary, making microbial confirmation of tuberculosis disease challenging. Additionally, expectorated sputum, the primary diagnostic specimen for tuberculosis in adults, cannot be obtained for most young children.5 Aspiration of gastric fluid (GA) and suctioning following sputum induction (IS) are typically recommended for obtaining pediatric specimens for tuberculosis diagnosis.6,7 However, both these approaches are invasive, and collection of GA generally requires hospitalization for specimen collection.7,8 Therefore, few children (estimated 30% to 40%) with tuberculosis have disease confirmed by mycobacterial culture even in ideal settings.9,10 This also hampers scientific research advances in tuberculosis treatment and prevention in children, as the optimal diagnostic approach for measuring an adequate end point in clinical treatment and vaccine trials in children is unknown.11,12 The self-contained nucleic acid amplification test, Xpert MTB/RIF (Cepheid), provides an attractive alternative to mycobacterial culture in many resource-limited settings with limited laboratory infrastructure.13 Since 2013, the World Health Organization has endorsed Xpert MTB/RIF as a first-line test for diagnosing tuberculosis in children.13-15 However, the challenge of collecting an appropriate specimen type from children to test remains.

    Several pediatric studies have explored the diagnostic yield of individual specimen types, such as nasopharyngeal aspirate (NPA), stool, and string tests (ST), and compared yield of these alternative specimens with reference-standard specimens by Xpert MTB/RIF or mycobacterial culture.16-21 However, comparisons were generally pair-wise or included few specimen types. The key question yet to be answered is what combinations of specimens, ideally minimally invasive, provides the highest yield for bacteriologic diagnosis of tuberculosis in young children. We aimed to rigorously answer that question by measuring yield and test sensitivity for a comprehensive range of specimen types and bacteriologic tests in a cohort of HIV-positive and HIV-negative children younger than 5 years.

    Methods
    Study Participants

    In this prospective diagnostic cross-sectional study, we recruited a consecutive series of children younger than 5 years who had persistent cough, fever, or malnutrition despite therapy for other common illnesses and lung parenchymal abnormality on chest radiography or who had persistent cervical lymphadenopathy between October 2013 and August 2015 from inpatient and outpatient settings in Kisumu County, Kenya. Details of study recruitment, eligibility criteria, and enrollment procedures are described in the eMethods in the Supplement. This study was approved by the institutional review boards of the US Centers for Disease Control and Prevention, the Kenya Medical Research Institute, and the Jaramogi Oginga Odinga Teaching and Referral Hospital. Children’s Hospital Boston/Harvard Medical School relied on the review and oversight of the Centers for Disease Control and Prevention institutional review board. Written informed consent was obtained by parents or legal guardians of participants. This study followed the Standards for Reporting of Diagnostic Accuracy (STARD) reporting guideline.

    Specimen Collection and Testing Procedures

    Study nurses and clinical officers collected specimens over 3 days and 2 nights for each child. The primary study specimen panel for testing with both Xpert MTB/RIF and mycobacteria growth indicator tube (MGIT) included 2 each of GA, NPA, IS, ST, and stool specimens and up to 2 urine specimens. In addition, 2 cervical lymph node fine-needle aspirate (FNA) were collected if indicated (ie, met enrollment criteria for cervical lymphadenopathy). A single blood sample was tested by BD BACTEC (Becton, Dickinson and Company) only. Cutoff values of MGIT and Xpert MTB/RIF do not apply; standard methods were used to determine positive results. Positive MGIT or Xpert MTB/RIF results on any of the primary study specimens were used to define the reference standard because this represents a comprehensive approach to bacteriologic detection of Mycobacterium tuberculosis. Different combinations of specimens and MGIT and Xpert MTB/RIF were evaluated as index tests. Clinical data were not available to laboratory staff; because index and reference tests are defined as different combinations of the same set of samples and tests, laboratory staff did have access to results of both reference and index tests. We evaluated the diagnostic yield of specimens and tests and discontinued testing for specimen types with low yield. Details of specimen collection, processing, and testing are described in the eMethods in the Supplement.

    Clinical Care

    Children were treated for tuberculosis or provided isoniazid preventive therapy according to the primary treating clinician. Participants were followed-up with at 2 weeks, 2 months, and 6 months.

    Statistical Analysis

    The analysis of cumulative and incremental yield included only participants with at least 1 evaluable specimen for at least 4 primary study specimen types. Confirmed tuberculosis was defined as having at least 1 Xpert MTB/RIF or MGIT result positive for M tuberculosis complex for at least 1 primary study specimen (maximum observed yield). Using this confirmed case definition as the reference, we performed resampling to estimate the sensitivity and yield of the various specimen types and tests alone and in combination (index tests), reported as resampling means and an interdecile range (80% interval between first and ninth decile) of the resampling distribution to represent variability in the estimation procedure. Sensitivity was estimated as the number of children with positive test results from the candidate index combination divided by the number of children with positive test results on the reference panel; difference in sensitivity was calculated as the arithmetic difference of the 2 measures. Statistical variability was assessed using resampling and reporting of interdecile ranges. Indeterminate test results were subjected to rigorous quality review and were analyzed as not positive, since this study focuses on yield. Our primary analysis of sensitivity of specimen types and their combinations included Xpert MTB/RIF and MGIT results in combination; if either was positive, the result of testing for that specimen was positive (eMethods in the Supplement). We determined that a sample size of 290 would allow us to detect a difference of 10% in the sensitivity of paired tests, based on the following assumptions: test 1 has sensitivity of 30%; test 2 has sensitivity of 21%; type I error set at 5%; type II error set at 20%; and the sensitivity of test 2 increases by 5% among persons with positive results on test 1.22

    Results
    Participants

    Of the 300 children enrolled in the study, 294 met criteria for the analysis of cumulative and incremental yield. Children were aged 1 to 47 months; the median (interquartile range) age was 2.0 (1.0-3.6) years, and 151 of 300 children (50.3%) were female. Of the 300 children, 73 (24.3%) were HIV positive, 223 (74.3%) were HIV negative, and 4 (1.3%) had unknown HIV status (Table). We reduced the number of urine and blood specimens collected based on interim review of assay yields. Of the first 138 participants enrolled, only 2 had a positive Xpert MTB/RIF or MGIT result on the second urine specimen; both were also positive on the first urine specimen. We therefore only collected and tested 1 urine specimen for each of the remaining participants. Of the first 135 participants, only 1 had a blood specimen with positive MGIT result, whereas 96 had negative results, 20 were contaminated, and 18 were not evaluable. We therefore discontinued collecting and culturing blood specimens.

    Of the 32 children who tested positive for tuberculosis by either Xpert MTB/RIF or MGIT performed on any of the primary study specimens, 27 (84%) had at least 1 GA, IS, NPA, ST, stool, and urine sample tested by Xpert MTB/RIF, MGIT, or both (Figure 1). Among those with confirmed tuberculosis, 14 (44%) had blood collected for MGIT and 4 (13%) had lymph node FNA specimens collected. One patient with confirmed tuberculosis had only NPA collected; this participant was excluded from analysis of cumulative and incremental yield. Of the primary specimens tested, GA, NPA, and IS demonstrated the highest yield (Figure 2).

    Yield of Individual Specimen Types

    Among the 294 children eligible for analysis of cumulative and incremental yield, 31 had confirmed tuberculosis (confirmed cases). Testing of up to 2 of each specimen type by Xpert MTB/RIF and/or MGIT resulted in an average yield of 24 of 31 children with positive test results (sensitivity, 77%; interdecile range, 68%-87%) for GA, 23 of 31 with positive test results (sensitivity, 74%; interdecile range, 64%-84%) for NPA, and 20 of 31 with positive test results (sensitivity, 64%; interdecile range, 53%-76%) for IS. The performance of ST and stool specimens was lower, with an average of 15 of 31 children with positive test results (sensitivity, 48%; interdecile range, 37%-60%) for ST, 14 of 31 with positive test results (sensitivity, 45%; interdecile range, 33%-57%) for stool, and 4 of 31 with positive test results (sensitivity, 13%; interdecile range, 5%-21%) for urine.

    Figure 2 shows the yields of testing each specimen by Xpert MTB/RIF only, MGIT only, or both Xpert MTB/RIF and MGIT among children with confirmed tuberculosis. The average incremental yield for testing up to 2 of each of GA, NPA, or IS specimens by Xpert MTB/RIF or MGIT was an additional 3 children with positive test results (sensitivity, 10%; interdecile range, 3%-17%) for GA, 2.5 with positive test results (sensitivity, 8%; interdecile range, 3%-15%) for NPA, and 3 with positive test results (sensitivity, 10%; interdecile range, 3%-17%) for IS relative to testing only 1 specimen. The number of positive bacteriologic test results increased with the number of specimens tested, although the relative additional yield decreased with increasing number of specimens (Figure 3) (eFigure in the Supplement). Yield tended to be higher on the first specimen for GA, NPA, and stool, although we cannot rule out chance as a reason for the difference. In contrast, for IS, yield was consistently higher for the second specimen (eTable 1 in the Supplement). Lymph node FNA had high yield among children with confirmed tuberculosis; 3 of 4 children had a positive Xpert MTB/RIF or MGIT result.

    Yield of Combinations of All Specimen Types

    Starting from a baseline average yield from Xpert MTB/RIF and/or MGIT of 21 children with positive test results (1 GA; sensitivity, 68%; interdecile range, 57%-79%) or 20.5 with positive test results (1 NPA; sensitivity, 66%; interdecile range, 55%-77%), combining these 2 specimens (ie, 1 GA and 1 NPA) increased yield to 25 of 31 with positive test results (sensitivity, 81%; interdecile range, 71%-90%). Stepwise additions improved yield further: for example, the average yield for up to 2 NPA and 2 GA samples was 28 of 31 with positive test results (sensitivity, 90%; interdecile range, 83%-97%), and adding IS and urine samples increased yield to 30 of 31 (sensitivity, 97%; interdecile range, 92%-100%) (Figure 4A). A minimum of 8 specimens was needed for an average yield of 31 with positive test results (100%; 2 example combinations shown in Figure 4A).

    Yield of Combinations of Minimally Invasive Specimen Types

    When considering only minimally invasive specimens (NPA, stool, and urine) tested by Xpert MTB/RIF and/or MGIT, the average yield of 1 NPA specimen (20.5 of 31 children with positive test results; sensitivity, 66%; interdecile range, 55%-77%) could be further increased with testing up to 2 NPA specimens (23 of 31 with positive test results; sensitivity, 74%; interdecile range, 64%-84%) or with also testing stool (22 of 31 with positive test results; sensitivity, 71%; interdecile range, 60%-81%) or urine (21.5 of 31 with positive test results; sensitivity, 69%; interdecile range, 58%-80%). Further testing restricted to these 3 specimens alone yielded an average of 25 of 31 children with positive test results (sensitivity, 81%; interdecile range, 71%-90%) (Figure 4B). Yield of these minimally invasive specimen combinations was comparable with that of current criterion standards (2 GA: 24 of 31 with positive test results; sensitivity, 77%; interdecile range, 68%-87%; 2 IS: 20 of 31 with positive test results; sensitivity, 64%; interdecile range, 53%-76%).

    Yield of MGIT Testing vs Xpert MTB/RIF

    Total yield from MGIT was higher than Xpert MTB/RIF for all specimen types except stool and urine. Among children with confirmed tuberculosis from primary study specimens, 13 had tuberculosis-positive stool samples via Xpert MTB/RIF (sensitivity, 42%; interdecile range, 30%-53%) compared with 7 via MGIT (sensitivity, 22%; interdecile range, 13%-32%). A total of 4 children had tuberculosis-positive urine samples via Xpert MTB/RIF (sensitivity, 13%; interdecile range, 5%-21%) compared with 2 children via MGIT (sensitivity, 6%; interdecile range, 0%-13%). One child had a single tuberculosis-positive urine Xpert MTB/RIF result, which was the only positive bacteriologic test result from any specimen. Results of each test and each specimen among children with a positive Xpert MTB/RIF or MGIT result on at least 1 sample of any type are shown in Figure 1 and are stratified by HIV status in eTable 2 in the Supplement. When tested by Xpert MTB/RIF alone, an average of 16 of 31 children with positive test results (sensitivity, 52%; interdecile range, 40%-63%) were identified with up to 2 NPA samples, 15 of 31 with positive test results (sensitivity, 48%; interdecile range, 37%-60%) were identified with 1 NPA sample and 1 stool sample, and 13 of 31 with positive test results (sensitivity, 42%; interdecile range, 31%-53%) were identified with 1 NPA sample and 1 urine sample. Yield was consistently higher among children with HIV, with 90% of pseudosample values exceeding 0 for NPA, ST, and stool specimens (eTable 3 in the Supplement).

    Discussion

    We identified combinations of minimally invasive specimen types with bacteriologic yields comparable with that of reference-standard specimens that are more invasive and less readily available. Specifically, we found that testing 2 NPA samples or 1 NPA sample plus 1 stool sample had similar bacteriologic yield to testing 2 GA or 2 IS samples. These combinations are a novel, less-invasive diagnostic approach for children in standard care settings. Additionally, we identified combinations of specimen types with potentially higher sensitivity than current standards, although these combinations include standard specimen types that are more invasive. These combinations could be appropriate for clinical trials of vaccines or antimicrobials and for complex clinical cases in which bacteriologic confirmation is especially important (for example, for patients with potential drug resistance). Our findings for NPA and stool samples are further supported by data from 4 countries that tested standard specimens (GA and expectorated sputum) and alternative specimens (including NPA and stool) from children with HIV younger than 13 years (median age, 7.2 years).19

    In our study, bacteriologic yield from the combination of NPA and stool samples was similar to that of NPA alone. However, stool is easily obtainable and increasingly of interest as a diagnostic specimen.19,24-27 Stool is worth further consideration particularly because its value may increase with a more sensitive test, such as Xpert MTB/RIF Ultra. For stool samples, yield of Xpert MTB/RIF testing was higher than yield of MGIT. Although MGIT may approximate a more sensitive Xpert MTB/RIF modality for other specimen types, it would substantially underestimate testing yield for stool samples. A limitation of methods for testing stool by Xpert MTB/RIF is the need to centrifuge specimens, which requires relatively well-equipped laboratories.18,19 Additional efforts to simplify use of stool processing for nucleic acid testing may also improve its utility.28,29

    Urine samples alone had very low yield, but 1 participant had positive test results on a single urine sample via Xpert MTB/RIF, which was the only positive bacteriologic test result from any specimen type. This suggests that bacteriologic diagnosis by urine alone is not a common finding but that urine may add incremental value in combination with other specimen types.

    Among children with confirmed tuberculosis, only 4 had cervical lymphadenopathy amenable to aspiration. Consistent with previous reports, the yield by both Xpert MTB/RIF and MGIT was high, suggesting that obtaining lymph node FNA samples should be considered for children with tuberculosis symptoms and with large peripheral lymph nodes.30,31 Testing both ST and GA samples increased confirmed tuberculosis cases by an average of only 0.5, suggesting that adding ST to the standard GA procedure would not effectively improve yield. However, since the combined nasogastric tube and ST device enables the collection of 2 specimens at different times through 1 device placement procedure, this combination may be considered in situations where GA is being performed, especially if advances in sample processing and testing improve yield.

    A total of 5 children tested positive by Xpert MTB/RIF only and not MGIT (2 GA samples and 1 sample each of ST, stool, and urine). All specimens collected as part of the standard diagnostic set were processed and then split between Xpert MTB/RIF and MGIT. Because childhood tuberculosis is generally paucibacillary and M tuberculosis complex bacteria frequently clump together, it is possible that bacteria within samples were not adequately distributed into both Xpert MTB/RIF and MGIT. Another explanation for this finding is that bacteria detected by Xpert MTB/RIF were nonviable and therefore did not grow in MGIT. Nonviable bacteria could result from laboratory decontamination processing or by gastrointestinal tract transit (affecting stool and possibly GA and ST). Finally, these results could be false-positive; however, reported specificity of Xpert MTB/RIF for sputum is greater than 99%, and all enrolled children had clinical findings consistent with tuberculosis.32 In general, yield of Xpert MTB/RIF and MGIT testing was higher among HIV-positive children than HIV-negative children; however, our study included only 7 HIV-positive children with confirmed tuberculosis.

    Limitations

    Our study had several limitations. Children enrolled may not be representative of the wide spectrum of tuberculosis presentation in children, particularly for those with early disease without pulmonary involvement. However, children included in this study did have symptoms consistent with indicators for a tuberculosis diagnostic evaluation per current international guidelines.6 MGIT outperformed Xpert MTB/RIF on 4 of 6 primary specimen types, but MGIT is unlikely to be used broadly in most settings because of the required laboratory capacity. However, results of MGIT testing obtained in this study approximate the yield of molecular tests (eg, Xpert MTB/RIF Ultra) that aim for sensitivity comparable with MGIT. The number of children with confirmed tuberculosis was relatively small, but with more than 4 specimens collected per participant, this is, to our knowledge, the most comprehensive study of its kind. The resampling analysis allows us to use the maximum amount of information from this set of children and gives us confidence that many of our observed differences in yield and sensitivity need not be attributed to chance. Additionally, this study was conducted at a single site, and therefore, we are not able to assess reproducibility of results. Most children with bacteriologically confirmed tuberculosis were identified using a limited number of samples, but 8 samples were needed to identify all of these children. It is possible that other combinations (eg, up to 3 of some sample types) could achieve similar results; however, we are not able to assess this in this study.

    Conclusions

    A simple, sensitive approach to tuberculosis diagnosis in young children is needed and could save many lives. We found that testing 2 NPA specimens or 1 NPA specimen plus 1 stool specimen is simpler than current standards and is equally sensitive. The availability of Xpert MTB/RIF Ultra or a similar molecular modality with sensitivity similar to MGIT could further increase the diagnostic value of these specimen combinations.

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    Article Information

    Accepted for Publication: September 23, 2020.

    Published Online: February 22, 2021. doi:10.1001/jamapediatrics.2020.6069

    Corresponding Author: Eleanor S. Click, MD, PhD, US Centers for Disease Control and Prevention, 1600 Clifton Rd, M/S US1-1, Atlanta, GA 30329 (eoc9@cdc.gov).

    Author Contributions: Drs Heilig and Smith had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Song and Click contributed equally to this work.

    Study concept and design: Song, Click, McCarthy, Heilig, Perez-Velez, Cain.

    Acquisition, analysis, or interpretation of data: Song, Click, McCarthy, Heilig, Mchembere, Smith, Fajans, Musau, Okeyo, Okumu, Orwa, Gethi, Odeny, Lee, Wright, Cain.

    Drafting of the manuscript: Song, Click, McCarthy, Heilig, Mchembere, Smith, Okeyo, Odeny.

    Critical revision of the manuscript for important intellectual content: Song, Click, Heilig, Smith, Fajans, Musau, Okeyo, Okumu, Orwa, Gethi, Odeny, Lee, Perez-Velez, Wright, Cain.

    Statistical analysis: Heilig, Smith, Orwa, Odeny, Lee.

    Obtained funding: Song, Cain.

    Administrative, technical, or material support: Click, McCarthy, Mchembere, Fajans, Musau, Okeyo, Gethi, Perez-Velez, Wright, Cain.

    Study supervision: Song, Click, McCarthy, Okeyo, Okumu, Cain.

    Conflict of Interest Disclosures: Dr Okumu has received nonfinancial support from the US Centers for Disease Control and Prevention and Kenya Medical Research Institute. No other disclosures were reported.

    Funding/Support: This study was supported by the US Agency for International Development and the US Centers for Disease Control and Prevention. A portion of this work was funded by the President’s Emergency Plan for AIDS Relief through the Centers for Disease Control and Prevention. Dr Song was supported by grant K23HD072802 from the Eunice Kennedy Shriver National Institute of Child Health & Human Development.

    Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Disclaimer The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.

    Additional Contributions: We acknowledge the study participants and their families and the clinical and laboratory and data management staff at participating sites.

    References
    1.
    World Health Organization. Global tuberculosis report 2020. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/336069/9789240013131-eng.pdf
    2.
    Graham  SM, Sismanidis  C, Menzies  HJ, Marais  BJ, Detjen  AK, Black  RE.  Importance of tuberculosis control to address child survival.   Lancet. 2014;383(9928):1605-1607. doi:10.1016/S0140-6736(14)60420-7PubMedGoogle ScholarCrossref
    3.
    Marais  BJ, Gie  RP, Schaaf  HS,  et al.  The natural history of childhood intra-thoracic tuberculosis: a critical review of literature from the pre-chemotherapy era.   Int J Tuberc Lung Dis. 2004;8(4):392-402.PubMedGoogle Scholar
    4.
    Dodd  PJ, Yuen  CM, Sismanidis  C, Seddon  JA, Jenkins  HE.  The global burden of tuberculosis mortality in children: a mathematical modelling study.   Lancet Glob Health. 2017;5(9):e898-e906. doi:10.1016/S2214-109X(17)30289-9PubMedGoogle ScholarCrossref
    5.
    Hanrahan  CF, Dansey  H, Mutunga  L,  et al.  Diagnostic strategies for childhood tuberculosis in the context of primary care in a high burden setting: the value of alternative sampling methods.   Paediatr Int Child Health. 2019;39(2):88-94. doi:10.1080/20469047.2018.1533321PubMedGoogle ScholarCrossref
    6.
    World Health Organization. Guidance for national tuberculosis programs on the management of tuberculosis in children: second edition. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/10665/112360/1/9789241548748_eng.pdf
    7.
    Zar  HJ, Hanslo  D, Apolles  P, Swingler  G, Hussey  G.  Induced sputum versus gastric lavage for microbiological confirmation of pulmonary tuberculosis in infants and young children: a prospective study.   Lancet. 2005;365(9454):130-134. doi:10.1016/S0140-6736(05)17702-2PubMedGoogle ScholarCrossref
    8.
    Perez-Velez  CM, Roya-Pabon  CL, Marais  BJ.  A systematic approach to diagnosing intra-thoracic tuberculosis in children.   J Infect. 2017;74(suppl 1):S74-S83. doi:10.1016/S0163-4453(17)30195-0PubMedGoogle ScholarCrossref
    9.
    Starke  JR, Taylor-Watts  KT.  Tuberculosis in the pediatric population of Houston, Texas.   Pediatrics. 1989;84(1):28-35.PubMedGoogle Scholar
    10.
    Cowger  TL, Wortham  JM, Burton  DC.  Epidemiology of tuberculosis among children and adolescents in the USA, 2007-17: an analysis of national surveillance data.   Lancet Public Health. 2019;4(10):e506-e516. doi:10.1016/S2468-2667(19)30134-3PubMedGoogle ScholarCrossref
    11.
    Cuevas  LE, Browning  R, Bossuyt  P,  et al.  Evaluation of tuberculosis diagnostics in children: 2. methodological issues for conducting and reporting research evaluations of tuberculosis diagnostics for intrathoracic tuberculosis in children. consensus from an expert panel.   J Infect Dis. 2012;205(suppl 2):S209-S215. doi:10.1093/infdis/jir879PubMedGoogle ScholarCrossref
    12.
    Mulenga  H, Tameris  MD, Luabeya  KK,  et al.  The role of clinical symptoms in the diagnosis of intrathoracic tuberculosis in young children.   Pediatr Infect Dis J. 2015;34(11):1157-1162. doi:10.1097/INF.0000000000000847PubMedGoogle ScholarCrossref
    13.
    Detjen  AK, DiNardo  AR, Leyden  J,  et al.  Xpert MTB/RIF assay for the diagnosis of pulmonary tuberculosis in children: a systematic review and meta-analysis.   Lancet Respir Med. 2015;3(6):451-461. doi:10.1016/S2213-2600(15)00095-8PubMedGoogle ScholarCrossref
    14.
    Raizada  N, Sachdeva  KS, Swaminathan  S,  et al.  Piloting upfront Xpert MTB/RIF testing on various specimens under programmatic conditions for diagnosis of TB & DR-TB in paediatric population.   PLoS One. 2015;10(10):e0140375. doi:10.1371/journal.pone.0140375PubMedGoogle Scholar
    15.
    World Health Organization. Automated real-time nucleic acid amplification technology for rapid and simultaneous detection of tuberculosis and rifampicin resistance: Xpert MTB/RIF assay for the diagnosis of pulmonary and extrapulmonary TB in adults and children: policy update. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/112472/9789241506335_eng.pdf
    16.
    Nansumba  M, Kumbakumba  E, Orikiriza  P,  et al.  Detection yield and tolerability of string test for diagnosis of childhood intrathoracic tuberculosis.   Pediatr Infect Dis J. 2016;35(2):146-151. doi:10.1097/INF.0000000000000956PubMedGoogle ScholarCrossref
    17.
    Atwebembeire  J, Orikiriza  P, Bonnet  M,  et al.  Xpert(®) MTB/RIF for detection of Mycobacterium tuberculosis from frozen string and induced sputum sediments.   Int J Tuberc Lung Dis. 2016;20(8):1113-1117. doi:10.5588/ijtld.15.0691PubMedGoogle ScholarCrossref
    18.
    Nicol  MP, Spiers  K, Workman  L,  et al.  Xpert MTB/RIF testing of stool samples for the diagnosis of pulmonary tuberculosis in children.   Clin Infect Dis. 2013;57(3):e18-e21. doi:10.1093/cid/cit230PubMedGoogle ScholarCrossref
    19.
    Marcy  O, Ung  V, Goyet  S,  et al.  Performance of Xpert MTB/RIF and alternative specimen collection methods for the diagnosis of tuberculosis in HIV-infected children.   Clin Infect Dis. 2016;62(9):1161-1168. doi:10.1093/cid/ciw036PubMedGoogle ScholarCrossref
    20.
    Oberhelman  RA, Soto-Castellares  G, Gilman  RH,  et al.  Diagnostic approaches for paediatric tuberculosis by use of different specimen types, culture methods, and PCR: a prospective case-control study.   Lancet Infect Dis. 2010;10(9):612-620. doi:10.1016/S1473-3099(10)70141-9PubMedGoogle ScholarCrossref
    21.
    Moussa  HS, Bayoumi  FS, Mohamed  AM.  Gene Xpert for direct detection of mycobacterium tuberculosis in stool specimens from children with presumptive pulmonary tuberculosis.   Ann Clin Lab Sci. 2016;46(2):198-203.PubMedGoogle Scholar
    22.
    Connor  RJ.  Sample size for testing differences in proportions for the paired-sample design.   Biometrics. 1987;43(1):207-211. doi:10.2307/2531961PubMedGoogle ScholarCrossref
    23.
    World Health Organization. WHO case definitions of HIV for surveillance and revised clinical staging and immunological classification of HIV-related disease in adults and children. Accessed January 13, 2021. https://apps.who.int/iris/bitstream/handle/10665/43699/9789241595629_eng.pdf
    24.
    Walters  E, van der Zalm  MM, Palmer  M,  et al.  Xpert MTB/RIF on stool is useful for the rapid diagnosis of tuberculosis in young children with severe pulmonary disease.   Pediatr Infect Dis J. 2017;36(9):837-843. doi:10.1097/INF.0000000000001563PubMedGoogle ScholarCrossref
    25.
    LaCourse  SM, Pavlinac  PB, Cranmer  LM,  et al.  Stool Xpert MTB/RIF and urine lipoarabinomannan for the diagnosis of tuberculosis in hospitalized HIV-infected children.   AIDS. 2018;32(1):69-78. doi:10.1097/QAD.0000000000001662PubMedGoogle ScholarCrossref
    26.
    Hasan  Z, Shakoor  S, Arif  F,  et al.  Evaluation of Xpert MTB/RIF testing for rapid diagnosis of childhood pulmonary tuberculosis in children by Xpert MTB/RIF testing of stool samples in a low resource setting.   BMC Res Notes. 2017;10(1):473. doi:10.1186/s13104-017-2806-3PubMedGoogle ScholarCrossref
    27.
    MacLean  E, Sulis  G, Denkinger  CM, Johnston  JC, Pai  M, Ahmad Khan  F.  Diagnostic accuracy of stool Xpert MTB/RIF for detection of pulmonary tuberculosis in children: a systematic review and meta-analysis.   J Clin Microbiol. 2019;57(6):57. doi:10.1128/JCM.02057-18PubMedGoogle ScholarCrossref
    28.
    Andriyoko  B, Janiar  H, Kusumadewi  R, Klinkenberg  E, de Haas  P, Tiemersma  E.  Simple stool processing method for the diagnosis of pulmonary tuberculosis using GeneXpert MTB/RIF.   Eur Respir J. 2019;53(3):53. doi:10.1183/13993003.01832-2018PubMedGoogle ScholarCrossref
    29.
    Walters  E, Scott  L, Nabeta  P,  et al.  Molecular detection of Mycobacterium tuberculosis from stools in young children by use of a novel centrifugation-free processing method.   J Clin Microbiol. 2018;56(9):56. doi:10.1128/JCM.00781-18PubMedGoogle ScholarCrossref
    30.
    Coetzee  L, Nicol  MP, Jacobson  R,  et al.  Rapid diagnosis of pediatric mycobacterial lymphadenitis using fine needle aspiration biopsy.   Pediatr Infect Dis J. 2014;33(9):893-896. doi:10.1097/INF.0000000000000312PubMedGoogle ScholarCrossref
    31.
    Wright  CA, Hesseling  AC, Bamford  C, Burgess  SM, Warren  R, Marais  BJ.  Fine-needle aspiration biopsy: a first-line diagnostic procedure in paediatric tuberculosis suspects with peripheral lymphadenopathy?   Int J Tuberc Lung Dis. 2009;13(11):1373-1379.PubMedGoogle Scholar
    32.
    Boehme  CC, Nabeta  P, Hillemann  D,  et al.  Rapid molecular detection of tuberculosis and rifampin resistance.   N Engl J Med. 2010;363(11):1005-1015. doi:10.1056/NEJMoa0907847PubMedGoogle ScholarCrossref
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