CClinicalTrials.gg
Status unknownNCT02776150PMTforDR-TBUpdated May 18, 2016

Probe Melting Technology for Rapid Detection of Drug Resistant Tuberculosis

An observational study in Tuberculosis, Pulmonary, sponsored by Beijing Hospital. Status unknown. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2016-05-18.

Sponsored by Beijing Hospital · Observational

The sponsor has not verified this record recently (last verified May 2016), so the status shown — last known as Not yet recruiting — may be out of date.
Study type
Observational
Model
Case-only
Time perspective
Prospective
Enrollment
3,100
Ages
18 Years and older
Sex
All
01

Study summary

Background:

Drug resistant tuberculosis is a serious public health problem that threatens the health of human life and the development of society and economy. At present, the diagnosis of drug-resistant tuberculosis mainly depends on traditional drug susceptibility test. But it is limited in Mycobacterium tuberculosis slow growth speed, traditional solid drug sensitivity test usually need to 3 months to results, delay the development of drug resistance in patients with effective treatment. Probe melting curves resistance detection technology is the recent emergence of a new molecular biology and drug resistant tuberculosis detection technology, probe melting curves with different fluorescent labeled probe coverage detection specific to M.tuberculosis drug resistance determining region, through changes in the melting point of the probe hybridization, acquire mutation information of detection region, shorten detection time and detect nonuniform resistance.

In this study, by selecting a nationally representative in different levels of hospitals jointly launched multi center, large sample clinical assessment, completed the comprehensive evaluation of sensitivity, specificity and health economics of drug resistant pulmonary tuberculosis, especially resistance to multidrug and extensively drug-resistant TB patients detection,in order to evaluate the rapid, accurate and economic and appropriate technology of drug resistance pulmonary tuberculosis detection.

In order to accomplish the overall goal of the project, in the framework of the overall design, according to the principles of the core tasks are divided into four sub topics, namely:

Sub topic 1 of the core mission is included in 3100 cases of smear positive pulmonary TB suspicious symptoms, from which selected more than 1000 cases of drug-resistant pulmonary tuberculosis patients, using MGIT liquid culture and drug sensitivity test as the gold standard,evaluate the sensitivity and specificity of probe melting curves in detction of resistance of four kinds of anti tuberculosis drug to Mycobacterium tuberculosis; Sub topic 2 core task is including at least 500 cases of culture positive pulmonary tuberculosis patients and treatment follow-up, using MGIT liquid culture and drug sensitivity test as the gold standard, evaluate the application value of probe melting curves for monitoring spectrum changes of drug resistance of Mycobacterium tuberculosis during pulmonary tuberculosis treatment.

The core mission of sub topic 3 is to project implementation of hospital as the research site,acquire the cost-effect evaluation and analysis by comparing probe melting technology with Mycobacterium tuberculosis MGIT liquid culture, and drug sensitivity test with xpert MTB/RIF technology.

Read the detailed description

Sub topic 1:Probe melting curve method for the analysis of drug resistance detection technology for detection of Mycobacterium tuberculosis resistance performance analysis.

Research methods: multi center clinical study. Research object: sputum acid fast staining microscopy positive of pulmonary tuberculosis with suspicious symptoms.

Technical principle and operation method: see attachment.

Entry criteria:

  1. during the study of all smear positive pulmonary tuberculosis with suspicious symptoms; 2) can provide 3-4ml sputum samples three times in 2 days; 3) informed consent. Exclusion criteria: the quality of sputum specimen is not qualified (sputum sample is less than 3ml or saliva sputum).
  1. sample estimate Method and formula: according to the national tuberculosis drug resistance in the baseline survey results, isoniazid, rifampicin, fluoroquinolones and streptomycin anti tuberculosis drugs, fluoroquinolones resistance rate is low; using fluoroquinolones detection estimation sample content, can meet the needs of other anti tuberculosis drug resistance rate analysis.
  2. observation index: (1) basic information: demographic data, underlying diseases, the diagnosis and treatment of tuberculosis, epidemiological characteristics.

(2) the clinical symptoms and signs: fever, night sweats, cough, sputum and sputum, weight loss, hemoptysis or sputum with blood, chest pain, dyspnea, fatigue, height, weight, pulmonary rales.

(3) chest imaging (chest X-ray or CT scan): the specific description of the lesion distribution and morphological characteristics and scoring.

(4) laboratory examination: erythrocyte sedimentation rate (ESR), blood routine test, blood biochemistry (AST, ALT, TP, ALB, BUN, Cr and Glu), C-reactive protein (CRP).

(5) microbiological examination of sputum, sputum acid fast staining microscopy, MGIT liquid culture and drug sensitivity detection, xpert MTB/RIF, probe melting curves technology.

95% confidence intervals, using statistical methods by chi square test and Kappa test.

sub topic 2:the follow up of diagnosis and treatment in application of Probe melting curve method of resistance detection in patients with pulmonary tuberculosis.

Research methods: multi center clinical study. Study subjects and sample size: MGIT liquid culture positive pulmonary tuberculosis patients in sub topic 1, to be included in at least 500 cases.

Entry criteria and exclusion criteria: the same as the research sub topic 1.

1 observation index:

  1. with the clinical symptom and physical sign of diagnostic node changes: fever, night sweats, cough, sputum and sputum, weight loss, hemoptysis or sputum with blood, chest pain, dyspnea, fatigue, height, weight, pulmonary rales.
  2. the changes of chest imaging in the follow up nodes: a detailed description of the image.
  3. with the clinical examination of diagnostic node: erythrocyte sedimentation rate (ESR), blood routine test, blood biochemistry (AST, ALT, TP, ALB, BUN, Cr and Glu), C-reactive protein, and so on.
  4. with diagnosis node sputum microbiology examination: sputum acid fast staining microscopy, MGIT liquid drug sensitive culture, Xpert-MTB/RIF and probe melting curves.
  5. classification of outcomes:

    1. effective: to complete the prescribed course of treatment, sputum culture negative; chest X-ray absorption improvement;
    2. failure: treatment for 6/8 months with smear / culture examination positive and / or radiographic improvement;
    3. non tuberculosis deaths: death due to causes other than tuberculosis;
    4. tuberculosis death: death due to disease progression or complications; (E) shedding: interruption of treatment and follow-up can not be achieved;

    (f) diagnostic change: diagnosis of pulmonary tuberculosis in the treatment process.

  6. the change of drug resistance spectrum (a) drug resistance spectrum change: the change of drug resistance of Mycobacterium tuberculosis in the course of follow-up; (b) not uniform resistance: refers to the of the results of the original probe melting curve resistance detection technology analysis, it is found that the probe melting curve peak spectrum chart presents the characteristics of two kinds of different genotype.

2.quality control and acceptance: the same research sub topic 1. 3 data statistics and analysis: Probe melting curves,the molecular diagnostic technique in patients with pulmonary tuberculosis treatment with statistical methods is the application of diagnosis in the calculated two-sided 95% confidence interval, chi square test and kappa test.

sub topic 3:Probe melting curve technology for the cost-effect analysis in detection of drug-resistant Mycobacterium tuberculosis.

Methods: using the cost analysis method and the questionnaire. Research object: research project implementation hospital laboratory.

Data collection, statistics and analysis:

1 cost analysis

  1. each of the implementation of the following basic data collection and data entry software.

    1. the basic costs: were collected for the implementation of the hospital basic input costs, including laboratory housing area, housing area of the office area, laboratory construction and renovation costs, considering the useful life of housing, the conversion of housing cost per unit time.
    2. laboratory equipment costs: all experimental equipment of the cost in purchasing the new price to calculate and the cost should include all procurement costs associated with, such as transportation, installation; annual collection of major equipment maintenance / repair costs, according to the useful life of the instrument, converted instrument unit time cost.
    3. laboratory management costs: laboratory water, electricity, garbage disposal fees, heating costs, etc.;
    4. personnel costs: laboratory staff wages, including all bonuses and allowances paid to employees; (E) cost of supplies: laboratory, including gloves, laboratory clothing, hats, conventional reagents, such as the unit price;

    (f) the above collection cost input software, as a basis for the implementation of the basic data of the hospital;

  2. selection of opportunity cost method, were three projects in the implementation of hospital laboratory independently collected nine laboratory personnel process time, the use of instruments, reagents, consumables and the number of consumption, accurately to the recorded in the tables of statistics in; every collection cost shall cover high, medium and low different sample size, average value of 3 times the amount of sample; will collect the data and time consuming product data entry forms, different batches of cost calculation, will each region three times the cost of taking the average value is real-time fluorescent nucleic acid isothermal amplification detection technique for each detection unit.
  3. to analyze the prevalence rate of tuberculosis in different projects, and to calculate the cost of tuberculosis patients in different regions.

2 acceptance survey: the design of the questionnaire, the survey of 3 projects in the implementation of the hospital not less than 10 laboratory technicians. The questionnaire covers the convenience of other methods, the needs of the laboratory, the application prospects and other aspects of the content.

02

Conditions studied

  • Tuberculosis, Pulmonary

Keywords

  • probe melting curve
  • Drug resistance
  • Tuberculosis, Pulmonary
03

In context

Tuberculosis

1,417 studies on the registry are indexed under Tuberculosis; 208 are open to participants now.

This study's planned enrollment of 3,100 is above the median of 250 across 421 observational studies indexed under Tuberculosis.

Browse Tuberculosis studies →

Lead sponsor

Beijing Hospital is the lead sponsor of 51 studies on the registry; 22 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

the population of suspected symptoms of tuberculosis with sputum smear microscopy positive

Inclusion criteria

  1. During the study of all smear positive pulmonary tuberculosis with suspicious symptoms
  2. Can provide 3-4ml sputum samples three times in 2 days
  3. Informed consent

Exclusion criteria

Exclusion Criteria:

  • The quality of the sputum sample is not qualified (the sputum sample is less than 3ml or saliva sputum)
05

Study design

Observational model
Case-only
Time perspective
Prospective
Enrollment
3,100 participants (estimated)
Patient registry
No

Groups and cohorts

  • MGIT liquid culture+drug sensitivity test

    MGIT: The bactec MGIT 960 system is non-radiometric. It uses MGIT media and patented sensors, making efficient use of advanced fluorometric technology, which permits highly accurate detection of O2 consumption without sharps. Automated quality control is performed continuously to ensure precise and reliable operation. Results are provided as positive/negative and numerical growth units.

  • Xpert-MTB/RIF

    xpert-MTB/RIF: The Xpert MTB/RIF assay is a nucleic acid amplification (NAA) test that uses a disposable cartridge with the GeneXpert Instrument System. A sputum sample is collected from the patient with suspected TB. The sputum is mixed with the reagent that is provided with the assay, and a cartridge containing this mixture is placed in the GeneXpert machine. All processing from this point on is fully automated.The test simultaneously detects Mycobacterium tuberculosis complex (MTBC) and resistance to rifampin (RIF) in less than 2 hours.

  • probe melting curve detection

    Probe-based fluorescence melting curve analysis (FMCA) is a powerful tool for mutation detection based on melting temperature generated by thermal denaturation of the probe-target hybrid, which performed for Mycobacterium tuberculosis's drug resistant monitor. The method was explored two dual-labeled, self-quenched probes, TaqMan and shared-stem molecular beacons, in their ability to conduct FMCA. Both probes could be directly used for FMCA and readily integrated with closed-tube amplicon hybridization under asymmetric PCR conditions. Improved flexibility of FMCA by using these probes was illustrated in three representative applications of FMCA: mutation scanning, mutation identification and mutation genotyping, all of which achieved improved color-multiplexing with easy probe design and versatile probe combination and all were validated with a large number of real clinical samples.

06

What researchers measure

Primary outcomes

  1. the sensitivity and specificity of probe melting curves technology

    assess the sensitivity and specificity of probe melting curves for four kinds of anti tuberculosis drug resistance to Mycobacterium tuberculosis.

    Time frame: up to 3.5 years

  2. Comparison of diagnostic efficacy

    Using Xpert-MTB/RIF as control technology, the diagnostic efficacy of two kinds of drug resistance detection technology was compared.

    Time frame: from January,2015 to December,2018

  3. Evaluation of the application value of probe melting curve technology

    For the first time in China to carry out drug-resistant TB rapid detection technology appllied in the follow-up, improve the resistance detection technology to monitor the change of TB drug resistance spectrum in the treatment of pulmonary tuberculosis.Selecting patients with MGIT liquid culture positive pulmonary tuberculosis(selected from sub topic1) were included in the study,at least 500 patients were included in the study.Observe the outcomes and the change of drug resistance spectrum.drug-resistant TB rapid detection technology applied in the follow-up of patients with pulmonary TB by monitoring TB drug resistance spectrum change,provides the basis for the resistant phenotype and genotype identification and diagnosis of nonuniform resistance.Data statistics and analysis:95% confidence intervals, chi square test and Kappa test were calculated respectively.

    Time frame: up to 3.5 years

  4. analyze the cost-effect assessment of probe melting curve technology and other two kinds of detection methods

    Complete the cost-effectiveness assessment analysis of the probe melting curve technology compared with Mycobacterium tuberculosis MGIT liquid culture and drug sensitivity test,and xpert MTB / RIF technology. Methods:Using cost analysis and acceptability questionnaire.Each of the implementation of the hospital, collecting the basic data and input the costs into the software,using opportunity cost method.

    Time frame: up to 3.5 years

07

Study locations

No study locations are listed for this record.

08

References and documents

Publications

  • Sanchez-Padilla E, Merker M, Beckert P, Jochims F, Dlamini T, Kahn P, Bonnet M, Niemann S. Detection of drug-resistant tuberculosis by Xpert MTB/RIF in Swaziland. N Engl J Med. 2015 Mar 19;372(12):1181-2. doi: 10.1056/NEJMc1413930. No abstract available. PubMed 25785984 ↗
  • Boehme CC, Nabeta P, Hillemann D, Nicol MP, Shenai S, Krapp F, Allen J, Tahirli R, Blakemore R, Rustomjee R, Milovic A, Jones M, O'Brien SM, Persing DH, Ruesch-Gerdes S, Gotuzzo E, Rodrigues C, Alland D, Perkins MD. Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med. 2010 Sep 9;363(11):1005-15. doi: 10.1056/NEJMoa0907847. Epub 2010 Sep 1. PubMed 20825313 ↗
  • Perkins MD, Cunningham J. Facing the crisis: improving the diagnosis of tuberculosis in the HIV era. J Infect Dis. 2007 Aug 15;196 Suppl 1:S15-27. doi: 10.1086/518656. PubMed 17624822 ↗
  • Getahun H, Harrington M, O'Brien R, Nunn P. Diagnosis of smear-negative pulmonary tuberculosis in people with HIV infection or AIDS in resource-constrained settings: informing urgent policy changes. Lancet. 2007 Jun 16;369(9578):2042-2049. doi: 10.1016/S0140-6736(07)60284-0. PubMed 17574096 ↗
  • Havlir DV, Getahun H, Sanne I, Nunn P. Opportunities and challenges for HIV care in overlapping HIV and TB epidemics. JAMA. 2008 Jul 23;300(4):423-30. doi: 10.1001/jama.300.4.423. PubMed 18647985 ↗
  • Uys PW, Warren RM, van Helden PD. A threshold value for the time delay to TB diagnosis. PLoS One. 2007 Aug 22;2(8):e757. doi: 10.1371/journal.pone.0000757. PubMed 17712405 ↗
  • Farmer P, Bayona J, Becerra M, Furin J, Henry C, Hiatt H, Kim JY, Mitnick C, Nardell E, Shin S. The dilemma of MDR-TB in the global era. Int J Tuberc Lung Dis. 1998 Nov;2(11):869-76. No abstract available. PubMed 9848606 ↗
  • Van Rie A, Enarson D. XDR tuberculosis: an indicator of public-health negligence. Lancet. 2006 Nov 4;368(9547):1554-6. doi: 10.1016/S0140-6736(06)69575-5. No abstract available. PubMed 17084741 ↗
  • Palomino JC. Molecular detection, identification and drug resistance detection in Mycobacterium tuberculosis. FEMS Immunol Med Microbiol. 2009 Jul;56(2):103-11. doi: 10.1111/j.1574-695X.2009.00555.x. Epub 2009 Mar 18. PubMed 19416361 ↗
  • Urdea M, Penny LA, Olmsted SS, Giovanni MY, Kaspar P, Shepherd A, Wilson P, Dahl CA, Buchsbaum S, Moeller G, Hay Burgess DC. Requirements for high impact diagnostics in the developing world. Nature. 2006 Nov 23;444 Suppl 1:73-9. doi: 10.1038/nature05448. No abstract available. PubMed 17159896 ↗
  • El-Hajj HH, Marras SA, Tyagi S, Kramer FR, Alland D. Detection of rifampin resistance in Mycobacterium tuberculosis in a single tube with molecular beacons. J Clin Microbiol. 2001 Nov;39(11):4131-7. doi: 10.1128/JCM.39.11.4131-4137.2001. PubMed 11682541 ↗
  • Piatek AS, Tyagi S, Pol AC, Telenti A, Miller LP, Kramer FR, Alland D. Molecular beacon sequence analysis for detecting drug resistance in Mycobacterium tuberculosis. Nat Biotechnol. 1998 Apr;16(4):359-63. doi: 10.1038/nbt0498-359. PubMed 9555727 ↗
  • Raja S, Ching J, Xi L, Hughes SJ, Chang R, Wong W, McMillan W, Gooding WE, McCarty KS Jr, Chestney M, Luketich JD, Godfrey TE. Technology for automated, rapid, and quantitative PCR or reverse transcription-PCR clinical testing. Clin Chem. 2005 May;51(5):882-90. doi: 10.1373/clinchem.2004.046474. Epub 2005 Mar 3. PubMed 15746302 ↗
  • Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, Lijmer JG, Moher D, Rennie D, de Vet HC; Standards for Reporting of Diagnostic Accuracy. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Standards for Reporting of Diagnostic Accuracy. Clin Chem. 2003 Jan;49(1):1-6. doi: 10.1373/49.1.1. PubMed 12507953 ↗
  • Hillemann D, Rusch-Gerdes S, Richter E. Application of the Capilia TB assay for culture confirmation of Mycobacterium tuberculosis complex isolates. Int J Tuberc Lung Dis. 2005 Dec;9(12):1409-11. PubMed 16466066 ↗
  • Helb D, Jones M, Story E, Boehme C, Wallace E, Ho K, Kop J, Owens MR, Rodgers R, Banada P, Safi H, Blakemore R, Lan NT, Jones-Lopez EC, Levi M, Burday M, Ayakaka I, Mugerwa RD, McMillan B, Winn-Deen E, Christel L, Dailey P, Perkins MD, Persing DH, Alland D. Rapid detection of Mycobacterium tuberculosis and rifampin resistance by use of on-demand, near-patient technology. J Clin Microbiol. 2010 Jan;48(1):229-37. doi: 10.1128/JCM.01463-09. Epub 2009 Oct 28. PubMed 19864480 ↗
  • Blakemore R, Story E, Helb D, Kop J, Banada P, Owens MR, Chakravorty S, Jones M, Alland D. Evaluation of the analytical performance of the Xpert MTB/RIF assay. J Clin Microbiol. 2010 Jul;48(7):2495-501. doi: 10.1128/JCM.00128-10. Epub 2010 May 26. PubMed 20504986 ↗
  • Yagui M, Perales MT, Asencios L, Vergara L, Suarez C, Yale G, Salazar C, Saavedra M, Shin S, Ferrousier O, Cegielski P. Timely diagnosis of MDR-TB under program conditions: is rapid drug susceptibility testing sufficient? Int J Tuberc Lung Dis. 2006 Aug;10(8):838-43. PubMed 16898366 ↗
  • Urbanczik R, Rieder HL. Scaling up tuberculosis culture services: a precautionary note. Int J Tuberc Lung Dis. 2009 Jul;13(7):799-800. No abstract available. PubMed 19555526 ↗
  • Banada PP, Sivasubramani SK, Blakemore R, Boehme C, Perkins MD, Fennelly K, Alland D. Containment of bioaerosol infection risk by the Xpert MTB/RIF assay and its applicability to point-of-care settings. J Clin Microbiol. 2010 Oct;48(10):3551-7. doi: 10.1128/JCM.01053-10. Epub 2010 Aug 18. PubMed 20720033 ↗
  • Sanchez-Padilla E, Dlamini T, Ascorra A, Rusch-Gerdes S, Tefera ZD, Calain P, de la Tour R, Jochims F, Richter E, Bonnet M. High prevalence of multidrug-resistant tuberculosis, Swaziland, 2009-2010. Emerg Infect Dis. 2012 Jan;18(1):29-37. doi: 10.3201/eid1801.110850. PubMed 22260950 ↗
  • Siu GK, Zhang Y, Lau TC, Lau RW, Ho PL, Yew WW, Tsui SK, Cheng VC, Yuen KY, Yam WC. Mutations outside the rifampicin resistance-determining region associated with rifampicin resistance in Mycobacterium tuberculosis. J Antimicrob Chemother. 2011 Apr;66(4):730-3. doi: 10.1093/jac/dkq519. Epub 2011 Jan 17. PubMed 21393153 ↗
  • Policy Statement: Automated Real-Time Nucleic Acid Amplification Technology for Rapid and Simultaneous Detection of Tuberculosis and Rifampicin Resistance: Xpert MTB/RIF System. Geneva: World Health Organization; 2011. Available from http://www.ncbi.nlm.nih.gov/books/NBK304235/ PubMed 26158191 ↗

Individual participant data

Plan to share: Yes

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on May 18, 2016, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT02776150
Lead sponsor
Beijing Hospital
Responsible party
Yanming Li (chief physician, Beijing Hospital) — Principal investigator
First posted
May 18, 2016
Start date
May 2016
Primary completion
Dec 2018 (estimated)
Completion
Jun 2019 (estimated)
Last update
May 18, 2016

Study contacts

Yanming Li, Principal Investigator
Contact
lymyl@263.net
13701097436
Shuyi Si, subordinate
Contact
shy_si@163.com
13051991568

Oversight

Data monitoring committee
Yes
View the source record on ClinicalTrials.gov ↗

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