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Spot sputum samples are at least as good as early morning samples for identifying Mycobacterium tuberculosis.

ABSTRACT: BACKGROUND:The use of early morning sputum samples (EMS) to diagnose tuberculosis (TB) can result in treatment delay given the need for the patient to return to the clinic with the EMS, increasing the chance of patients being lost during their diagnostic workup. However, there is little evidence to support the superiority of EMS over spot sputum samples. In this new analysis of the REMoxTB study, we compare the diagnostic accuracy of EMS with spot samples for identifying Mycobacterium tuberculosis pre- and post-treatment. METHODS:Patients who were smear positive at screening were enrolled into the study. Paired sputum samples (one EMS and one spot) were collected at each trial visit pre- and post-treatment. Microscopy and culture on solid LJ and liquid MGIT media were performed on all samples; those missing corresponding paired results were excluded from the analyses. RESULTS:Data from 1115 pre- and 2995 post-treatment paired samples from 1931 patients enrolled in the REMoxTB study were analysed. Patients were recruited from South Africa (47%), East Africa (21%), India (20%), Asia (11%), and North America (1%); 70% were male, median age 31 years (IQR 24-41), 139 (7%) co-infected with HIV with a median CD4 cell count of 399 cells/?L (IQR 318-535). Pre-treatment spot samples had a higher yield of positive Ziehl-Neelsen smears (98% vs. 97%, P?=?0.02) and LJ cultures (87% vs. 82%, P?=?0.006) than EMS, but there was no difference for positivity by MGIT (93% vs. 95%, P?=?0.18). Contaminated and false-positive MGIT were found more often with EMS rather than spot samples. Surprisingly, pre-treatment EMS had a higher smear grading and shorter time-to-positivity, by 1 day, than spot samples in MGIT culture (4.5 vs. 5.5 days, P?

SUBMITTER: Murphy ME

PROVIDER: S-EPMC5658986 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Spot sputum samples are at least as good as early morning samples for identifying Mycobacterium tuberculosis.

Murphy Michael E ME Phillips Patrick P J PPJ Mendel Carl M CM Bongard Emily E Bateson Anna L C ALC Hunt Robert R Murthy Saraswathi S Singh Kasha P KP Brown Michael M Crook Angela M AM Nunn Andrew J AJ Meredith Sarah K SK Lipman Marc M McHugh Timothy D TD Gillespie Stephen H SH

BMC medicine 20171027 1

<h4>Background</h4>The use of early morning sputum samples (EMS) to diagnose tuberculosis (TB) can result in treatment delay given the need for the patient to return to the clinic with the EMS, increasing the chance of patients being lost during their diagnostic workup. However, there is little evidence to support the superiority of EMS over spot sputum samples. In this new analysis of the REMoxTB study, we compare the diagnostic accuracy of EMS with spot samples for identifying Mycobacterium tu ...[more]

PMID: 29073910

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Project description:Next-Generation Sequencing (NGS) is widely used to investigate genomic variation. In several studies, the genetic variation of Mycobacterium tuberculosis has been analyzed in sputum samples without previous culture, using target enrichment methodologies for NGS. Alignments obtained by different programs generally map the sequences under default parameters, and from these results, it is assumed that only Mycobacterium reads will be obtained. However, variants of interest microorganism in clinical samples can be confused with a vast collection of reads from other bacteria, viruses, and human DNA. Currently, there are no standardized pipelines, and the cleaning success is never verified since there is a lack of rigorous controls to identify and remove reads from other sputum-microorganisms genetically similar to M. tuberculosis. Therefore, we designed a bioinformatic pipeline to process NGS data from sputum samples, including several filters and quality control points to identify and eliminate non-M. tuberculosis reads to obtain a reliable genetic variant report. Our proposal uses the SURPI software as a taxonomic classifier to filter input sequences and perform a mapping that provides the highest percentage of Mycobacterium reads, minimizing the reads from other microorganisms. We then use the filtered sequences to perform variant calling with the GATK software, ensuring the mapping quality, realignment, recalibration, hard-filtering, and post-filter to increase the reliability of the reported variants. Using default mapping parameters, we identified reads of contaminant bacteria, such as Streptococcus, Rhotia, Actinomyces, and Veillonella. Our final mapping strategy allowed a sequence identity of 97.8% between the input reads and the whole M. tuberculosis reference genome H37Rv using a genomic edit distance of three, thus removing 98.8% of the off-target sequences with a Mycobacterium reads loss of 1.7%. Finally, more than 200 unreliable genetic variants were removed during the variant calling, increasing the report's reliability.

Project description:The Fujifilm SILVAMP TB LAM (FujiLAM) assay offers improved sensitivity compared to Determine TB LAM Ag (AlereLAM) for detecting tuberculosis (TB) among people with HIV. Here, we examined the diagnostic value of FujiLAM testing on early morning urine versus spot urine and the added value of a two-sample strategy. We assessed the diagnostic accuracy of FujiLAM on cryopreserved urine samples collected and stored as part of a prospective cohort of adults with HIV presenting for antiretroviral treatment in Ghana. We compared FujiLAM sensitivity and specificity in spontaneously voided urine samples collected at inclusion (spot urine) versus in the first voided early morning urine (morning urine) and for a one (spot urine) versus two samples (spot and morning urine) strategy. Diagnostic accuracy was determined against both microbiological (using sputum culture and Xpert MTB/RIF testing of sputum and urine to confirm TB) and composite reference standards (including microbiologically confirmed and probable TB cases). Paired urine samples of spot and morning urine were available for 389 patients. Patients had a median CD4 cell count of 176 cells/μL (interquartile range [IQR], 52 to 361). Forty-three (11.0%) had confirmed TB, and 19 (4.9%) had probable TB. Overall agreement for spot versus morning urine test results was 94.6% (kappa, 0.81). Compared to a microbiological reference standard, the FujiLAM sensitivity (95% confidence interval [CI]) was 67.4% (51.5 to 80.9) for spot and 69.8% (53.9 to 82.8) for morning urine, an absolute difference (95% CI) of 2.4% (-10.2 to 14.8). Specificity was 90.2% (86.5 to 93.1) versus 89.0% (85.2 to 92.1) for spot and morning urine, respectively, a difference of 1.2% (-3.7 to 1.4). A two-sample strategy increased FujiLAM sensitivity from 67.4% (51.5 to 80.9) to 74.4% (58.8 to 86.5), a difference of 7.0% (-3.0 to 16.9), while specificity decreased from 90.2% (86.5 to 93.1) to 87.3% (83.3 to 90.6), a difference of -2.9% (-4.9 to -0.8). This study indicates that FujiLAM testing performs equivalently on spot and early morning urine samples. Sensitivity could be increased with a two-sample strategy but at the risk of lower specificity. These data can inform future guidelines and clinical practice. IMPORTANCE This study indicates that FujiLAM testing performs equivalently on spot and early morning urine samples for detecting tuberculosis among people with HIV. Sensitivity could be increased with a two-sample strategy but at the risk of lower specificity. These data can inform future guidelines and clinical practice around FujiLAM.

Project description:Tuberculosis remains a major global health problem. Laboratory diagnostic methods that allow effective, early detection of cases are central to management of tuberculosis in the individual patient and in the community. Since the 1880s, laboratory diagnosis of tuberculosis has relied primarily on microscopy and culture. However, microscopy fails to provide species- or lineage-level identification and culture-based workflows for diagnosis of tuberculosis remain complex, expensive, slow, technically demanding and poorly able to handle mixed infections. We therefore explored the potential of shotgun metagenomics, sequencing of DNA from samples without culture or target-specific amplification or capture, to detect and characterise strains from the Mycobacterium tuberculosis complex in smear-positive sputum samples obtained from The Gambia in West Africa. Eight smear- and culture-positive sputum samples were investigated using a differential-lysis protocol followed by a kit-based DNA extraction method, with sequencing performed on a benchtop sequencing instrument, the Illumina MiSeq. The number of sequence reads in each sputum-derived metagenome ranged from 989,442 to 2,818,238. The proportion of reads in each metagenome mapping against the human genome ranged from 20% to 99%. We were able to detect sequences from the M. tuberculosis complex in all eight samples, with coverage of the H37Rv reference genome ranging from 0.002X to 0.7X. By analysing the distribution of large sequence polymorphisms (deletions and the locations of the insertion element IS6110) and single nucleotide polymorphisms (SNPs), we were able to assign seven of eight metagenome-derived genomes to a species and lineage within the M. tuberculosis complex. Two metagenome-derived mycobacterial genomes were assigned to M. africanum, a species largely confined to West Africa; the others that could be assigned belonged to lineages T, H or LAM within the clade of "modern" M. tuberculosis strains. We have provided proof of principle that shotgun metagenomics can be used to detect and characterise M. tuberculosis sequences from sputum samples without culture or target-specific amplification or capture, using an accessible benchtop-sequencing platform, the Illumina MiSeq, and relatively simple DNA extraction, sequencing and bioinformatics protocols. In our hands, sputum metagenomics does not yet deliver sufficient depth of coverage to allow sequence-based sensitivity testing; it remains to be determined whether improvements in DNA extraction protocols alone can deliver this or whether culture, capture or amplification steps will be required. Nonetheless, we can foresee a tipping point when a unified automated metagenomics-based workflow might start to compete with the plethora of methods currently in use in the diagnostic microbiology laboratory.

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Spot sputum samples are at least as good as early morning samples for identifying Mycobacterium tuberculosis.

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Spot sputum samples are at least as good as early morning samples for identifying Mycobacterium tuberculosis.

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