Literature DB >> 22854185

Data interpretation in breath biomarker research: pitfalls and directions.

Wolfram Miekisch1, Jens Herbig, Jochen K Schubert.   

Abstract

Most--if not all--potential diagnostic applications in breath research involve different marker concentrations rather than unique breath markers which only occur in the diseased state. Hence, data interpretation is a crucial step in breath analysis. To avoid artificial significance in breath testing every effort should be made to implement method validation, data cross-testing and statistical validation along this process. The most common data analysis related problems can be classified into three groups: confounding variables (CVs), which have a real correlation with both the diseased state and a breath marker but lead to the erroneous conclusion that disease and breath are in a causal relationship; voodoo correlations (VCs), which can be understood as statistically true correlations that arise coincidentally in the vast number of measured variables; and statistical misconceptions in the study design (SMSD). CV: Typical confounding variables are environmental and medical history, host factors such as gender, age, weight, etc and parameters that could affect the quality of breath data such as subject breathing mode, effects of breath sampling and effects of the analytical technique itself. VC: The number of measured variables quickly overwhelms the number of samples that can feasibly be taken. As a consequence, the chances of finding coincidental 'voodoo' correlations grow proportionally. VCs can typically be expected in the following scenarios: insufficient number of patients, (too) many measurement variables, the use of advanced statistical data mining methods, and non-independent data for validation. SMSD: Non-prospective, non-blinded and non-randomized trials, a priori biased study populations or group selection with unrealistically high disease prevalence typically represent misconception of study design. In this paper important data interpretation issues are discussed, common pitfalls are addressed and directions for sound data processing and interpretation are proposed.

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Year:  2012        PMID: 22854185     DOI: 10.1088/1752-7155/6/3/036007

Source DB:  PubMed          Journal:  J Breath Res        ISSN: 1752-7155            Impact factor:   3.262


  10 in total

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Authors:  Sandrah P Eckel; Jan Baumbach; Anne-Christin Hauschild
Journal:  J Breath Res       Date:  2014-02-24       Impact factor: 3.262

2.  Cellular respiration, metabolomics and the search for illicit drug biomarkers in breath: report from PittCon 2017.

Authors:  Joachim Pleil; Jonathan Beauchamp; Wolfram Miekisch
Journal:  J Breath Res       Date:  2017-08-04       Impact factor: 3.262

3.  Breath analysis by two-dimensional gas chromatography with dual flame ionisation and mass spectrometric detection - Method optimisation and integration within a large-scale clinical study.

Authors:  Michael J Wilde; Rebecca L Cordell; Dahlia Salman; Bo Zhao; Wadah Ibrahim; Luke Bryant; Dorota Ruszkiewicz; Amisha Singapuri; Robert C Free; Erol A Gaillard; Caroline Beardsmore; C L Paul Thomas; Chris E Brightling; Salman Siddiqui; Paul S Monks
Journal:  J Chromatogr A       Date:  2019-02-05       Impact factor: 4.759

4.  Profiling of volatile organic compounds in exhaled breath as a strategy to find early predictive signatures of asthma in children.

Authors:  Agnieszka Smolinska; Ester M M Klaassen; Jan W Dallinga; Kim D G van de Kant; Quirijn Jobsis; Edwin J C Moonen; Onno C P van Schayck; Edward Dompeling; Frederik J van Schooten
Journal:  PLoS One       Date:  2014-04-21       Impact factor: 3.240

5.  Breath analysis in disease diagnosis: methodological considerations and applications.

Authors:  Célia Lourenço; Claire Turner
Journal:  Metabolites       Date:  2014-06-20

Review 6.  Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview.

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Journal:  Metabolites       Date:  2015-01-09

7.  Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening.

Authors:  Michael Phillips; Thomas L Bauer; Renee N Cataneo; Cassie Lebauer; Mayur Mundada; Harvey I Pass; Naren Ramakrishna; William N Rom; Eric Vallières
Journal:  PLoS One       Date:  2015-12-23       Impact factor: 3.240

8.  Natural menstrual rhythm and oral contraception diversely affect exhaled breath compositions.

Authors:  Pritam Sukul; Jochen K Schubert; Phillip Trefz; Wolfram Miekisch
Journal:  Sci Rep       Date:  2018-07-18       Impact factor: 4.379

9.  Profiling of exhaled volatile organics in the screening scenario of a COVID-19 test center.

Authors:  Rasmus Remy; Nele Kemnitz; Phillip Trefz; Patricia Fuchs; Julia Bartels; Ann-Christin Klemenz; Leo Rührmund; Pritam Sukul; Wolfram Miekisch; Jochen K Schubert
Journal:  iScience       Date:  2022-09-23

10.  Metabolite profiling of the ripening of Mangoes Mangifera indica L. cv. 'Tommy Atkins' by real-time measurement of volatile organic compounds.

Authors:  Iain R White; Robert S Blake; Andrew J Taylor; Paul S Monks
Journal:  Metabolomics       Date:  2016-02-18       Impact factor: 4.290

  10 in total

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