| Title: | Use of a least absolute shrinkage and selection operator (LASSO) model to selected ion flow tube mass spectrometry (SIFT-MS) analysis of exhaled breath to predict the efficacy of dialysis: a pilot study |
| Author(s): | Wang MH; Chong KC; Storer M; Pickering JW; Endre ZH; Lau SY; Kwok C; Lai M; Chung HY; Ying Zee BC; |
| Address: | "Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, People's Republic of China. ShenZhen Research Institute, The Chinese University of Hong Kong, ShenZhen, People's Republic of China. These authors contributed equally to this work" |
| DOI: | 10.1088/1752-7155/10/4/046004 |
| ISSN/ISBN: | 1752-7163 (Electronic) 1752-7155 (Linking) |
| Abstract: | "Selected ion flow tube-mass spectrometry (SIFT-MS) provides rapid, non-invasive measurements of a full-mass scan of volatile compounds in exhaled breath. Although various studies have suggested that breath metabolites may be indicators of human disease status, many of these studies have included few breath samples and large numbers of compounds, limiting their power to detect significant metabolites. This study employed a least absolute shrinkage and selective operator (LASSO) approach to SIFT-MS data of breath samples to preliminarily evaluate the ability of exhaled breath findings to monitor the efficacy of dialysis in hemodialysis patients. A process of model building and validation showed that blood creatinine and urea concentrations could be accurately predicted by LASSO-selected masses. Using various precursors, the LASSO models were able to predict creatinine and urea concentrations with high adjusted R-square (>80%) values. The correlation between actual concentrations and concentrations predicted by the LASSO model (using precursor H(3)O(+)) was high (Pearson correlation coefficient = 0.96). Moreover, use of full mass scan data provided a better prediction than compounds from selected ion mode. These findings warrant further investigations in larger patient cohorts. By employing a more powerful statistical approach to predict disease outcomes, breath analysis using SIFT-MS technology could be applicable in future to daily medical diagnoses" |
| Keywords: | "Adult Breath Tests/*methods Creatinine/blood *Exhalation Humans Mass Spectrometry/*methods *Models, Theoretical Monitoring, Physiologic Pilot Projects *Renal Dialysis Reproducibility of Results Urea/blood Volatile Organic Compounds/analysis;" |
| Notes: | "MedlineWang, Maggie Haitian Chong, Ka Chun Storer, Malina Pickering, John W Endre, Zoltan H Lau, Steven Yf Kwok, Chloe Lai, Maria Chung, Hau Yin Ying Zee, Benny Chung eng Research Support, Non-U.S. Gov't England 2016/09/30 J Breath Res. 2016 Sep 28; 10(4):046004. doi: 10.1088/1752-7155/10/4/046004" |
