IT implementation challenges and solutions. Roundtable discussion.
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Communication↗
Biomedical subjects
Leigh Anderson
Publications and source records attributed to Leigh Anderson.
Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins.
Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2-22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2-7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R(2)) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 microg/ml) indicates that proteins down to the microg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)).
Amino Acid Sequence↗
Candidate-based proteomics in the search for biomarkers of cardiovascular disease.
The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a 'directed proteomics' approach.
Animals↗
The hazards of stroke case selection using administrative data.
BACKGROUND: Administrative data and ICD-9-CM diagnostic codes are frequently used in research efforts to evaluate risk adjusted patient outcomes, particularly mortality. Varying ICD-9-CM sampling algorithms have been used to identify stroke patients. OBJECTIVES: This study evaluates the effects of different sampling strategies (one high sensitivity and one high specificity) on modeling stroke mortality as a performance indicator. RESEARCH DESIGN: Risk adjustment models were developed for two stroke cohorts identified using differing ICD-9-CM algorithms. Standard mortality ratios were calculated in a validation sample as network performance measures and compared across the two stroke samples. SUBJECTS: VHA inpatients with stroke during years 1997 (model development) and 1998 (model validation) were selected from the Patient Treatment File based on cerebrovascular diagnostic codes. MEASURES: Patient mortality within 30 days of admission. RESULTS: The model development and validation for each stroke sampling method produced consistent results: c-statistics 0.74 to 0.75, R2 0.07 to 0.09, concordance 73% to 74%. However, ranking differences in network performance varied by 5 or more positions for 7 of the 22 patient networks. CONCLUSIONS: These findings highlight a potential problem when using administrative data to assess stroke mortality. In the absence of an agreed upon definition of stroke patients, results of provider profiling will vary depending on the ICD-9 algorithm used.
Algorithms↗
Theorized improvisation--a new type of leadership.
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Facility Regulation and Control↗
Perspective: a program to improve protein biomarker discovery for cancer.
Biomarkers for cancer risk, early detection, prognosis, and therapeutic response promise to revolutionize cancer management. Protein biomarkers offer tremendous potential in this regard due to their great diversity and intimate involvement in physiology. An effective program to discover protein biomarkers using existing technology will require team science, an integrated informatics platform, identification and quantitation of candidate biomarkers in disease tissue, mouse models of disease, standardized reagents for analyzing candidate biomarkers in bodily fluids, and implementation of automation. Technology improvements for better fractionation of the proteome, selection of specific biomarkers from complex mixtures, and multiplexed assay of biomarkers would greatly enhance progress.
Animals↗
Outcomes from stroke rehabilitation in Veterans Affairs rehabilitation units: detecting and correcting for selection bias.
This paper addresses the issue of statistical selection bias in multivariate models of functional gain estimated from observational data. Stroke patients from 20 high-volume Veterans Affairs Medical Centers (VAMCs) with acute and subacute inpatient rehabilitation treatment units were observed. Their gains in overall, motor, and cognitive functional status were measured with the use of the Functional Independence Measure (FIM). In estimating multivariate models of FIM gain during rehabilitation using these observational data, we found statistically significant evidence of selection bias, along with considerable differences in inferences between standard multivariate analyses and our selectivity-corrected models. Our results demonstrate the importance of detecting and correcting for statistical selection bias when one uses nonexperimental data to study gains in functional status.
Activities of Daily Living↗