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Three color cDNA microarrays: quantitative assessment through the use of fluorescein-labeled probes.

Gene expression studies using microarrays have great potential to generate new insights into human disease pathogenesis, but data quality remains a major obstacle. In particular, there does not exist a method to determine prior to hybridization whether an array will yield high quality data, given good study design and target preparation. We have solved this problem through development of a three-color cDNA microarray platform where printed probes are fluorescein labeled, but are spectrally compatible with Cy3 and Cy5 dye-labeled targets when using confocal laser scanners possessing narrow bandwidths. This approach enables prehybridization evaluation of array/spot morphology, DNA deposition and retention and background levels. By using these measurements and the intra-slide coefficient of variation for fluorescence intensity we show that slides in the same batch are not equivalent and measurable prehybridization parameters can be predictive of hybridization performance as determined by replicate consistency. When hybridizing target derived from two cell lines to high and low quality replicate pairs (n = 50 pairs), a direct and significant relationship between prehybridization signal-to-background noise and post-hybridization reproducibility (R2 = 0.80, P < 0.001) was observed. We therefore conclude that slide selection based upon prehybridization quality scores will greatly benefit the ability to generate reliable gene expression data.

Carbocyanines↗

Nonsampling measurement error in administrative data: implications for economic evaluations.

Administrative databases are increasingly being used to measure resource use in economic evaluations. Traditionally, it is assumed that any measurement error within the resource data source is stochastic and uncorrelated with group assignment. If the error is correlated with characteristics of the service delivery system and/or correlated by group, the estimated differences in consumption between groups may be reflecting errors in measurement rather than treatment effects. This paper is concerned with the effect of nonsampling measurement error on the internal and external validity of cost estimates based on data drawn from administrative record systems. Two service delivery characteristics, ownership form and financial incentives, are likely to influence systemically an agency's data collection effort. Using data from three community mental health centres located in three different states, evidence of systematic differences in data quality was found; private agencies with reimbursement property rights had higher quality data than public agencies without property rights. Simple tests for detecting variation in service use and costs data and cost-effective solutions for managing these problems are proposed.

Bias↗

Implementation issues of multivoxel STEAM-localized 1H spectroscopy.

Single-voxel STEAM-localized spectroscopy studies of neuropsychiatric patients yield high-quality data at short echo times, but are often limited to only a few regions of interest due to the linear increase of acquisition time with the number of regions examined. A multivoxel STEAM approach increases the number of regions of interest examined with a less than linear increase in acquisition time. Several implementation issues were considered, especially the signal contribution of outer voxel stimulated echoes (OVSE), which can lead to systematic errors in the quantification of relative metabolite concentrations. The relative signal contribution of OVSEs was found to be as great as 30% in phantoms. Gradient polarity switching completely canceled the contribution of OVSEs. A two-voxel STEAM approach produces phantom and in vivo data quality comparable to single-voxel STEAM in practically half the time. Quantification precision and accuracy are preserved in phantoms and in vivo.

Analysis of Variance↗

1995 coronary artery bypass risk model: The Society of Thoracic Surgeons Adult Cardiac National Database.

BACKGROUND: The Society of Thoracic Surgeons (STS) Adult Cardiac National Database has recently completed the development of the 1995 risk model to be used to estimate the risk of operative death for isolated coronary artery bypass graft (CABG) procedures. This article describes the detailed methodology used, as well as a new Expert Advisory Panel review mechanism that was initiated by The Society. METHODS: Placing emphasis on clinical relevance, data quality, data completeness, and univariate analyses, a logistic regression analysis was used to develop the 1995 CABG-only risk model. The STS National Office invited an Expert Advisory Panel (composed of nationally recognized, independent biostatisticians) to review the modeling process used. RESULTS: The 1995 CABG-only model details are reported. Standard performance measures indicated the model had high predictive power and an acceptable level of calibration. The Expert Advisory Panel reviewed the 1995 CABG model and concluded that the current modeling techniques were adequate. Suggestions for future model development and reporting were proposed by the Panel. CONCLUSIONS: The most current STS risk model of CABG operative mortality is a reliable and statistically valid tool. Its development and performance have been critically examined and approved by an independent panel of experts.

Coronary Artery Bypass↗

The 1996 coronary artery bypass risk model: the Society of Thoracic Surgeons Adult Cardiac National Database.

BACKGROUND: The Society of Thoracic Surgeons Adult Cardiac National Database has recently completed the update for the 1996 risk model to be used to estimate the risk of operative death for isolated coronary artery bypass graft (CABG) procedures. METHODS: We placed emphasis on clinical relevance, data quality, data completeness, and univariate analyses. A logistic regression approach was used to develop the 1996 CABG-only risk model. RESULTS: Odds ratios for the factors with highest risk are multiple reoperations (OR = 4.3), emergent salvage status (OR = 3.7), and first reoperation (OR = 2.7). Standard performance measures indicated the model had high predictive power and an acceptable level of calibration after adjustment for a large sample size effect. CONCLUSION: The most current STS risk model of CABG operative mortality is a reliable and statistically valid tool. The 1996 CABG-only model has been approved for use by The Society of Thoracic Surgeons.

Adult↗

A prospective comparison of four study designs used in assessing safety and effectiveness of drug therapy in hypertension management.

The objective of the study was to compare prospectively the impact of study design on drug therapy safety and effectiveness data obtained in hypertension management. The main study was a randomized controlled clinical trial of four different prospective study designs used in postmarketing assessment involving 1008 primary care practices in nine Canadian provinces. Two thousand nine hundred sixty-four patients with mild to moderate hypertension received an angiotensin converting enzyme (ACE) inhibitor daily for 14 weeks in one of four postmarketing studies--a randomized double-blind clinical trial (RCT) (10 to 40 mg fosinopril daily v 5 to 20 mg enalapril daily), two structured open label trials of 10 to 40 mg fosinopril daily (one with free drugs), or an unstructured open label trial of 10 to 40 mg fosinopril daily. Patient demographic and baseline characteristics, systolic and diastolic blood pressures, adverse events reported, and data quality were recorded as the outcome measures. The results showed that the RCT patients were titrated to higher doses of ACE inhibitor than patients in the open studies, P < .008; patients in the open studies were more likely to receive adjuvant diuretic therapy, P < .008. The decrease in blood pressure was similar for patients in all four studies, mean decrease in systolic BP was between 18 and 20 mm Hg, mean decrease in diastolic BP was between 11 and 13 mm Hg. Fewer patients in the unstructured open trial reported adverse events than patients in the RCT; a 55% relative reduction in reported adverse events (P < .008) was associated with the unstructured trial. There were also fewer drug-related adverse events per patient reported in the unstructured study (17 per 100 patients) than in the other studies (27 to 41 per 100 patients), P < .008. Physician preference for rounding off blood pressure measurements to 0 or 5 occurred most often in the unstructured open trial (P < .008). In conclusion, despite differences in dose titration and in the use of adjuvant therapy, antihypertensive drug therapy effectiveness observed in an RCT may be similar to uncontrolled postmarketing studies. Open trials with scheduled follow-up visits are as effective in detecting severe adverse events as RCT, but postmarketing studies with unstructured schedules of follow-up are insufficient in identifying drug-related adverse events and have poorer quality data.

Antihypertensive Agents↗

Advances in analytical technologies for environmental protection and public safety.

Due to the increased threats of chemical and biological agents of injury by terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat chemical and biochemical toxins. In addition to the right mix of policies and training of medical personnel on how to recognize symptoms of biochemical warfare agents, the major success in combating terrorism still lies in the prevention, early detection and the efficient and timely response using reliable analytical technologies and powerful therapies for minimizing the effects in the event of an attack. The public and regulatory agencies expect reliable methodologies and devices for public security. Today's systems are too bulky or slow to meet the "detect-to-warn" needs for first responders such as soldiers and medical personnel. This paper presents the challenges in monitoring technologies for warfare agents and other toxins. It provides an overview of how advances in environmental analytical methodologies could be adapted to design reliable sensors for public safety and environmental surveillance. The paths to designing sensors that meet the needs of today's measurement challenges are analyzed using examples of novel sensors, autonomous cell-based toxicity monitoring, 'Lab-on-a-Chip' devices and conventional environmental analytical techniques. Finally, in order to ensure that the public and legal authorities are provided with quality data to make informed decisions, guidelines are provided for assessing data quality and quality assurance using the United States Environmental Protection Agency (US-EPA) methodologies.

Biosensing Techniques↗

Automated electrophysiology: high throughput of art.

Electrophysiological measurements, in particular, patch clamping, have long been regarded as the "gold standard" for assaying ion channels. Despite its high information content, the technique suffers from laborious, manual processing by highly skilled workers and extremely low throughput. Recently, a number of researchers have started to automate patch clamping by either automating conventional micropipette-based patch clamping or developing planar microelectrode arrays. This article reviews the brief history of these emerging technologies and discusses the technical details, advantages, and disadvantages of each approach and technique. As will be evident from the discussion, two types of automated patch-clamping technologies are emerging. The first places emphasis on data quality, comparable to conventional patch clamping, and the second has much higher throughput. Future developments will include sophisticated patch-clamping devices with both high-quality data and high throughput capabilities and further integration of patch clamping with other cell-based assays.

Animals↗

The Protein Data Bank and lessons in data management.

The Protein Data Bank (PDB) is a widely used biological database of macromolecular structures with a long history. This history is treated as lessons learned and is used to highlight what are believed to be the best practices important to developers of biological databases today. While the focus is on data quality, data representation and the information technology to support these data, the non-data and technology issues cannot be ignored. The role of the human factor in the form of users, collaborators, scientific society and ad hoc committees is also included.

Database Management Systems↗

Historical background and anticipated developments.

Expression profiling using DNA arrays is often believed to have appeared during the second half of the 1990s, and to be based exclusively on nonisotopic methods. In fact, the first article describing the application of cDNA arrays to expression analysis was published in 1992, relied on radioactive labeling, and was a new development of "high-density" membranes used until then essentially for efficient screening of libraries. Several papers described the use of this technology for simultaneous expression measurement of thousands of genes at the time when the first glass microarrays were published. Simultaneously, oligonucleotide chips, originally developed for resequencing and mutation detection applications, were shown to be capable of expression measurement as well. The three approaches have developed over the years and still coexist, as each of them has specific advantages (and drawbacks); the major issues have become those of data quality, data analysis and storage (ideally in a common public database). Meanwhile, the technology continues to evolve. The most obvious trend is a shift towards using arrays of relatively long oligonucleotides that combine most of the advantages of very long (cDNA) and very short (25-mer) DNA segments. The search for better detection methods, ideally without labeling of the sample, is continuing, although it seems difficult to reach the required sensitivity. New materials for microarray manufacture and new implementations of existing methods have appeared. In addition, the field is progressively becoming segmented into high gene number, low volume (research) applications on the one hand, and low gene number, high throughput (diagnostic) uses on the other.

Computational Biology↗

Mental disorders and quality of diabetes care in the veterans health administration.

OBJECTIVE: The population of persons with mental disorders is potentially vulnerable to poor quality of medical care. This study examined the relationship between mental disorders and quality of diabetes care in a national sample of veterans. METHOD: Chart-abstracted quality data were merged with outpatient and inpatient administrative database records for a sample of veterans with diabetes who had at least three outpatient visits in the previous year (N=38,020). Mental health diagnoses were identified by use of the administrative data. Quality of diabetes care was assessed with five indicators by chart documentation: annual foot inspection, pedal pulses examination, foot sensory examination, retina examination, and glycated hemoglobin determination. RESULTS: Approximately a quarter of the sample had a diagnosed mental disorder (23.7% with psychiatric disorder only, 1.3% with substance use disorder only, and 2.6% with a dual diagnosis). Overall rates of receipt for the indicators were higher than national benchmarks for all patient subgroups, ranging from 70.8% for retina examination to 95.0% for foot inspection. Rates for both retina examination and foot sensory examination differed significantly by mental health status, mainly because of lower rates among those with a substance use disorder. The associations remained significant in multivariate generalized estimating equation analyses that controlled for demographic characteristics, health status, use of medical services, and hospital-level characteristics. CONCLUSIONS: Rates for secondary prevention of diabetes were remarkably high at Department of Veterans Affairs medical centers, although patients with mental disorders (particularly substance use disorders) were somewhat less likely to receive some of the recommended interventions.

Aged↗

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project.

BACKGROUND AND PURPOSE: Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. METHODS AND RESULTS: In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. CONCLUSIONS: Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

Body Mass Index↗

Multi-level models for repeated measurement data: application to quality of life data in clinical trials.

Quality of life data present considerable statistical challenges because of their longitudinal and multidimensional nature, and also because the available data are often very unbalanced through missing values. Here we exemplify the potential of multi-level models, that is, hierarchical random coefficient models, for such data. The discussion is developed in the context of analysing the quality of life data from a trial of palliative treatment in non-small-cell lung cancer. Not only do multi-level models provide a flexible modelling framework for the investigation of the underlying behaviour of response, for example, giving simple estimates of treatment effects, but they also permit a description of the differences between subjects and allow the analysis of multi-dimensional outcomes. The assumptions of Normality, homogeneity, and independence of the within- and between-subject variance components can be investigated and the models can be extended to provide explicit modelling of variance heterogeneity. It is concluded that multi-level models, for which software is now available, provide a natural and powerful approach to the analysis of longitudinal data in general, and multi-dimensional quality of life data in particular.

Carcinoma, Non-Small-Cell Lung↗

The Genome Sequence DataBase: towards an integrated functional genomics resource.

During 1998 the primary focus of the Genome Sequence DataBase (GSDB; http://www.ncgr.org/gsdb ) located at the National Center for Genome Resources (NCGR) has been to improve data quality, improve data collections, and provide new methods and tools to access and analyze data. Data quality has been improved by extensive curation of certain data fields necessary for maintaining data collections and for using certain tools. Data quality has also been increased by improvements to the suite of programs that import data from the International Nucleotide Sequence Database Collaboration (IC). The Sequence Tag Alignment and Consensus Knowledgebase (STACK), a database of human expressed gene sequences developed by the South African National Bioinformatics Institute (SANBI), became available within the last year, allowing public access to this valuable resource of expressed sequences. Data access was improved by the addition of the Sequence Viewer, a platform-independent graphical viewer for GSDB sequence data. This tool has also been integrated with other searching and data retrieval tools. A BLAST homology search service was also made available, allowing researchers to search all of the data, including the unique data, that are available from GSDB. These improvements are designed to make GSDB more accessible to users, extend the rich searching capability already present in GSDB, and to facilitate the transition to an integrated system containing many different types of biological data.

Animals↗

Using feedback to raise the quality of primary care computer data: a literature review.

BACKGROUND: Primary care is recognised as a medical specialty and its unique information needs justify the existence of its own health informatics sub-specialty: primary care informatics (PCI). A challenge for PCI is how to raise the standard of computerised medical records so that meaningful conclusions can be drawn from them. In the UK the Primary Care Data Quality (PCDQ) programme has eight years experience of using feedback in an educational context to improve data quality. OBJECTIVE: This literature review set out to define the characteristics of a feedback process most likely to achieve change; the principles of which could be applied to PCDQ or to other data quality initiatives. METHOD: A literature review of the major medical bibliographical databases, and the websites and working groups of the international medical informatics associations. RESULTS: There are generalisable lessons for primary care derived from the literature about implementing best evidence, feedback and the theory of diffusion of innovation. The principles identified are: (1) Engage and support local innovators - i.e. those most likely to adopt change, demonstrate the evidence-base for the intervention and the form of feedback most acceptable to them (2) Model the clinical context in which quality improvement is required; (3) Develop an understanding of the health system, its culture and management system; and, (4) Identify and address technical issues relating to computer use and coding. CONCLUSIONS: Feedback is most effective when: clinically relevant, educationally orientated, given by peers, and sensitive to the socio-technical context.

Feedback↗

The importance of internal quality control data in National External Quality Assessment schemes. Plasma progesterone assays.

Co-ordinators of external quality assessment schemes in the U.K. despatch samples of quality control material to participant laboratories at frequent intervals to assess laboratory performance. We show, via a controlled experiment on the plasma progesterone assay, that the current analysis performed by the external assessors is inadequate and often leads to erroneous conclusions about a laboratory's performance. It is concluded that for a proper assessment of a laboratory's performance, the external assessor should prepare large pools of plasma and distribute them to all participants in the scheme to use as internal quality control material.

Chemistry Techniques, Analytical↗

Quality assurance for screening mammography data collection systems in 22 countries.

OBJECTIVES: To document the mammography data that are gathered by the organized screening programs participating in the International Breast Cancer Screening Network (IBSN), the nature of their procedures for data quality assurance, and the measures used to assess program performance and impact. METHODS: A detailed questionnaire covering multiple aspects of quality assurance in screening mammography was mailed to IBSN representatives in 23 countries. RESULTS: Countries collect a wealth of screening mammography data, much of it computerized. Most countries have designated staff for data quality assurance. All provide staff training, and most have documentation requirements for data collection. Nearly all have one or more procedures to maintain data confidentiality. Countries are heterogeneous in collecting and assessing data to monitor screening program performance and impact. CONCLUSIONS: Demonstrating that population-based screening mammography reduces breast cancer mortality requires collection of high-quality data on key aspects of the multi-step screening process. Assuring the quality of data collection systems for screening mammography programs is an important and evolving area for IBSN countries.

Breast Neoplasms↗