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PubMedDate not supplied

Expressions of accuracy in the evaluation of biomedical instrumentation.

This review discusses and compares the most common and appropriate expressions and representations of accuracy in the evaluation of biomedical instrumentation. Instruments used to measure blood pressure illustrate the various expressions of accuracy in common use. Accuracy of biomedical instruments can be defined as a measure of system error. In system error there is a consistent, systematic bias inherent in the method or instrument being tested. Two cases or conditions in which accuracy may be determined were identified and analyzed: 1) static or single-target conditions, and 2) dynamic or continuum-of-target conditions. Expressions of accuracy tested included the mean difference/standard deviation (MD/SD) method and the regression analysis (RA) method. In the static, single-target cases examined, the MD/SD method proved acceptable. In the dynamic, continuum-of-targets cases examined, the RA method proved the most accurate and useful expression of instrumental accuracy. The MD/SD method could be significantly misleading in these dynamic target cases. Since the majority of biomedical instruments are used in dynamic or continuum-of-targets situations, RA is, generally, the method of choice.

Blood Pressure Determination↗
PubMed1998

Metamemory accuracy: effects of feedback and the stability of individual differences.

This study addressed two questions about metamemory accuracy: how feedback about recall performance affects confidence-recall accuracy and whether individual differences in confidence-recall accuracy are stable across different sets of test items. College students answered general knowledge questions and made confidence ratings about the correctness of the answers. Half the students were told whether their answers were correct. All students answered half the questions a second time. The results show that feedback did not produce a general improvement in metamemory accuracy; the improvement was specific to the questions for which feedback was provided. Also, individual students' metamemory accuracy showed moderate alternate-forms stability when each test was made up of 250 items. Therefore, researchers studying individual differences in metamemory accuracy on recall tasks should use tests that yield several hundred responses.

Adult↗
PubMed1998

Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

Bias↗
PubMed1998

Meta-analyses of studies of the diagnostic accuracy of laboratory tests: a review of the concepts and methods.

OBJECTIVE: To provide practicing pathologists and other laboratory professionals with the necessary background for reading and evaluating published reports of meta-analyses of studies of the diagnostic accuracy of laboratory tests. STUDY SELECTION: English language literature, 1980 to present, pertaining to the rationale, objectives, and interpretation of meta-analyses of randomized controlled trials, and meta-analyses of studies of the diagnostic accuracy of laboratory tests. CONCLUSIONS: Meta-analysis has several applications in the investigation of the diagnostic accuracy of laboratory tests. It can improve the quality of future primary studies by drawing attention to the methodologic deficiencies of existing reports; it can identify reasons for the variation in the results of those reports; and it can generate valid summary estimates of the diagnostic accuracy of laboratory tests based on all completed investigations, providing that the available primary studies are of high scientific validity. Several statistical techniques for integrating data from reports on diagnostic test accuracy have either been developed or are under development, but meta-analysis is often limited by the poor quality of the primary studies and the effect of publication bias. Meta-analysis can evolve into a reliable tool for assessing the accuracy of laboratory tests if both investigators and editors strive to improve the quality of the primary studies and to reduce the extent of publication bias in this area of the literature.

Clinical Laboratory Techniques↗
PubMed2003

Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative.

OBJECTIVE: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy in order to allow readers to assess the potential for bias in the study and to evaluate its generalisability. METHODS: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organizations shortened this list during a two-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. RESULTS: The search for published guidelines regarding diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to 25 items, using evidence on bias whenever available. A prototypical flow diagram provides information about the method of patient recruitment, the order of test execution and the numbers of patients undergoing the test under evaluation, the reference standard or both. CONCLUSIONS: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of the clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2003

Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative.

AIM: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy in order to allow readers to assess the potential for bias in a study and to evaluate the general isability of its results. METHODS: The standards for reporting of diagnostic accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a 2 day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. RESULTS: The search for published guidelines about diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25-item checklist, by using evidence whenever available. A prototype of a flow diagram provides information about the method of recruitment of patients, the order of test execution and the numbers of patients undergoing the test under evaluation, the reference standard, or both. CONCLUSIONS: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2003

Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative.

OBJECTIVE: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy, to allow readers to assess the potential for bias in a study, and to evaluate a study's generalisability. METHODS: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a two day consensus meeting, with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. RESULTS: The search for published guidelines about diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25 item checklist, by using evidence, whenever available. A prototype of a flow diagram provides information about the method of patient recruitment, the order of test execution, and the numbers of patients undergoing the test under evaluation and the reference standard, or both. CONCLUSIONS: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the STARD checklist and flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2003

Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD Initiative.

OBJECTIVE: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy, to allow readers to assess the potential for bias in the study and to evaluate its generalisability. METHODS: The Standards for Reporting of Diagnostic Accuracy (STARD) steering group searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a two-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. RESULTS: The search for published guidelines regarding diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25-item checklist, using evidence, whenever available. A prototypical flow diagram provides information about the method of patient recruitment, the order of test execution and the numbers of patients undergoing the test under evaluation, the reference standard or both. CONCLUSIONS: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of the clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2003

Toward complete and accurate reporting of studies of diagnostic accuracy. The STARD initiative.

Our objective was to improve the accuracy and completeness of reporting of studies of diagnostic accuracy, to allow readers to assess the potential for bias in the study, and to evaluate its generalizability. The Standards for Reporting of Diagnostic Accuracy Steering Committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organizations shortened this list during a 2-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. The search for published guidelines regarding diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25-item checklist, using evidence whenever available. A prototypical flow diagram provides information about the method of patient recruitment, the order of test execution, and the numbers of patients undergoing the test under evaluation, the reference standard, or both. Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve, to the advantage of clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2003

Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative.

OBJECTIVE: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy in order to allow readers to assess the potential for bias in a study and to evaluate the generalisability of its results. METHODS: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a 2-day consensus meeting with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. RESULTS: The search for published guidelines about diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25-item checklist, by using evidence whenever available. A prototype of a flow diagram provides information about the method of recruitment of patients, the order of test execution and the numbers of patients undergoing the test under evaluation, the reference standard, or both. CONCLUSIONS: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the checklist and the flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.

Algorithms↗
PubMed2001

A comparison of dermatologists' and primary care physicians' accuracy in diagnosing melanoma: a systematic review.

OBJECTIVE: To compare the accuracy of dermatologists and primary care physicians (PCPs) in identifying pigmented lesions suggestive of melanoma and making the appropriate management decision to perform a biopsy or to refer the patient to a specialist. DATA SOURCES: Studies published between January 1966 and October 1999 in the MEDLINE, EMBASE, and CancerLit databases; reference lists of identified studies; abstracts from recent conference proceedings; and direct contact with investigators. Medical subject headings included melanoma, diagnosis, screening, primary care, family practitioner, general practitioner, internal medicine, dermatologist, and skin specialist. Articles were restricted to those involving human subjects. STUDY SELECTION: Studies that presented sufficient data to determine the sensitivity and specificity of dermatologists' or PCPs' ability to correctly diagnose lesions suggestive of melanoma and to perform biopsies on or refer patients with such lesions. DATA EXTRACTION: Two reviewers independently abstracted data regarding the sensitivity and specificity of the dermatologists and PCPs for diagnostic and biopsy or referral accuracy. Disagreements were resolved by discussion. The quality of the studies was also evaluated. DATA SYNTHESIS: Thirty-two studies met inclusion criteria; 10 were prospective studies. For diagnostic accuracy, sensitivity was 0.81 to 1.00 for dermatologists and 0.42 to 1.00 for PCPs. None of the studies reported specificity for dermatologists; one reported specificity for PCPs (0.98). For biopsy or referral accuracy, sensitivity ranged from 0.82 to 1.00 for dermatologists and 0.70 to 0.88 for PCPs; specificity, 0.70 to 0.89 for dermatologists and 0.70 to 0.87 for PCPs. Receiver operating characteristic curves for biopsy or referral ability were inconclusive. CONCLUSIONS: The published data are inadequate to demonstrate differences in dermatologists' and PCPs' diagnostic and biopsy or referral accuracy of lesions suggestive of melanoma. We offer study design suggestions for future studies.

Clinical Competence↗
PubMed1997

Artificial neural networks improve the accuracy of cancer survival prediction.

BACKGROUND: The TNM staging system originated as a response to the need for an accurate, consistent, universal cancer outcome prediction system. Since the TNM staging system was introduced in the 1950s, new prognostic factors have been identified and new methods for integrating prognostic factors have been developed. This study compares the prediction accuracy of the TNM staging system with that of artificial neural network statistical models. METHODS: For 5-year survival of patients with breast or colorectal carcinoma, the authors compared the TNM staging system's predictive accuracy with that of artificial neural networks (ANN). The area under the receiver operating characteristic curve, as applied to an independent validation data set, was the measure of accuracy. RESULTS: For the American College of Surgeons' Patient Care Evaluation (PCE) data set, using only the TNM variables (tumor size, number of positive regional lymph nodes, and distant metastasis), the artificial neural network's predictions of the 5-year survival of patients with breast carcinoma were significantly more accurate than those of the TNM staging system (TNM, 0.720; ANN, 0.770; P < 0.001). For the National Cancer Institute's Surveillance, Epidemiology, and End Results breast carcinoma data set, using only the TNM variables, the artificial neural network's predictions of 10-year survival were significantly more accurate than those of the TNM staging system (TNM, 0.692; ANN, 0.730; P < 0.01). For the PCE colorectal data set, using only the TNM variables, the artificial neural network's predictions of the 5-year survival of patients with colorectal carcinoma were significantly more accurate than those of the TNM staging system (TNM, 0.737; ANN, 0.815; P < 0.001). Adding commonly collected demographic and anatomic variables to the TNM variables further increased the accuracy of the artificial neural network's predictions of breast carcinoma survival (0.784) and colorectal carcinoma survival (0.869). CONCLUSIONS: Artificial neural networks are significantly more accurate than the TNM staging system when both use the TNM prognostic factors alone. New prognostic factors can be added to artificial neural networks to increase prognostic accuracy further. These results are robust across different data sets and cancer sites.

Breast Neoplasms↗
PubMed2003

Assessment of the accuracy of transrectal ultrasonography in anorectal neoplasia.

BACKGROUND: Accurate preoperative staging of anorectal neoplasia is required to identify patients for whom local excision or adjuvant therapy may be appropriate. The objectives of this study were to review the accuracy of endoluminal transrectal ultrasonography (TRUS) in the staging of rectal cancers and to determine the learning curve before optimal staging accuracy can be achieved. METHODS: The results of all TRUS examinations for the assessment of anorectal neoplasia performed by two colorectal surgeons at two teaching hospitals of the University of Sydney from 1991 to 2001 were collected prospectively. RESULTS: Of the 433 patients examined by TRUS, 356 were included, of whom 263 (73.9 per cent) had nodal status assessed histologically. Of the 77 patients excluded, 50 had undergone radiotherapy before operation. TRUS achieved excellent accuracy when compared with histopathology reports using kappa statistics for standard Union Internacional Contra la Cancrum (UICC) staging (kappa = 0.89), tumour wall penetration (kappa = 0.70), lymph node detection (kappa = 0.66) and a proposed new staging system (kappa = 0.94). In addition, the increase in TRUS accuracy with operator experience demonstrates the need to perform 50 or more procedures before optimal accuracy is achieved. CONCLUSION: TRUS provides an appropriate investigation with which to select patients with T1 tumours for local excision, and patients with T3 or T4 tumours for preoperative radiotherapy. The relative inaccuracy of staging T2 tumours by TRUS has led to a proposed alternative ultrasonographic staging system.

Anus Neoplasms↗
PubMed2002

Predicting the home location of serial offenders: a preliminary comparison of the accuracy of human judges with a geographic profiling system.

The accuracy with which human judges, before and after 'training', could predict the likely home location of serial offenders was compared with predictions produced by a geographic profiling system known as Dragnet. All predictions were derived from ten spatial displays, one for each of ten different U.S. serial murderers, indicating five crime locations. In all conditions participants were asked to place an 'X' on each spatial display corresponding to where they thought the offender lived. In the control condition, a comparison was made between the accuracy of these predictions for 21 participants on two separate occasions a few minutes apart. In the experimental condition, between their first and second predictions the 21 participants were given two heuristics to follow--distance-decay and circle hypothesis. Results showed that participants with no previous knowledge of geographic profiling were able to use the two heuristics to improve the accuracy of their predictions. The overall accuracy of the second set of predictions for the experimental group was also not significantly different from the accuracy of predictions generated by Dragnet.

Adult↗
PubMed1990

Accuracy of subjective and computer-assisted assessments of angiographic left ventricular regional wall motion.

To evaluate the accuracy of angiographic methods for analysis of left ventricular regional wall motion, we measured the ability of a carefully performed subjective analysis (three independent observers) and that of three computer-assisted methods (centerline, radial, and area) to detect the presence of significant coronary artery disease. Normal ranges were established in 90 studies showing normal wall motion, and accuracy was tested in a second, consecutive series of 43 ventriculograms. The results show that the subjective method best separated those regions with from those without significant coronary disease. The subjective method also demonstrated sensitivity comparable to the centerline and radial methods. Among the computer-assisted methods, the area method was least sensitive but most specific for both anterior and inferior region coronary disease. The centerline and radial methods were highly sensitive, but less specific. When coronary disease was defined by electrocardiographic Q-waves, the area method had superior accuracy. Further analysis showed the following: 1) For the centerline and radial methods, long-axis reregistration of the end-systolic frame resulted in loss of sensitivity but increased specificity for anterior wall coronary disease, and little change in analysis of the inferior wall; 2) inclusion or exclusion of the apex had little effect on predictive accuracy for anterior wall coronary disease; 3) as expected, sensitivity and specificity results of all methods were dependent on the selection of a normal range cutoff value; but when performance was optimized, the subjective and area methods had a higher overall predictive accuracy than the centerline method; 4) It is likely that all three computer-assisted methods could be calibrated to give indications of degrees of hypokinesis, as their results correlated well with subjective observers' evaluations over the entire range of scores. These results should assist in selection of the optimal method for regional wall motion analysis in clinical and research applications. As currently applied, the area method is the most specific of the computer-assisted methods tested; the centerline and radial methods have highest sensitivity and therefore are most suited to detection of mild degrees of hypokinesis.

Angiocardiography↗
PubMed2000

Registration of functional and anatomical MRI: accuracy assessment and application in navigated neurosurgery.

OBJECTIVE: A procedure for acquisition, automated registration, and fusion of functional and anatomical magnetic resonance images is presented. Its accuracy is quantitatively assessed using a publicly available gold standard. A patient case is used to illustrate the technique's clinical usefulness in image-guided neurosurgery. MATERIALS AND METHODS: Before and after functional MRI (fMRI) acquisition, additional anatomical images were acquired at spatial locations identical to those of the functional images (5-10 slices) for the purpose of voxel-based image registration. Registration accuracy of the anatomical volumes and high-resolution 3D MRI volumes (MP-RAGE imaging) was quantified using adapted data (8 patients) originating from the Vanderbilt Retrospective Registration Evaluation Project (NIH project 1 R01 NS33926-02). Selecting three subsets of slices from that data (5 slices/6 mm slice distance, 10 slices/3 mm distance, and 10 slices/6 mm distance), the small number of images available from fMRI acquisition was taken into account. Accuracies in registering these sparse data sets were then compared to the accuracy achieved using complete data. For clinical patient data (16 patients), fMRI images were fused with MP-RAGE images, thereby integrating anatomical images with information about the locations of functional areas. The resulting images were used for planning and navigation during tumor resections using an operating microscope (MKM, Zeiss). RESULTS: Quantitative analysis showed no loss of registration accuracy due to a reduced number of slices, regardless of whether 5 or 10 slices were used. For small-volume coverage in the anatomical images (thickness 24 mm), registration of one patient failed, and this could easily be identified by visual inspection. No failures were experienced when 54 mm was covered. In the clinical environment, all 16 interventions using fused fMRI and MRI data were successful. CONCLUSIONS: Automatic registration of functional and high-resolution anatomical MRI was found to be sufficiently accurate and reliable for use in stereotactic neurosurgery.

Adolescent↗
PubMed2003

Accuracy of cartilage and subchondral bone spatial thickness distribution from MRI.

PURPOSE: To assess three-dimensional measurement accuracy of articular cartilage (AC) and subchondral bone (SB) thickness from MRI. MATERIALS AND METHODS: A computer program was used to calculate AC and SB thickness from MRI (three-dimensional spoiled gradient echo (SPGR),.31-mm resolution, 1-mm slice thickness) of six adult femoral heads. Specimens were imaged in five anatomical planes ranging between +30 degrees to -30 degrees from neutral and cut into 2-mm thick sections along the five anatomical planes. Faxitron x-ray was used to produce microradiographic (.05-mm resolution) images of the sections. RESULTS: In-plane measurement accuracy was.165 +/-.108 mm for AC thickness and.387 +/-.174 mm for SB thickness. Taking into account chemical-shift misregistration in SB thickness, accuracy of measurements improved to.213 +/- 128 mm. Out-of-plane (three-dimensional) thickness accuracy of the model, assessed by numerical simulation, was.015 mm. However, three-dimensional thickness errors in specimens were.319 +/-.256 mm for AC and.253 +/-.183 mm for SB thickness. CONCLUSION: Errors in three-dimensional AC thickness were attributed to volume-averaging effects caused by oblique intersection of the image plane with the joint surface. Errors in three-dimensional SB thickness were attributed to chemical-shift artifact. We conclude that accuracy of AC thickness is within clinically acceptable standards but that more sophisticated pulse sequences are needed to improve the measurement of SB thickness.

Adult↗
PubMedDate not supplied

Classification of 1H MR spectra of human brain neoplasms: the influence of preprocessing and computerized consensus diagnosis on classification accuracy.

We study how classification accuracy can be improved when both different data preprocessing methods and computerized consensus diagnosis (CCD) are applied to 1H magnetic resonance (MR) spectra of astrocytomas, meningiomas, and epileptic brain tissue. The MR spectra (360 MHz, 37 degrees C) of tissue specimens (biopsies) from subjects with meningiomas (95; 26 cases), astrocytomas (74; 26 cases), and epilepsy (37; 8 cases) were preprocessed by several methods. Each data set was partitioned into training and validation sets. Robust classification was carried out via linear discriminant analysis (LDA), artificial neural nets (NN), and CCD, and the results were compared with histopathological diagnosis of the MR specimens. Normalization of the relevant spectral regions affects classification accuracy significantly. The spectra-based average three-class classification accuracies of LDA and NN increased from 81.7% (unnormalized data sets) to 89.9% (normalized). CCD increased the classification accuracy of the normalized sets to an average of 91.8%. CCD invariably decreases the fraction of unclassifiable spectra. The same trends prevail, with improved results, for case-based classification. Preprocessing the 1H MR spectra is essential for accurate and reliable classification of astrocytomas, meningiomas, and nontumorous epileptic brain tissue. CCD improves classification accuracy, with an attendant decrease in the fraction of unclassifiable spectra or cases.

Astrocytoma↗