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PubMed2000

Assay of prick test inoculum volume. I. Use and reliability of a gamma camera-based method.

INTRODUCTION: In dermatology and allergy there are clinical research circumstances where very small amounts of substances introduced into the skin have to be measured "in vivo." An example is the assay of reagents injected by prick test. As injected volumes are very small, it is necessary to use indicators that can be measured at very low concentrations. In in vitro studies, gamma-emitting radioisotopes have been shown suitable for use as the indicators. In in vivo studies, except for instruments devised for specific research requirements, the measurement of small sources is taken with a common gamma camera. OBJECTIVE: The purpose of the present study is to evaluate the experimental reliability of a gamma camera-based method to measure microvolumes labeled with radioisotopes and its suitable application in vivo studies. METHODS: Using a solution of 99m Tc-pertechnetate, we prepared, with precision pipettes, some sets of scalar volumes ranging from 1 micro to 200 picoliters, which correspond to activities between some micros and some hundreds of picocuries. The volumes were measured with a gamma camera both with and without a collimator. The overall reliability of the method under different experimental conditions was evaluated for sensitivity, precision, and accuracy. Last, a blind measurement was taken as a final check on the overall reliability of the method. RESULTS: The volume-activity correlation appeared to be linear, with a Spearman coefficient higher than 0.99. The correlation straight lines of the measurements taken with and without a collimator proved that, in both cases, the linearity of the system did not change. The method showed a high degree of precision and accuracy. The maximum variation coefficient never exceeded 1.5% and the standard error 2%. The sampling error of the measured volumes was less than 8% in all the sets: up to 7% was due to the manual operations and to the technical characteristics of the micropipettes. The gamma camera measurement error ranged from 1% to 3%. The blind tests experimentally confirmed the overall reliability of the method. CONCLUSIONS: The method we studied proved highly reliable and inexpensive. Measurement errors are almost exclusively due to sampling errors. The gamma camera is a device any nuclear medicine department is equipped with, and a solution of 99m Tc-pertechnetate is readily available.

Evaluation Studies as Topic↗
PubMed2000

Prostate biopsy grading errors: a sampling problem?

Potential reasons for discordance between the Gleason score in biopsies and surgical specimens are: 1) pathological interpretation bias, and 2) sampling effects. The importance of sampling effects in grading errors was examined in a series where the number of biopsy cores obtained was high. Biopsies were obtained using a technique whereby 18 directed cores were systematically obtained and mapped out within the gland. Gleason scores from biopsies and matched prostatectomy specimens were compared among 28 consecutive patients with localized prostate cancer. A pooled database from 10 series (n = 2,687) served as a baseline for comparison in the accuracy of Gleason score grading. With the present biopsy technique, an exact Gleason score match was achieved in 57% of cases, compared with the pooled database (PD) mean of 42% (P = 0.055), and was within 1 point in 93% of cases compared with 78% (PD) (P = 0.029). Upgrading of biopsies was seen in 35% of cases, compared with 43% (PD) (P = 0.19). With respect to Gleason score 7, an exact match was present in 78% of cases, compared with 63% (PD) (P = 0.17), and upgrading was 0%, compared with 20% (PD) (P = 0.07). The data suggest a significant reduction in grade errors by minimizing sampling effects, one that it is of the same order of magnitude as the reduction achieved from consensus pathologic evaluation. In our study, seven patients (25%) would have had their cancers missed altogether with sextant biopsies. Sampling effects may contribute significantly to grading errors in prostate needle biopsies, although a larger study is needed to confirm this. A methodology which adopts a higher number of cores combined with a consensus pathologic evaluation could potentially reduce grading errors substantially. The optimal number of cores remains to be determined in a larger study. Int. J. Cancer (Radiat. Oncol. Invest.) 90, 326-330 (2000).

Biopsy, Needle↗
PubMed2000

Effects of measurement error and sampling resolution on estimates of atrial tissue recovery parameters.

We studied the effect of sampling resolution and measurement error on estimates of tissue recovery parameters using experimental and simulated data. Action potential duration (APD) was estimated from monophasic action potentials recorded at 250 sites (delta x = 3.5 mm) on the endocardium of the canine right atrium (n = 8) during control and acetylcholine perfusion. APD distributions were also simulated using a random number generator, then scaled and filtered to physiological values. The following parameters were estimated at increasing APD sampling interval and measurement error: mean APD, standard deviation of APD, mean APD gradient, standard deviation of APD gradient, APD wavelength, and APD correlation length. We found that large errors can result from APDs collected at inadequate sampling intervals and adequate sampling intervals may be 3-6 times less than the Nyquist interval. Large parameter errors also resulted from data with relatively low levels of measurement error. The effect of measurement error was dependent upon the standard deviation of APD, sampling resolution, and APD wavelength. Inadequate sampling resolution was the largest source of error in experimental parameter estimates. Estimates of mean and standard deviation of APD gradient decreased with spacing as estimates of correlation length and wavelength increased. Careful selection of spacing interval, taking into account the spatial complexity of recovery, as well as considerably low measurement errors will produce accurate estimates of gradients, correlation length, and wavelength.

Acetylcholine↗
PubMed2004

Predicting and correcting bias caused by measurement error in line transect sampling using multiplicative error models.

Line transect sampling is one of the most widely used methods for animal abundance assessment. Standard estimation methods assume certain detection on the transect, no animal movement, and no measurement errors. Failure of the assumptions can cause substantial bias. In this work, the effect of error measurement on line transect estimators is investigated. Based on considerations of the process generating the errors, a multiplicative error model is presented and a simple way of correcting estimates based on knowledge of the error distribution is proposed. Using beta models for the error distribution, the effect of errors and of the proposed correction is assessed by simulation. Adequate confidence intervals for the corrected estimates are obtained using a bootstrap variance estimate for the correction and the delta method. As noted by Chen (1998, Biometrics 54, 899-908), even unbiased estimators of the distances might lead to biased density estimators, depending on the actual error distribution. In contrast with the findings of Chen, who used an additive model, unbiased estimation of distances, given a multiplicative model, lead to overestimation of density. Some error distributions result in observed distance distributions that make efficient estimation impossible, by removing the shoulder present in the original detection function. This indicates the need to improve field methods to reduce measurement error. An application of the new methods to a real data set is presented.

Animals↗
PubMed1995

Estimating stand transpiration in a Eucalyptus populnea woodland with the heat pulse method: measurement errors and sampling strategies.

Sap flow measurement techniques, such as the heat pulse (compensation) method, are practical means for estimating the water use of individual trees and are often the only reasonable alternative for measuring forest and woodland transpiration in complex heterogeneous terrain. The need to scale estimates of water use from a sample of individual stems to a stand (population) of known area may be satisfied by applying scalars of flux based on tree size or domain. We estimated the aggregate errors in applying the heat pulse technique to the estimation of stand transpiration in a poplar box (Eucalyptus populnea F.J. Muell.) woodland in southeastern Queensland, Australia, by a combination of precision analyses, experimental validation and Monte Carlo simulations of sampling errors. Errors in sap flux density measurements were approximately 13%. The potential error in the flux estimates for individual stems with stratified sampling of sap flux density with depth and bole quadrant based on four sensors was an additional 25%. Conducting wood area, diameter at 1.3 m, leaf area and domain based on Ecological Field Theory all proved excellent scalars of flux at the stand level. With a sample size of six trees stratified by diameter, coefficients of variation in scaling to the stand level were approximately 5% for any of these scalars. The greatest potential source of error in estimating stand transpiration by the heat pulse method was in the measurement of the fluxes of individual stems; scaling these measurements to a homogeneous stand of trees involved less uncertainty.

Journal Article↗
PubMed2025

Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles.

In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.

Journal Article↗
PubMed2001

Influence of errors in sampling time and in activity measurement on the single sample clearance determination.

INTRODUCTION: Plasma clearance rate of 51Cr-EDTA estimated by using one blood sample is commonly used for the calculation of glomerular filtration rate. AIM: To estimate the error on single-sample clearance determination induced by errors in sampling time and activity measurement, and to compare it with the error observed on the clearance determination obtained using the slope-intercept method. METHODS: Forty-five adult patients were chosen from a data base of 51Cr-EDTA plasma clearance values determined by using two blood samples taken around 2 and 4 h. Patients were selected in such a way as to include clearances from 30 ml.min-1 to 155 ml.min-1, with steps of 3 ml.min-1. Based on the slope and the intercept of the slope with the y-axis, the plasma concentration at exactly 2 and 4 h was determined. Normally distributed random errors were then introduced in the sampling time (SD of 0, 1 and 2 min) as well as in the activity measurement (SD of 0, 1, 2 and 5%). Then, clearance was calculated using two single-sample methods (i.e. the algorithms of Groth and Tauxe), and the slope-intercept method, which requires two blood samples. For each setting, the simulation was repeated 200 times. The effects on clearance of a random error on the time sampling and/or the activity measurement were then evaluated. RESULTS: The error on single-sample clearance induced by a 2 min error in sampling time associated with a 5% error in activity measurement was negligible. For all clearance levels, the SD of the error on the calculated clearance was less than 3.8 ml.min-1. Whatever algorithm was chosen, the errors on the single-sample clearance were systematically lower than those observed with the slope-intercept method, for the whole clearance range. CONCLUSION: Errors in sampling time and in activity measurement induced only a very small error on the single-sample EDTA clearance, which is systematically lower compared to that observed on the slope-intercept method using two blood samples.

Adult↗
PubMed1986

Some coverage error models for census data.

"Alternative models are presented for representing coverage error in surveys and censuses of human populations. The models are related to the capture-recapture models used in wildlife applications and to the dual-system models employed in the vital events literature. Estimation methodologies are discussed for one of the coverage error models." After a discussion of the theory underlying the methodology, "distinctions are made between two kinds of error: (a) sampling error and (b) error associated with the model. An example involving data from the 1980 U.S. census is presented. The problem of adjusting census and survey data for coverage error is also discussed."

Americas↗
PubMed1986

Frozen-section diagnosis in surgical pathology. A prospective analysis of 526 frozen sections.

Five hundred eighty-six consecutive frozen-section consultations performed during a 1-year period were studied prospectively in order to assess the accuracy of the method and develop a quality control mechanism. The overall accuracy was 97.1%. The accuracy of the method with breast lesions was 97.9%. Specimens from the gastrointestinal tract and thyroid were incorrectly interpreted in 5% of the cases. The accuracy for lymph node specimens was 96.2%, with more than 50% consulted out of curiosity. The authors conclude that frozen section of lymph node is not recommended. Most of the errors were sampling errors made by the pathologist. The authors therefore conclude that in clinically suspected malignancy, more than one sample must be examined in order to decrease the false-negative diagnosis in frozen section.

Breast Neoplasms↗
PubMed2002

The fragility of cardiovascular clinical trial results.

BACKGROUND: Clinical trials that have their prospective analysis plan altered are difficult to interpret. METHODS AND RESULTS: After providing 4 examples of problematic trial results that have had their findings reversed, the necessity of a fixed research protocol is developed. Investigators generally wish to extend the results from their research sample to the larger population; however, this delicate extension is complicated by the presence of sampling error. No computational or statistical tools can remove sampling error--the most that researchers can do is to provide to the medical and regulatory communities a measure of the distorting effect that sampling error can produce. Investigators accomplish this by providing an estimate of how likely it is that the population produced a misleading sample for them to study. However, studies in which the data determine the analysis plan damage these estimators. When they are damaged, these estimators produce untrustworthy assessments of the degree to which the study results reflect the population findings. CONCLUSIONS: The way to avoid these complications is to design the experiment carefully, then carefully execute the experiment as it was designed.

Cardiovascular Agents↗
PubMed1979

Collaborative study of reference vinyl chloride charcoal tubes.

The reference vinyl chloride charcoal tubes generated by a permeation technique are evaluated by collaborative testing. The statistical analysis of Youden's method provides an estimate of replication error, sample generation error, and interlaboratory error.

Air Pollutants↗
PubMed2001

Effects of uncertainties on exposure estimates to methylmercury: a Monte Carlo analysis of exposure biomarkers versus dietary recall estimation.

This article presents a general model for estimating population heterogeneity and "lack of knowledge" uncertainty in methylmercury (MeHg) exposure assessments using two-dimensional Monte Carlo analysis. Using data from fish-consuming populations in Bangladesh, Brazil, Sweden, and the United Kingdom, predictive model estimates of dietary MeHg exposures were compared against those derived from biomarkers (i.e., [Hg]hair and [Hg]blood). By disaggregating parameter uncertainty into components (i.e., population heterogeneity, measurement error, recall error, and sampling error) estimates were obtained of the contribution of each component to the overall uncertainty. Steady-state diet:hair and diet:blood MeHg exposure ratios were estimated for each population and were used to develop distributions useful for conducting biomarker-based probabilistic assessments of MeHg exposure. The 5th and 95th percentile modeled MeHg exposure estimates around mean population exposure from each of the four study populations are presented to demonstrate lack of knowledge uncertainty about a best estimate for a true mean. Results from a U.K. study population showed that a predictive dietary model resulted in a 74% lower lack of knowledge uncertainty around a central mean estimate relative to a hair biomarker model, and also in a 31% lower lack of knowledge uncertainty around central mean estimate relative to a blood biomarker model. Similar results were obtained for the Brazil and Bangladesh populations. Such analyses, used here to evaluate alternative models of dietary MeHg exposure, can be used to refine exposure instruments, improve information used in site management and remediation decision making, and identify sources of uncertainty in risk estimates.

Algorithms↗
PubMed2005

Histologic variation of grade and stage of non-alcoholic fatty liver disease in liver biopsies.

BACKGROUND: Sampling error regarding disease grade and stage has been ascribed to needle liver biopsies in patients with chronic liver disease. Although several studies evaluating sampling error in liver biopsies exist, none have investigated this phenomenon in patients with non-alcoholic fatty liver disease (NAFLD). This study aims to determine the rate and extent of sampling error in liver biopsies obtained from patients undergoing Roux-en-Y gastric bypass (RYGBP) surgery for morbid obesity. METHODS: 10 morbidly obese patients underwent simultaneous liver biopsies from the right and left hepatic lobes during an open examination preceding the RYGBP procedure. The biopsies were subsequently randomly evaluated and then blindly re-evaluated by a liver pathologist. Degrees of inflammatory activity and fibrosis were determined and scored for each sample using a semi-quantitative system with 3 grades and 4 stages. RESULTS: No grading differences were observed, and 3 patients (30%) had a difference of at least 1 stage between the right and left lobes. One patient had a 2-stage difference in paired samples, with significantly different biopsy sizes and number of portal tracts. Blinded histologic re-evaluation did not result in grading or staging scores that differed from the original evaluation. CONCLUSIONS: Liver biopsy samples taken from the right and left hepatic lobes showed similar grades of disease activity, but differed in histopathologic staging in 30% of the NAFLD patients. Obtaining an adequately sized biopsy (>1.0 cm in length with >10 portal tracts) greatly reduces sampling error.

Adult↗
PubMed1992

Perimetric follow-up in glaucoma with a reduced set of test points.

The global mean defect (GM) is probably the most useful visual field index for glaucoma follow-up. We compared 50 regional subsets of test locations to estimate the GM. Using the data on 424 automated fields of 257 patients with either primary open-angle glaucoma or ocular hypertension, we calculated the partial sample error of the regional mean defect as compared with the GM. In many regions, the measured sample error was greater than expected for a representative sample of points. Some sample errors were up to 5 times larger (regions "upper hemifield" and "lower hemifield"). Only a few subsets proved to be representative of the whole field, namely, regions "ring 3" (10 degrees-15 degrees), "ring 4" (15 degrees-20 degrees) and "ring 5" (20 degrees-25 degrees). The use of such programs for follow-up is very accurate for staging. Moreover, theoretical calculations reveal that trend analysis is even more significant if the reduction in examination time is combined with a proportional increase in examination frequency.

Adolescent↗
PubMed1992

Estimates from two survey designs: national hospital discharge survey.

The methodology for the National Hospital Discharge Survey (NHDS) has been revised in several ways. These revisions, which were implemented for the 1988 NHDS, included adoption of a different hospital sampling frame, changes in the sampling design (in particular the implementation of a three-stage design), increased use of data purchased from abstracting service organizations, and adjustments to the estimation procedures used to derive the national estimates. To investigate the effects of these revisions on the estimates of hospital use from the NHDS, data were collected from January through March of 1988 using both the old and the new survey methods. This study compared estimates based on the old and the new survey methods for a variety of hospital and patient characteristics. Although few estimates were identical across survey methodologies, most of the variations could be attributed to sampling error. Estimates from two different samples of the same population would be expected to vary by chance even if precisely the same methods were used to collect and process the data. Because probability samples were used for the old and new survey methodologies, sampling error could be measured. Approximate relative standard errors were calculated for the estimates using the old and new survey methods. Taking these errors into account, less than 10 percent of the estimates were found to differ across survey methodologies at the 0.05 level of significance. Because a large number of comparisons were made, 5 percent of the estimates could have been found to be significantly different by chance alone. When there were statistically significant differences in nonmedical data, the new methods appeared to produce more accurate estimates than the old methods did. Race was more likely to be reported using the new methods. "New" estimates for hospitals in the West Region and government-owned hospitals were more similar than the corresponding "old" estimates to data from the census of hospitals conducted by the American Hospital Association. The numerous significant differences in estimates for bed size categories between the two survey methodologies reflected the change in the universe and definition of beds for the new survey. Few statistically significant differences were found in the medical data using the old and the new survey methods. Two main differences, in estimates for cataract and alcohol dependence syndrome, may have resulted from problems with the new survey. A measurement error, reporting outpatients to the NHDS, is one possible explanation of the higher estimates for diagnosis of cataract using the new survey methods.(ABSTRACT TRUNCATED AT 400 WORDS)

Bias↗
PubMed1980

Estimation and comparison of parameters in stochastic growth models for barn owls.

Alternative methods for parameter estimation and the incorporation of stochasticity into growth models are investigated and compared to the commonly used sampling error model in which error terms are simply added-on to the integrated form of the growth equation. A process error model, in which the process of growth is assumed to have stochastic variation or error incorporated within it, was found to be more appropriate for use with nonlinear estimation procedures based on a minimization of sigma ei2. The process error model tended to minimize and/or eliminate the autocorrelation of residuals, which were characteristic of the sampling error model. These analyses further suggest that while the commonly used sampling error growth model may indeed provide unbiased parameter estimates, the estimated variances of such estimates are likely to be unwarrantedly low, thus raising questions as to the validity of any statistical comparisons based on such analyses. The procedure is illustrated with growth data from captive-reared sibling nestling barn owls, using the Richards' growth curve. These analyses suggest that both growth rate and growth form are subject to a higher degree of genetic control than is asymptotic weight which showed a greater tendency to vary according to the hatching order of the nestlings.

Age Factors↗
PubMed1994

Convenience or calamity? Pharmaceutical study explores the effects of sample frame error on research results.

Survey results of a nationwide sample frame did not differ from those of a statewide sample frame with respect to questions that were professional/procedural in nature or that dealt with putative industry knowledge. However, on questions that were attitudinal in nature, the sample frames differed significantly. Because of this, the authors conclude that using a geographically narrow convenience sample may or may not result in frame error, depending on the information being sought.

Data Collection↗
PubMed2001

Estimation of error and bias in Bayesian Monte Carlo decision analysis using the bootstrap.

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.

Journal Article↗