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PubMed1990

Quality assurance in gynecologic cytology. What is practical?

The quality of gynecologic cytology has been questioned in the last two years. This author's hospital laboratory has a sizable outpatient gynecologic cytology and biopsy practice from which data have been obtained in several different quality assurance projects. In this article the author analyzes those data with respect to detection of false negative cytology screening errors, specimen sampling errors, precision in cytology and biopsy interpretation, and productivity of quality assurance methods. Sampling errors in obtaining cytology specimens are a major problem to be addressed by cytology quality assurance. The most sensitive and efficient method for detection of false negative cytologic results in this laboratory was rescreening of previous negative Papanicolaou's (Pap) smears in patients presenting for the first time with an abnormal Pap smear. Data indicate that the currently mandated requirement for rescreening 10% of a laboratory's negative Pap smears should be reconsidered and rescinded in certain circumstances.

Cytological Techniques↗
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↗
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↗
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↗
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↗
PubMed1978

Comparative validity of random-interval and fixed-interval urinalysis schedules.

Accurate detection of unprescribed drug use by addicts in treatment may facilitate their rehabilitation. Many clinics collect urine samples at random, using fixed-interval collection schedules, which are not free from sampling error. Random-interval schedules minimize sampling error and consequently increase detectability of drug use by eliminating safe periods during which drug use cannot be detected. We compared these two methods by observing rates of detected opiate- and quinine-positive samples preceding and following implementation of random-interval schedules. Detected drug use doubled initially. As detection and clinical sanctions became more certain, drug use declined to well below its former level. Programs that use fixed-interval schedules may underdetect drug use by more than 50%. If patients can reliably predict safe periods, the possibility of using drugs without fear of detection may impede their rehabilitation.

Appointments and Schedules↗