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PubMedDate not supplied

The compliance and science of Blend Uniformity Analysis.

According to 21CFR section 211.110(a) pharmaceutical manufacturers are legally required to demonstrate the adequacy of their mixing operations. The CFR, however, is intentionally silent on how this should be accomplished. The situation changed dramatically in 1993 as a consequence of The US vs. Barr Laboratories when Judge Alfred Wolin ruled for the government that the appropriate sample size for Blend Uniformity Analysis (BUA) is, at most, three times the weight of the final dosage unit. This ruling defined the Current Good Manufacturing Practices (cGMPs) for BUA in greater detail than is specified in 21CFR section 211.110(a). It also established a precedent that has been the focus of an almost decade long controversy between pharmaceutical manufacturers and the FDA. At the heart of the matter is the inability of current sampling technology to consistently and reliably provide small representative samples from significantly larger static powder blends. The sample thief is the state-of-the-art powder sampling technology used by the pharmaceutical industry today for purposes of BUA. Unfortunately, sample thieves are intrusive devices that are prone to sampling error. Sampling error can lead to powder samples that are not representative of the bulk blend from which they were collected. In general, sampling error increases as the concentration of the drug substance and the size of the sample decrease. Since Judge Wolin's ruling, sampling error has made it difficult, if not impossible, to validate the manufacturing processes for some acceptably uniform pharmaceutical products. This article reviews the compliance history of BUA as well as the associated scientific literature.

Chemistry, Pharmaceutical↗
PubMed1980

Monitoring central nervous system methotrexate levels via subcutaneous reservoir. Sources of errors in sampling and their avoidance.

The Ommaya reservoir allows for ready, well-tolerated direct access to the intraventricular cerebrospinal fluid (CSF). The toxicities associated with central nervous system (CNS) methotrexate (MTX) therapy have been attributed to prolonged high levels of the drug. When samples of CSF are removed from a reservoir for the monitoring of MTX levels, there may be sampling errors introduced by retention of high concentrations of drug in the reservoir. Using an in vitro system we confirm this possibility and show that using different injection or sampling techniques will increase or decrease this error. Without proper sampling, particularly several days after the initial injection, one may overestimate the MTX level and may unnecessarily alter treatment. A simple method of avoiding this error is to flush the reservoir after drug injection with a small (3-5 ml) volume of CSF withdrawn prior to injection.

Injections, Spinal↗
PubMed1998

ThinPrep Papanicolaou testing to reduce false-negative cervical cytology.

The false-negative Papanicolaou (Pap) smear is the major quality issue currently facing the practitioners of diagnostic cytology. Failure to detect cervical disease in women can be due either to sampling error or to screening error. Sampling errors account for the majority of false-negative Pap tests; the remainder are due to the cervical abnormality either not being detected or not being properly classified during microscopic screening. The ThinPrep Pap test was recently cleared by the United States Food and Drug Administration as significantly more effective than the conventional Pap smear and as a replacement for the conventional method of Pap smear preparation. The ThinPrep Pap test increases detection of squamous intraepithelial lesions and significantly improves specimen quality. These features of the ThinPrep Pap test also have a heretofore unreported direct effect on the false-negative rate of the Pap examination. In two recently conducted clinical trials, the ThinPrep test resulted in a significant reduction in the sampling false-negative rate in women undergoing routine Pap screening. In addition, screening false negatives, as expressed by the false-negative proportion, were reduced from 5.6% with the conventional Pap smear, to 2.2% with the ThinPrep Pap test. More high-grade squamous intraepithelial lesions were detected in the screening populations with the ThinPrep test. The ThinPrep Pap test improves the quality of cervical cancer screening through a reduction in false-negative Pap examinations. This improvement has important implications for women undergoing Pap screening and for those who practice gynecologic cytopathology.

False Negative Reactions↗
PubMed2005

[Comparison on energy values of matching food items in food compositon table of four northeast Asian countries or region].

OBJECTIVE: To evaluate the consistency and compatibility of the energy values in present applied Food Composition Tables or Databases (FCTs or FCDs) of NeasiaFoods members. METHODS: A total 101 matching food items (N = 101 x 4) were selected from the FCTs or FCD of Japan, Korea, Taiwan and China. Statistical comparisons were conducted before and after water adjustment. Data profile plots, means and relative differences were provided. The significance of differences were examined by the block designed ANOVA (alpha = 0.05). RESULTS: The population mean of Chinese food items is significantly low than that of other three. Relative difference (mean and 95% CI) of water adjusted estimation indicate that energy of China is totally less 7.7% (-0.6% - 15.9%), 11.7% (3.5 % - 20.1 %) and 2.6% (-5.2% - 10.3%) than that of Japan, Taiwan, and Korea respectively. Major bias occurred in Nuts & seeds and Fungi & Algae, Japan and Taiwan higher 22% to 68% than China. CONCLUSIONS: The energy values in FCTs of these NEASIAFOODS members lack consistency, especially between China and other three members. Differences of food energy conversion systems are the main effect that producing discrepancies. The effect of bias in energy contributing nutrients (e.g. fat) are considerable; analytical errors, sampling errors, food processing effects, different of food species, and accumulation of them only can be estimated through interlaboratory comparison studies on the basis of totally same food samples.

Asia↗
PubMedDate not supplied

Why is high grade squamous intraepithelial neoplasia under-diagnosed on cytology in a quarter of cases? Analysis of smear characteristics in discrepant cases.

BACKGROUND: The accuracy of cervical cytology has been questioned due to high false negative rate. In order to improve the sensitivity of cytology it is prudent to analyze the factors which hamper with the diagnosis of high grade lesions. AIMS: To study the cyto-histologic agreement in High grade squamous intraepithelial lesions (HSIL) of uterine cervix and to analyze the smear characteristics in discrepant cases. SETTINGS AND DESIGN: Cervical smears of 100 histology proven cases of Cervical intraepithelial neoplasia III (CIN III) were retrieved and reviewed to study cyto-histologic agreement in the diagnosis of high grade lesions. The discrepant smears, undercalled on cytology, were further analyzed to determine the reasons for misinterpretations. Statistical analysis was performed to find out any significant factors for discrepancies. RESULTS: Cytology was able to correctly identify 74 HSILs while in 26 cases a diagnosis of Low grade squamous intraepithelial lesions (LSIL) or below was given. On review, 16 of these non correlating cases could be reclassified as HSIL on cytology while in 10 the diagnosis of LSIL or less persisted. 12/16 (75%) discrepant cases, reclassified as HSIL represented interpretive errors. Sampling errors (7/10) and air drying (5/10) were more frequent in under diagnosed cases. The statistical analysis did not yield any significant differences in the two review groups. CONCLUSION: 26% of HSIL cases were underdiagnosed on cervical smears. The major confounding factors responsible for under interpretation on cytology included air drying artifacts and metaplastic maturation of abnormal cells.

Adult↗
PubMed2006

Analysis of the statistical error in umbrella sampling simulations by umbrella integration.

Umbrella sampling simulations, or biased molecular dynamics, can be used to calculate the free-energy change of a chemical reaction. We investigate the sources of different sampling errors and derive approximate expressions for the statistical errors when using harmonic restraints and umbrella integration analysis. This leads to generally applicable rules for the choice of the bias potential and the sampling parameters. Numerical results for simulations on an analytical model potential are presented for validation. While the derivations are based on umbrella integration analysis, the final error estimate is evaluated from the raw simulation data, and it may therefore be generally applicable as indicated by tests using the weighted histogram analysis method.

Journal Article↗
PubMed1994

Retrospective analysis of non-correlating cervical smears and colposcopically directed biopsies.

The purpose of this study is to evaluate the cause of discrepancies between non-correlating cytologic and histologic cervical samples. The biopsy results of 433 women examined colposcopically were compared to their referral cervical smears (RS). There was a discrepancy between the RS and the subsequent biopsy in 120 women (28%). One hundred of these 120 RS were available for review; and in each case, a reason for the discrepancy was established and classified as RS overcall, RS undercall, RS sampling error, or biopsy sampling error. Fifty-one discrepant RS were overcalled. They were reported initially as condyloma (19), mild dysplasia (22), and moderate dysplasia (10). One RS was undercalled. Nine RS were not diagnostic of the biopsy-proven lesion due to smear sampling error. The discrepancies in the remaining 39 cases were due to biopsy sampling error. Twenty-one of these 39 cases had additional biopsies or smears that confirmed the presence of condyloma/dysplasia, and 18 had negative follow-up. In summary, discrepancies were a result of pathologists' interpretative error, predominantly overcalls, in 52% of non-correlating cases, and smear or biopsy sampling error in the remaining 48%.

Biopsy↗
PubMed2005

Use and misuse of p-values in designed and observational studies: guide for researchers and reviewers.

Analysis of scientific data involves many components, one of which is often statistical testing with the calculation of p-values. However, researchers too often pepper their papers with p-values in the absence of critical thinking about their results. In fact, statistical tests in their various forms address just one question: does an observed difference exceed that which might reasonably be expected solely as a result of sampling error and/or random allocation of experimental material? Such tests are best applied to the results of designed studies with reasonable control of experimental error and sampling error, as well as acquisition of a sufficient sample size. Nevertheless, attributing an observed difference to a specific treatment effect requires critical thinking on the part of the scientist. Observational studies involve data sets whose size is usually a matter of convenience with results that reflect a number of potentially confounding factors. In this situation, statistical testing is not appropriate and p-values may be misleading; other more modern statistical tools should be used instead, including graphic analysis, computer-intensive methods, regression trees, and other procedures broadly classified as bioinformatics, data mining, and exploratory data analysis. In this review, the utility of p-values calculated from designed experiments and observational studies are discussed, leading to the formation of a decision tree to aid researchers and reviewers in understanding both the benefits and limitations of statistical testing.

Clinical Trials as Topic↗
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↗
PubMed1993

Assessing response reliability of health interview surveys using reinterviews.

Data from interview surveys of households or health facilities are used to assess community parameters such as health status and factors related to the ability and willingness of individuals to pay for health services. Although the effect of sample size on confidence intervals is generally well understood by the survey designers and policy-makers who use the results, the typical survey is also subject to non-sampling errors whose magnitude may exceed that of the sampling errors. The non-sampling errors associated with surveys are only rarely assessed and reported, even though they may have a major effect on the interpretation of findings. The present study reports the non-sampling errors associated with a household survey in Sierra Leone by comparing the results of reinterviews with the responses given during the original interviews. Certain types of questions were subject to greater non-sampling errors than others. The findings should be of use to designers of similar surveys and to those who rely on such surveys for making policy decisions.

Adolescent↗
PubMed2002

Cervical biopsy/cytology correlation data can be collected prospectively and shared clinically.

Cervical cytology (Cy) and biopsy (Bx) correlation is used by institutions for the evaluation of their cytodiagnostic capabilities as a part of overall laboratory quality improvement (QI). However, the data obtained from correlation are not routinely included in most surgical pathology (SP) reports. Our laboratory's procedure is to include the correlation of the patient's previous (most recent) cytology smear in the surgical pathology report of all/any gynecologic surgical pathology specimens. We reviewed this process for the time period between July 1998-June 1999. Any noncorrelating cases were assigned a correlation review code by the reviewing cytopathologist: major Cy diagnostic error (DE1), minor Cy diagnostic error (DE2), Cy sampling error (Cy SE), or biopsy sampling error (Bx SE). Of 3,486 cases reviewed, 3,229 cases were satisfactory for correlation studies. Concordant results were found in 86.9%. Cy DE1 due to either Cy screening or interpretation errors or both were found in 0.2% (n = 7) of all cases, while Cy DE2 due to the same were found in 1% (n = 32). Bx SE accounted for discrepancies in 6.8% (n = 220) of all cases, while 5.1% (n = 164) of the total cases were discrepancies due to Cy SE. Follow-up Bx was available in 97.2% (n = 214) of the Bx SE, and showed 16.4% (n = 35) to be major discrepancies and 83.6% (n = 179) to be minor discrepancies. Cervical Cy/Bx correlation is useful for the evaluation of a laboratory's QI. It is also useful for the identification of either Cy or Bx SE. While QI data exist as "internal use only" documents, SE data (as part of the CC (correlation comment) included in SP reports) are vital to a specific/given patient. Bx SE was identified in 6.3% of our patients, indicating a possible need for rebiopsy. This type of QI data may be shared clinically, and may direct the management for maximum diagnostic and patient benefit.

Biopsy↗
PubMed2005

A Bayesian approach on sample size calculation for comparing means.

In clinical research, parameters required for sample size calculation are usually unknown. A typical approach is to use estimates from some pilot studies as the true parameters in the calculation. This approach, however, does not take into consideration sampling error. Thus, the resulting sample size could be misleading if the sampling error is substantial. As an alternative, we suggest a Bayesian approach with noninformative prior to reflect the uncertainty of the parameters induced by the sampling error. Based on the informative prior and data from pilot samples, the Bayesian estimators based on appropriate loss functions can be obtained. Then, the traditional sample size calculation procedure can be carried out using the Bayesian estimates instead of the frequentist estimates. The results indicate that the sample size obtained using the Bayesian approach differs from the traditional sample size obtained by a constant inflation factor, which is purely determined by the size of the pilot study. An example is given for illustration purposes.

Aged↗