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At least 1,549 records · Page 86Linked to original sources
PubMed1997

A t-statistic for objective interpretation of comparative genomic hybridization (CGH) profiles.

An objective method for interpreting comparative genomic hybridization (CGH) is described and compared with current methods of interpretation. The method is based on a two-sample t-statistic in which composite test:reference and reference:reference CGH profiles are compared at each point along the genome to detect regions of significant differences. Composite profiles are created by combining CGH profiles measured from several metaphase chromosomes for each type of chromosome in the normal human karyotype. Composites for both test:reference and reference:reference CGH analyses are used to generate mean CGH profiles and information about the variance therein. The utility of the method is demonstrated through analysis of aneusomies and partial gain and loss of DNA sequence in a myeloid leukemia specimen. Banding analyses of this specimen indicated inv (3)(q21q26), del (5)(q2?q35), -7, +8 and add (17)(p11.2). The t-statistic analyses of CGH data indicated rev ish enh (8) and rev ish dim (5q31.1q33.1,7q11.23qter). The undetected gain on 17p was small and confined to a single band (17p11.2). Thus, the t-statistic is an objective and effective method for defining significant differences between test and reference CGH profiles.

Humans↗
PubMedDate not supplied

Statistical inference for cost-effectiveness ratios.

Methods for statistical inference for cost-effectiveness (C/E) ratios for individual treatment and for incremental cost-effectiveness (delta C/ delta E) ratios when two treatments are compared are presented. In a lemma, we relate the relative magnitude of two C/E ratios to the delta C/ delta E ratio. We describe a statistical procedure to test for dominance, or admissibility, that can be used to eliminate an inferior treatment. The one-sided Bonferroni's confidence interval procedure is generalized to the two-sided case. The method requires only that two confidence intervals be available, one for cost and one for effectiveness. We describe Fieller-based confidence intervals and show them to be shorter than Bonferroni intervals. When distribution assumptions hold and variance and covariance estimates are available, Fieller intervals are preferable. However, Bonferroni intervals can be applied in more diverse situations and are easier to calculate. A simple Bonferroni based technique, and a likelihood ratio statistic given by Siegel, Laska and Meisner, for testing the null hypothesis that the C/E ratios of two treatments are equal is presented. The approaches are applied to the data from a phase II clinical trial of a new treatment for sepsis considered previously by others.

Confidence Intervals↗
PubMed1977

Radiotherapy in the postoperative treatment of operable cancer of the breast. Part II. A re-examination of Stjernswärd's application of the Mantel-Haenszel statistical method. Evaluation of the effect of the radiation on immune response and suggestions for postoperative radiotherapy.

A re-examination of the statistical methods used to develop the claim that radiation postoperatively decreases survival was carried out. This study demonstrates that a) when correct figures are used, statistical significance is not demonstrated, i.e. there is not statistically significant evidence that irradiation of the peripheral lymphatics and/or chest wall following mastectomy has a deleterious effect on survival, b) the use of the Mantel-Haenszel procedure was inappropriate for the purpose for which it was used. A survey of the available evidence fails to substatiate the claim that the immunological system effects of local irradiation relate in any way to decreased survival. Recommendations for the use of irradiation postoperatively in the treatment of breast cancer are made.

Adult↗
PubMed1993

Some statistical considerations for the interpretation of trials of combined androgen therapy.

Since 1989, there have been strongly conflicting opinions regarding the validity of the proposition that an antiandrogen added to standard hormonal therapy could improve the outcome in patients with newly diagnosed metastatic prostate cancer. To some degree, these conflicting opinions arose from misinterpretations of a number of "negative" clinical trials. The misinterpretations happened because these "negative" trials had insufficient statistical power to refute the reported "positive trial", and information illustrating their statistical power was absent from their reports. Thus, readers were not given the necessary information to distinguish between negative and inconclusive results. In addition, many of the negative reports were early analyses of ongoing clinical trials, a practice that always should be avoided. This article reviews and illustrates the statistical principles that are applicable to the interpretation of low-powered negative clinical trials and discusses the design and conduct of clinical trials.

Androgen Antagonists↗
PubMed2001

Comparison of artificial neural networks with other statistical approaches: results from medical data sets.

BACKGROUND: In recent years, considerable attention has been given to the development of sophisticated techniques for exploring data sets. One such class of techniques is artificial neural networks (ANNs). Artificial neural networks have many attractive theoretic properties, specifically, the ability to detect non predefined relations such as nonlinear effects and/or interactions. These theoretic advantages come at the cost of reduced interpretability of the model output. Many authors have analyzed the same data set, based on these factors, with both standard statistical methods (such as logistic or Cox regression) and ANN. METHODS: The goal of this work is to review the literature comparing the performance of ANN with standard statistical techniques when applied to medium to large data sets (sample size > 200 patients). A thorough literature search was performed, with specific criteria for a published comparison to be included in this review. RESULTS: In the 28 studies included in this review, ANN outperformed regression in 10 cases (36%), was outperformed by regression in 4 cases (14%), and the 2 methods had similar performance in the remaining 14 cases (50%). However, in the 8 largest studies (sample size > 5000), regression and ANN tied in 7 cases, with regression winning in the remaining case. In addition, there is some suggestion of publication bias. CONCLUSIONS: Neither method achieves the desired performance. Both methods should continue to be used and explored in a complementary manner. However, based on the available data, ANN should not replace standard statistical approaches as the method of choice for the classification of medical data.

Humans↗
PubMed2000

Strategic use of statistical thinking in drug development.

The role of the statistician and statistical thinking in the pharmaceutical industry has evolved greatly in the last four or five decades. Regulatory developments and the changing face of the science of drug development have driven this evolution. The increasing regulatory requirement for statistical input in critical areas has facilitated a wider range of applications. The pace of change of science in general has brought statisticians into contact with a wider range of potential customers. More importantly, it has allowed the statistician to become increasingly involved in strategic issues with the possibility of influencing the direction of the business. However, it is not clear that the statistical profession in industry is adequately prepared for these opportunities either in attitude or training. Changing the statisticians' approach to their role and acquiring the correct training and experience are critical for the profession to optimize their contribution to the drug discovery and development processes.

Drug Approval↗
PubMed2006

Statistical basis for positive identification in forensic anthropology.

Forensic scientists are often expected to present the likelihood of DNA identifications in US courts based on comparative population data, yet forensic anthropologists tend not to quantify the strength of an osteological identification. Because forensic anthropologists are trained first and foremost as physical anthropologists, they emphasize estimation problems at the expense of evidentiary problems, but this approach must be reexamined. In this paper, the statistical bases for presenting osteological and dental evidence are outlined, using a forensic case as a motivating example. A brief overview of Bayesian statistics is provided, and methods to calculate likelihood ratios for five aspects of the biological profile are demonstrated. This paper emphasizes the definition of appropriate reference samples and of the "population at large," and points out the conceptual differences between them. Several databases are introduced for both reference information and to characterize the "population at large," and new data are compiled to calculate the frequency of specific characters, such as age or fractures, within the "population at large." Despite small individual likelihood ratios for age, sex, and stature in the case example, the power of this approach is that, assuming each likelihood ratio is independent, the product rule can be applied. In this particular example, it is over three million times more likely to obtain the observed osteological and dental data if the identification is correct than if the identification is incorrect. This likelihood ratio is a convincing statistic that can support the forensic anthropologist's opinion on personal identity in court.

Age Determination by Skeleton↗
PubMedDate not supplied

Limitations of the MANOVA of statistical moments in bioequivalence trials of drugs with slow elimination rate: a study with spironolactone.

The capacity of the statistical moments for detecting bioavailability changes in bioequivalence studies of drugs with high disposition mean residence time (MRT) is analysed. Two bioavailability trials were carried out with spironolactone in which extent and rate of absorption were modified in a controlled way. The statistical analysis employed was a two-way MANOVA of statistical moments of the urinary excretion profiles of canrenone. The results indicate a loss in the sensitivity of MRT for detecting changes in absorption rate as drug elimination rate decreases.

Adult↗
PubMed1989

Statistical approach to combining the results of similar experiments, with application to the hematologic effects of extremely-low-frequency electric field exposures.

A large proportion of scientific effort in investigating the possible biological effects of exposure to extremely-low-frequency (ELF) fields consists of laboratory studies on experimental animals. Most experiments in which hematologic properties are measured show no statistically significant effect due to exposure. However, some studies show significant effects which, in general, are not clearly reproducible. A difficult question must then be addressed: Are these relatively few indications of ELF effects statistical artifacts due to the increased risk of a type I error in multiple studies, or is there a real biological effect that is undetected in most studies due to the relatively small sample sizes commonly used? A statistical approach for examining the accumulated results of multiple experiments which results in a single test for treatment effect is presented. The technique requires very mild assumptions, and is valid for experiments that vary widely in specific characteristics such as exposure level, duration, and laboratory. The method is applied to the results of a collection of hematologic and serum chemistry experiments, and the combined results indicate the existence of experimental effects on some end points.

Animals↗
PubMed1992

Statistical review of the henhouse experiments: the effects of a pulsed magnetic field on chick embryos.

This paper analyzes data from a study conducted by the United States Office of Naval Research on the effects of pulsed magnetic fields on chick embryos. The experiment involved incubation of eggs under carefully controlled conditions in six different laboratories. The original analysis included inappropriate statistical methodology for analyzing the experimental results. Since the conclusions from this study rest so heavily on the results of statistical analyses, choosing the proper methodology is imperative. The major aim of this paper then is to introduce more appropriate analytic tools and illustrate their use in the present context. Qualitatively our results agree with those of the original analysis; our findings about interactions between effects, however, makes interpretation of these effects more subtle. We apply linear logistic modeling to counts of damaged embryos, using as covariates factors corresponding to exposure, laboratory, incubator, run, and measurements of background radiation. This facilitates estimation of the size of the effects. The effects of laboratory, incubator, and run are explored both as fixed and random effects. We find statistically significant exposure and laboratory effects, in accordance with the original study. However, we also find that the inter-laboratory variation in exposure effect is at least as large as the exposure effect itself. The presence of such effects fundamentally alters the interpretation of the fitted model, as is graphically presented.

Animals↗
PubMed2003

Statistical bioinformatic methods in microbial genome analysis.

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome-wide scanning for positively selected amino acids. I conclude with speculations on the future course of genome statistical modeling.

Computational Biology↗
PubMed2006

Maximally selected chi-square statistics and binary splits of nominal variables.

We address the problem of maximally selected chi-square statistics in the case of a binary Y variable and a nominal X variable with several categories. The distribution of the maximally selected chi-square statistic has already been derived when the best cutpoint is chosen from a continuous or an ordinal X, but not when the best split is chosen from a nominal X. In this paper, we derive the exact distribution of the maximally selected chi-square statistic in this case using a combinatorial approach. Applications of the derived distribution to variable selection and hypothesis testing are discussed based on simulations. As an illustration, our method is applied to a birth data set.

Biometry↗
PubMed1988

The task of a statistical referee.

The results are presented of an audit of the statistical standard of papers published in The British Journal of Surgery. A number of deficiencies are highlighted, many of which stem from an over-emphasis on statistical significance at the expense of any assessment of the clinical relevance of research findings. The flaws in the design of published studies, and in particular the many instances of inadequate sample sizes, emphasize that statistical input should be sought at the beginning of a research project rather than at the end.

General Surgery↗
PubMed1989

Two statistical approaches to nuclei shape and size in a morphometric description of lymph node sections in non-Hodgkin's lymphoma.

An attempt is made to evaluate more clearly the potential contribution of quantitative nuclear profile shape and size measurements to lymph node section histologic description in 70 cases of non-Hodgkin's lymphoma (NHL). The area of nuclear profiles and five nonredundant and size-free shape indices were measured using the THECLA program on a Leitz Texture Analysis System (Leitz-TAS). Two statistical approaches were applied, known respectively as "parametric," (first statistical moments of variable distributions over samples of 200 nuclear profiles) and "nonparametric," which are percentages of nuclear profiles distributed into five "cytological" classes that are defined by shape: round (A), elongated (B), kidney shaped (C), irregular (D) and cleaved (E) nuclear profiles. Both statistical approaches provide proper overall discrimination of the eight histological categories identified with reasonable reliability by pathologists. Above all, the present report discusses the ability of a set of parametric and nonparametric variables to describe NHL cell populations, in an objective and meaningful way, according to nuclei shape. A method of synthesizing multidimensional correlations (CORICO program) is proposed in support of the discussion. Also, the specific descriptive power of each of the variables is described; in particular, it is concluded that there is a close link between the shape and size of the nuclear profiles of the cells.

Cell Nucleus↗
PubMed2007

Statistical considerations for enumeration of circulating tumor cells.

BACKGROUND: Circulating tumor cells (CTCs) in patients with carcinomas are extremely rare. In metastatic breast cancer, the presence of >or=5 CTCs in 7.5 ml of blood has been associated with short survival. As this threshold has clinical implications, it is important to recognize the limitations associated with the detection and enumeration of CTCs. METHODS: Statistical analyses were performed on data generated from a multi-center clinical trial that utilized the CellSearchtrade mark System to isolate and enumerate CTCs in 7.5 ml blood samples. The statistical issues associated with each step of the process, from blood collection to final image analysis and CTC enumeration, were determined and implemented into a model. RESULTS: A model describing the statistics of the different process steps that are needed for the isolation and detection of CTCs was developed. The model uses the Poisson distribution for blood collection and empirically determined distributions for the isolation and identification of CTCs. The variability between readers was identified as one of the main sources of errors responsible for the current threshold level of five CTCs. CONCLUSIONS: Elimination of the errors made in the identification of tumor cells isolated from 7.5 ml of blood could potentially reduce the CTC threshold for the identification of patients with a poor prognosis from the current value of five CTCs to one CTC per 7.5 ml of blood.

Breast Neoplasms↗
PubMed2006

Kolmogorov-Smirnov statistical test for analysis of ZAP-70 expression in B-CLL, compared with quantitative PCR and IgV(H) mutation status.

BACKGROUND: ZAP-70 has been proposed as a surrogate marker for immunoglobulin heavy-chain variable region (IgV(H)) mutation status, which is known as a prognostic marker in B-cell chronic lymphocytic leukemia (CLL). The flow cytometric analysis of ZAP-70 suffers from difficulties in standardization and interpretation. We applied the Kolmogorov-Smirnov (KS) statistical test to make analysis more straightforward. METHODS: We examined ZAP-70 expression by flow cytometry in 53 patients with CLL. Analysis was performed as initially described by Crespo et al. (New England J Med 2003; 348:1764-1775) and alternatively by application of the KS statistical test comparing T cells with B cells. Receiver-operating-characteristics (ROC)-curve analyses were performed to determine the optimal cut-off values for ZAP-70 measured by the two approaches. ZAP-70 protein expression was compared with ZAP-70 mRNA expression measured by a quantitative PCR (qPCR) and with the IgV(H) mutation status. RESULTS: Both flow cytometric analyses correlated well with the molecular technique and proved to be of equal value in predicting the IgV(H) mutation status. Applying the KS test is reproducible, simple, straightforward, and overcomes a number of difficulties encountered in the Crespo-method. CONCLUSIONS: The KS statistical test is an essential part of the software delivered with modern routine analytical flow cytometers and is well suited for analysis of ZAP-70 expression in CLL.

Adult↗
PubMed1994

Overview of the workshops on statistical analysis of mutation data from transgenic mice.

Early results from two transgenic mouse mutation assays, Big Blue [Kohler SW et al. (1991): Proc Natl Acad Sci USA 88:7958-7962] and Muta Mouse [Myhr BC (1991): Environ Mol Mutagen 18:308-315], raised questions about appropriate study design and methods for statistical analysis. First, there were a number of potential sources of variability in the technical aspects of the assay. These are "how we do it in our laboratory" differences, which, if not controlled, ultimately make inter-laboratory comparison of data difficult. Second, separate from the technical sources of variability were a number of study design issues, e.g., how many animals are needed in each treatment group, how many times should the animal be dosed, what is the appropriate expression period for a particular tissue, how many plaques need to be collected from each animal, and so on. To address these questions and to identify and understand the sources of variability in mutation data from these systems, a workshop was held in June, 1992 in Cincinnati, Ohio, USA. A core group of biologists and statisticians discussed possible sources of bias (tissue sampling, phage recovery and transgene recovery), possible sources of variability in mutant frequency (between animals, protocol-based sources, and design-based sources) and assay sensitivity. Following two days of discussion on protocol design and assay procedures, three action steps were recommended: (1) compile a data base of existing mutation data in transgenic mice to study its statistical features, (2) develop standard protocols for the mutation assays; and (3) use the standard protocol to generate a large data base of mutant frequencies in liver DNA from untreated mice for statistical study and analysis. This report summarizes the proceedings and recommendations of the workshop. The progress made toward these recommendations was reviewed in a second workshop, held in April, 1993, in Norfolk, Virginia, part of which is the subject of the accompanying paper by Piegorsch et al. To date, a standard protocol has been developed for the Big Blue mutagenesis assay and a data base of over 90 million plaques from seven labs using either the Big Blue or Muta Mouse system has been assembled, including a large data set of spontaneous liver mutant frequencies in the Big Blue system.

Animals↗