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PubMed2006

Radiation-induced untargeted germline mutations in Japanese medaka.

Radiation has been shown to increase mutation frequencies at tandem repeat loci by indirect interactions of radiation with DNA. We studied germline mutations in chronically exposed Japanese medaka (Oryzias latipes) using microsatellite loci. After screening 26 randomly selected loci among unirradiated parents and their 200 offspring, we selected seven highly mutable loci (0.5-1.0 x 10(-2) mutants per locus per gamete) and two bonus loci for further study. To determine if radiation exposure increases mutation frequencies in these loci, medaka were chronically irradiated from subadults through maturation at relatively low dose rates of 68 mGy/d. Total doses for males and females were 10.4 and 3 Gy, respectively. The mean number of mutations for the offspring of exposed families (0.149+/-0.044) was significantly higher (P=0.018) than for control families (0.080+/-0.028), indicating induction of germline mutations from chronic irradiation. This increase in the microsatellite mutation rate is greater than expected from direct interaction of radiation with DNA, suggesting indirect, untargeted mechanism(s) for mutations. This study identified microsatellite loci with a high mutational background in medaka, variation among loci and families as important variables, and demonstrated the usefulness of this fish model for studying radiation-induced germline mutations.

Alleles↗
PubMed2006

Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration.

BACKGROUND: There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences. RESULTS: Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant. CONCLUSION: Gene annotating remains an ongoing and challenging task that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become more precisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualize sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.

Alternative Splicing↗
PubMed1992

Abortion attitudes, 1984-1987-1988: effects of item order and dimensionality.

The comparability of surveys is often hampered by differences in the item order of presentation. The major focus of the present study was to investigate whether a general item or a specific item at the beginning of the questionnaire would affect the endorsement as well as the scalability of a set of attitude items. By using a quasi-A-B-A experimental design for the six abortion items that appeared in the Edmonton Area Survey for the years 1984, 1987, and 1988, we found that the order of presentation of the items affected dramatically the endorsement of the abortion items. Approval of a general item was considerably higher when asked first than when asked after a specific item. In contrast, it was shown by means of a nonparametric item response theory model (the Mokken scale analysis) that the unidimensionality of the six abortion items was not affected by the manipulations of item order (i.e., the six abortion items measured the same concept in the three surveys). It was concluded that the six items are unidimensional and, therefore, create a single scale to measure the change in abortion attitudes across the three periods.

Abortion, Legal↗
PubMed2003

Implications of 2001 Census for local authority district mid-year population estimates.

ONS published mid-2001 population estimates for England and Wales based on the 2001 Census in October 2002. Mid-2001 estimates were also produced, but not published, rolled forward from the 1991 Census. By considering the differences between these two estimates, ONS is able to assess how accurate estimates of population change have been between mid-1991 and mid-2001. Results of this comparison at national and regional levels have already been published on the National Statistics website. This article concentrates on the differences at local authority district level. Analyses of these differences within the article are in three parts-basic descriptive statistics, comparison of the local authority districts as a proportion of their national totals, and more complex multiple regression analysis. The implications of these results are then assessed and recommendations put forward to help improve the mid-year estimates in the following decade. Improvements will also come through other studies such as the National Statistics Quality Review on international migration.

Censuses↗
PubMed2005

Large-scale statistical analysis of secondary xylem ESTs in pine.

A computational analysis of pine transcripts was conducted to contribute to the functional annotation of conifer sequences. A statistical analysis of expressed sequential tags(ESTs) belonging the 7732 contigs in the TIGR Pinus Gene Index (PGI1.0) identified 260 differentially represented gene sequences across six cDNA libraries from loblolly pine secondary xylem. Cluster analysis of this subset of contigs resulted in five groups representing genes preferentially represented in one of the xylem samples (compression wood, plannings, root xylem, latewood) and one group containing mostly genes simultaneously present in compression and side wood libraries. To complement the sequence annotation, 27 cDNA clones representing selected transcripts were completely sequenced. Several genes were identified that could represent putative markers for xylem from different organs, at different stages of development. Several sequences encoding regulatory proteins were over-represented in root xylem as opposed to the other xylem samples. Some of them belonged to known families of plant transcription factors, but two genes were previously uncharacterized in plants. One transcript was homologous to the gene encoding the Smad4 interacting factor, a key co-activator in TGFbeta (transforming growth factor) signalling in animals. Thus, the digital analysis of pine ESTs highlighted a putative gene function of potentially broad interest but that has yet to be investigated in plants. More generally, this study showed that the application of numerical approaches to EST databases should be helpful in establishing priorities among genes to consider for targeted functional studies. Thus, we illustrated the potential of extracting information from conifer sequences already accessible through well-structured public databases.

Amino Acid Sequence↗
PubMed1988

Compliance in clinical trials: impact on design, analysis and interpretation.

A positive association between compliance and clinical outcome has been observed in several randomized, controlled, clinical trials. This association, seen in the placebo-treated group as well as the active-treatment group, clarifies the possibility that data analyses incorporating estimates of protocol adherence are potentially biased. In the presence of non-compliance, or missing data from any cause, several statistical analyses may seem plausible, with none clearly superior to the others. These may include an analysis of all patients randomized, with imputed values for missing data, and an analysis restricted to protocol-adherent patients. The recommended approach is a conservative one that examines consistency among the plausible analyses. Using compliance data in trial conduct can also introduce bias into trial results by inducing differential treatment of compliers and non-compliers. This possibility arises, for instance, when adherence is affected by the randomized treatment. Non-compliance can have a substantial impact on statistical power and sample size requirements in a clinical trial. Under certain assumptions, required sample sizes are doubled with 30% non-compliance and tripled with 40% non-compliance.

Clinical Trials as Topic↗
PubMed2000

Methods for assessing responsiveness: a critical review and recommendations.

A review of the literature suggests there are two major aspects of responsiveness. We define the first as "internal responsiveness," which characterizes the ability of a measure to change over a prespecified time frame, and the second as "external responsiveness, " which reflects the extent to which change in a measure relates to corresponding change in a reference measure of clinical or health status. The properties and interpretation of commonly used internal and external responsiveness statistics are examined. It is from the interpretation point of view that external responsiveness statistics are considered particularly attractive. The usefulness of regression models for assessing external responsiveness is also highlighted.

Arthritis, Psoriatic↗
PubMed1994

Issues in biomedical statistics: statistical inference.

The first step in making inferences under the frequentist system of statistical logic is to propose a null hypothesis. An experiment is then performed, or a set of observations made. The resulting data are subjected to statistical analysis to determine whether the null hypothesis should be rejected or not. If it is, then some alternative hypothesis must have been entertained. In biomedical work, the alternative hypothesis should usually be non-specific and it follows that the statistical test of the null hypothesis should be interpreted in a two-sided fashion. The decision to reject or accept statistical null hypotheses, whether on the basis of a P value or confidence intervals, is probabilistic in nature and always attended by the risk of error. It is argued that, in biomedical research, it is the risk of making false-positive statistical inferences (Type I error) that should be most closely controlled. The risks of Type I error cannot be considered in isolation from the model of inference under which the null hypothesis is tested. That which forms the basis for using the classical t, F and X2 tests is the population model, in which the inference is referred to a defined population that has been randomly sampled and which conforms to a specified frequency distribution. Under this model, serious errors in statistical inference can occur if the actual distributions of the populations do not conform to those specified by theory. More importantly, the population model is inappropriate to most biomedical research, in which treatment groups are created by randomization but not by random sampling.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed2003

Assessing and interpreting treatment effects in longitudinal clinical trials with missing data.

Treatment effects are often evaluated by comparing change over time in outcome measures; however, valid analyses of longitudinal data can be problematic, particularly if some data are missing. For decades, the last observation carried forward (LOCF) approach has been a common method of handling missing data. Considerable advances in statistical methodology and our ability to implement those methods have been made in recent years. Thus, it is appropriate to reconsider analytic approaches for longitudinal data. This review examines the following from a clinical perspective: 1) the characteristics of missing data that influence analytic choices; 2) the attributes of common methods of handling missing data; and 3) the use of the data characteristics and the attributes of the various methods, along with empirical evidence, to develop a robust approach for the analysis and interpretation of data from longitudinal clinical trials. We propose that, in many settings, the primary efficacy analysis should use a repeated measures, likelihood-based, mixed-effects modeling approach, with LOCF used as a secondary, composite measure of efficacy, safety, and tolerability. We illustrate how repeated-measures analyses can be used to enhance decision-making, and we review the caveats that remain regarding the use of LOCF as a composite measure.

Analysis of Variance↗
PubMed1999

Facilitating the work of a meta-analyst.

Meta-analysis facilitates the transfer of knowledge from nurse researchers to clinicians. In this article, the benefits and criticisms of meta-analysis for nursing are identified along with the specific problems a meta-analyst may encounter in conducting a quantitative analysis and synthesis of the literature. Problems in data retrieval from the primary studies for a quantitative literature review can plague a meta-analyst. These problems can include insufficient data such as inexact p-values, incomplete descriptions of samples or experimental and control groups, and errors in tables in research reports. Suggestions for removing some of these roadblocks are addressed along with recommendations to authors, editors, and manuscript reviewers. An example of a suggestion for authors is to focus on reporting exact statistical values and p-levels. Also, sample characteristics and methodological variables are deserving of detailed descriptions in research reports. Editors can consider including a summary table of basic descriptive and inferential statistics. Another recommendation for editors is to develop a reviewer's checklist to ensure the author has included all relevant statistical information and study characteristics a meta-analyst needs.

Authorship↗
PubMed2001

A study comparing precision of the maximum multipoint heterogeneity LOD statistic to three model-free multipoint linkage methods.

This study compared the performance of the maximum lod (MLOD), maximum heterogeneity lod (MHLOD), maximum non-parametric linkage score (MNPL), maximum Kong and Cox linear extension (MKC(lin)) of NPL, and maximum Kong and Cox exponential extension (MKC(exp)) of NPL as calculated in Genehunter 1.2 and Genehunter-Plus. Our performance measure was the distance between the marker with maximum value for each linkage statistic and the trait locus. We performed a simulation study considering: 1) four modes of transmission, 2) 100 replicates for each model, 3) 58 pedigrees (with 592 subjects) per replicate, 4) three linked marker loci each having three equally frequent alleles, and 5) either 0% unlinked families (linkage homogeneity) or 50% unlinked families (linkage heterogeneity). For each replicate, we obtained the Haldane map position of the location at which each of the five statistics is maximized. The MLOD and MHLOD were obtained by maximizing over penetrances, phenocopy rate, and risk-allele frequencies. For the models simulated, MHLOD appeared to be the best statistic both in terms of identifying a marker locus having the smallest mean distance from the trait locus and in terms of the strongest negative correlation between maximum linkage statistic and distance of the identified position and the trait locus. The marker loci with maximum value of the Kong and Cox extensions of the NPL statistic also were closer to the trait locus than the marker locus with maximum value of the NPL statistic.

Bias↗
PubMedDate not supplied

Confidence intervals for cost/effectiveness ratios.

The reduction of costs is becoming increasingly important in the medical field. The relevant topic of many clinical trials is not effectiveness per se, but rather cost-effectiveness ratios. Surprisingly, no statistical tools for analyzing cost-effectiveness ratios have been provided in the medical literature yet. This paper explains the gap in the literature, and provides a first technique for obtaining confidence intervals for cost-effectiveness ratios. The technique does not use sophisticated tools to achieve maximal optimality, but seeks for tractability and ease of application while still satisfying all formal statistical requirements.

Clinical Trials as Topic↗
PubMed2006

Statistical evaluation of biomarkers as surrogate endpoints: a literature review.

A valid surrogate endpoint allows correct inference to be drawn regarding the effect of an intervention on the unobserved true clinical endpoint of interest. The perceived practical and ethical advantages of substituting a surrogate endpoint for a clinical endpoint have led to a considerable number of statistical methods being proposed for the evaluation of a biomarker as a surrogate endpoint. We review the main statistical schools of thought which have developed and consider how the validation process might be arranged within the regulatory and practical constraints of the drug development process. We conclude by assessing which of the candidate statistical methods offer the best approach for surrogate endpoint evaluation.

Biomarkers↗
PubMed2007

Adaptive design method based on sum of p-values.

Bauer and Kohne proposed an adaptive design using Fisher's combination of independent p-values based on subsamples from different stages (Biometrics 1994; 50(4):1029-1041). Their method provides great flexibility in the selection of statistical methods for hypothesis testing of subsamples. However, the choices for the stopping boundaries are not flexible enough to meet practical needs (Biometrics 2001; 57(3): 886-891). In this paper, an adaptive design method is proposed using linear combination of the independent p-values. The method provides great flexibility in the selection of stopping boundaries and no numerical integration is required for the two-stage designs. The stopping boundaries and p-values can be calculated manually. The operating characteristics of the adaptive designs are studied using computer simulations with and without sample size adjustment. Examples are presented for superiority and non-inferiority trials with different endpoints (normal, binary, and survival) under different adaptations. The statistical efficiency of the proposed method is compared with other methods based on conditional power.

Data Interpretation, Statistical↗
PubMed1997

Factors that influence effect size in 15O PET studies: a meta-analytic review.

The PET literature is growing exponentially, creating a need and an opportunity to perform a meta-analytic review consolidating the published information. This study describes the use of effect size as an index in PET studies and discusses how this measure can be used for comparing findings across studies, laboratories, and paradigms. In comparing studies across laboratories it is essential to know how the methods employed affect the results and conclusions drawn. This study also compared effect size for two different methods of tracer delivery in 15O PET studies ([15O]H2O bolus injection versus inhalation of [15O]CO2), whether averaged versus single-scan conditions were used, and the data analytic strategy employed. The effect sizes observed across studies were consistently large with a median effect size of 8.55, indicating that the phenomena investigated in 15O PET studies are strong. The largest peak activation reported in a study was found to be affected by variability in sample size, data analytic strategy, and repeat versus single-scan conditions. However, the impact of these factors was not examined on smaller or less intense peaks. Minimal standards for reporting statistical results are discussed.

Data Interpretation, Statistical↗
PubMed1998

Statistical considerations in clinical trials testing empiric antibiotic regimens in patients with febrile neutropenia.

The Chalmers scoring system for assessing the quality of randomized controlled trials was applied to 19 papers (published in 1976-1984) reporting the results of trials of antibiotics in febrile neutropenic patients, it was found at the time of this survey (publication 1986) that statistical issues were inadequately addressed in the papers and that the scoring system was a measure of the quality of reporting in the papers rather than the quality of the actual trials. Some new items have been added to the system to improve the validity of results, and 15 more recent papers have been reviewed with reference to the updated scoring procedure, to find whether the quality of trials and of their reporting has improved since 1986. Further discussion of statistical issues in clinical trials is recommended.

Anti-Bacterial Agents↗
PubMed1988

On the sensitivity of linear discriminant analysis to sampling variation and analytical errors.

The influence of analytical inaccuracy and imprecision on the linear discriminant function is considered. Analytical shifts occurring between the analysis of samples from each of two groups give spuriously low error rates if the function is evaluated on the training set, notably at high dimensions. Inaccuracy arising after the establishment of a discriminant function may change considerably the individual group error rates whereas the overall error rate is moderately affected. Imprecision decreases the group separation by an amount comparable to that in the univariate situation. In conclusion, evaluation of the error rates of a discriminant function on an independent test set is important to obtain realistic estimates of the performance and is preferable to using unbiased statistical methods or the split-sample principle based solely upon the training set.

Biometry↗