Improved reporting of statistical design and analysis: guidelines, education, and editorial policies

Learning gaps among statistical competencies for clinical and translational science learners

INTRODUCTION

Statistical literacy is essential in clinical and translational science (CTS). Statistical competencies have been published to guide coursework design and selection for graduate students in CTS. Here, we describe common elements of graduate curricula for CTS and identify gaps in the statistical competencies.

METHODS

We surveyed statistics educators using e-mail solicitation sent through four professional organizations. Respondents rated the degree to which 24 educational statistical competencies were included in required and elective coursework in doctoral-level and master's-level programs for CTS learners. We report competency results from institutions with Clinical and Translational Science Awards (CTSAs), reflecting institutions that have invested in CTS training.

RESULTS

There were 24 CTSA-funded respondents representing 13 doctoral-level programs and 23 master's-level programs. For doctoral-level programs, competencies covered extensively in required coursework for all doctoral-level programs were basic principles of probability and hypothesis testing, understanding the implications of selecting appropriate statistical methods, and computing appropriate descriptive statistics. The only competency extensively covered in required coursework for all master's-level programs was understanding the implications of selecting appropriate statistical methods. The least covered competencies included understanding the purpose of meta-analysis and the uses of early stopping rules in clinical trials. Competencies considered to be less fundamental and more specialized tended to be covered less frequently in graduate courses.

CONCLUSION

While graduate courses in CTS tend to cover many statistical fundamentals, learning gaps exist, particularly for more specialized competencies. Educational material to fill these gaps is necessary for learners pursuing these activities.

Do Addiction Science Journals Endorse Unbiased Reporting of Research? A Systematic Evaluation of Instructions for Authors

Introduction: Well-structured instructions for authors in journals help researchers in reporting unbiased results, which subsequently facilitates the review process. There have been reports of systematic evaluations of instructions for authors from journals in various medical specialties. However, precise information on the nature and extent of these instructions for authors in addiction science is lacking. Hence, this study systematically evaluated the instructions for authors for journals in addiction science. Methods: A total of 1139 journal titles were retrieved across multiple databases. Finally, 88 exclusive titles fulfilling the eligibility criteria were considered in this study. The four domains evaluated were journal characteristics, reporting, statistical reporting, and ethical requirements. Results: More than half of the journals were published by academic institutions or professional societies. Less than one-fourth of the journals endorsed adherence to various reporting guidelines and endorsed the Consolidated Statements on Randomized Controlled Trials guidelines to the maximum level (14.8%). Approximately, half (48.9%) of the journals had a separate section on "statistical analysis." The various parameters of statistical reporting were suboptimally endorsed. Conclusion/Importance: The instructions for authors in addiction science journals provide insufficient information in various domains. There is an urgent need to improve the author instructions segment of addiction science journals so that the process of research dissemination can occur more effectively. A higher rate of endorsement of various reporting guidelines and statistical reporting may help to minimize reporting bias as well as prevent unnecessary delays in the publication of important research findings.

The Importance of Statistical Competencies for Medical Research Learners

It is very important for medical professionals and medical researchers to be literate in statistics. However, we have found that the degree of literacy that is required should not be identical for every statistical competency or even for every learner. We first begin by describing why the development, teaching, and assessment of statistical competencies for medical professionals and medical researchers are critical tasks. We next review our three substantial efforts at developing a comprehensive list of statistical competencies that can be used as a guide for what medical research learners should know about statistics, for curricular development, and for assessment of statistical education. We then summarize the origin and the inclusion of the statistical competency items. We follow this with a description of potential uses and applications of the statistical competencies to improve targeted learning for medical research learners. Finally, we discuss implications of the statistical competencies for undergraduate statistics education.

Strategies for Success: Early-Stage Collaborating Biostatistics Faculty in an Academic Health Center

Collaborative biostatistics faculties (CBF) are increasingly valued by academic health centers (AHCs) for their role in increasingsuccess rates of grants and publications, and educating medical students and clinical researchers. Some AHCs have a biostatistics department that consists of only biostatisticians focused on methodological research, collaborative research, and education. Others may have a biostatistics unit within an interdisciplinary department, or statisticians recruited into clinical departments. Within each model, there is also variability in environment, influenced by the chair's background, research focus of colleagues, type of students taught, funding sources, and whether the department is in a medical school or school of public health. CBF appointments may be tenure track or non-tenure, and expectations for promotion may vary greatly depending on the type of department, track, and the AHC. In this article, the authors identify strategies for developing early-stage CBFs in four domains: 1)Influenceof department/environment, 2) Skills to develop, 3) Ways to increase productivity, and 4) Ways to document accomplishments. Graduating students and postdoctoral fellows should consider the first domain when choosing a faculty position. Early-stage CBFs will benefit by understanding the requirements of their environment early in their appointment and by modifying the provided progression grid with their chair and mentoring team as needed. Following this personalized grid will increase the chances of a satisfying career with appropriate recognition for academic accomplishments.

Reproducibility Issues: Avoiding Pitfalls in Animal Inflammation Models

In light of an enhanced awareness of ethical questions and ever increasing costs when working with animals in biomedical research, there is a dedicated and sometimes fierce debate concerning the (lack of) reproducibility of animal models and their relevance for human inflammatory diseases. Despite evident advancements in searching for alternatives, that is, replacing, reducing, and refining animal experiments-the three R's of Russel and Burch (1959)-understanding the complex interactions of the cells of the immune system, the nervous system and the affected tissue/organ during inflammation critically relies on in vivo models. Consequently, scientific advancement and ultimately novel therapeutic interventions depend on improving the reproducibility of animal inflammation models. As a prelude to the remaining hands-on protocols described in this volume, here, we summarize potential pitfalls of preclinical animal research and provide resources and background reading on how to avoid them.

Important statistical points to improve and promote the methodology of the articles on medical sciences, particularly nephrology and kidney; a review article

Background: Quality of articles’ methodology is one of the important factors which is considered by researchers.

Objectives: This study was conducted to determine statistical guidelines on promotion of methodology’s quality in the articles concerning medical sciences, particularly nephrology, to assist authors and reviewers.

Materials and Methods: This study is a systematic review. Initially, the keywords "Epidemiologic Methods/analysis" [Mesh] OR "Epidemiologic Methods/epidemiology" and "reporting" were selected in Medline database. Then, reliable databases were searched for relevant publications. Being relevant, containing viewpoints, and recommending statistical guidelines as well as approval of at least two of the three examiners of articles were determined as the inclusion criteria into the study.

Results: Two hundred relevant articles were retrieved. Thirty-two articles met the inclusion criteria. By the examined articles, 30 applied points have determinative role for improving and promoting quality of articles methodology. Of the important points, introducing and describing target community and statistical population, mentioning article title, introducing independent and dependent variables as well as confounders, reporting sample size for subgroups and the whole study, summarizing the data according to their statistical distribution (reporting mean and standard deviation for data with normal distribution), reporting the type of rate (incidence, survival), ratio (odds, hazard) or risk (absolute, relative, difference) with 95% CI and the used software could be mentioned.

Conclusion: The most important factors contributing greatly to the quality of articles’ methodology on nephrology were reported in the present study. Applying these factors by articles authors and reviewers could lead to improve articles’ and journals’ quality. In addition, use of the findings of the present study in articles’ materials and methods could avoid research errors.

A regression-based differential expression detection algorithm for microarray studies with ultra-low sample size

Global gene expression analysis using microarrays and, more recently, RNA-seq, has allowed investigators to understand biological processes at a system level. However, the identification of differentially expressed genes in experiments with small sample size, high dimensionality, and high variance remains challenging, limiting the usability of these tens of thousands of publicly available, and possibly many more unpublished, gene expression datasets. We propose a novel variable selection algorithm for ultra-low-n microarray studies using generalized linear model-based variable selection with a penalized binomial regression algorithm called penalized Euclidean distance (PED). Our method uses PED to build a classifier on the experimental data to rank genes by importance. In place of cross-validation, which is required by most similar methods but not reliable for experiments with small sample size, we use a simulation-based approach to additively build a list of differentially expressed genes from the rank-ordered list. Our simulation-based approach maintains a low false discovery rate while maximizing the number of differentially expressed genes identified, a feature critical for downstream pathway analysis. We apply our method to microarray data from an experiment perturbing the Notch signaling pathway in Xenopus laevis embryos. This dataset was chosen because it showed very little differential expression according to limma, a powerful and widely-used method for microarray analysis. Our method was able to detect a significant number of differentially expressed genes in this dataset and suggest future directions for investigation. Our method is easily adaptable for analysis of data from RNA-seq and other global expression experiments with low sample size and high dimensionality.

Assessing statistical competencies in clinical and translational science education: one size does not fit all

INTRODUCTION

Statistics is an essential training component for a career in clinical and translational science (CTS). Given the increasing complexity of statistics, learners may have difficulty selecting appropriate courses. Our question was: what depth of statistical knowledge do different CTS learners require?

METHODS

For three types of CTS learners (principal investigator, co-investigator, informed reader of the literature), each with different backgrounds in research (no previous research experience, reader of the research literature, previous research experience), 18 experts in biostatistics, epidemiology, and research design proposed levels for 21 statistical competencies.

RESULTS

Statistical competencies were categorized as fundamental, intermediate, or specialized. CTS learners who intend to become independent principal investigators require more specialized training, while those intending to become informed consumers of the medical literature require more fundamental education. For most competencies, less training was proposed for those with more research background.

DISCUSSION

When selecting statistical coursework, the learner's research background and career goal should guide the decision. Some statistical competencies are considered to be more important than others. Baseline knowledge assessments may help learners identify appropriate coursework.

CONCLUSION

Rather than one size fits all, tailoring education to baseline knowledge, learner background, and future goals increases learning potential while minimizing classroom time.

[Report of the editors, 2010]

The Editors of the Rev Clin Esp inform herein on their editorial activity in the last year (November 2009 to October 2010) according to three different sections: (a) Objectives and achievements during 2010, (b) editorial activity, and (c) objectives for 2011. During 2010, we have updated the editorial algorithm (manuscript time lag). We have developed the "E-case reports" section and we have linked the abstracts of the Annual Congress of the Spanish Society of Internal Medicine (SEMI) to a journal supplement (electronically available). Since 2010, the subscribers have been able to receive all of the contents of the Rev Clin Esp on-line and to perform self-evaluations in order to obtain 1.7 credits per each journal issue (continuing education). In 2010 we handled 402 manuscripts (7.2% more than in 2009), 35% of which were accepted for publication. We asked 186 reviewers for their expert opinion, 75% of whom sent their reports in less than two weeks. The mean time needed to reach an editorial decision concerning original manuscripts ("accepted / rejected") was 44.5 days and for papers not sent to external reviewers 19.5 days. Collaboration with the work groups produced good results (2.4 published manuscripts per issue), but this could be improved if all the groups collaborated in all the journal sections. Our objectives for 2011 are to complete the renewal of the Rev Clin Esp scientific committee, in accordance with the SEMI Council, and to continue to proceed with the actions initiated to increase the journal impact factor. Rev Clim Esp is an open forum for all internal medicine specialists. Responsibility falls on all of us to collaborate in order to make our journal a little better day by day.