scholarly journals We need to talk about reliability: making better use of test-retest studies for study design and interpretation

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6918 ◽  
Author(s):  
Granville J. Matheson
Keyword(s):  
Clinical Research ◽  
Study Design ◽  
Validation Studies ◽  
Clinical Studies ◽  
R Package ◽  
Experimental Designs ◽  
Summary Statistics ◽  
Different Populations ◽  
Scientific Questions ◽  
Healthy Participants

Neuroimaging, in addition to many other fields of clinical research, is both time-consuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is exacerbated by the use of outcome measures whose accuracy is sometimes insufficient to answer the scientific questions posed. Reliability is usually assessed in validation studies using healthy participants, however these results are often not easily applicable to clinical studies examining different populations. I present a new method and tools for using summary statistics from previously published test-retest studies to approximate the reliability of outcomes in new samples. In this way, the feasibility of a new study can be assessed during planning stages, and before collecting any new data. An R package called relfeas also accompanies this article for performing these calculations. In summary, these methods and tools will allow researchers to avoid performing costly studies which are, by virtue of their design, unlikely to yield informative conclusions.

scholarly journals We need to talk about reliability: Making better use of test-retest studies for study design and interpretation

2018 ◽  
Author(s):  
Granville J. Matheson
Keyword(s):  
Positron Emission Tomography ◽  
Validation Studies ◽  
R Package ◽  
Experimental Designs ◽  
Emission Tomography ◽  
Summary Statistics ◽  
Positron Emission ◽  
Different Populations ◽  
Scientific Questions ◽  
Healthy Participants

ABSTRACTPositron emission tomography (PET), along with many other fields of clinical research, is both timeconsuming and expensive, and recruitable patients can be scarce. These constraints limit the possibility of large-sample experimental designs, and often lead to statistically underpowered studies. This problem is exacerbated by the use of outcome measures whose accuracy is sometimes insufficient to answer the scientific questions posed. Reliability is usually assessed in validation studies using healthy participants, however these results are often not easily applicable to clinical studies examining different populations. I present a new method and tools for using summary statistics from previously published test-retest studies to approximate the reliability of outcomes in new samples. In this way, the feasibility of a new study can be assessed during planning stages, and before collecting any new data. An R package called relfeas also accompanies this article for performing these calculations. In summary, these methods and tools will allow researchers to avoid performing costly studies which are, by virtue of their design, unlikely to yield informative conclusions.

scholarly journals In Vitro,In Vivo, and Clinical Studies of Tedizolid To Assess the Potential for Peripheral or Central Monoamine Oxidase Interactions

2013 ◽  
Vol 57 (7) ◽  
pp. 3060-3066 ◽  
Author(s):  
S. Flanagan ◽  
K. Bartizal ◽  
S. L. Minassian ◽  
E. Fang ◽  
P. Prokocimer
Keyword(s):  
Blood Pressure ◽  
Monoamine Oxidase ◽  
Clinical Research ◽  
Systolic Blood Pressure ◽  
Clinical Studies ◽  
Geometric Mean ◽  
Interaction Study ◽  
Mao B ◽  
Mao A

ABSTRACTTedizolid phosphate is a novel oxazolidinone prodrug whose active moiety, tedizolid, has improved potency against Gram-positive pathogens and pharmacokinetics, allowing once-daily administration. Given linezolid warnings for drug-drug and drug-food interactions mediated by monoamine oxidase (MAO) inhibition, including sporadic serotonergic toxicity, these studies evaluated tedizolid for potential MAO interactions.In vitro, tedizolid and linezolid were reversible inhibitors of human MAO-A and MAO-B; the 50% inhibitory concentration (IC50) for tedizolid was 8.7 μM for MAO-A and 5.7 μM for MAO-B and 46.0 and 2.1 μM, respectively, with linezolid. Tedizolid phosphate was negative in the mouse head twitch model of serotonergic activity. Two randomized placebo-controlled crossover clinical studies assessed the potential of 200 mg/day tedizolid phosphate (at steady state) to enhance pressor responses to coadministered oral tyramine or pseudoephedrine. Sensitivity to tyramine was determined by comparing the concentration of tyramine required to elicit a ≥30-mmHg increase in systolic blood pressure (TYR30) when administered with placebo versus tedizolid phosphate. The geometric mean tyramine sensitivity ratio (placebo TYR30/tedizolid phosphate TYR30) was 1.33; a ratio of ≥2 is considered clinically relevant. In the pseudoephedrine study, mean maximum systolic blood pressure was not significantly different when pseudoephedrine was coadministered with tedizolid phosphate versus placebo. In summary, tedizolid is a weak, reversible inhibitor of MAO-A and MAO-Bin vitro. Provocative testing in humans and animal models failed to uncover significant signals that would suggest potential for hypertensive or serotonergic adverse consequences at the therapeutic dose of tedizolid phosphate. Clinical studies are registered atwww.clinicaltrials.govas NCT01539473 (tyramine interaction study conducted at Covance Clinical Research Center, Evansville, IN) and NCT01577459 (pseudoephedrine interaction study conducted at Vince and Associates Clinical Research, Overland Park, KS).

scholarly journals CLARITY: comparing heterogeneous data using dissimilarity

2021 ◽  
Vol 8 (12) ◽  
Author(s):  
Daniel J. Lawson ◽  
Vinesh Solanki ◽  
Igor Yanovich ◽  
Johannes Dellert ◽  
Damian Ruck ◽  
...  
Keyword(s):  
Cultural Beliefs ◽  
R Package ◽  
Heterogeneous Data ◽  
Gene Methylation ◽  
Evolution Of Language ◽  
Word Use ◽  
Country Level ◽  
Expression Evolution ◽  
Scientific Questions ◽  
Robust To Noise

Integrating datasets from different disciplines is hard because the data are often qualitatively different in meaning, scale and reliability. When two datasets describe the same entities, many scientific questions can be phrased around whether the (dis)similarities between entities are conserved across such different data. Our method, CLARITY, quantifies consistency across datasets, identifies where inconsistencies arise and aids in their interpretation. We illustrate this using three diverse comparisons: gene methylation versus expression, evolution of language sounds versus word use, and country-level economic metrics versus cultural beliefs. The non-parametric approach is robust to noise and differences in scaling, and makes only weak assumptions about how the data were generated. It operates by decomposing similarities into two components: a ‘structural’ component analogous to a clustering, and an underlying ‘relationship’ between those structures. This allows a ‘structural comparison’ between two similarity matrices using their predictability from ‘structure’. Significance is assessed with the help of re-sampling appropriate for each dataset. The software, CLARITY, is available as an R package from github.com/danjlawson/CLARITY .

scholarly journals Time arrow in published clinical studies/trials indexed in MEDLINE: a systematic analysis of Retrospective vs Prospective study design, from 1960 to 2017.

2018 ◽  
Author(s):  
Michele M Ciulla ◽  
Patrizia Vivona
Keyword(s):  
Prospective Study ◽  
Study Design ◽  
Low Income ◽  
Clinical Studies ◽  
Human Subjects ◽  
Systematic Analysis ◽  
Time Line ◽  
Time Arrow ◽  
Prospective Study Design ◽  
Single Time Point

Clinical studies/trials are experiments or observations on human subjects considered by the scientific community the most appropriate instrument to answer specific research questions on interventions on health outcomes. The time-line of the observations might be focused on a single time point or to follow time, backward or forward, in the so called, respectively, retrospective and prospective study design. Since the retrospective approach has been criticized for the possible sources of errors due to bias and confounding, we aimed this study to assess if there is a prevalence of retrospective vs prospective design in the clinical studies/trials by querying MEDLINE. Our results on a sample of 1,438,872 studies/trials, (yrs 1960-2017), support a prevalence of retrospective, respectively 55% vs 45%. To explain this result, arandom sub-sample of studies where the country of origin was reported (n=1576) was categorized in high and low-income based onthe nominal Gross Domestic Product (GDP) and matched with the topic of the research. As expected, the absolute majority of studies/trials are carried on by high-income countries, respectively 86% vs 14%; even if a slight prevalence of retrospective was recorded in both income groups, nonetheless the most part of prospective studies are carried out by high-GDP countries, 85% vs 15%. Finally the differences in the design of the study are understandable when considering the topic of the research.

scholarly journals Reporting Standards for Clinical and Translational Research

2019 ◽  
pp. 69-73
Author(s):  
Fengyu Zhang ◽  
Claude Hughes
Keyword(s):  
Clinical Research ◽  
Study Design ◽  
Repeated Measurements ◽  
Sufficient Information ◽  
Reporting Standards ◽  
Preclinical Research ◽  
Study Protocols ◽  
Real World Evidence ◽  
Funding Agencies ◽  
Rigorous Study

Transparency in reporting the results of clinical and preclinical research is critical for unbiased publications. Funding agencies, publishers, and regulators have the responsibility to advocate and implement reporting standards for rigorous design. While individual study protocols may have included these standards, the items reported in the respective publications have often been inconsistent or lack transparency. This editorial intends to provide some specific guidelines for reporting results of clinical research with standards required for rigorous study design. We recommend that reporting clinical research should include sufficient information on study design and analysis plan that contains data processing, quality assurance, and appropriate methods used for rigorous statistical analysis or modeling. Any discrepancy between publications and original study design should be disclosed and discussed. Additionally, recent advances in the analysis of outcome with repeated measurements and statistical modeling should be employed to obtain unbiased estimates. Finally, we briefly discuss some issues reporting real-world evidence in clinical research.

scholarly journals Remdesivir: Critical Clinical Appraisal for COVID 19 Treatment

Drug Research ◽  
2020 ◽  
Author(s):  
Saptarshi Chatterjee
Keyword(s):  
Clinical Trials ◽  
Clinical Research ◽  
Clinical Studies ◽  
Promising Result ◽  
Drug Repurposing ◽  
In Vitro Studies ◽  
Therapeutic Molecules ◽  
Regulatory Aspect ◽  
Plausible Mechanism

AbstractRemdesivir is presently been considered as ‘molecule of hope’ to curb the menace of COVID19. Non-availability of any USFDA approved drug has led to several attempt of drug-repurposing and development of new therapeutic molecules. However, Remdesivir has been found to be effective against a broad range of virus including SARS, MERS and COVID 19 through in-vitro studies. Several clinical research attempt are presently being conducted showing promising result yet not conclusive. This review summarized all such clinical trials to critically appraise the usage of Remdesivir against COVID 19 along with the publications related to the results of the clinical studies. The present regulatory aspect i. e. Emergency Use Authorization (EYA) and information of molecule and plausible mechanism is also dealt.

Gene-based association tests using GWAS summary statistics

2019 ◽  
Vol 35 (19) ◽  
pp. 3701-3708 ◽  
Author(s):  
Gulnara R Svishcheva ◽  
Nadezhda M Belonogova ◽  
Irina V Zorkoltseva ◽  
Anatoly V Kirichenko ◽  
Tatiana I Axenovich
Keyword(s):  
Association Analysis ◽  
Association Studies ◽  
R Package ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
New Material ◽  
Artery Disease ◽  
The Many ◽  
Functional Linear Regression

Abstract Motivation A huge number of genome-wide association studies (GWAS) summary statistics freely available in databases provide a new material for gene-based association analysis aimed at identifying rare genetic variants. Only a few of the many popular gene-based methods developed for individual genotype and phenotype data are adapted for the practical use of the GWAS summary statistics as input. Results We analytically prove and numerically illustrate that all popular powerful methods developed for gene-based association analysis of individual phenotype and genotype data can be modified to utilize GWAS summary statistics. We have modified and implemented all of the popular methods, including burden and kernel machine-based tests, multiple and functional linear regression, principal components analysis and others, in the R package sumFREGAT. Using real summary statistics for coronary artery disease, we show that the new package is able to detect genes not found by the existing packages. Availability and implementation The R package sumFREGAT is freely and publicly available at: https://CRAN.R-project.org/package=sumFREGAT. Supplementary information Supplementary data are available at Bioinformatics online.

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