Quality Of Experimental Design Research Articles

An Umbrella Review of Effectiveness of Intravenous Ketamine in Treatment-Resistant Depression

IntroductionMajor depressive disorder (MDD) is a tremendous global disease burden and the leading cause of disability worldwide. Unfortunately, individuals diagnosed with MDD typically experience a delayed response to traditional antidepressants and many do not adequately respond to pharmacotherapy, even after multiple trials. The critical need for novel antidepressant treatments has led to a recent resurgence in the clinical application of psychedelics, and intravenous ketamine, which has been investigated as a rapid-acting treatment for treatment resistant depression (TRD) as well acute suicidal ideation and behavior. However, variations in the type and quality of experimental design as well as a range of treatment outcomes in clinical trials of ketamine make interpretation of this large body of literature challenging.ObjectivesThis umbrella review aims to advance our understanding of the effectiveness of intravenous ketamine as a pharmacotherapy for TRD by providing a systematic, quantitative, large-scale synthesis of the empirical literature.MethodsWe performed a comprehensive PubMed search for peer-reviewed meta-analyses of primary studies of intravenous ketamine used in the treatment of TRD. Meta-analysis and primary studies were then screened by two independent coding teams according to pre-established inclusion criteria as well as PRISMA and METRICS guidelines. We then employed metaumbrella, a statistical package developed in R, to perform effect size calculations and conversions as well as statistical tests.ResultsIn a large-scale analysis of 1,182 participants across 51 primary studies, repeated-dose administration of intravenous ketamine demonstrated statistically significant effects (p<0.05) compared to placebo-controlled as well as other experimental conditions in patients with TRD, as measured by standardized clinician-administered and self-report depression symptom severity scales.ConclusionsThis study provides large-scale, quantitative support for the effectiveness of intravenous, repeated-dose ketamine as a therapy for TRD and a report of the relative effectiveness of several treatment parameters across a large and rapidly growing literature. Future investigations should use similar analytic tools to examine evidence-stratified conditions and the comparative effectiveness of other routes of administration and treatment schedules as well as the moderating influence of other clinical and demographic variables on the effectiveness of ketamine on TRD and suicidal ideation and behavior.Disclosure of InterestNone Declared

Compressive Review on Plant Profile, Ethnomedicinal Uses, Phytochemistry and Pharmacology of Paeonia emodi Royle (Himalayan Paeony)

Members of the genus Paeonia, which contains well-known ornamentals as well as traditional medicinal plants with a history reaching back over 1500 years, may be found all throughout the Northern Hemisphere. Many of these ethnomedicinal properties have been studied in animal models. It has been listed as a critically endangered plant species. P. emodi has been shown to have antioxidant, nephroprotective, lipoxygenase inhibitory, cognition and oxidative stress release, cytotoxic, anti-inflammatory, antiepileptic, anticonvulsant, haemaglutination, alphachymotrypsin inhibitory, hepatoprotective, hepatic chromes, and pharmacokinetics of carbamazepine expression. spas Data was acquired from unpublished theses (India, China, Pakistan, and Nepal) and numerous published research articles related to pharmacology, phytochemistry, and other activities using certain keywords. The pertinent information about medicinal uses, taxonomic/common names, parts used, collection and recognition source, authentication, voucher specimen number, plant extracts and their characterization, isolation and characterization of phytochemicals, methods of study (in silico, in vivo, or in vitro), model organism used, dose and time, minimal active concentration, bioactive compound(s), mechanism of action on single or multiple targets, and toxicological information. Triterpenoids, monoterpenoids, phenolics, and tannins are among the natural substances produced by the species. The purpose of this study was to collect broad traditional medicinal uses, phytochemistry, pharmacology, and toxicological data on P. emodi. This work also emphasises taxonomic validity, experimental design quality, and weaknesses in previously published Himalayan paeony material, which may help researchers plan for future research.

Abstract 153: Development of a workflow to handle the quality control and analysis of Olink protein biomarker data in early phase oncology clinical trials

Abstract INTRODUCTION: Olink is a high-throughput targeted biomarker platform based on Proximity Extension Assay (PEA) technology using oligonucleotide-labeled antibody pairs. At AbbVie RWC, we have primarily utilized the 96-plex Immune-Oncology (IO) panel measuring 92 proteins to support our early-phase oncology clinical trials. As we analyzed batches of specimens from ongoing trials, we set out to develop a workflow to control data quality and streamline analysis. METHODS: Prior to sample shipment to Olink, we randomize sample position onto plates to ensure key factors such as dose and cohort are balanced within and across plates. This prevents plate or location effects from becoming a confounder. If the study specimens are analyzed in more than one batch, subsequent batches require bridging samples from the first batch to allow us to detect and remove batch effects if necessary. Our workflow thus identifies bridging samples and recommends the optimal number. Upon receiving the data, we evaluate its quality by calculating inter- and intra-plate coefficients of variation (CVs) and visualizing it in multiple ways. The next step in our workflow is analysis, including pharmacodynamic (PD) analysis and association with clinical response. In the PD analysis, we identify biomarkers that significantly change across time and/or exhibit a dose effect. To help interpret the results, enrichment analysis is performed to identify biological processes enriched in the significantly modulated biomarkers. Heatmaps and volcano plots are also generated. For analysis of association with clinical response, we examine how each biomarkers' baseline value and modulation over time associates with progression free survival (PFS) and best overall response (BOR). RESULTS: We successfully created a workflow that handles quality control and analysis of Olink protein biomarker data. The workflow starts from experimental design quality control. Upon receiving the data, we conduct data quality assessment and examination and removal of potential batch effects. Finally, we perform analysis of the data to identify potential biomarkers of interest. We used elements of this workflow on data from M15-891 (ABBV-181) and have now applied the full workflow to multiple batches of data from three early-phase oncology trials (M15-862 (ABBV-927), M16-074 (ABBV-368) and M19-345 (ABBV-151)), with plans to incorporate this methodology into several additional upcoming trials. CONCLUSIONS: We have developed a comprehensive workflow that manages Olink quality control and analysis and can potentially be implemented to all early-phase oncology clinical trials using Olink. It allows us to standardize and streamline Olink data handling and provide robust and efficient analyses that enable rapid biomarker data interpretation, hypothesis generation, and decision making for our trials. Citation Format: Claire J. Guo, Mary Saltarelli, Stacie Lambert, Hua Fang, Chun Zhang. Development of a workflow to handle the quality control and analysis of Olink protein biomarker data in early phase oncology clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 153.

Clinician certainty with the evidence: In practice, it's complicated

Clinician certainty with the evidence: In practice, it's complicated

Testing experimental designs in liquid chromatography (I): Development and validation of a method for the comprehensive inspection of experimental designs

The basis of interpretive optimisation in liquid chromatography is the prediction of resolution, from appropriate solute retention models. The reliability of the process depends critically on the quality of the experimental design. This work develops, validates and applies a general methodology aimed to evaluate the quality of any training experimental design, which will be applied in Part II to design optimisation. The methodology is based on the systematic evaluation of the uncertainties associated to the prediction of retention times in comprehensive scans of both isocratic and gradient experimental conditions. It is able to evaluate comprehensively experimental designs of arbitrary complexity. Five common training experimental designs were used to model the retention, according to the Linear Solvent Strength (LSS) and the Neue-Kuss (NK) equations, using a set of 14 sulphonamides of different polarity. The results are presented in terms of relative uncertainties in predictions, which provide significant and interpretable results. The magnitude of such uncertainties, together with the systematic, coherent and logical changes observed at increasing solute hydrophobicity, give support to the results. The NK model gave smaller errors and unbiased predictions, whereas the LSS model gave rise to lack of fit. Isocratic training designs, which are widely accepted as the most informative, are confirmed as the best. As a general conclusion, gradients are predicted with intrinsically smaller uncertainties, independently of the training experimental design. In addition, gradients are more insensitive than isocratic predictions with regard to the type of training design used. Isocratic predictions deteriorate quickly with mobile phase composition. This explains the better performance of gradient predictions, even with biased models.

A sequential experimental design for multivariate sensitivity analysis using polynomial chaos expansion

ABSTRACT Multivariate output sensitivity analysis has gained much attention when the output of the computational model is a vector. A preferable strategy to deal with the multivariate output issue is the covariance decomposition approach based on the polynomial chaos expansion (PCE) metamodel. However, since the PCE construction depends on the quality of experimental design to some extent, the selection of design points is significant in determining the accuracy of the sensitivity estimator. In this article, a PCE-based sequential experimental design is proposed to estimate the multivariate output sensitivity index. In this method, the optimal design point is sequentially selected to minimize the determinant of covariance matrix of the sensitivity estimator. To validate the performance of the proposed method, several numerical examples are presented, which show that the sequential design approach performs better than other prevalent methods in terms of accuracy and robustness.

Exploring a Mechanistic Approach to Experimentation in Computing

The mechanistic approach in philosophy of science contributes to our understanding of experimental design. Applying the mechanistic approach to experimentation in computing is beneficial for two reasons. It connects the methodology of experimentation in computing with the methodology of experimentation in established sciences, thereby strengthening the scientific reputability of computing and the quality of experimental design therein. Furthermore, it pinpoints the idiosyncrasies of experimentation in computing: computing deals closely with both natural and engineered mechanisms. Better understanding of the idiosyncrasies, which manifest in terms of a nonstandard role for experimentation, are interesting both for computer scientists and for philosophers of science. Computer scientists can think more clearly about their experimental choices. The role of experimentation elucidated by computer science merits further study from philosophers of science generally, as it highlights a role for experimentation hitherto unrecognized by philosophers: demonstration that activities exist.

Errorless learning of everyday tasks in people with dementia

Errorless learning (EL) is a principle used to teach new information or skills to people with cognitive impairment. In people with dementia, EL principles have mostly been studied in laboratory tasks that have little practical relevance for the participants concerned, yet show positive effects. This is the first paper to exclusively review the literature concerning the effects of EL on the performance of useful everyday tasks in people with dementia. The role of factors such as type of dementia, type of task, training intensity, EL elements, outcome measures, quality of experimental design, and follow-up are discussed. The results indicate that, compared with errorful learning (EF) or no treatment, EL is more effective in teaching adults with dementia a variety of meaningful daily tasks or skills, with gains being generally maintained at follow-up. The effectiveness of EL is highly relevant for clinical practice because it shows that individuals with dementia are still able to acquire meaningful skills and engage in worthwhile activities, which may potentially increase their autonomy and independence, and ultimately their quality of life, as well as reduce caregiver burden and professional dependency. Suggestions for future research are given, along with recommendations for effective EL-based training programs, with the aim of developing a clinical manual for professionals working in dementia care.

Validity of the Clinical Diagnostic Criteria for Vascular Dementia: A Critical Review. Part II

This review is the second of a two-part series focusing on the validity of eight clinical criteria for vascular dementia. Sixteen studies were selected according to their purposes and quality of experimental design. The analysis revealed that criteria for vascular dementia are not interchangeable; the eight criteria sets yielded different sensitivity and specificity results, as well as marked variability in incidence, prevalence, and frequency rates. Although the State of California Alzheimer's Disease Diagnostic and Treatment Centers (ADDTC) were the most sensitive and useful criteria in clinical settings and the National Institute of Neurological Disorders and Stroke-Association Internationale pour la Recherche et l'Enseignement en Neurosciences (NINDS-AIREN) were the most specific and useful criteria in research, all criteria shared similar flaws. A definition of the cognitive syndrome, associated vascular causes or lesions, and methods of assessment should be clearly specified in the future. Suggestions for improvement are made.

A Compromise Experimental Design Method for Parametric Polynomial Response Surface Approximations

This study presents a compromise approach to augmentation of experimental designs, necessitated by the expense of performing each experiment (computational or physical), that yields higher quality parametric polynomial response surface approximations than traditional augmentation. Based on the D-optimality criterion as a measure of experimental design quality, the method simultaneously considers several polynomial models during the experimental design, resulting in good quality designs for all models under consideration, as opposed to good quality designs only for lower-order models, as in the case of traditional augmentation. Several numerical examples and an engineering example are presented to illustrate the efficacy of the approach.

Soy Isoflavones—Phytoestrogens and What Else?

The weak estrogen-like properties of isoflavonoids were discovered over 50 y ago. In recent years, the overall effects of the isoflavones in soy on human health have been the subject of lively debate largely based on their presumed estrogenic properties. Missing from our knowledge base is the systematic identification of the cellular and biochemical targets of isoflavones and the mechanisms that they influence. Because of the benign effects of isoflavones on cellular integrity, a concentration of the isoflavones can be reached in cell culture models where almost any process can be modulated. Modern systems biology approaches and high dimensional analysis techniques offer new ways to better understand the function of how cells and integrated biological mechanisms respond to compounds such as isoflavones. Data from experiments using DNA microarray analysis for examining the effects of genistein in the developing rat uterus indicate that genistein alters the expression of 6-8 times as many genes as does a physiological estrogen such as 17 beta-estradiol. Although these new approaches are exciting, their incipient high dimensionality places considerable strain on the quality of experimental design and meaningful statistical interpretation of the resulting data. In another approach using affinity chromatography methods, DING, a novel genistein-binding protein of yet unknown function, was isolated from human breast cancer MCF-7 cells. Its function remains to be established.

Software Reviews : Topics in Research Methods: Power, Version 1.0

POWER uses a series of simulated experiments to introduce students to the statistical concepts of quality of experimental design and error variance. The experiments are based on a real-life comparison of electricity use in homes with and without a signaling device for home cooling. POWER allows the student to modify the experiment in six variable areas and manipulate combinations of those variables to influence changes in the power of the test and in the amount of statistical error in the experimental setting. POWER is useful for demonstrating the concepts of power and error variance, but it does not allow for the introduction of independent data for student-generated investigations.