Research Design Considerations.
Ontology highlight
ABSTRACT:
SUBMITTER: Wright S
PROVIDER: S-EPMC4763399 | biostudies-literature | 2016 Feb
REPOSITORIES: biostudies-literature
Publications
Research Design Considerations.
Wright Sarah S O'Brien Bridget C BC Nimmon Laura L Law Marcus M Mylopoulos Maria M
Journal of graduate medical education 20160201 1
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Project description:Although certain risk factors can identify individuals who are most likely to develop chronic pain, few interventions to prevent chronic pain have been identified. To facilitate the identification of preventive interventions, an IMMPACT meeting was convened to discuss research design considerations for clinical trials investigating the prevention of chronic pain. We present general design considerations for prevention trials in populations that are at relatively high risk for developing chronic pain. Specific design considerations included subject identification, timing and duration of treatment, outcomes, timing of assessment, and adjusting for risk factors in the analyses. We provide a detailed examination of 4 models of chronic pain prevention (ie, chronic postsurgical pain, postherpetic neuralgia, chronic low back pain, and painful chemotherapy-induced peripheral neuropathy). The issues discussed can, in many instances, be extrapolated to other chronic pain conditions. These examples were selected because they are representative models of primary and secondary prevention, reflect persistent pain resulting from multiple insults (ie, surgery, viral infection, injury, and toxic or noxious element exposure), and are chronically painful conditions that are treated with a range of interventions. Improvements in the design of chronic pain prevention trials could improve assay sensitivity and thus accelerate the identification of efficacious interventions. Such interventions would have the potential to reduce the prevalence of chronic pain in the population. Additionally, standardization of outcomes in prevention clinical trials will facilitate meta-analyses and systematic reviews and improve detection of preventive strategies emerging from clinical trials.
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Project description:High-throughput, massively parallel sequence analysis has revolutionized the way that researchers design and execute scientific investigations. Vast amounts of sequence data can be generated in short periods of time. Regarding ophthalmology and vision research, extensive interrogation of patient samples for underlying causative DNA mutations has resulted in the discovery of many new genes relevant to eye disease. However, such analysis remains functionally limited. RNA-sequencing accurately snapshots thousands of genes, capturing many subtypes of RNA molecules, and has become the gold standard for transcriptome gene expression quantification. RNA-sequencing has the potential to advance our understanding of eye development and disease; it can reveal new candidates to improve our molecular diagnosis rates and highlight therapeutic targets for intervention. But with a wide range of applications, the design of such experiments can be problematic, no single optimal pipeline exists, and therefore, several considerations must be undertaken for optimal study design. We review the key steps involved in RNA-sequencing experimental design and the downstream bioinformatic pipelines used for differential gene expression. We provide guidance on the application of RNA-sequencing to ophthalmology and sources of open-access eye-related data sets.
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Project description:Opioids are essential to the management of pain in many patients, but they also are associated with potential risks for abuse, overdose, and diversion. A number of efforts have been devoted to the development of abuse-deterrent formulations of opioids to reduce these risks. This article summarizes a consensus meeting that was organized to propose recommendations for the types of clinical studies that can be used to assess the abuse deterrence of different opioid formulations. Because of the many types of individuals who may be exposed to opioids, an opioid formulation will need to be studied in several populations using various study designs to determine its abuse-deterrent capabilities. It is recommended that the research conducted to evaluate abuse deterrence should include studies assessing: (1) abuse liability, (2) the likelihood that opioid abusers will find methods to circumvent the deterrent properties of the formulation, (3) measures of misuse and abuse in randomized clinical trials involving pain patients with both low risk and high risk of abuse, and (4) postmarketing epidemiological studies.
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Project description:The changing landscape of genomics research and clinical practice has created a need for computational pipelines capable of efficiently orchestrating complex analysis stages while handling large volumes of data across heterogeneous computational environments. Workflow Management Systems (WfMSs) are the software components employed to fill this gap. This work provides an approach and systematic evaluation of key features of popular bioinformatics WfMSs in use today: Nextflow, CWL, and WDL and some of their executors, along with Swift/T, a workflow manager commonly used in high-scale physics applications. We employed two use cases: a variant-calling genomic pipeline and a scalability-testing framework, where both were run locally, on an HPC cluster, and in the cloud. This allowed for evaluation of those four WfMSs in terms of language expressiveness, modularity, scalability, robustness, reproducibility, interoperability, ease of development, along with adoption and usage in research labs and healthcare settings. This article is trying to answer, which WfMS should be chosen for a given bioinformatics application regardless of analysis type?. The choice of a given WfMS is a function of both its intrinsic language and engine features. Within bioinformatics, where analysts are a mix of dry and wet lab scientists, the choice is also governed by collaborations and adoption within large consortia and technical support provided by the WfMS team/community. As the community and its needs continue to evolve along with computational infrastructure, WfMSs will also evolve, especially those with permissive licenses that allow commercial use. In much the same way as the dataflow paradigm and containerization are now well understood to be very useful in bioinformatics applications, we will continue to see innovations of tools and utilities for other purposes, like big data technologies, interoperability, and provenance.
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Project description:E-mental health programmes have great potential to provide young people with access to mental health support. However, it is commonly reported that adherence to these programmes is low. Low adherence can be problematic, particularly if young people do not receive the full benefits of a programme. In a research trial setting, non-adherence to treatment recommendations can prevent researchers from drawing strong conclusions about effectiveness. Although adherence has been recognised as an issue in need of attention, many of the reviews available are focused on adults and lack clear direction towards what strategies to employ. This paper presents a broad review of the adherence literature, focusing on factors associated with improving adherence to e-mental health among youth. Our view on the key elements to improve adherence identified from the existing literature are presented, and key recommendations for e-mental health intervention design are provided. These include: developing and communicating adherence guidelines based on individuals' needs and symptom severity, including customisable features to provide a tailored experience and promote a sense of agency, including engagement checks and adopting a user-centred approach by utilising strategies such as co-design. This paper provides guidance to intervention designers and researchers by outlining recommendations and considerations for intervention development and research design.
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Project description:Loss of function screens using shRNA and CRISPR are routinely used to identify genes that modulate responses of tumor cells to anti-cancer drugs. Here, by integrating GSEA and CMAP analyses of multiple published shRNA screens, we identified a core set of pathways that affect responses to multiple drugs with diverse mechanisms of action. This suggests that these pathways represent “weak points” or “Achilles heels”, whose mild disturbance should make cancer cells vulnerable to a variety of treatments. These “weak points” include proteasome, protein synthesis, RNA splicing, RNA synthesis, cell cycle, Akt-mTOR, and tight junction-related pathways. Therefore, inhibitors of these pathways are expected to sensitize cancer cells to a variety of drugs. This hypothesis was tested by analyzing the diversity of drugs that synergize with FDA-approved inhibitors of the proteasome, RNA synthesis, and Akt-mTOR pathways. Indeed, the quantitative evaluation indicates that inhibitors of any of these signaling pathways can synergize with a more diverse set of pharmaceuticals, compared to compounds inhibiting targets distinct from the “weak points” pathways. Our findings described here imply that inhibitors of the “weak points” pathways should be considered as primary candidates in a search for synergistic drug combinations. We used microarray to identify genetic interaction partners of 2 drugs
2025-01-06 | GSE221858 | GEO
Project description:ObjectiveMedication non-adherence is a widespread problem and has been known to be associated with worse health outcomes and increased healthcare costs. Although many measures of adherence have been developed, their usage is not consistent across studies. Furthermore, statistical methods for analyzing adherence measures have not been rigorously evaluated.MethodsUsing Proportion of Days Covered (PDC), a commonly used adherence measure, we examine the variability inherent to study inclusion criteria and several variations of the PDC calculation method using a motivating data example. We illustrated via sensitivity analyses the potential for flawed inference when modeling PDC as an outcome measure. We also performed simulation studies to investigate the statistical properties of three statistical models: logistic regression, negative binomial, and ordinal logistic regression models.ResultsOur sensitivity analysis showed that parameter estimates can vary greatly depending on the rules for determining the study end date in calculating PDC, or the minimum number of fills in defining the cohort. In simulation studies, logistic regression had lower power than ordinal logistic and negative binomial regression models. Naivete to treatment was an important predictor of adherence and omitting it from statistical models can lead to inflated type I errors.ConclusionsWe discourage dichotomizing adherence data as it results in low power. The negative binomial model offers advantages in modeling adherence data, as it avoids the problematic use of a ratio in regression models. The ordinal logistic regression is robust to distributional assumptions with greater power, but naivete to treatment should be adjusted to reserve type I error rate. We also provide a recommendation for defining the observation window in calculating PDC.
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Project description:Background:Several typologies and guidelines are available to address the methodological and practical considerations required in mental health research. However, few studies have actually attempted to systematically identify and synthesise these considerations. This paper provides an integrative review that identifies and synthesises the available research evidence on mental health research methodological considerations. Methods:A search of the published literature was conducted using EMBASE, Medline, PsycINFO, CINAHL, Web of Science, and Scopus. The search was limited to papers published in English for the timeframe 2000-2018. Using pre-defined inclusion and exclusion criteria, three reviewers independently screened the retrieved papers. A data extraction form was used to extract data from the included papers. Results:Of 27 papers meeting the inclusion criteria, 13 focused on qualitative research, 8 mixed methods and 6 papers focused on quantitative methodology. A total of 14 papers targeted global mental health research, with 2 papers each describing studies in Germany, Sweden and China. The review identified several methodological considerations relating to study design, methods, data collection, and quality assurance. Methodological issues regarding the study design included assembling team members, familiarisation and sharing information on the topic, and seeking the contribution of team members. Methodological considerations to facilitate data collection involved adequate preparation prior to fieldwork, appropriateness and adequacy of the sampling and data collection approach, selection of consumers, the social or cultural context, practical and organisational skills; and ethical and sensitivity issues. Conclusion:The evidence confirms that studies on methodological considerations in conducting mental health research largely focus on qualitative studies in a transcultural setting, as well as recommendations derived from multi-site surveys. Mental health research should adequately consider the methodological issues around study design, sampling, data collection procedures and quality assurance in order to maintain the quality of data collection.
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Project description:Nanotherapeutics have improved the quality of life of cancer patients, primarily by reducing the adverse effects of chemotherapeutic agents, but improvements in overall survival are modest. This is in large part due to the fact that the enhanced permeability and retention effect, which is the basis for the use of nanoparticles in cancer, can be also a barrier to the delivery of nanomedicines. A careful design of nanoparticle formulations can overcome barriers posed by the tumor microenvironment and result in better treatments. In this review, we first discuss strengths and limitations of clinically-approved nanoparticles. Then, we evaluate design parameters that can be modulated to optimize delivery. The benefits of active tumor targeting and drug release rate on intratumoral delivery and treatment efficacy are also discussed. Finally, we suggest specific design strategies that should optimize delivery to most solid tumors and discuss under what conditions active targeting would be beneficial.Advances in nanotechnology have seen the introduction of new treatment modalities for cancer. The principle of action using nanocarriers for drug delivery is based mostly on the Enhanced Permeability and Retention effect. This phenomenon however, can also be a hindrance. In this article, the authors performed an in-depth review on various nanoparticle platforms in cancer therapeutics. They also suggested options to improve drug delivery, in terms of carrier design.
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