Clinical Trials, Case Studies, and Oral Care R&D: Inclusivity, Consistency, and Other Atypical Evidence

2010 ◽  
Vol 10 (1) ◽  
pp. 10-12 ◽  
Author(s):  
Robert W. Gerlach
Keyword(s):  
Clinical Trials ◽  
Case Studies ◽  
Oral Care

scholarly journals Accounting for quality improvement during the conduct of embedded pragmatic clinical trials within healthcare systems: NIH Collaboratory case studies

Healthcare ◽  
2021 ◽  
Vol 8 ◽  
pp. 100432
Author(s):  
Leah Tuzzio ◽  
Catherine M. Meyers ◽  
Laura M. Dember ◽  
Corita R. Grudzen ◽  
Edward R. Melnick ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Quality Improvement ◽  
Case Studies ◽  
Healthcare Systems ◽  
Pragmatic Clinical Trials

scholarly journals The impact of patient-reported outcome (PRO) data from clinical trials: a systematic review and critical analysis

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Samantha Cruz Rivera ◽  
Derek G. Kyte ◽  
Olalekan Lee Aiyegbusi ◽  
Anita L. Slade ◽  
Christel McMullan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Case Studies ◽  
Real World ◽  
Clinical Trial Data ◽  
Research Impact ◽  
Trial Data ◽  
Patient Reported ◽  
The Impact

Abstract Background Patient-reported outcomes (PROs) are commonly collected in clinical trials and should provide impactful evidence on the effect of interventions on patient symptoms and quality of life. However, it is unclear how PRO impact is currently realised in practice. In addition, the different types of impact associated with PRO trial results, their barriers and facilitators, and appropriate impact metrics are not well defined. Therefore, our objectives were: i) to determine the range of potential impacts from PRO clinical trial data, ii) identify potential PRO impact metrics and iii) identify barriers/facilitators to maximising PRO impact; and iv) to examine real-world evidence of PRO trial data impact based on Research Excellence Framework (REF) impact case studies. Methods Two independent investigators searched MEDLINE, EMBASE, CINAHL+, HMIC databases from inception until December 2018. Articles were eligible if they discussed research impact in the context of PRO clinical trial data. In addition, the REF 2014 database was systematically searched. REF impact case studies were included if they incorporated PRO data in a clinical trial. Results Thirty-nine publications of eleven thousand four hundred eighty screened met the inclusion criteria. Nine types of PRO trial impact were identified; the most frequent of which centred around PRO data informing clinical decision-making. The included publications identified several barriers and facilitators around PRO trial design, conduct, analysis and report that can hinder or promote the impact of PRO trial data. Sixty-nine out of two hundred nine screened REF 2014 case studies were included. 12 (17%) REF case studies led to demonstrable impact including changes to international guidelines; national guidelines; influencing cost-effectiveness analysis; and influencing drug approvals. Conclusions PRO trial data may potentially lead to a range of benefits for patients and society, which can be measured through appropriate impact metrics. However, in practice there is relatively limited evidence demonstrating directly attributable and indirect real world PRO-related research impact. In part, this is due to the wider challenges of measuring the impact of research and PRO-specific issues around design, conduct, analysis and reporting. Adherence to guidelines and multi-stakeholder collaboration is essential to maximise the use of PRO trial data, facilitate impact and minimise research waste. Trial registration Systematic Review registration PROSPERO CRD42017067799.

Planning and Executing Response-Adaptive Learn-Phase Clinical Trials: 2. Case Studies

2009 ◽  
Vol 43 (6) ◽  
pp. 725-734 ◽  
Author(s):  
Parvin Fardipour ◽  
Gary Littman ◽  
Daniel D. Burns ◽  
Vladimir Dragalin ◽  
S. Krishna Padmanabhan ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Case Studies

scholarly journals Do we need to adjust for interim analyses in a Bayesian adaptive trial design?

2019 ◽  
Author(s):  
Elizabeth Ryan ◽  
Kristian Brock ◽  
Simon Gates ◽  
Daniel Slade
Keyword(s):  
Clinical Trials ◽  
Case Studies ◽  
Type I Error ◽  
Error Rates ◽  
Adaptive Designs ◽  
Alternative Methods ◽  
Type I ◽  
Early Stopping ◽  
Interim Analyses ◽  
Stopping For Futility

Abstract Background Bayesian adaptive methods are increasingly being used to design clinical trials and offer a number of advantages over traditional approaches. Decisions at analysis points are usually based on the posterior distribution of the parameter of interest. However, there is some confusion amongst statisticians and trialists as to whether control of type I error is required for Bayesian adaptive designs as this is a frequentist concept. Methods We discuss the arguments for and against adjusting for multiplicities in Bayesian trials with interim analyses. We present two case studies demonstrating the effect on type I/II error rates of including interim analyses in Bayesian clinical trials. We propose alternative approaches to adjusting stopping boundaries to control type I error, and also alternative methods for decision-making in Bayesian clinical trials. Results In both case studies we found that the type I error was inflated in the Bayesian adaptive designs through incorporation of interim analyses that allowed early stopping for efficacy and do not make adjustments to account for multiplicity. Incorporation of early stopping for efficacy also increased the power in some instances. An increase in the number of interim analyses that only allowed early stopping for futility decreased the type I error, but also decreased power. An increase in the number of interim analyses that allowed for either early stopping for efficacy or futility generally increased type I error and decreased power. Conclusions If one wishes to demonstrate control of type I error in Bayesian adaptive designs then adjustments to the stopping boundaries are usually required for designs that allow for early stopping for efficacy as the number of analyses increase. If the designs only allow for early stopping for futility then adjustments to the stopping boundaries are not needed to control type I error, but may be required to ensure adequate power. If one instead uses a strict Bayesian approach then type I errors could be ignored and the designs could instead focus on the posterior probabilities of treatment effects of particular values.

scholarly journals Do we need to adjust for interim analyses in a Bayesian adaptive trial design?

2020 ◽  
Author(s):  
Elizabeth Ryan ◽  
Kristian Brock ◽  
Simon Gates ◽  
Daniel Slade
Keyword(s):  
Clinical Trials ◽  
Case Studies ◽  
Type I Error ◽  
Error Rates ◽  
Adaptive Designs ◽  
Alternative Methods ◽  
Type I ◽  
Early Stopping ◽  
Interim Analyses ◽  
Stopping For Futility

Abstract Background: Bayesian adaptive methods are increasingly being used to design clinical trials and offer several advantages over traditional approaches. Decisions at analysis points are usually based on the posterior distribution of the treatment effect. However, there is some confusion as to whether control of type I error is required for Bayesian designs as this is a frequentist concept.Methods: We discuss the arguments for and against adjusting for multiplicities in Bayesian trials with interim analyses. With two case studies we illustrate the effect of including interim analyses on type I/II error rates in Bayesian clinical trials where no adjustments for multiplicities are made. We propose several approaches to control type I error, and also alternative methods for decision-making in Bayesian clinical trials.Results: In both case studies we demonstrated that the type I error was inflated in the Bayesian adaptive designs through incorporation of interim analyses that allowed early stopping for efficacy and without adjustments to account for multiplicity. Incorporation of early stopping for efficacy also increased the power in some instances. An increase in the number of interim analyses that only allowed early stopping for futility decreased the type I error, but also decreased power. An increase in the number of interim analyses that allowed for either early stopping for efficacy or futility generally increased type I error and decreased power.Conclusions: Currently, regulators require demonstration of control of type I error for both frequentist and Bayesian adaptive designs, particularly for late-phase trials. To demonstrate control of type I error in Bayesian adaptive designs, adjustments to the stopping boundaries are usually required for designs that allow for early stopping for efficacy as the number of analyses increase. If the designs only allow for early stopping for futility then adjustments to the stopping boundaries are not needed to control type I error. If one instead uses a strict Bayesian approach, which is currently more accepted in the design and analysis of exploratory trials, then type I errors could be ignored and the designs could instead focus on the posterior probabilities of treatment effects of clinically-relevant values.

Chiropractic (DRAFT)

2018 ◽  
Author(s):  
Susan R. Eisen
Keyword(s):  
Clinical Trials ◽  
Alternative Medicine ◽  
Complementary And Alternative Medicine ◽  
Case Studies ◽  
National Institutes Of Health ◽  
Low Back ◽  
Chiropractic Treatment ◽  
Medical Journals ◽  
Full Discussion ◽  
Definition Of

This chapter focuses on mechanical disorders of the lumbar and pelvic spine associated with sexuality, with a detailed overview of neuromusculoskeletal anatomy. A full discussion is also included regarding the definition of chiropractic as recognized by the National Institutes of Health, as well as its place in complementary and alternative medicine. An explanation of sensory and motor functions of associated nerves is provided. Individual in-office case studies are offered along with reported clinical trials regarding the use of chiropractic in low back conditions and outcomes as reported in prestigious medical journals. Lastly, specific types of chiropractic treatment utilized in the author’s office are discussed.

scholarly journals LACTOBACILLUS-FERMENTED PLANT JUICE AS A POTENTIAL INGREDIENT IN COSMETICS: FORMULATION AND ASSESSMENT OF NATURAL MOUTHWASH

2016 ◽  
Vol 9 (9) ◽  
pp. 52 ◽  
Author(s):  
Sasithorn Sirilun ◽  
Bhagavathi Sundaram Sivamaruthi ◽  
Naphatsorn Kumar ◽  
Periyanaina Kesika ◽  
Sartjin Peerajan ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Pseudomonas Aeruginosa ◽  
Antimicrobial Activity ◽  
Clinical Trials ◽  
Medicinal Plants ◽  
Microbial Contamination ◽  
Oral Care ◽  
Peppermint Oil ◽  
Kaempferia Parviflora ◽  
Group A

ABSTRACTObjective: Oral care cosmetics are essential for all populations and are systematically used to treat oral problems. The chemicals free natural cosmeticsare the choice of many people. Thus, this study was aimed to formulate and to assess the natural mouthwash (MW) solution from LactobacillusfermentedThai medicinal plants juice.Methods: The selected (betel, green tea, clove, black galingale, mangosteen, and noni) plant juices were subjected to Lactobacillus plantarum mediatedfermentation. The fermented plant juices (FPJ) were formulated into MW solution with different concentrations of peppermint oil. MW formulationswere assessed for physical appearance, stability, and anti-microbial activities.Results: About 2% of peppermint oil in FPJ was found as organoleptically optimum. The pH and refractive indexes of the MWs were not affectedduring storage and stability assessments. All the FPJ-MWs formulations showed antimicrobial activity against Group A Staphylococcus, and other oralpathogens - Escherichia coli, Streptococcus aureus, and Pseudomonas aeruginosa. Moreover, black galingale, mangosteen, and noni based MW formulasalso exhibited anti-candida activity. The MW made from fermented black galingale (Kaempferia parviflora) juice was the most potent antimicrobialformulation with excellent physical stability.Conclusion: The study concluded that fermented plant-herbal juices can be used as natural MW recipe with 2% of peppermint oil to improve theflavor and aroma. The formulations were stable, free of microbial contamination, and also exhibited antimicrobial activity. Further extended stabilitystudy and clinical trials are necessary to develop a commercial FPJ-based natural MW recipe.Keywords: Fermentation, Formulation, Lactobacillus, Mouthwash.

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