Relevant bibliographies by topics / Clinical Trial Randomization

Academic literature on the topic 'Clinical Trial Randomization'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Clinical Trial Randomization"

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Harvin, John A., Ben L. Zarzaur, Raminder Nirula, Benjamin T. King, and Ajai K. Malhotra. "Alternative clinical trial designs." Trauma Surgery & Acute Care Open 5, no. 1 (February 2020): e000420. http://dx.doi.org/10.1136/tsaco-2019-000420.

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High-quality clinical trials are needed to advance the care of injured patients. Traditional randomized clinical trials in trauma have challenges in generating new knowledge due to many issues, including logistical difficulties performing individual randomization, unclear pretrial estimates of treatment effect leading to often unpowered studies, and difficulty assessing the generalizability of an intervention given the heterogeneity of both patients and trauma centers. In this review, we discuss alternative clinical trial designs that can address some of these difficulties. These include pragmatic trials, cluster randomization, cluster randomized stepped wedge designs, factorial trials, and adaptive designs. Additionally, we discuss how Bayesian methods of inference may provide more knowledge to trauma and acute care surgeons compared with traditional, frequentist methods.
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Baghbaninaghadehi, Fatemeh. "Fundamentals of Randomization in Clinical Trial." International Journal of Advanced Nutritional and Health Science 4, no. 1 (2016): 174–87. http://dx.doi.org/10.23953/cloud.ijanhs.143.

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Deserno, Thomas M., and András P. Keszei. "Mobile access to virtual randomization for investigator-initiated trials." Clinical Trials 14, no. 4 (April 28, 2017): 396–405. http://dx.doi.org/10.1177/1740774517706509.

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Background/aims Randomization is indispensable in clinical trials in order to provide unbiased treatment allocation and a valid statistical inference. Improper handling of allocation lists can be avoided using central systems, for example, human-based services. However, central systems are unaffordable for investigator-initiated trials and might be inaccessible from some places, where study subjects need allocations. We propose mobile access to virtual randomization, where the randomization lists are non-existent and the appropriate allocation is computed on demand. Methods The core of the system architecture is an electronic data capture system or a clinical trial management system, which is extended by an R interface connecting the R server using the Java R Interface. Mobile devices communicate via the representational state transfer web services. Furthermore, a simple web-based setup allows configuring the appropriate statistics by non-statisticians. Our comprehensive R script supports simple randomization, restricted randomization using a random allocation rule, block randomization, and stratified randomization for un-blinded, single-blinded, and double-blinded trials. For each trial, the electronic data capture system or the clinical trial management system stores the randomization parameters and the subject assignments. Results Apps are provided for iOS and Android and subjects are randomized using smartphones. After logging onto the system, the user selects the trial and the subject, and the allocation number and treatment arm are displayed instantaneously and stored in the core system. So far, 156 subjects have been allocated from mobile devices serving five investigator-initiated trials. Conclusion Transforming pre-printed allocation lists into virtual ones ensures the correct conduct of trials and guarantees a strictly sequential processing in all trial sites. Covering 88% of all randomization models that are used in recent trials, virtual randomization becomes available for investigator-initiated trials and potentially for large multi-center trials.
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Supawattan, Busaba, and Lily Ingsrisawa. "Bayesian Adaptive Randomization Designs for Clinical Trial." Journal of Applied Sciences 15, no. 2 (January 15, 2015): 374–76. http://dx.doi.org/10.3923/jas.2015.374.376.

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Michael, Nelson L. "Clinical trial design: The nobility of randomization." Science Translational Medicine 9, no. 419 (December 6, 2017): eaaq0810. http://dx.doi.org/10.1126/scitranslmed.aaq0810.

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Tiwari, Jawahar, and Cornelius J. Lynch. "81P Tightening the clinical trial by randomization." Controlled Clinical Trials 15, no. 3 (June 1994): 122–23. http://dx.doi.org/10.1016/0197-2456(94)90209-7.

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Grant, William C. "Run-Reversal Equilibrium for Clinical Trial Randomization." PLOS ONE 10, no. 6 (June 16, 2015): e0128812. http://dx.doi.org/10.1371/journal.pone.0128812.

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Hilgers, Ralf-Dieter, Martin Manolov, Nicole Heussen, and William F. Rosenberger. "Design and analysis of stratified clinical trials in the presence of bias." Statistical Methods in Medical Research 29, no. 6 (May 10, 2019): 1715–27. http://dx.doi.org/10.1177/0962280219846146.

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Background Among various design aspects, the choice of randomization procedure have to be agreed on, when planning a clinical trial stratified by center. The aim of the paper is to present a methodological approach to evaluate whether a randomization procedure mitigates the impact of bias on the test decision in clinical trial stratified by center. Methods We use the weighted t test to analyze the data from a clinical trial stratified by center with a two-arm parallel group design, an intended 1:1 allocation ratio, aiming to prove a superiority hypothesis with a continuous normal endpoint without interim analysis and no adaptation in the randomization process. The derivation is based on the weighted t test under misclassification, i.e. ignoring bias. An additive bias model combing selection bias and time-trend bias is linked to different stratified randomization procedures. Results Various aspects to formulate stratified versions of randomization procedures are discussed. A formula for sample size calculation of the weighted t test is derived and used to specify the tolerated imbalance allowed by some randomization procedures. The distribution of the weighted t test under misclassification is deduced, taking the sequence of patient allocation to treatment, i.e. the randomization sequence into account. An additive bias model combining selection bias and time-trend bias at strata level linked to the applied randomization sequence is proposed. With these before mentioned components, the potential impact of bias on the type one error probability depending on the selected randomization sequence and thus the randomization procedure is formally derived and exemplarily calculated within a numerical evaluation study. Conclusion The proposed biasing policy and test distribution are necessary to conduct an evaluation of the comparative performance of (stratified) randomization procedure in multi-center clinical trials with a two-arm parallel group design. It enables the choice of the best practice procedure. The evaluation stimulates the discussion about the level of evidence resulting in those kind of clinical trials.
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Sidani, Souraya, Mary Fox, and Laura Collins. "Towards Patient-Centered Clinical Trial Designs." European Journal for Person Centered Healthcare 5, no. 3 (September 26, 2017): 300. http://dx.doi.org/10.5750/ejpch.v5i3.1308.

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Rationale, aims and objectives: Evidence shows a trend towards low enrollment in randomized clinical trials (RCTs), which negatively affect validity of conclusions. Low enrollment is associated with different factors, but has recently been attributed to an increasing proportion of patients expressing concerns about randomization. In this paper, we summarize the evidence on reasons for non-enrollment, and we propose preference-based and shared decision-making as alternative methods for allocating patients to treatments in effectiveness and comparative effectiveness trials.Methods: This paper is a narrative review of available literature.Results: Converging findings of quantitative and qualitative studies revealed three interrelated and frequently mentioned reasons for declining enrollment in RCTs: 1) concerns about randomization related to the lack of understanding of equipoise, lack of appreciation of the scientific merits of randomization, and unfavorable perceptions of randomization as not reflecting methods of treatment selection used in practice; 2) preferences for treatments under evaluation, which contribute to unwillingness to be randomized; and 3) desires for involvement in treatment decision-making, which are not respected with randomization.Conclusions: Alternative methods for treatment allocation are needed to make effectiveness and comparative effectiveness trials attractive to patients. Preference-based and shared decision-making are viable methods that respectively represent the informed choice and the collaborative choice styles of treatment selection commonly used in practice. The extent to which these two methods of treatment allocation enhance enrollment should be further investigated.
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Cellamare, Matteo, Steffen Ventz, Elisabeth Baudin, Carole D. Mitnick, and Lorenzo Trippa. "A Bayesian response-adaptive trial in tuberculosis: The endTB trial." Clinical Trials 14, no. 1 (September 23, 2016): 17–28. http://dx.doi.org/10.1177/1740774516665090.

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Purpose: To evaluate the use of Bayesian adaptive randomization for clinical trials of new treatments for multidrug-resistant tuberculosis. Methods: We built a response-adaptive randomization procedure, adapting on two preliminary outcomes for tuberculosis patients in a trial with five experimental regimens and a control arm. The primary study outcome is treatment success after 73 weeks from randomization; preliminary responses are culture conversion at 8 weeks and treatment success at 39 weeks. We compared the adaptive randomization design with balanced randomization using hypothetical scenarios. Results: When we compare the statistical power under adaptive randomization and non-adaptive designs, under several hypothetical scenarios we observe that adaptive randomization requires fewer patients than non-adaptive designs. Moreover, adaptive randomization consistently allocates more participants to effective arm(s). We also show that these advantages are limited to scenarios consistent with the assumptions used to develop the adaptive randomization algorithm. Conclusion: Given the objective of evaluating several new therapeutic regimens in a timely fashion, Bayesian response-adaptive designs are attractive for tuberculosis trials. This approach tends to increase allocation to the effective regimens.
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Dissertations / Theses on the topic "Clinical Trial Randomization"

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Batidzirai, Jesca Mercy. "Randomization in a two armed clinical trial: an overview of different randomization techniques." Thesis, University of Fort Hare, 2011. http://hdl.handle.net/10353/395.

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Randomization is the key element of any sensible clinical trial. It is the only way we can be sure that the patients have been allocated into the treatment groups without bias and that the treatment groups are almost similar before the start of the trial. The randomization schemes used to allocate patients into the treatment groups play a role in achieving this goal. This study uses SAS simulations to do categorical data analysis and comparison of differences between two main randomization schemes namely unrestricted and restricted randomization in dental studies where there are small samples, i.e. simple randomization and the minimization method respectively. Results show that minimization produces almost equally sized treatment groups, but simple randomization is weak in balancing prognostic factors. Nevertheless, simple randomization can also produce balanced groups even in small samples, by chance. Statistical power is also improved when minimization is used than in simple randomization, but bigger samples might be needed to boost the power.
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Wang, Hui. "Response Adaptive Randomization using Surrogate and Primary Endpoints." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4517.

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In recent years, adaptive designs in clinical trials have been attractive due to their efficiency and flexibility. Response adaptive randomization procedures in phase II or III clinical trials are proposed to appeal ethical concerns by skewing the probability of patient assignments based on the responses obtained thus far, so that more patients will be assigned to a superior treatment group. General response-adaptive randomizations usually assume that the primary endpoint can be obtained quickly after the treatment. However, in real clinical trials, the primary outcome is delayed, making it unusable for adaptation. Therefore, we utilize surrogate and primary endpoints simultaneously to adaptively assign subjects between treatment groups for clinical trials with continuous responses. We explore two types of primary endpoints commonly used in clinical tirials: normally distributed outcome and time-to-event outcome. We establish a connection between the surrogate and primary endpoints through a Bayesian model, and then update the allocation ratio based on the accumulated data. Through simulation studies, we find that our proposed response adaptive randomization is more effective in assigning patients to better treatments as compared with equal allocation randomization and standard response adaptive randomization which is solely based on the primary endpoint.
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Di, Pace Brian S. "Site- and Location-Adjusted Approaches to Adaptive Allocation Clinical Trial Designs." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5706.

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Response-Adaptive (RA) designs are used to adaptively allocate patients in clinical trials. These methods have been generalized to include Covariate-Adjusted Response-Adaptive (CARA) designs, which adjust treatment assignments for a set of covariates while maintaining features of the RA designs. Challenges may arise in multi-center trials if differential treatment responses and/or effects among sites exist. We propose Site-Adjusted Response-Adaptive (SARA) approaches to account for inter-center variability in treatment response and/or effectiveness, including either a fixed site effect or both random site and treatment-by-site interaction effects to calculate conditional probabilities. These success probabilities are used to update assignment probabilities for allocating patients between treatment groups as subjects accrue. Both frequentist and Bayesian models are considered. Treatment differences could also be attributed to differences in social determinants of health (SDH) that often manifest, especially if unmeasured, as spatial heterogeneity amongst the patient population. In these cases, patient residential location can be used as a proxy for these difficult to measure SDH. We propose the Location-Adjusted Response-Adaptive (LARA) approach to account for location-based variability in both treatment response and/or effectiveness. A Bayesian low-rank kriging model will interpolate spatially-varying joint treatment random effects to calculate the conditional probabilities of success, utilizing patient outcomes, treatment assignments and residential information. We compare the proposed methods with several existing allocation strategies that ignore site for a variety of scenarios where treatment success probabilities vary.
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Lunceford, Jared Kenneth. "ESTIMATING CAUSAL TREATMENT EFFECTS VIA THE PROPENSITY SCORE AND ESTIMATING SURVIVAL DISTRIBUTIONS IN CLINICAL TRIALS THAT FOLLOW TWO-STAGE RANDOMIZATION DESIGNS." NCSU, 2001. http://www.lib.ncsu.edu/theses/available/etd-20010803-202112.

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LUNCEFORD, JARED KENNETH. Estimating Causal Treatment Effects Via thePropensity Score and Estimating Survival Distributions in Clinical TrialsThat Follow Two-stage Randomization Designs. (Under the direction ofProfessor Marie Davidian)Estimation of treatment effects with causalinterpretation from obervational data is complicated by the fact thatexposure to treatment is confounded with subject characteristics. Thepropensity score, the probability of exposure to treatment conditionalon covariates, is the basis for two competing classes of approachesfor adjusting for confounding: methods based on stratification ofobservations by quantiles of estimated propensity scores, and methodsbased on weighting individual observations by weights depending onestimated propensity scores. We review these approaches andinvestigate their relative performance.Some clinical trials follow a design in which patientsare randomized to a primary therapy upon entry followed by anotherrandomization to maintenance therapy contingent upon diseaseremission. Ideally, analysis would allow different treatmentpolicies, i.e. combinations of primary and maintenance therapy ifspecified up-front, to be compared. Standard practice is to conductseparate analyses for the primary and follow-up treatments, which doesnot address this issue directly. We propose consistent estimators ofthe survival distribution and mean survival time for each treatmentpolicy in such two-stage studies and derive large sampleproperties. The methods are demonstrated on a leukemia clinical trialdata set and through simulation.

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Souley, Issoufou Mamane Sani. "Anthropologie d'un essai clinique : enjeux de santé globale autour d'un nouveau vaccin testé par un complexe humanitaro-scientifique." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEN035.

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En 2015, Epicentre, un centre de recherche épidémiologique crée en 1987 par l'ONG humanitaire Médecins Sans Frontières (MSF) se lance dans un essai clinique randomisé sur un nouveau vaccin contre les formes sévères de diarrhées des enfants de moins de cinq ans. Il est produit par le Serum Institute Of India Limited (entreprise pharmaceutique indienne). L'essai est conduit à Madarounfa, une localité rurale située dans le Sud du Niger. Cette thèse propose de discuter des dimensions globales et des enjeux locaux autour d'un vaccin, le Rotasiil que l'on peut définir comme « un vaccin africain » si l'on tient compte de la façon dont il est présenté et promu par le Serum Institute, MSF et Epicentre. Cet essai vaccinal sur le Rotasiil témoigne de l'utopie des acteurs de la santé globale qui veut que la technologie et la toute-puissance de la médecine puisse venir à bout des maladies en occultant le contexte de violence structurelle dans lequel leur intervention prend place (Farmer 2002; Farmer 2002; Galtung and Hoivik 1971). Il témoigne également de l'émergence de nouveaux acteurs (ONG et industries) dans le champ des politiques de santé mondiale. Cette thèse s'intéresse également à la science « en train de se faire » et analyse les conditions sociales de collecte des échantillons, de leur analyse au laboratoire jusqu'à l'inscription des résultats dans une base de données. Elle décrit également les ajustements et les négociations à l'œuvre dans l'application des « gold standard » des essais cliniques qui se heurtent au contexte interactionnel de leur mise en œuvre (Brives, Le Marcis, and Sanabria 2016)
In 2015, Epicentre, an epidemiological research center created in 1987 by the humanitarian NGO Médecins Sans Frontières (MSF), will begin a randomised clinical trial of a new vaccine against severe forms of diarrhoea in children under five years of age. It is produced by the Serum Institute Of lndia Limited (an Indian pharmaceutical company). The trial is being conducted in Madarounfa, a rural community in southem Niger. This thesis proposes to discuss the global dimensions and local issues surrounding a vaccine, Rotasiil which can be defined as "an African vaccine" if on considers the way it is presented and promoted by the Serwn Institute, MSF, and Epicentre. The Rotasiil vaccine trial is testament to the utopia of global health actors that technology and the omnipotence of medicine can defeat disease b obscuring the context of structural violence in which their intervention takes place (Farmer 2002; Farmer 2002; Galtun · and Hôivik 1971). It also testifies to the emergence of new actors (NGOs and industries) in the field of global healt policies (Bertho-Huidal 2012). This thesis is also interested in the science "in the making" and analyses the social conditions of sample collection, from their analysis in the laboratory to the entry of the results in a database. It ais describes the adjustrnents and negotiations at work in the application of the "gold standard" of clinical trials that are confronted with the interactional context of their implementation (Brives, Le Marcis, and Sanabria 2016)
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Han, Baoguang. "Statistical analysis of clinical trial data using Monte Carlo methods." Thesis, 2014. http://hdl.handle.net/1805/4650.

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Indiana University-Purdue University Indianapolis (IUPUI)
In medical research, data analysis often requires complex statistical methods where no closed-form solutions are available. Under such circumstances, Monte Carlo (MC) methods have found many applications. In this dissertation, we proposed several novel statistical models where MC methods are utilized. For the first part, we focused on semicompeting risks data in which a non-terminal event was subject to dependent censoring by a terminal event. Based on an illness-death multistate survival model, we proposed flexible random effects models. Further, we extended our model to the setting of joint modeling where both semicompeting risks data and repeated marker data are simultaneously analyzed. Since the proposed methods involve high-dimensional integrations, Bayesian Monte Carlo Markov Chain (MCMC) methods were utilized for estimation. The use of Bayesian methods also facilitates the prediction of individual patient outcomes. The proposed methods were demonstrated in both simulation and case studies. For the second part, we focused on re-randomization test, which is a nonparametric method that makes inferences solely based on the randomization procedure used in clinical trials. With this type of inference, Monte Carlo method is often used for generating null distributions on the treatment difference. However, an issue was recently discovered when subjects in a clinical trial were randomized with unbalanced treatment allocation to two treatments according to the minimization algorithm, a randomization procedure frequently used in practice. The null distribution of the re-randomization test statistics was found not to be centered at zero, which comprised power of the test. In this dissertation, we investigated the property of the re-randomization test and proposed a weighted re-randomization method to overcome this issue. The proposed method was demonstrated through extensive simulation studies.
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Cerqueira, Franck Pires. "Modelos Dinâmicos de Ensaios Clínicos: Desenho Adaptativo." Master's thesis, 2018. http://hdl.handle.net/10316/84533.

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Dissertação de Mestrado em Farmacologia Aplicada apresentada à Faculdade de Farmácia
Apesar da despesa em I & D na indústria farmacêutica ter tido nas últimas décadas um crescimento sustentado, o número de produtos medicinais colocados em desenvolvimento clínico até à autorização de comercialização não tem aumentado na mesma proporção. Um número pequeno mas crescente de ensaios clínicos usa um desenho de estudos clínicos chamado Desenho Adaptativo que permite aos investigadores responderem aos dados recolhidos durante o estudo. Num ensaio adaptativo, o investigador pode ter a opção de responder a dados interinos de segurança e eficácia de várias formas, incluindo estreitar o foco do estudo ou aumentar o número de participantes, equilibrar a alocação ao tratamento ou ainda com diferentes formas de randomização com base na resposta de participantes anteriores ao tratamento. De forma a inverter este impasse na investigação clínica e a incrementar a competitividade económica e a segurança para os participantes nos ensaios clínicos, este trabalho visa o levantamento das guidelines internacionais (FDA, EMA) para a aplicação e condução de ensaios através de desenho adaptativo, bem como a recolha de artigos referentes diversos ensaios conduzidos em vários países de modo a importar essas experiências para a realidade da investigação clínica nacional.Desta análise é possível inferir que o uso de Desenho Adaptativo constitui uma vantagem ética e científica quando adequadamente planeado e aplicado dado aumentar a flexibilidade do ensaio, encurtar o tempo global de investigação clínica de um medicamento e reduzir o risco de exposição de doentes a efeitos adversos relacionados com o medicamento experimental. Contudo, não é uma metodologia extrapolável para todas as fases de investigação clínica (maioritariamente fases exploratórias e confirmatórias) e sua maior complexidade metodológica e analítica requerem uma metodologia estatística adequada, bem como sua aplicação limitar-se a ensaios com menor número de centros de estudo, com extensões de tempo mais limitadas e a medicamentos experimentais com efeitos clínicos mais imediatos para análise interina.
Although R & D spending in the pharmaceutical industry has been growing steadily in recent decades, the number of medicinal products under clinical development up to the marketing authorization has not increased by the same proportion.A small but growing number of clinical trials use a clinical study design called Adaptive Design that allows researchers to respond to data collected during the study.In an adaptive trial, the investigator may have the option of responding to interim safety and efficacy data in a number of ways, including narrowing the study focus or increasing the number of participants, balancing treatment allocation or different forms of randomization based on responses of participants prior to treatment.In order to reverse this setback in clinical research and to increase economic competitiveness and safety for participants in clinical trials, this essay aims at raising the international guidelines (FDA, EMA) for the application and conduct of trials through adaptive design, as well as the collection of different articles referring to several trials conducted in several countries in order to import these experiences into the reality of national clinical research.From this analysis it is possible to infer that the use of Adaptive Design is an ethical and scientific advantage when properly planned and applied, since it increases the flexibility of the trial, shorten the overall clinical investigation time of a drug and reduce the risk of patient exposure to adverse effects related to the experimental drug. However, it is not an extrapolated methodology for all phases of clinical investigation (mainly exploratory and confirmatory phases). Its greater methodological and analytical complexity require an adequate statistical methodology, its application is limited to trials with smaller number of study centers with smaller extensions of time and to experimental drugs with more immediate clinical effects for their interim analysis.
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Guo, Xiang. "Statistical analysis in two stage randomization designs in clinical trials." 2005. http://www.lib.ncsu.edu/theses/available/etd-06232005-143538/unrestricted/etd.pdf.

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TU, JUI-CHUAN, and 涂瑞銓. "Adaptive Randomization for Multiarm Survival Clinical Trials Using Short-Term Response Information." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/bncgwj.

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碩士
東海大學
統計學系
107
We usually don’t want to waste substantial amount of time and resources in phase two clinical trials, therefore we need effective methods of randomization, so that we can chose a potential treatment on survival, and confirm its benefit in phase three trial quickly. Traditionally, using survival time as a primary endpoint, takes a long period of time to assign patients to different groups ineffectively during the adaptive-randomization trails. However, using short-term efficacy (e.g. tumor response rate) as a primary endpoint, may show that patients have good efficacy shortly, but do not have long period of survival time. Owing to prolonging survival time is a common goal of a better treatment, Huang et al. (2009) proposed a model which used short-term response information to facility adaptive randomization for survival clinical trials. In this article, we extend the method which Huang et al. (2009) proposed to multi-arms clinical trials. Moreover, we assume that the survival time of patients is following the mixture Weibull distribution. In addition, since the model of Huang et al. (2009) proposed conduct interim analyses each cohort of one patient, and following patient randomize into the trial is based on the revised probability of adaptive randomization. In order to save time, we consider to conduct interim analyses each cohort of five patients, then compare the respective simulation results.
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Wahed, Abdus Shakoor Fazlul. "Efficient estimation of the survival distribution and related quantities of treatment policies in two-stage randomization designs in clinical trials." 2003. http://www.lib.ncsu.edu/theses/available/etd-08112003-164310/unrestricted/etd.pdf.

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Books on the topic "Clinical Trial Randomization"

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Rosenberger, William F., and John M. Lachin. Randomization in Clinical Trials. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2002. http://dx.doi.org/10.1002/0471722103.

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Rosenberger, William F., and John M. Lachin. Randomization in Clinical Trials. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781118742112.

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Rosenberger, William F. Randomization in clinical trials: Theory and practice. New York: Wiley, 2002.

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1942-, Lachin John M., ed. Randomization in clinical trials: Theory and practice. Hoboken, New Jersey: John Wiley & Sons, Inc., 2016.

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F, Rosenberger William, ed. The theory of response-adaptive randomization in clinical trials. Hoboken, NJ: John Wiley & Sons, 2006.

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Hu, Feifang, and William F. Rosenberger. The Theory of Response-Adaptive Randomization in Clinical Trials. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/047005588x.

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Neil, Klar, ed. Design and analysis of cluster randomization trials in health research. London: Arnold, 2000.

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Haynes, Richard, Martin J. Landray, William G. Herrington, and Colin Baigent. Clinical trials. Edited by Christopher G. Winearls. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199592548.003.0019.

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Randomized trials are the best method for identifying and quantifying the benefits and risks of interventions in clinical practice. Nephrology lags behind most specialties in medicine in its evidence base. Many commonly used therapies are untested and may be ineffective or even cause harm. For trials to provide reliable answers to important clinical questions they must first avoid two sources of error. Firstly, systematic error (or bias) can only be removed by proper randomization. Secondly, random error (the play of chance) can only be removed by the randomization of large numbers of patients (and therefore the accrual of large numbers of trial outcomes). Following successful large-scale randomization, it is critical that patients’ compliance with their allocated treatment is maintained, relevant study outcomes are systematically ascertained, and appropriate statistical analyses are performed. There is an urgent need to conduct such trials to address the many important clinical questions in nephrology.
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Wiffen, Philip, Marc Mitchell, Melanie Snelling, and Nicola Stoner. Clinical trials. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780199603640.003.0005.

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Clinical trial regulations 108Licensing of a clinical trial 109Clinical trial development phases 110Trial design, randomization, and blinding 111European Clinical Trials Directive 112Clinical trials: hospital pharmacy guidance 114Ethical committees 116Clinical trials form a fundamental part in the research, development, and licensing of new medicines. Research of how the drug interacts in humans is essential to ensure safe and effective medicines are licensed as new treatments. It is an exciting and varied role at the cutting edge of modern research with trials ranging across all therapeutic specialities. Clinical Trial pharmacists are therefore required to have a broad clinical knowledge and a specialist knowledge of the regulations that clinical trials have to follow....
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Hershberger, Scott L. Multivariate Clinical Trials For Randomized Experiments In The Behavioral Sciences. Psychology Press, 2011.

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Book chapters on the topic "Clinical Trial Randomization"

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Zhang, Lanju, and William F. Rosenberger. "Response-Adaptive Randomization for Clinical Trials." In Practical Considerations for Adaptive Trial Design and Implementation, 183–99. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1100-4_10.

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Unbehaun, V. "Randomization and Follow-up Care of Patients in a Breast Cancer Clinical Trial: Personal Experience." In Cancer Clinical Trials, 171–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83419-6_19.

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Lin, Jianchang, Li-An Lin, and Serap Sankoh. "A Phase II Trial Design with Bayesian Adaptive Covariate-Adjusted Randomization." In Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics, 61–73. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42568-9_6.

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Pocock, Stuart J. "Methods of Randomization." In Clinical Trials, 66–89. West Sussex, England: John Wiley & Sons Ltd,., 2013. http://dx.doi.org/10.1002/9781118793916.ch5.

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Proschan, Michael A., and Julian Barreiro-Gomez. "Randomization/Allocation." In Statistical Thinking in Clinical Trials, 65–74. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781315164090-5.

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Friedman, Lawrence M., Curt D. Furberg, and David L. DeMets. "The Randomization Process." In Fundamentals of Clinical Trials, 97–117. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1586-3_6.

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Friedman, Lawrence M., Curt D. Furberg, and David L. DeMets. "The Randomization Process." In Fundamentals of Clinical Trials, 61–81. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2915-3_5.

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Friedman, Lawrence M., Curt D. Furberg, David L. DeMets, David M. Reboussin, and Christopher B. Granger. "The Randomization Process." In Fundamentals of Clinical Trials, 123–45. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18539-2_6.

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Proschan, Michael A., and Julian Barreiro-Gomez. "Randomization-Based Inference." In Statistical Thinking in Clinical Trials, 75–108. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781315164090-6.

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Zhang, Lanju, and William F. Rosenberger. "Adaptive Randomization in Clinical Trials." In Design and Analysis of Experiments, 251–81. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118147634.ch7.

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Conference papers on the topic "Clinical Trial Randomization"

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Cai, HongWei, YongJi Wang, and JieLai Xia. "Comparison of balance ability of minimization, simple and stratified block randomization from true data of a clinical trial." In 2011 International Symposium on Information Technology in Medicine and Education (ITME 2011). IEEE, 2011. http://dx.doi.org/10.1109/itime.2011.6132058.

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Tiancai, Wen, Liu Baoyan, He Liyun, Lv Xiaoying, Wang Xin, and Zhang Yanning. "A randomization and trial supply management system for adaptive clinical studies of TCM and its scientific research application in recurrent tuberculosis." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621116.

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Poniewierski, M., M. Barthels, and H. Poliwoda. "THE SAFETY AND EFFICACY OF A LOW MOLECULAR WEIGHT HEPARIN (FRAGMIN) IN THE PREVENTION OF DEEP VEIN THROMBOSIS IN MEDICAL PATIENTS: A RANDOMIZED DOUBLE-BLIND TRIAL." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1643224.

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The safety and efficacy of 2500 anti-Factor Xa U of a low molecular weight heparin (Kabi 2165, Fragmin) subcutaneously once a day, and 5000 IU of standard unfractionated Heparin (KabiVitrum, Stockholm) subcutaneously twice daily as thromboprophylaxis was compared in 200 medical patients in a randomized double blind trial. According to the risk of DVT the patients were stratified before randomization in a high and low risk group. The high risk group consisted of 100 patients mainly with malignant diseases and/or previous history of thromboembolism, the low risk group of 100 patients with mainly myocardial infarction and/or coronary heart disease. The prophylaxis was given for seven to ten days. In 192 consecutive patients the clinical status and thermographic screening for DVT (leg temperature profiles, DeVeTherm) were daily evaluated. In two cases of suspected DVT and one case of suspected PE, the following phlebography or pulmonary scintigraphy were found to be negative. In the high risk group, one patient treated with Fragmin having a central venous catheter developed on day 10 symptoms of an arm vein thrombosis. There were no bleeding complications observed in either of the two treatment groups. Two patients with trombocytopenia (25.000 and 22.000/pl) due to chemotherapy and underlying malignant disease were successfully treated with Fragmin without developing any bleeding complications. In eight patients during Fragmin prophylaxis invasive diagnostic methods as heart catheterization, gastroscopy, bronchoscopy or spinal puncture were performed without noticing any bleeding events. 2500 anti-Factor Xa U of Fragmin gave plasma levels by anti-Factor Xa assay (S-2222, Kabi) of mean 0,1 U/ml when blood was sampled three to four hours after the subcutaneus application. There was no accumulation during the treatment periode observed.This study suggests that 2500 anti-Factor Xa U of Fragmin once daily is as safe and effective as 5000 IU of standard heparin twice daily in these medical patients. Especially in patients who need prophylaxis for a long time eg. with malignant disease, the once daily injection is welcomed.
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MILLER, E. R. "IMPLEMENTATION OF ADAPTIVE RANDOMIZATIONS FOR CLINICAL TRIALS." In Proceedings of the 5th International ISAAC Congress. WORLD SCIENTIFIC, 2009. http://dx.doi.org/10.1142/9789812835635_0138.

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Cordeiro, Tatiana Virgínia Fidélis, Aline Silva Ziehe, Tamie Mota Arbex, Barbara Cunha Vasconcellos, Lara Cruz de Senna Fernandes, and Maria teresa de Castro Lima Pereira. "The management of migraine through Acupuncture: a literature review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.339.

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Background: Migraine is one of the most disabling conditions worldwide, and acupuncture can be used as prophylaxis. This practice is indicated to relieve tension, stress, induce analgesia, and has been gaining space due to its A level evidence. Objectives: Investigate the impact of acupuncture on the management of migraine disorders. Design and Settings: literature review. Methods: After searching the MEDLINE database for “migraine disorders OR headache”, “acupuncture” and “integrative medicine OR alternative medicine”, 271 articles were found and 6 used. Only those with full text available and published between 2011-2021 were included. Those that addressed a specific type of migraine were excluded. Results: Acupuncture was analyzed in 4 studies as prophylaxis for migraine, in which there was a general reduction in symptoms and 50% reduction in frequency of episodes (p <0.05), with its effects comparable to drugs such as Depakene, Topamax, Metoprolol and Flunarizine. A meta-analysis involving 39 clinical trials showed that the acupuncture group obtained better results than the control group (p <0.001), these results were sustained when analyzing pain after randomization, in agreement with another study that demonstrated pain reduction in the group that used simulated acupuncture (p=0.002). It should be noted that, although some patients report adverse effects, it’s safe and as effective than drugs used in the treatment of migraine. Conclusions: Acupuncture is a good prophylactic method for migraine. It reduces pain episodes and has less adverse effects when compared to conventional methods. However, further studies on this therapy are needed.
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Reports on the topic "Clinical Trial Randomization"

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Gupta, Tejpal, Riddhijyoti Talukdar, Sadhana Kannan, Archya Dasgupta, Abhishek Chatterjee, and Vijay Patil. Meta-Analysis of Standard Temozolomide versus Extended Adjuvant Temozolomide following concurrent Radiochemotherapy in newly-diagnosed Glioblastoma (MASTER-G). INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, December 2021. http://dx.doi.org/10.37766/inplasy2021.12.0114.

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Review question / Objective: To assess the safety and efficacy of extended adjuvant temozolomide compared to standard adjuvant temozolomide after concurrent radiochemotherapy in patients with newly-diagnosed glioblastoma. Condition being studied: Newly-diagnosed glioblastoma. Eligibility criteria: Prospective clinical trials randomly assigning patients to extended (>6-cycles) adjuvant TMZ (experimental arm) or standard (6-cycles) adjuvant TMZ will be included. Randomization in an individual study may have been done upfront before concurrent phase (RT/TMZ), after completion of concurrent RT/TMZ and before starting adjuvant phase, or after completion of standard adjuvant TMZ (6-cycles). Emulated RCTs, quasi-randomized trials, propensity matched analyses, non-randomized comparative studies, or observational studies will not be considered in this review.
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Lumpkin, Shamsie, Isaac Parrish, Austin Terrell, and Dwayne Accardo. Pain Control: Opioid vs. Nonopioid Analgesia During the Immediate Postoperative Period. University of Tennessee Health Science Center, July 2021. http://dx.doi.org/10.21007/con.dnp.2021.0008.

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Background Opioid analgesia has become the mainstay for acute pain management in the postoperative setting. However, the use of opioid medications comes with significant risks and side effects. Due to increasing numbers of prescriptions to those with chronic pain, opioid medications have become more expensive while becoming less effective due to the buildup of patient tolerance. The idea of opioid-free analgesic techniques has rarely been breached in many hospitals. Emerging research has shown that opioid-sparing approaches have resulted in lower reported pain scores across the board, as well as significant cost reductions to hospitals and insurance agencies. In addition to providing adequate pain relief, the predicted cost burden of an opioid-free or opioid-sparing approach is significantly less than traditional methods. Methods The following groups were considered in our inclusion criteria: those who speak the English language, all races and ethnicities, male or female, home medications, those who are at least 18 years of age and able to provide written informed consent, those undergoing inpatient or same-day surgical procedures. In addition, our scoping review includes the following exclusion criteria: those who are non-English speaking, those who are less than 18 years of age, those who are not undergoing surgical procedures while admitted, those who are unable to provide numeric pain score due to clinical status, those who are unable to provide written informed consent, and those who decline participation in the study. Data was extracted by one reviewer and verified by the remaining two group members. Extraction was divided as equally as possible among the 11 listed references. Discrepancies in data extraction were discussed between the article reviewer, project editor, and group leader. Results We identified nine primary sources addressing the use of ketamine as an alternative to opioid analgesia and post-operative pain control. Our findings indicate a positive correlation between perioperative ketamine administration and postoperative pain control. While this information provides insight on opioid-free analgesia, it also revealed the limited amount of research conducted in this area of practice. The strategies for several of the clinical trials limited ketamine administration to a small niche of patients. The included studies provided evidence for lower pain scores, reductions in opioid consumption, and better patient outcomes. Implications for Nursing Practice Based on the results of the studies’ randomized controlled trials and meta-analyses, the effects of ketamine are shown as an adequate analgesic alternative to opioids postoperatively. The cited resources showed that ketamine can be used as a sole agent, or combined effectively with reduced doses of opioids for multimodal therapy. There were noted limitations in some of the research articles. Not all of the cited studies were able to include definitive evidence of proper blinding techniques or randomization methods. Small sample sizes and the inclusion of specific patient populations identified within several of the studies can skew data in one direction or another; therefore, significant clinical results cannot be generalized to patient populations across the board.
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