223 resultados para Randomized-trials


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Background/Aim. Mesenchymal stromal cells (MSCs) have been utilised in many clinical trials as an experimental treatment in numerous clinical settings. Bone marrow remains the traditional source tissue for MSCs but is relatively hard to access in large volumes. Alternatively, MSCs may be derived from other tissues including the placenta and adipose tissue. In an initial study no obvious differences in parameters such as cell surface phenotype, chemokine receptor display, mesodermal differentiation capacity or immunosuppressive ability, were detected when we compared human marrow derived- MSCs to human placenta-derived MSCs. The aim of this study was to establish and evaluate a protocol and related processes for preparation placenta-derived MSCs for early phase clinical trials. Methods. A full-term placenta was taken after delivery of the baby as a source of MSCs. Isolation, seeding, incubation, cryopreservation of human placentaderived MSCs and used production release criteria were in accordance with the complex regulatory requirements applicable to Code of Good Manufacturing Practice manufacturing of ex vivo expanded cells. Results. We established and evaluated instructions for MSCs preparation protocol and gave an overview of the three clinical areas application. In the first trial, MSCs were co-transplanted iv to patient receiving an allogeneic cord blood transplant as therapy for treatmentrefractory acute myeloid leukemia. In the second trial, MSCs were administered iv in the treatment of idiopathic pulmonary fibrosis and without serious adverse effects. In the third trial, MSCs were injected directly into the site of tendon damage using ultrasound guidance in the treatment of chronic refractory tendinopathy. Conclusion. Clinical trials using both allogeneic and autologous cells demonstrated MSCs to be safe. A described protocol for human placenta-derived MSCs is appropriate for use in a clinical setting, relatively inexpensive and can be relatively easily adjusted to a different set of regulatory requirements, as applicable to early phase clinical trials.

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Background Multiple health behavior change can ameliorate adverse effects of cancer. Purpose The purpose of this study was to determine the effects of a multiple health behavior change intervention (CanChange) for colorectal cancer survivors on psychosocial outcomes and quality of life. Methods A total of 410 colorectal cancer survivors were randomized to a 6-month telephone-based health coaching intervention (11 sessions using acceptance and commitment therapy strategies focusing on physical activity, weight management, diet, alcohol, and smoking) or usual care. Posttraumatic growth, spirituality, acceptance, mindfulness, distress, and quality of life were assessed at baseline, 6 and 12 months. Results Significant intervention effects were observed for posttraumatic growth at 6 (7.5, p < 0.001) and 12 months (4.1, p = 0.033), spirituality at 6 months (1.8, p = 0.011), acceptance at 6 months (0.2, p = 0.005), and quality of life at 6 (0.8, p = 0.049) and 12 months (0.9, p = 0.037). Conclusions The intervention improved psychosocial outcomes and quality of life (physical well-being) at 6 months with most effects still present at 12 months. (Trial Registration Number: ACTRN12608000399392).

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Objectives Funding for early career researchers in Australia's largest medical research funding scheme is determined by a competitive peer-review process using a panel of four reviewers. The purpose of this experiment was to appraise the reliability of funding by duplicating applications that were considered by separate grant review panels. Study Design and Methods Sixty duplicate applications were considered by two independent grant review panels that were awarding funding for Australia's National Health and Medical Research Council. Panel members were blinded to which applications were included in the experiment and to whether it was the original or duplicate application. Scores were compared across panels using Bland–Altman plots to determine measures of agreement, including whether agreement would have impacted on actual funding. Results Twenty-three percent of the applicants were funded by both panels and 60 percent were not funded by both, giving an overall agreement of 83 percent [95% confidence interval (CI): 73%, 92%]. The chance-adjusted agreement was 0.75 (95% CI: 0.58, 0.92). Conclusion There was a comparatively high level of agreement when compared with other types of funding schemes. Further experimental research could be used to determine if this higher agreement is due to nature of the application, the composition of the assessment panel, or the characteristics of the applicants.

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Malnutrition is common in children with end-stage liver disease (ESLD) awaiting orthotopic liver transplantation (OLT), and nutritional support is assuming an important role in preoperative management. To evaluate preoperative nutritional therapy, 19 children (median age 1.25 y) with ESLD awaiting OLT were prospectively studied. Two high-energy, isoenergetic and isonitrogenous nutritional formulations delivered nasogastrically were compared: a branched-chain amino acid (BCAA)-enriched semielemental formulation and a matched standard semielemental formulation. Twelve of 19 patients completed a randomized controlled study before OLT and 10 of 19 completed a full crossover study. Improvements in weight and height occurred during the BCAA supplements, with no statistical change on the standard formulation. Significant increases in total body potassium, midupper arm circumference, and subscapular skinfold thickness occurred during the BCAA supplements, whereas no significant changes occurred during the standard formulation period. Significantly fewer albumin infusions were required during the BCAA supplement. These findings suggest that BCAA-enriched formulas have advantages over standard semielemental formulas in improving nutritional status in children with ESLD. and are deserving of wider application and study.

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Background Tarsal tunnel syndrome is classified as a focal compressive neuropathy of the posterior tibial nerve or one of its associated branches individually or collectively. The tunnel courses deep to fascia, the flexor retinaculum and within the abductor hallucis muscle of the foot/ankle. The condition is rare and regularly under-diagnosed leading to a range of symptoms affecting the plantar margins of the foot. There are many intervention strategies for treating tarsal tunnel syndrome with limited robust evidence to guide the clinical management of this condition. The role of conservative versus surgical interventions at various stages of the disease process remains unclear, and there is a need for a structured, step-wise approach in treating patients with this syndrome based on derived empirical evidence. This narrative review attempts to scrutinize the literature to date by clarifying initial presentation, investigations and definitive treatment for the purpose of assisting future informed clinical decision and prospective research endeavours. Process The literature searches that have been incorporated in compiling a rigorous review of this condition have included: the Cochrane Neuromuscular Group's Specialized Register (Cochrane Library 2013), the databases of EMBASE, AMED, MEDLINE, CINAHL, Physiotherapy evidence database (PEDRO), Biomed Central, Science Direct and Trip Database (1972 to the present). Reference listings of located articles were also searched and scrutinized. Authors and experts within the field of lower-limb orthopaedics were contacted to discuss applicable data. Subject-specific criteria searches utilizing the following key terms were performed across all databases: tarsal tunnel syndrome, tibial neuralgia, compression neuropathy syndromes, tibial nerve impingement, tarsal tunnel neuropathy, entrapment tibial nerve, posterior tibial neuropathy. These search strategies were modified with differing databases, adopting specific sensitivity-searching tools and functions unique to each. This search strategy identified 88 journal articles of relevance for this narrative literature review. Findings This literature review has appraised the clinical significance of tarsal tunnel syndrome, whilst assessing varied management interventions (non-surgical and surgical) for the treatment of this condition in both adults and children. According to our review, there is limited high-level robust evidence to guide and refine the clinical management of tarsal tunnel syndrome. Requirements for small-scaled randomized controlled trials in groups with homogenous aetiology are needed to analyse the effectiveness of specific treatment modalities. Conclusions It is necessary that further research endeavours be pursued for the clinical understanding, assessment and treatment of tarsal tunnel syndrome. Accordingly, a structured approach to managing patients who have been correctly diagnosed with this condition should be formulated on the basis of empirical evidence where possible.

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A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.

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Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

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The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

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A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

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Summary. Interim analysis is important in a large clinical trial for ethical and cost considerations. Sometimes, an interim analysis needs to be performed at an earlier than planned time point. In that case, methods using stochastic curtailment are useful in examining the data for early stopping while controlling the inflation of type I and type II errors. We consider a three-arm randomized study of treatments to reduce perioperative blood loss following major surgery. Owing to slow accrual, an unplanned interim analysis was required by the study team to determine whether the study should be continued. We distinguish two different cases: when all treatments are under direct comparison and when one of the treatments is a control. We used simulations to study the operating characteristics of five different stochastic curtailment methods. We also considered the influence of timing of the interim analyses on the type I error and power of the test. We found that the type I error and power between the different methods can be quite different. The analysis for the perioperative blood loss trial was carried out at approximately a quarter of the planned sample size. We found that there is little evidence that the active treatments are better than a placebo and recommended closure of the trial.

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Stallard (1998, Biometrics 54, 279-294) recently used Bayesian decision theory for sample-size determination in phase II trials. His design maximizes the expected financial gains in the development of a new treatment. However, it results in a very high probability (0.65) of recommending an ineffective treatment for phase III testing. On the other hand, the expected gain using his design is more than 10 times that of a design that tightly controls the false positive error (Thall and Simon, 1994, Biometrics 50, 337-349). Stallard's design maximizes the expected gain per phase II trial, but it does not maximize the rate of gain or total gain for a fixed length of time because the rate of gain depends on the proportion: of treatments forwarding to the phase III study. We suggest maximizing the rate of gain, and the resulting optimal one-stage design becomes twice as efficient as Stallard's one-stage design. Furthermore, the new design has a probability of only 0.12 of passing an ineffective treatment to phase III study.

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The purpose of a phase I trial in cancer is to determine the level (dose) of the treatment under study that has an acceptable level of adverse effects. Although substantial progress has recently been made in this area using parametric approaches, the method that is widely used is based on treating small cohorts of patients at escalating doses until the frequency of toxicities seen at a dose exceeds a predefined tolerable toxicity rate. This method is popular because of its simplicity and freedom from parametric assumptions. In this payer, we consider cases in which it is undesirable to assume a parametric dose-toxicity relationship. We propose a simple model-free approach by modifying the method that is in common use. The approach assumes toxicity is nondecreasing with dose and fits an isotonic regression to accumulated data. At any point in a trial, the dose given is that with estimated toxicity deemed closest to the maximum tolerable toxicity. Simulations indicate that this approach performs substantially better than the commonly used method and it compares favorably with other phase I designs.

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Suppose two treatments with binary responses are available for patients with some disease and that each patient will receive one of the two treatments. In this paper we consider the interests of patients both within and outside a trial using a Bayesian bandit approach and conclude that equal allocation is not appropriate for either group of patients. It is suggested that Gittins indices should be used (using an approach called dynamic discounting by choosing the discount rate based on the number of future patients in the trial) if the disease is rare, and the least failures rule if the disease is common. Some analytical and simulation results are provided.

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Physical and psychological decline is common in the post-treatment breast cancer population, yet the efficacy of concurrent interventions to meet both physical- psychosocial needs in this population has not been extensively examined. PURPOSE: This study explores the effects of a combined exercise and psychosocial intervention model on selected physiological-psychological parameters in post-treated breast cancer. METHODS: Forty-one breast cancer survivors were randomly assigned to one of four groups for an 8-week intervention: exercise only [EX, n=13] (aerobic and resistance training), psychosocial therapy only [PS, n=11] (biofeedback), combined EX and PS [EX+PS, n=11], or to control conditions [CO, n=6]. Mean delta score (post-intervention - baseline) were calculated for each of the following: body weight, % body fat (skin folds), predicted VO2max (Modified Bruce Protocol), overall dynamic muscular endurance [OME] (RMCRI protocol), static balance (Single leg stance test), dynamic balance (360° turn and 4-square step test), fatigue (Revised Piper Scale), and quality of life (FACT-B). A one-way ANOVA was used to analyze the preliminary results of this on-going randomized trial. RESULTS: Overall, there were significant differences in the delta scores for predicted VO2max, OME, and dynamic balance among the 4 groups (p<0.05). The EX+PS group showed a significant improvement in VO2max compared with the PS group (4.2 ± 3.8 vs. -0.9 ± 4.2 mL/kg/min; p<0.05). Both the EX+PS and EX groups showed significant improvements in OME compared with the PS and CO groups (44.5 ± 23.5 and 43.4 ± 22.1 vs. -3.9 ± 15.2 and 2.7 ± 13.7 repetitions; p<0.05). All 3 intervention groups showed significant improvements in dynamic balance compared with the CO group (-0.8 ± 0.6, -0.6 ± 0.8, and -0.6 ±1.0 vs. 0.6 ± 0.6 seconds; p<0.05). Overall, changes in fatigue tended towards significance among the 4 groups (p = 0.08), with decreased fatigue in the intervention groups and increased fatigue in the CO group. CONCLUSIONS: Our preliminary findings suggest that EX and PS seem to produce greater positive changes in the outcome measures than CO. However, at this point no definite conclusions can be made on the additive effects of combining the EX and PS interventions.

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Introduction Cannabis remains the most used illegal substance across the globe, and negative outcomes and disorders are common. A spotlight therefore falls on reductions in cannabis use in people with cannabis use disorder. Current estimates of unassisted cessation or reduction in cannabis use rely on community surveys, and few studies focus on individuals with disorder. A key interest of services and researchers is to estimate effect size of reductions in consumption among treatment seekers who do not obtain treatment. Effects within waiting list or information-only control conditions of randomised controlled trials offer an opportunity to study this question. Method This paper examines the extent of reductions in days of cannabis use in the control groups of randomised controlled trials on treatment of cannabis use disorders. A systematic literature search was performed to identify trials that reported days of cannabis use in the previous 30 (or equivalent). Results Since all but one of the eight identified studies had delayed treatment controls, results could only be summarised across 2–4 months. Average weighted days of use in the previous 30 days fell from 24.5 to 19.9, and a meta-analysis using a random effects model showed an average reduction of 0.442 SD. However, every study had at least one significant methodological issue. Conclusions While further high-quality data is needed to confirm the observed effects, these results provide a baseline from which researchers and practitioners can estimate the extent of change required to detect effects of cannabis treatments in services or treatment trials.