883 resultados para Variety Trials
Resumo:
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.
Resumo:
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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In Pediatric AIDS Clinical Trials Group 377, antiretroviral therapy-experienced children were randomized to 4 treatment arms that included different combinations of stavudine, lamivudine (3TC), nevirapine (Nvp), nelfinavir (Nfv), and ritonavir (Rtv). Previous treatment with zidovudine (Zdv), didanosine (ddI), or zalcitabine (ddC) was acceptable. Drug resistance ((R)) mutations were assessed before study treatment (baseline) and at virologic failure. Zdv(R), ddI(R), and ddC(R) mutations were detected frequently at baseline but were not associated with virologic failure. Children with drug resistance mutations at baseline had greater reductions in virus load over time than did children who did not. Nvp(R) and 3TC(R) mutations were detected frequently at virologic failure, and Nvp(R) mutations were more common among children receiving 3-drug versus 4-drug Nvp-containing regimens. Children who were maintained on their study regimen after virologic failure accumulated additional Nvp(R) and 3TC(R) mutations plus Rtv(R) and Nfv(R) mutations. However, Rtv(R) and Nfv(R) mutations were detected at unexpectedly low rates.
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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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We explore the use of Gittins indices to search for near optimality in sequential clinical trials. Some adaptive allocation rules are proposed to achieve the following two objectives as far as possible: (i) to reduce the expected successes lost, (ii) to minimize the error probability at the end. Simulation results indicate the merits of the rules based on Gittins indices for small trial sizes. The rules are generalized to the case when neither of the response densities is known. Asymptotic optimality is derived for the constrained rules. A simple allocation rule is recommended for one-stage models. The simulation results indicate that it works better than both equal allocation and Bather's randomized allocation. We conclude with a discussion of possible further developments.
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A recently developed radioimmunoassay (RIA) for measuring insulin-like growth factor (IGF-I) in a variety of fish species was used to investigate the correlation between growth rate and circulating IGF-I concentrations of barramundi (Lates calcarifer), Atlantic salmon (Salmo salar) and Southern Bluefin tuna (Thunnus maccoyii). Plasma IGF-I concentration significantly increased with increasing ration size in barramundi and IGF-I concentration was positively correlated to growth rates obtained in Atlantic salmon (r2=0.67) and barramundi (r2=0.65) when fed a variety of diet formulations. IGF-I was also positively correlated to protein concentration (r2=0.59). This evidence suggested that measuring IGF-I concentration may provide a useful tool for monitoring fish growth rate and also as a method to rapidly assess different aquaculture diets. However, no such correlation was demonstrated in the tuna study probably due to seasonal cooling of sea surface temperature shortly before blood was sampled. Thus, some recommendations for the design and sampling strategy of nutritional trials where IGF-I concentrations are measured are discussed
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The sciaenid Protonibea diacanthus is a large, long-lived predatory fish of inshore northern Australian waters, which forms annual aggregations that are fished extensively by traditional (subsistence) and recreational fishers. There are now widespread concerns that the resource is being overexploited. Indigenous fishers of the Cape York Northern Peninsula Area (NPA) relate that large adult fish (up to 1500 mm total length (TL)) made up the bulk of the catch from the sciaenid aggregations until about 1994. In contrast, sexually mature P. diacanthus comprised only a small component (12 fish out of 270=4.4%) examined in a 1999–2000 sampling programme that was biased towards the largest individuals available. At 790 mm TL, the minimum size at first maturity for female P. diacanthus in this study is much smaller than the 920 mm TL reported previously in Queensland waters. Developing ovaries were observed in specimens sampled from sciaenid aggregations which formed in NPA waters between May and September 2000. However, no fish with ripe or spent gonads were found in the study, so the current timing and location of the spawning season for P. diacanthus in the region remain unknown. Food items observed in the analysis of the diet of P. diacanthus from the NPA included a variety of teleosts and invertebrates. The range of animal taxa represented in the prey items support the description of an ‘opportunistic predator’ attributed to the species. In our sampling, the stomach contents of fish caught during the time of the aggregation events did not differ from those observed at other times of the year. A total of 114 P. diacanthus were tagged and released at aggregation sites during the study period, and 3 fish (2.6%) were subsequently recaptured. The low rate of tag returns from the wild stock tagging programme, both in this study (2.6%) and from recreational fisher tag/release programmes for the sciaenid elsewhere in Queensland (6.5%), were not explained by tag loss nor mortality, given the high retention rate of tags and the zero mortality seen in tank trials. In response to the biological findings from this study, indigenous community councils of the NPA imposed a 2-year fishing moratorium for P. diacanthus. Surveys at aggregation sites in 2002 and 2003 established that much larger fish (mean size 103.5 cm TL) were again present on the grounds, albeit in very low numbers. These recent preliminary results highlight the critical need for continued monitoring and management of the P. diacanthus fishery in the NPA, if prospects for resource recovery are to be realised. The NPA initiative has provided a rare opportunity to negotiate a co-management strategy, based on scientific data and traditional knowledge, for the recovery of a cultural and economically significant fished resource.
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An important question of biological relevance is the polymorphism of the double-helical DNA structure in its free form, and the changes that it undergoes upon protein-binding. We have analysed a database of free DNA crystal structures to assess the inherent variability of the free DNA structure and have compared it with a database of protein-bound DNA crystal structures to ascertain the protein-induced variations.
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Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.
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The efficacy of supported covers was investigated under field conditions using a series of prototypes deployed on an anaerobic pond treating typical piggery waste. Research focused on identifying effective cover support materials and deployment methods, quantifying odour reduction, and estimating the life expectancy of various permeable cover materials. Over a 10-month period, median odour emission rates were five to eight times lower from supported straw cover surfaces and a non-woven, spun fibre polypropylene weed control material than from the adjacent uncovered pond surface. While the straw covers visually appeared to degrade very rapidly, they continued to reduce odour emissions effectively. The polypropylene cover appeared to offer advantages from the perspectives of cost, reduced maintenance and ease of manufacture.
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Pratylenchus thornei and P. neglectus are two species of root-lesion nematode that cause substantial yield losses in wheat. No commercially available wheat variety has resistance to both species. A doubled-haploid population developed from a cross between the synthetic hexaploid wheat line CPI133872 and the bread wheat Janz was used to locate and tag quantitative trait loci (QTLs) associated with resistance to both P. thornei and P. neglectus. Wheat plants were inoculated with both species of nematode in independent replicated glasshouse trials repeated over 2 years. Known locations of wheat microsatellite markers were used to construct a framework map. After an initial single-marker analysis to detect marker-trait linkages, chromosome regions associated with putative QTLs were targetted with microsatellite markers to increase map density in the chromosome regions of interest. In total, 148 wheat microsatellite markers and 21 amplified fragment length polymorphism markers were mapped. The codominant microsatellite marker Xbarc183 on the distal end of chromosome 6DS was allelic for resistance to both P. thornei and P. neglectus. The QTL were designated QRlnt.lrc-6D.1 and QRlnn.lrc-6D.1, for the 2 traits, respectively. The allele inherited from CPI133872 explained 22.0-24.2% of the phenotypic variation for P. thornei resistance, and the allele inherited from Janz accounted for 11.3-14.0% of the phenotypic variation for P. neglectus resistance. Composite interval mapping identified markers that flank a second major QTL on chromosome 6DL (QRlnt.lrc-6D.2) that explained 8.3-13.4% of the phenotypic variation for P. thornei resistance. An additional major QTL associated with P. neglectus resistance was detected on chromosome 4DS (QRlnn.lrc-4D.1) and explained a further 10.3-15.4% of the phenotypic variation. The identification and tagging of nematode resistance genes with molecular markers will allow appropriate allele combinations to be selected, which will aid the successful breeding of wheat with dual nematode resistance.
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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.
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The Australian sheep blowfly, Lucilia cuprina initiates more than 85% of fly strikes on sheep in Australia with an estimated average annual cost of A$280 million to the Australian wool industry. LuciTrap® is a commercially available, selective trap for L. cuprina consisting of a plastic bucket with multiple fly entry cones and a synthetic attractant. The impact of LuciTrap on populations of L. cuprina on sheep properties in five Australian states was evaluated by comparing L. cuprina populations on paired properties with and without LuciTraps over seasons when significant fly populations could be expected. Twenty-four comparisons (trials) were conducted over four years. During times of ‘higher fly density’ (when the 48 h geometric mean of trap catches on the control property was greater than five L. cuprina), the overall geometric mean trap catches for control and trapped properties differed significantly (P<0.001) with mean trap catches of 19.4 and 7.74 L. cuprina respectively. The selectivity of the LuciTrap was confirmed with 59% of all trapped flies being L. cuprina. Chrysomya spp. and Calliphora spp. constituted 9.3% and 1.1% of the catches with a variety of other flies (mainly Sarcophagidae and Muscidae) providing the remainder (31%). L. sericata was only trapped in Tasmania and made up 7.7% of the Lucilia spp. catch in this State. Seventy-two percent of the trapped L. cuprina were female. The deployment of LuciTrap on sheep properties at one trap per 100 sheep from the beginning of the anticipated fly season suppressed the populations of L. cuprina by 60% compared to matched control properties. The LuciTrap is a selective and easy to use fly trap and constitutes an effective, non-insecticidal tool for use in integrated management programs for L. cuprina.