AMMI adjustment for statistical analysis of an international wheat yield trial

Summary Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.     

Robust modeling in screening studies: estimation of sensitivity and preclinical sojourn time distribution

In early-detection clinical trials, quantities such as the sensitivity of the screening modality and the preclinical duration of the disease are important to describe the natural history of the disease and its interaction with a screening program. Assume that the schedule of a screening program is periodic and that the sojourn time in the preclinical state has a piecewise density function. Modeling the preclinical sojourn time distribution as a piecewise density function results in robust estimation of the distribution function. Our aim is to estimate the piecewise density function and the examination sensitivity using both generalized least squares and maximum likelihood methods. We carried out extensive simulations to evaluate the performance of the methods of estimation. The different estimation methods provide complimentary tools to obtain the unknown parameters. The methods are applied to three breast cancer early-detection trials.     

Simultaneous group sequential analysis of rank-based and weighted Kaplan-Meier tests for paired censored survival data

This research sequentially monitors paired survival differences using a new class of nonparametric tests based on functionals of standardized paired weighted log-rank (PWLR) and standardized paired weighted Kaplan-Meier (PWKM) tests. During a trial, these tests may alternately assume the role of the more extreme statistic. By monitoring PEMAX, the maximum between the absolute values of the standardized PWLR and PWKM, one combines advantages of rank-based (RB) and non-RB paired testing paradigms. Simulations show that monitoring treatment differences using PEMAX maintains type I error and is nearly as powerful as using the more advantageous of the two tests in proportional hazards (PH) as well as non-PH situations. Hence, PEMAX preserves power more robustly than individually monitored PWLR and PWKM, while maintaining a reasonably simple approach to design and analysis of results. An example from the Early Treatment Diabetic Retinopathy Study (ETDRS) is given.     

A note on P-values under group sequential testing and nonproportional hazards

Summary .   Group sequential designs are often used for periodically assessing treatment efficacy during the course of a clinical trial. Following a group sequential test, P -values computed under the assumption that the data were gathered according to a fixed sample design are no longer uniformly distributed under the null hypothesis of no treatment effect. Various sample space orderings have been proposed for computing proper P -values following a group sequential test. Although many of the proposed orderings have been compared in the setting of time-invariant treatment effects, little attention has been given to their performance when the effect of treatment within an individual varies over time. Our interest here is to compare two of the most commonly used methods for computing proper P -values following a group sequential test, based upon the analysis time (AT) and Z -statistic orderings, with respect to resulting power functions when treatment effects on survival are delayed. Power under the AT ordering is shown to be heavily influenced by the presence of a delayed treatment effect, while power functions corresponding to the Z -statistic ordering remain robust under time-varying treatment effects.     

The clinical syndrome of Alzheimer's disease: aspects particularly relevant to clinical trials

This paper describes the natural history of the clinical syndrome of Alzheimer's disease (AD) including the cognitive deficit, the neuropsychiatric symptoms, impact on daily functioning, risk factors, medical complications and impact on the use of health-care resources. The clinical presentation of the disease varies greatly from the prodrome through end stage; instruments used to quantify the severity of each aspect of the disease have been developed and are described along with their use in clinical drug trials. Drug treatments for AD are usually developed by first showing a positive effect on the cognitive deficit, with later studies investigating drug effects on other clinical aspects of the disease.     

Consent for participating in clinical trials ‐ Is it really informed?

The article explores the challenges of ensuring voluntary and informed consent which is obtained from potential research subjects in the north‐eastern part of Romania. This study is one of the first empirical papers of this nature in Romania. The study used a quantitative survey design using the adapted Quality of Informed Consent (QuIC) questionnaire. The target population consisted of 100 adult persons who voluntarily enrolled in clinical trials. The informed consent form must contain details regarding the potential risks and benefits, the aim of the clinical trial, study design, confidentiality, insurance and contact details in case of additional questions. Our study confirmed that although all required information was included in the ICF, few clinical trial participants truly understood it. We also found that the most important predictive factor for a good subjective and objective understanding of the clinical trial was the level of education. Our study suggests that researchers should consider putting more effort in order to help clinical trials participants achieve a better understanding of the informed consent. In this way they will ensure that participants’ decision‐making is meaningful and that their interests are protected.     

Seed‐specific RNAi in safflower generates a superhigh oleic oil with extended oxidative stability

Vegetable oils extracted from oilseeds are an important component of foods, but are also used in a range of high value oleochemical applications. Despite being biodegradable, nontoxic and renewable current plant oils suffer from the presence of residual polyunsaturated fatty acids that are prone to free radical formation that limit their oxidative stability, and consequently shelf life and functionality. Many decades of plant breeding have been successful in raising the oleic content to ~90%, but have come at the expense of overall field performance, including poor yields. Here, we engineer superhigh oleic (SHO) safflower producing a seed oil with 93% oleic generated from seed produced in multisite field trials spanning five generations. SHO safflower oil is the result of seed‐specific hairpin‐based RNA interference of two safflower lipid biosynthetic genes, FAD2.2 and FATB, producing seed oil containing less than 1.5% polyunsaturates and only 4% saturates but with no impact on lipid profiles of leaves and roots. Transgenic SHO events were compared to non‐GM safflower in multisite trial plots with a wide range of growing season conditions, which showed no evidence of impact on seed yield. The oxidative stability of the field‐grown SHO oil produced from various sites was 50 h at 110°C compared to 13 h for conventional ~80% oleic safflower oils. SHO safflower produces a uniquely stable vegetable oil across different field conditions that can provide the scale of production that is required for meeting the global demands for high stability oils in food and the oleochemical industry.     

Gene therapy clinical trials worldwide to 2017: An update

To date, almost 2600 gene therapy clinical trials have been completed, are ongoing or have been approved worldwide. Our database brings together global information on gene therapy clinical activity from trial databases, official agency sources, published literature, conference presentations and posters kindly provided to us by individual investigators or trial sponsors. This review presents our analysis of clinical trials that, to the best of our knowledge, have been or are being performed worldwide. As of our November 2017 update, we have entries on 2597 trials undertaken in 38 countries. We have analysed the geographical distribution of trials, the disease indications (or other reasons) for trials, the proportions to which different vector types are used, and the genes that have been transferred. Details of the analyses presented, and our searchable database are available via The Journal of Gene Medicine Gene Therapy Clinical Trials Worldwide website at: http://www.wiley.co.uk/genmed/clinical . We also provide an overview of the progress being made in gene therapy clinical trials around the world, and discuss key trends since the previous review, namely the use of chimeric antigen receptor T cells for the treatment of cancer and advancements in genome editing technologies, which have the potential to transform the field moving forward.     

SEX PHEROMONE OF THE FEMALE MOTHS CYDIA TRASIAS MEYRICK: IDENTIFICATION OF AN ACTIVE COMPONENT AND FIELD TRIALS*

Abstract An active component of the female sex pheromone of Chinese locust moth, Cydia Trash Meyrick, was identified as (E, E)-8, 10-dodecadienyl acetate (E8, E10–12:Ac) by GC, GC—MS analyses and microchemical reactions. The results of field trials showed that synthetic E8, E10—-12: Ac was very attractive to the male moths.     

Efficiency of check-plot designs in unreplicated field trials

Check-plot designs have a lower selection intensity than unreplicated non-check-plot designs if both the number of test lines to be selected (s) and of total plots in the trial (N) are kept constant. For a check-plot design to be more efficient, local control must effectively reduce the plot error variance and increase heritability to such a level that it compensates for the corresponding loss in selection intensity and makes the expected gain from selection at least equal to that in the non-check-plot design. To realize this goal, the required minimum reduction in plot error variance in a checkplot design (relative to that in a non-check-plot design) depends on (1) check-plot frequencyf _c , (2) fractionk = s/N, and (3) ratiow ₀= ₀ ² / _g ² of non-check-plot design plot error variance ₀ ² to genetic variance _g ² among test lines. Lowerw ₀ and higherf _c andk are found to require a relatively higher reduction in plot error variance in check-plot designs. A condition is derived to show when a check-plot design may never be more efficient.