Niche and phenotypic differentiation in fern hybrid speciation, a case study of Pteris fauriei (Pteridaceae).

BACKGROUND AND AIMS: Niche differentiation is a crucial issue in speciation. Although it has a well-known role in adaptive processes of hybrid angiosperms, it is less understood in hybrid ferns. Here, we investigate whether an intermediate ecological niche of a fern hybrid is a novel adaptation that provides insights into fern hybrid speciation. METHODS: Pteris fauriei (Pteridaceae) is a natural hybrid fern, occurring in environments between its parent species. The maternal Pteris minor is found in sunny areas, but the habitat of the paternal Pteris latipinna is shady. We combined data from morphology, leaf anatomy and photosynthetic traits to explore adaptation and differentiation, along with measuring the environmental features of their niches. We also performed experiments in a common garden to understand ecological plasticity. KEY RESULTS: The hybrid P. fauriei was intermediate between the parent species in stomatal density, leaf anatomical features and photosynthetic characteristics in both natural habitats and a common garden. Interestingly, the maternal P. minor showed significant environmental plasticity and was more similar to the hybrid P. fauriei in the common garden, suggesting that the maternal species experiences stress in its natural habitats but thrives in environments similar to those of the hybrid. CONCLUSIONS: Based on the similar niche preferences of the hybrid and parents, we propose hybrid superiority. Our results indicate that the hybrid P. fauriei exhibits greater fitness and can compete with and occupy the initial niches of the maternal P. minor. Consequently, we suggest that the maternal P. minor has experienced a niche shift, elucidating the pattern of niche differentiation in this hybrid group. These findings offer a potential explanation for the frequent occurrence of hybridization in ferns and provide new insights into fern hybrid speciation, enhancing our understanding of fern diversity.

Confidence intervals for odds ratio from multistage randomized phase II trials.

A multi-stage randomized trial design can significantly improve efficiency by allowing early termination of the trial when the experimental arm exhibits either low or high efficacy compared to the control arm during the study. However, proper inference methods are necessary because the underlying distribution of the target statistic changes due to the multi-stage structure. This article focuses on multi-stage randomized phase II trials with a dichotomous outcome, such as treatment response, and proposes exact conditional confidence intervals for the odds ratio. The usual single-stage confidence intervals are invalid when used in multi-stage trials. To address this issue, we propose a linear ordering of all possible outcomes. This ordering is conditioned on the total number of responders in each stage and utilizes the exact conditional distribution function of the outcomes. This approach enables the estimation of an exact confidence interval accounting for the multi-stage designs.

Are the tests overpowered or underpowered? A unified solution to correctly specify type I errors in design of clinical trials for two sample proportions.

As one of the most commonly used data types, methods in testing or designing a trial for binary endpoints from two independent populations are still being developed until recently. However, the power and the minimum required sample size comparisons between different tests may not be valid if their type I errors are not controlled at the same level. In this article, we unify all related testing procedures into a decision framework, including both frequentist and Bayesian methods. Sufficient conditions of the type I error attained at the boundary of hypotheses are derived, which help reduce the magnitude of the exact calculations and lay out a foundation for developing computational algorithms to correctly specify the actual type I error. The efficient algorithms are thus proposed to calculate the cutoff value in a deterministic decision rule and the probability value in a randomized decision rule, such that the actual type I error is under but closest to, or equal to, the intended level, respectively. The algorithm may also be used to calculate the sample size to achieve the prespecified type I error and power. The usefulness of the proposed methodology is further demonstrated in the power calculation for designing superiority and noninferiority trials.

Application of deep eutectic solvents on extraction of flavonoids.

Deep eutectic solvents (DESs), as a new type of eco-friendly solvent, have attracted increasing attention on the extraction and separation of flavonoid compounds from various samples, owing to their excellent properties such as biodegradability and ease of handling with very low toxicity. This article provides a status review of the applications of DESs in the extraction of flavonoids, including the introduction of flavonoid compounds, the properties and superiority of DESs, and extraction methods (ultrasonic-assisted extraction, heating reflux extraction, matrix solid-phase dispersion, and solid-phase extraction). Finally, prospects and challenges in the application of DESs on extraction and separation are extensively elucidated and critically reviewed.

Estimation of the odds ratio from multi-stage randomized trials.

A multi-stage design for a randomized trial is to allow early termination of the study when the experimental arm is found to have low or high efficacy compared to the control during the study. In such a trial, an early stopping rule results in bias in the maximum likelihood estimator of the treatment effect. We consider multi-stage randomized trials on a dichotomous outcome, such as treatment response, and investigate the estimation of the odds ratio. Typically, randomized phase II cancer clinical trials have two-stage designs with small sample sizes, which makes the estimation of odds ratio more challenging. In this paper, we evaluate several existing estimation methods of odds ratio and propose bias-corrected estimators for randomized multi-stage trials, including randomized phase II cancer clinical trials. Through numerical studies, the proposed estimators are shown to have a smaller bias and a smaller mean squared error overall.

Applying the Estimand Framework to Non­Inferiority Trials.

Most published applications of the estimand framework have focused on superiority trials. However, non-inferiority trials present specific challenges compared to superiority trials. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use notes in their addendum on estimands and sensitivity analysis in clinical trials that there may be special considerations to the implementation of estimands in clinical trials with a non-inferiority objective yet provides little guidance. This paper discusses considerations that trial teams should make when defining estimands for a clinical trial with a non-inferiority objective. We discuss how the pre-addendum way of establishing non-inferiority can be embraced by the estimand framework including a discussion of the role of the Per Protocol analysis set. We examine what clinical questions of interest can be formulated in the context of non-inferiority trials and outline why we do not think it is sensible to describe an estimand as 'conservative'. The impact of the estimand framework on key considerations in non-inferiority trials such as whether trials should have more than one primary estimand, the choice of non-inferiority margin, assay sensitivity, switching from non-inferiority to superiority and estimation are discussed. We conclude by providing a list of recommendations, and important considerations for defining estimands for trials with a non-inferiority objective.

[Establishment and content validity assessment of evaluation index system for development value of traditional Chinese medicine preparations in medical institutions].

The development of traditional Chinese medicine(TCM) preparations as an incubator for new drugs in medical institutions has flourished, while an evaluation index system remains to be established for comprehensively assessing the development value of these prescriptions. This study established an item pool through literature research, employed the Delphi method to determine the content of evaluation indexes, and adopted the superiority chart to determine the weight of each index. Two-level evaluation index system for the development value of TCM preparations in medical institutions was established, which included 7 first-level items and 36 se-cond-level items, demonstrating scientific validity. The first-level items(weight) were inheritance(10.61%), effectiveness(23.22%), safety(22.71%), innovation(13.21%), economy(10.00%), suitability(8.57%), and accessibility(11.68%). The top three second-level items in terms of weight distribution were adverse reaction monitoring(6.73%), evidence of therapeutic effect(5.71%), and clinical response rate(4.75%). The bottom three second-level items were production advantages(0.86%), medicinal dosage(0.48%), and medicinal smell or taste(0.18%). The content validity of the established system was assessed, which revealed that the index system was reliable, with the overall and average content validity indexes of 0.47 and 0.90, respectively. Furthermore, the established evaluation index system was used to evaluate six TCM preparations in a city-level hospital of TCM in Sichuan Province, which demonstrated that the system had operability. The results indicate that the evaluation index system is scientific, reliable, and operable, providing a reference for developers to selectively develop TCM preparations in medical institutions. In practical application, the system can be adjusted regarding the index weights according to actual conditions.

A novel statistical test for treatment differences in clinical trials using a response-adaptive forward-looking Gittins Index Rule.

The most common objective for response-adaptive clinical trials is to seek to ensure that patients within a trial have a high chance of receiving the best treatment available by altering the chance of allocation on the basis of accumulating data. Approaches that yield good patient benefit properties suffer from low power from a frequentist perspective when testing for a treatment difference at the end of the study due to the high imbalance in treatment allocations. In this work we develop an alternative pairwise test for treatment difference on the basis of allocation probabilities of the covariate-adjusted response-adaptive randomization with forward-looking Gittins Index (CARA-FLGI) Rule for binary responses. The performance of the novel test is evaluated in simulations for two-armed studies and then its applications to multiarmed studies are illustrated. The proposed test has markedly improved power over the traditional Fisher exact test when this class of nonmyopic response adaptation is used. We also find that the test's power is close to the power of a Fisher exact test under equal randomization.

baymedr: an R package and web application for the calculation of Bayes factors for superiority, equivalence, and non-inferiority designs.

BACKGROUND: Clinical trials often seek to determine the superiority, equivalence, or non-inferiority of an experimental condition (e.g., a new drug) compared to a control condition (e.g., a placebo or an already existing drug). The use of frequentist statistical methods to analyze data for these types of designs is ubiquitous even though they have several limitations. Bayesian inference remedies many of these shortcomings and allows for intuitive interpretations, but are currently difficult to implement for the applied researcher. RESULTS: We outline the frequentist conceptualization of superiority, equivalence, and non-inferiority designs and discuss its disadvantages. Subsequently, we explain how Bayes factors can be used to compare the relative plausibility of competing hypotheses. We present baymedr, an R package and web application, that provides user-friendly tools for the computation of Bayes factors for superiority, equivalence, and non-inferiority designs. Instructions on how to use baymedr are provided and an example illustrates how existing results can be reanalyzed with baymedr. CONCLUSIONS: Our baymedr R package and web application enable researchers to conduct Bayesian superiority, equivalence, and non-inferiority tests. baymedr is characterized by a user-friendly implementation, making it convenient for researchers who are not statistical experts. Using baymedr, it is possible to calculate Bayes factors based on raw data and summary statistics.

Investigating the cognitive processing of tools: Effects of dangerousness and directionality on attentional biases.

Research has found a tool-based head-superiority effect (responses are faster to target stimuli that appear at the head than at the handle position). However, these studies did not consider the effects of directionality and dangerousness. This study investigated how directionality and dangerousness influence the head-superiority effect. Subjects were required to respond to the target location in all experiments. Experiment 1 manipulated the directionality, dangerousness and target location. Experiment 2 matched the sharpness of the tool tip in the directed conditions. Experiment 3 shortened the presentation time of the cue stimuli from 800 ms to 200 ms. Experiment 4 selected four tools with different functions to rule out an alternative explanation caused by functional repetition. The results indicate that a head-superiority effect emerges in the directed condition, and that dangerousness modulates the magnitude of this effect during the 800 ms condition. However, the modulation effect of dangerousness diminishes during the 200 ms condition.

Working memory modulates the anger superiority effect in central and peripheral visual fields.

Angry faces have been shown to be detected more efficiently in a crowd of distractors compared to happy faces, known as the anger superiority effect (ASE). The present study investigated whether the ASE could be modified by top-down manipulation of working memory (WM), in central and peripheral visual fields. In central vision, participants held a colour in WM for a final memory test while simultaneously performing a visual search task that required them to determine whether a face showed a different expression from other coloured faces. The colour held in WM matched either the colour of the target face (target-matching), the colour of a distractor face (distractor-matching), or neither (non-matching). Results showed that the ASE was observed when the probability of target-matching trials was low. However, when the top-down WM effect was strengthened by raising the probability of target-matching trials, the ASE in the target-matching condition was completely eliminated. Intriguingly, when the visual search task was substituted by a peripheral crowding task, similar results to central vision were found in the target-matching condition. Taken together, our findings indicate that the ASE is subject to the top-down WM effect, regardless of the visual field.

artbin: Extended sample size for randomized trials with binary outcomes.

We describe the command artbin, which offers various new facilities for the calculation of sample size for binary outcome variables that are not otherwise available in Stata. While artbin has been available since 2004, it has not been previously described in the Stata Journal. artbin has been recently updated to include new options for different statistical tests, methods and study designs, improved syntax, and better handling of noninferiority trials. In this article, we describe the updated version of artbin and detail the various formulas used within artbin in different settings.

artcat: Sample-size calculation for an ordered categorical outcome.

We describe a new command, artcat, that calculates sample size or power for a randomized controlled trial or similar experiment with an ordered categorical outcome, where analysis is by the proportional-odds model. artcat implements the method of Whitehead (1993, Statistics in Medicine 12: 2257-2271). We also propose and implement a new method that 1) allows the user to specify a treatment effect that does not obey the proportional-odds assumption, 2) offers greater accuracy for large treatment effects, and 3) allows for noninferiority trials. We illustrate the command and explore the value of an ordered categorical outcome over a binary outcome in various settings. We show by simulation that the methods perform well and that the new method is more accurate than Whitehead's method.

Probability of superiority for comparing two groups of clusters.

The probability of superiority (PS) has been recommended as a simple-to-interpret effect size for comparing two independent samples-there are several methods for computing the PS for this particular study design. However, educational and psychological interventions increasingly occur in clustered data contexts; and a review of the literature returned only one method for computing the PS in such contexts. In this paper, we propose a method for estimating the PS in clustered data contexts. Specifically, the proposal addresses study designs that compare two groups and group membership is determined at the cluster level. A cluster may be: (i) a group of cases with each case measured once, or (ii) a single case with each case measured multiple times, resulting in longitudinal data. The proposal relies on nonparametric point estimates of the PS coupled with cluster-robust variance estimation, such that the proposed approach should remain adequate regardless of the distribution of the response data. Using Monte Carlo simulation, we show the approach to be unbiased for continuous and binary outcomes, while maintaining adequate frequentist properties. Moreover, our proposal performs better than the single extant method we found in the literature. The proposal is simple to implement in commonplace statistical software and we provide accompanying R code. Hence, it is our hope that the method we present helps applied researchers better estimate group differences when comparing two groups and group membership is determined at the cluster level.

PSMA PET/CT guided intensification of therapy in patients at risk of advanced prostate cancer (PATRON): a pragmatic phase III randomized controlled trial.

BACKGROUND: Positron emission tomography targeting the prostate specific membrane antigen (PSMA PET/CT) has demonstrated unparalleled performance as a staging examination for prostate cancer resulting in substantial changes in management. However, the impact of altered management on patient outcomes is largely unknown. This study aims to assess the impact of intensified radiotherapy or surgery guided by PSMA PET/CT in patients at risk of advanced prostate cancer. METHODS: This pan-Canadian phase III randomized controlled trial will enroll 776 men with either untreated high risk prostate cancer (CAPRA score 6-10 or stage cN1) or biochemically recurrent prostate cancer post radical prostatectomy (PSA > 0.1 ng/mL). Patients will be randomized 1:1 to either receive conventional imaging or conventional plus PSMA PET imaging, with intensification of radiotherapy or surgery to newly identified disease sites. The primary endpoint is failure free survival at 5 years. Secondary endpoints include rates of adverse events, time to next-line therapy, as well as impact on health-related quality of life and cost effectiveness as measured by incremental cost per Quality Adjusted Life Years gained. DISCUSSION: This study will help create level 1 evidence needed to demonstrate whether or not intensification of radiotherapy or surgery based on PSMA PET findings improves outcomes of patients at risk of advanced prostate cancer in a manner that is cost-effective. TRIAL REGISTRATION: This trial was prospectively registered in ClinicalTrials.gov as NCT04557501 on September 21, 2020.

Adaptive treatment allocation and selection in multi-arm clinical trials: a Bayesian perspective.

BACKGROUND: Adaptive designs offer added flexibility in the execution of clinical trials, including the possibilities of allocating more patients to the treatments that turned out more successful, and early stopping due to either declared success or futility. Commonly applied adaptive designs, such as group sequential methods, are based on the frequentist paradigm and on ideas from statistical significance testing. Interim checks during the trial will have the effect of inflating the Type 1 error rate, or, if this rate is controlled and kept fixed, lowering the power. RESULTS: The purpose of the paper is to demonstrate the usefulness of the Bayesian approach in the design and in the actual running of randomized clinical trials during phase II and III. This approach is based on comparing the performance of the different treatment arms in terms of the respective joint posterior probabilities evaluated sequentially from the accruing outcome data, and then taking a control action if such posterior probabilities fall below a pre-specified critical threshold value. Two types of actions are considered: treatment allocation, putting on hold at least temporarily further accrual of patients to a treatment arm, and treatment selection, removing an arm from the trial permanently. The main development in the paper is in terms of binary outcomes, but extensions for handling time-to-event data, including data from vaccine trials, are also discussed. The performance of the proposed methodology is tested in extensive simulation experiments, with numerical results and graphical illustrations documented in a Supplement to the main text. As a companion to this paper, an implementation of the methods is provided in the form of a freely available R package 'barts'. CONCLUSION: The proposed methods for trial design provide an attractive alternative to their frequentist counterparts.

What role for cognitive remediation in the treatment of depressive symptoms? A superiority and noninferiority meta-analysis for clinicians.

BACKGROUND: Cognitive remediation (CR) is a promising technique in the treatment of the cognitive dimension of depression. The present study evaluated the potential of CR in treating depressive symptoms and provides practical information about its usefulness in clinical settings. METHODS: We performed two meta-analyses of published randomized (and nonrandomized) clinical trials, comparing CR to control conditions in subjects with current depressive symptomatology. The superiority meta-analysis aimed to determine the superiority of CR when compared with placebo/waiting list interventions and its efficacy when used as an augmentation therapy. The noninferiority meta-analysis determined whether CR had noninferior efficacy compared with standard antidepressant interventions. RESULTS: CR was found to significantly improve depressive symptomatology in the superiority meta-analysis (CR: n = 466, control n = 478). Moreover, CR seemed to be noninferior to standard antidepressant interventions (CR: n = 230, control n = 235). CR was more effective when addressing hot (vs. cold) cognition, when involving younger patients (i.e., <30 years), and in the case of mild-moderate (vs. severe) depression. CONCLUSIONS: CR should be considered an augmentation treatment to improve treatment outcomes in depressed subjects, especially among young individuals. Interventions addressing hot cognition seem to be the most promising.

Do graspable objects always leave a motor signature? A study on memory traces.

Several studies have reported the existence of reciprocal interactions between the type of motor activity physically performed on objects and the conceptual knowledge that is retained of them. Whether covert motor activity plays a similar effect is less clear. Certainly, objects are strong triggers for actions, and motor components can make the associated concepts more memorable. However, addition of an action-related memory trace may not always be automatic and could rather depend on 'how' objects are encountered. To test this hypothesis, we compared memory for objects that passive observers experienced as verbal labels (the word describing them), visual images (color photographs) and actions (pantomimes of object use). We predicted that the more direct the involvement of action-related representations the more effective would be the addition of a motor code to the experience and the more accurate would be the recall. Results showed that memory for objects presented as words i.e., a format that might only indirectly prime the sensorimotor system, was generally less accurate compared to memory for objects presented as photographs or pantomimes, which are more likely to directly elicit motor simulation processes. In addition, free recall of objects experienced as pantomimes was more accurate when these items afforded actions performed towards one's body than actions directed away from the body. We propose that covert motor activity can contribute to objects' memory, but the beneficial addition of a motor code to the experience is not necessarily automatic. An advantage is more likely to emerge when the observer is induced to take a first-person stance during the encoding phase, as may happen for objects affording actions directed towards the body, which obviously carry more relevance for the actor.

Partition testing for real-world evidence studies.

Traditional approaches to hypothesis testing in comparative post-approval safety and effectiveness studies of medical products are often inadequate because of a limited scope of possible inferences (e.g., superiority or inferiority). Often there is interest in simultaneously testing for superiority, equivalence, inferiority, non-inferiority, and non-superiority, which can be achieved using a partition testing framework. Partition testing only requires selection of an equivalence margin and calculation of a two-sided Wald confidence interval. In addition to permitting a broader range of inferences, the strengths of the approach include: mitigating publication bias, avoiding use of a clinically irrelevant nil hypothesis, and more transparent and impartial appraisal of the clinical importance of a study's findings by pre-specifying an equivalence margin. However, a challenge in implementing the approach can be the process for identifying an equivalence margin. The methodology is illustrated using a published study of the safety of Ondansetron for the off-label treatment of nausea and vomiting during pregnancy. Applying the method to the study results would have led to a conclusion that women exposed to Ondansetron in comparison to those that are not, are equivalent with respect to risk of cardiac malformations and oral clefts. These conclusions are more in line with the magnitude of the observed effects than the conclusions resulting from a traditional inferiority/superiority testing conducted by the study authors.

A Bayesian adaptive design for clinical trials of rare efficacy outcomes with multiple definitions.

INTRODUCTION: Bayesian adaptive designs for clinical trials have gained popularity in the recent years due to the flexibility and efficiency that they offer. We consider the scenario where the outcome of interest comprises events with relatively low risk of occurrence and different case definitions resulting in varying control group risk assumptions. This is a scenario that occurs frequently for infectious diseases in global health research. METHODS: We propose a Bayesian adaptive design that incorporates different case definitions of the outcome of interest that vary in stringency. A set of stopping rules are proposed where superiority and futility may be concluded with respect to different outcome definitions and therefore maintain a realistic probability of stopping in trials with low event rates. Through a simulation study, a variety of stopping rules and design configurations are compared. RESULTS: The simulation results are provided in an interactive web application that allows the user to explore and compare the design operating characteristics for a variety of assumptions and design parameters with respect to different outcome definitions. The results for select simulation scenarios are provided in the article. DISCUSSION: Bayesian adaptive designs offer the potential for maximizing the information learned from the data collected through clinical trials. The proposed design enables monitoring and utilizing multiple composite outcomes based on rare events to optimize the trial design operating characteristics.