To add or not to add a new treatment arm to a multiarm study: A decision-theoretic framework.

Multiarm clinical trials, which compare several experimental treatments against control, are frequently recommended due to their efficiency gain. In practise, all potential treatments may not be ready to be tested in a phase II/III trial at the same time. It has become appealing to allow new treatment arms to be added into on-going clinical trials using a "platform" trial approach. To the best of our knowledge, many aspects of when to add arms to an existing trial have not been explored in the literature. Most works on adding arm(s) assume that a new arm is opened whenever a new treatment becomes available. This strategy may prolong the overall duration of a study or cause reduction in marginal power for each hypothesis if the adaptation is not well accommodated. Within a two-stage trial setting, we propose a decision-theoretic framework to investigate when to add or not to add a new treatment arm based on the observed stage one treatment responses. To account for different prospect of multiarm studies, we define utility in two different ways; one for a trial that aims to maximise the number of rejected hypotheses; the other for a trial that would declare a success when at least one hypothesis is rejected from the study. Our framework shows that it is not always optimal to add a new treatment arm to an existing trial. We illustrate a case study by considering a completed trial on knee osteoarthritis

Fast automatic solution of the inverse resistivity problem

The paper presents a fast automatic approach to solve the inverse resisti vity problem, assisted by optimization, which is a non-linear model-fitting technique. The selected inverse problems are ill-posed and the inverse solution is defined by 'best fit' in the sense of least-squares. Formulations are presented in a systematic manner for Newton's method, least squares method and Marquardt's modification (ridge regression) method based on local linearization of non-linear problem. The convergence of least-squares method and Marquardt's method, to provide a robust solution, are first tested on a theoretical model and effectiveness of Marquardt's method is demonstrated, and then two-field apparent resistivity curves from Banda district, India are interpreted and discussed

Explaining Evidence Denial as Motivated Pragmatically Rational Epistemic Irrationality

This paper introduces a model for evidence denial that explains this behavior as a manifestation of rationality and it is based on the contention that social values (measurable as utilities) often underwrite these sorts of responses. Moreover, it is contended that the value associated with group membership in particular can override epistemic reason when the expected utility of a belief or belief system is great. However, it is also true that it appears to be the case that it is still possible for such unreasonable believers to reverse this sort of dogmatism and to change their beliefs in a way that is epistemically rational. The conjecture made here is that we should expect this to happen only when the expected utility of the beliefs in question dips below a threshold where the utility value of continued dogmatism and the associated group membership is no longer sufficient to motivate defusing the counter-evidence that tells against such epistemically irrational beliefs

Empirical Analysis of Factors Affecting Confirmation Bias Levels of Software Engineers

Confirmation bias is defined as the tendency of people to seek evidence that verifies a hypothesis rather than seeking evidence to falsify it. Due to the confirmation bias, defects may be introduced in a software product during requirements analysis, design, implementation and/or testing phases. For instance, testers may exhibit confirmatory behavior in the form of a tendency to make the code run rather than employing a strategic approach to make it fail. As a result, most of the defects that have been introduced in the earlier phases of software development may be overlooked leading to an increase in software defect density. In this paper, we quantify confirmation bias levels in terms of a single derived metric. However, the main focus of this paper is the analysis of factors affecting confirmation bias levels of software engineers. Identification of these factors can guide project managers to circumvent negative effects of confirmation bias, as well as providing guidance for the recruitment and effective allocation of software engineers. In this empirical study, we observed low confirmation bias levels among participants with logical reasoning and hypothesis testing skills

Rationality in context: An analogical perspective

At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality"

Healthy Campus Trial: A multiphase optimization strategy (MOST) fully factorial trial to optimize the smartphone cognitive behavioral therapy (CBT) app for mental health promotion among university students: Study protocol for a randomized controlled trial

This is the final version. Available from the publisher via the DOI in this record.After the publication of the primary findings, the de-identified and completely anonymized individual participant-level dataset will be posted on the UMIN-ICDR website (http://www.umin.ac.jp/icdr/index-j.html) so that it can be accessed by qualified researchers.Background: Youth in general and college life in particular are characterized by new educational, vocational, and interpersonal challenges, opportunities, and substantial stress. It is estimated that 30-50% of university students meet criteria for some mental disorder, especially depression, in any given year. The university has traditionally provided many channels to promote students' mental health, but until now only a minority have sought such help, possibly owing to lack of time and/or to stigma related to mental illness. Smartphone-delivered cognitive behavioral therapy (CBT) shows promise for its accessibility and effectiveness. However, its most effective components and for whom it is more (or less) effective are not known. Methods/design: Based on the multiphase optimization strategy framework, this study is a parallel-group, multicenter, open, fully factorial trial examining five smartphone-delivered CBT components (self-monitoring, cognitive restructuring, behavioral activation, assertion training, and problem solving) among university students with elevated distress, defined as scoring 5 or more on the Patient Health Questionnaire-9 (PHQ-9). The primary outcome is change in PHQ-9 scores from baseline to week 8. We will estimate specific efficacy of the five components and their interactions through the mixed-effects repeated-measures analysis and propose the most effective and efficacious combinations of components. Effect modification by selected baseline characteristics will be examined in exploratory analyses. Discussion: The highly efficient experimental design will allow identification of the most effective components and the most efficient combinations thereof among the five components of smartphone CBT for university students. Pragmatically, the findings will help make the most efficacious CBT package accessible to a large number of distressed university students at reduced cost; theoretically, they will shed light on the underlying mechanisms of CBT and help further advance CBT for depression

Prospective study evaluating the relative sensitivity of 18F-NaF PET/CT for detecting skeletal metastases from renal cell carcinoma in comparison to multidetector CT and 99mTc-MDP bone scintigraphy, using an adaptive trial design.

BACKGROUND: The detection of occult bone metastases is a key factor in determining the management of patients with renal cell carcinoma (RCC), especially when curative surgery is considered. This prospective study assessed the sensitivity of (18)F-labelled sodium fluoride in conjunction with positron emission tomography/computed tomography ((18)F-NaF PET/CT) for detecting RCC bone metastases, compared with conventional imaging by bone scintigraphy or CT. PATIENTS AND METHODS: An adaptive two-stage trial design was utilized, which was stopped after the first stage due to statistical efficacy. Ten patients with stage IV RCC and bone metastases were imaged with (18)F-NaF PET/CT and (99m)Tc-labelled methylene diphosphonate ((99m)Tc-MDP) bone scintigraphy including pelvic single photon emission computed tomography (SPECT). Images were reported independently by experienced radiologists and nuclear medicine physicians using a 5-point scoring system. RESULTS: Seventy-seven lesions were diagnosed as malignant: 100% were identified by (18)F-NaF PET/CT, 46% by CT and 29% by bone scintigraphy/SPECT. Standard-of-care imaging with CT and bone scintigraphy identified 65% of the metastases reported by (18)F-NaF PET/CT. On an individual patient basis, (18)F-NaF PET/CT detected more RCC metastases than (99m)Tc-MDP bone scintigraphy/SPECT or CT alone (P = 0.007). The metabolic volumes, mean and maximum standardized uptake values (SUV mean and SUV max) of the malignant lesions were significantly greater than those of the benign lesions (P < 0.001). CONCLUSIONS: (18)F-NaF PET/CT is significantly more sensitive at detecting RCC skeletal metastases than conventional bone scintigraphy or CT. The detection of occult bone metastases could greatly alter patient management, particularly in the context when standard-of-care imaging is negative for skeletal metastases.This work was supported by Cancer Research UK [grant number C19212/A16628]. The authors also received research support from the National Institute of Health Research Cambridge Biomedical Research Centre, Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and Manchester, and the Cambridge Experimental Cancer Medicine Centre. The research has also been partly funded by a generous donation from the family and friends of a patient.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/annonc/mdv28

Ensuring that COVID-19 research is inclusive: guidance from the NIHR INCLUDE project

Objective: To provide guidance to researchers, funders, regulators and study delivery teams to ensure that research on COVID-19 is inclusive, particularly of groups disproportionately affected by COVID-19 and who may have been historically under-served by research. Summary of key points: Groups who are disproportionately affected by COVID-19 include (but are not limited to) older people, people with multiple long-term conditions, people with disabilities, people from Black, Asian and Ethnic minority groups, people living with obesity, people who are socioeconomically deprived and people living in care homes. All these groups are under-served by clinical research, and there is an urgent need to rectify this if COVID-19 research is to deliver relevant evidence for these groups who are most in need. We provide a framework and checklists for addressing key issues when designing and delivering inclusive COVID-19 research, based on the National Institute for Health Research INnovations in CLinical trial design and delivery for the UnDEr-served project roadmap. Strong community engagement, codevelopment and prioritisation of research questions and interventions are essential. Under-served groups should be represented on funding panels and ethics committees, who should insist on the removal of barriers to participation. Exclusion criteria should be kept to a minimum; intervention delivery and outcome measurement should be simple, flexible and tailored to the needs of different groups, and local advice on the best way to reach and engage with under-served communities should be taken by study delivery teams. Data on characteristics that allow identification of under-served groups must be collected, analyses should include these data to enable subgroup comparisons and results should be shared with under-served groups at an early stage. Conclusion: Inclusive COVID-19 research is a necessity, not a luxury, if research is to benefit all the communities it seeks to serve. It requires close engagement with under-served groups and attention to aspects of study topic, design, delivery, analysis and dissemination across the research life cycle

Costs and staffing resource requirements for adaptive clinical trials: quantitative and qualitative results from the Costing Adaptive Trials project

Background Adaptive designs offer great promise in improving the efficiency and patient-benefit of clinical trials. An important barrier to further increased use is a lack of understanding about which additional resources are required to conduct a high-quality adaptive clinical trial, compared to a traditional fixed design. The Costing Adaptive Trials (CAT) project investigated which additional resources may be required to support adaptive trials. Methods We conducted a mock costing exercise amongst seven Clinical Trials Units (CTUs) in the UK. Five scenarios were developed, derived from funded clinical trials, where a non-adaptive version and an adaptive version were described. Each scenario represented a different type of adaptive design. CTU staff were asked to provide the costs and staff time they estimated would be needed to support the trial, categorised into specified areas (e.g. statistics, data management, trial management). This was calculated separately for the non-adaptive and adaptive version of the trial, allowing paired comparisons. Interviews with 10 CTU staff who had completed the costing exercise were conducted by qualitative researchers to explore reasons for similarities and differences. Results Estimated resources associated with conducting an adaptive trial were always (moderately) higher than for the non-adaptive equivalent. The median increase was between 2 and 4% for all scenarios, except for sample size re-estimation which was 26.5% (as the adaptive design could lead to a lengthened study period). The highest increase was for statistical staff, with lower increases for data management and trial management staff. The percentage increase in resources varied across different CTUs. The interviews identified possible explanations for differences, including (1) experience in adaptive trials, (2) the complexity of the non-adaptive and adaptive design, and (3) the extent of non-trial specific core infrastructure funding the CTU had. Conclusions This work sheds light on additional resources required to adequately support a high-quality adaptive trial. The percentage increase in costs for supporting an adaptive trial was generally modest and should not be a barrier to adaptive designs being cost-effective to use in practice. Informed by the results of this research, guidance for investigators and funders will be developed on appropriately resourcing adaptive trials