Determining sample size in a personalized randomized controlled (PRACTical) trial.

In clinical settings with no commonly accepted standard-of-care, multiple treatment regimens are potentially useful, but some treatments may not be appropriate for some patients. A personalized randomized controlled trial (PRACTical) design has been proposed for this setting. For a network of treatments, each patient is randomized only among treatments which are appropriate for them. The aim is to produce treatment rankings that can inform clinical decisions about treatment choices for individual patients. Here we propose methods for determining sample size in a PRACTical design, since standard power-based methods are not applicable. We derive a sample size by evaluating information gained from trials of varying sizes. For a binary outcome, we quantify how many adverse outcomes would be prevented by choosing the top-ranked treatment for each patient based on trial results rather than choosing a random treatment from the appropriate personalized randomization list. In simulations, we evaluate three performance measures: mean reduction in adverse outcomes using sample information, proportion of simulated patients for whom the top-ranked treatment performed as well or almost as well as the best appropriate treatment, and proportion of simulated trials in which the top-ranked treatment performed better than a randomly chosen treatment. We apply the methods to a trial evaluating eight different combination antibiotic regimens for neonatal sepsis (NeoSep1), in which a PRACTical design addresses varying patterns of antibiotic choice based on disease characteristics and resistance. Our proposed approach produces results that are more relevant to complex decision making by clinicians and policy makers.

The impact of heterogeneity on the analysis of platform trials with normally distributed outcomes.

BACKGROUND: A platform trial approach allows adding arms to on-going trials to speed up intervention discovery programs. A control arm remains open for recruitment in a platform trial while intervention arms may be added after the onset of the study and could be terminated early for efficacy and/or futility when early stopping is allowed. The topic of utilising non-concurrent control data in the analysis of platform trials has been explored and discussed extensively. A less familiar issue is the presence of heterogeneity, which may exist for example due to modification of enrolment criteria and recruitment strategy. METHOD: We conduct a simulation study to explore the impact of heterogeneity on the analysis of a two-stage platform trial design. We consider heterogeneity in treatment effects and heteroscedasticity in outcome data across stages for a normally distributed endpoint. We examine the performance of some hypothesis testing procedures and modelling strategies. The use of non-concurrent control data is also considered accordingly. Alongside standard regression analysis, we examine the performance of a novel method that was known as the pairwise trials analysis. It is similar to a network meta-analysis approach but adjusts for treatment comparisons instead of individual studies using fixed effects. RESULTS: Several testing strategies with concurrent control data seem to control the type I error rate at the required level when there is heteroscedasticity in outcome data across stages and/or a random cohort effect. The main parameter of treatment effects in some analysis models correspond to overall treatment effects weighted by stage wise sample sizes; while others correspond to the effect observed within a single stage. The characteristics of the estimates are not affected significantly by the presence of a random cohort effect and/ or heteroscedasticity. CONCLUSION: In view of heterogeneity in treatment effect across stages, the specification of null hypotheses in platform trials may need to be more subtle. We suggest employing testing procedure of adaptive design as opposed to testing the statistics from regression models; comparing the estimates from the pairwise trials analysis method and the regression model with interaction terms may indicate if heterogeneity is negligible.

Effects of dual-task resistance exercise on cognition, mood, depression, functional fitness, and activities of daily living in older adults with cognitive impairment: a single-blinded, randomized controlled trial.

BACKGROUND: Regular exercise is emphasized for the improvement of functional capacity and independence of older adults. This study aimed to compare the effects of a dual-task resistance exercise program and resistance exercise on cognition, mood, depression, physical function, and activities of daily living (ADL) in older adults with cognitive impairment. METHODS: A total of 44 older adults participated in the study. Participants were randomly allocated to an experimental group (n = 22) performing a dual-task resistance exercise program for cognitive function improvement and a control group (n = 22) performing a resistance exercise program. Both groups performed the exercise for 40 min per session, three times a week, for 6 weeks (18 sessions). Cognition, mood, depression, functional fitness, and ADL were quantified before and after the intervention using the Mini-Mental State Examination (MMSE), profile of mood states (POMS), geriatric depression scale (GDS), senior fitness test (SFT), and Korean version of ADL, respectively. RESULTS: There was a significant time and group interaction on the MMSE (p = 0.044). There were no significant time and group interactions in the POMS, GDS, SFT, or ADL. Cognitive function (p < 0.001), mood (p < 0.001), depression (p < 0.001), functional fitness (p < 0.001), and ADL (p < 0.001) significantly improved after dual-task resistance exercise, and cognitive function (p < 0.001), mood (p < 0.001), depression (p < 0.001), functional fitness (p < 0.001), and ADL (p < 0.001) significantly improved after resistance exercise. CONCLUSIONS: Dual-task resistance exercise is more effective than resistance exercise in improving cognitive function in older adults with cognitive impairment. Both dual-task resistance exercise and resistance exercise improves mood, depression, functional fitness, and ADL after the intervention. We propose using dual-task resistance exercises for cognitive and physical health management in the older adults with cognitive impairment. TRIAL REGISTRATION: This study was registered with the Clinical Research Information Service (WHO International Clinical Trials Registry Platform) (Registration ID, KCT0005389; Registration date, 09/09/2020).

Experimental Quantum Channel Discrimination Using Metastable States of a Trapped Ion.

We present experimental demonstrations of accurate and unambiguous single-shot discrimination between three quantum channels using a single trapped ^{40}Ca^{+} ion. The three channels cannot be distinguished unambiguously using repeated single channel queries, the natural classical analogue. We develop techniques for using the six-dimensional D_{5/2} state space for quantum information processing, and we implement protocols to discriminate quantum channel analogues of phase shift keying and amplitude shift keying data encodings used in classical radio communication. The demonstrations achieve discrimination accuracy exceeding 99% in each case, limited entirely by known experimental imperfections.

Response-adaptive randomization in clinical trials: from myths to practical considerations.

Response-Adaptive Randomization (RAR) is part of a wider class of data-dependent sampling algorithms, for which clinical trials are typically used as a motivating application. In that context, patient allocation to treatments is determined by randomization probabilities that change based on the accrued response data in order to achieve experimental goals. RAR has received abundant theoretical attention from the biostatistical literature since the 1930's and has been the subject of numerous debates. In the last decade, it has received renewed consideration from the applied and methodological communities, driven by well-known practical examples and its widespread use in machine learning. Papers on the subject present different views on its usefulness, and these are not easy to reconcile. This work aims to address this gap by providing a unified, broad and fresh review of methodological and practical issues to consider when debating the use of RAR in clinical trials.

The Personalised Randomized Controlled Trial: Evaluation of a new trial design.

In some clinical scenarios, for example, severe sepsis caused by extensively drug resistant bacteria, there is uncertainty between many common treatments, but a conventional multiarm randomized trial is not possible because individual participants may not be eligible to receive certain treatments. The Personalised Randomized Controlled Trial design allows each participant to be randomized between a "personalised randomization list" of treatments that are suitable for them. The primary aim is to produce treatment rankings that can guide choice of treatment, rather than focusing on the estimates of relative treatment effects. Here we use simulation to assess several novel analysis approaches for this innovative trial design. One of the approaches is like a network meta-analysis, where participants with the same personalised randomization list are like a trial, and both direct and indirect evidence are used. We evaluate this proposed analysis and compare it with analyses making less use of indirect evidence. We also propose new performance measures including the expected improvement in outcome if the trial's rankings are used to inform future treatment rather than random choice. We conclude that analysis of a personalized randomized controlled trial can be performed by pooling data from different types of participants and is robust to moderate subgroup-by-intervention interactions based on the parameters of our simulation. The proposed approach performs well with respect to estimation bias and coverage. It provides an overall treatment ranking list with reasonable precision, and is likely to improve outcome on average if used to determine intervention policies and guide individual clinical decisions.

How women differently felt guilt from men in Korea: Focusing on the influence of demographic factors and leisure motivation.

Although leisure provides numerous advantages, people sometimes feel guilty while engaging in leisure. The study objective was to explore the gender differences in the effects of socio-demographic factors and motivational factors on leisure guilt in Korea. Results showed that socio-demographic factors and leisure motivations influenced leisure guilt and the influence of these factors was different by gender. While age, number of children, and household income significantly influenced men's leisure guilt, only leisure expenditure did for women. When motivation was entered, only development and separation motivation were significant for men and adventure and relaxation motivation were significant for women.

Temporal Transitions in Fibrinolysis after Trauma: Adverse Outcome Is Principally Related to Late Hypofibrinolysis.

BACKGROUND: The relationship between late clinical outcomes after injury and early dynamic changes between fibrinolytic states is not fully understood. The authors hypothesized that temporal transitions in fibrinolysis states using rotational thromboelastometry (ROTEM) would aid stratification of adverse late clinical outcomes and improve understanding of how tranexamic acid modulates the fibrinolytic response and impacts mortality. METHODS: The authors conducted a secondary analysis of previously collected data from trauma patients enrolled into an ongoing prospective cohort study (International Standard Randomised Controlled Trial Number [ISRCTN] 12962642) at a major trauma center in the United Kingdom. ROTEM was performed on admission and at 24 h with patients retrospectively grouped into three fibrinolysis categories: tissue factor-activated ROTEM maximum lysis of less than 5% (low); tissue factor-activated ROTEM maximum lysis of 5 to 15% (normal); or tissue factor-activated ROTEM maximum lysis of more than 15% (high). Primary outcomes were multiorgan dysfunction syndrome and 28-day mortality. RESULTS: Seven-hundred thirty-one patients were included: 299 (41%) were treated with tranexamic acid and 432 (59%) were untreated. Two different cohorts with low-maximum lysis at 24 h were identified: (1) severe brain injury and (2) admission shock and hemorrhage. Multiple organ dysfunction syndrome was greatest in those with low-maximum lysis on admission and at 24 h, and late mortality was four times higher than in patients who remained normal during the first 24 h (7 of 42 [17%] vs. 9 of 223 [4%]; P = 0.029). Patients that transitioned to or remained in low-maximum lysis had increased odds of organ dysfunction (5.43 [95% CI, 1.43 to 20.61] and 4.85 [95% CI, 1.83 to 12.83], respectively). Tranexamic acid abolished ROTEM hyperfibrinolysis (high) on admission, increased the frequency of persistent low-maximum lysis (67 of 195 [34%]) vs. 8 of 79 [10%]; P = 0.002), and was associated with reduced early mortality (28 of 195 [14%] vs. 23 of 79 [29%]; P = 0.015). No increase in late deaths, regardless of fibrinolysis transition patterns, was observed. CONCLUSIONS: Adverse late outcomes are more closely related to 24-h maximum lysis, irrespective of admission levels. Tranexamic acid alters early fibrinolysis transition patterns, but late mortality in patients with low-maximum lysis at 24 h is not increased.

Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials.

Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size should be determined conditional on the accrued information. To this end, we first review and compare common approaches to estimating conditional power, which is often used in heuristic sample size recalculation rules. We then discuss the connection of heuristic sample size recalculation and optimal two-stage designs, demonstrating that the latter is the superior approach in a fully preplanned setting. Hence, unplanned design adaptations should only be conducted as reaction to trial-external new evidence, operational needs to violate the originally chosen design, or post hoc changes in the optimality criterion but not as a reaction to trial-internal data. We are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations where an initially planned optimal design is not invariant under the adaptation rule even if the planning assumptions do not change. Finally, we propose two alternative ways of reacting to newly emerging trial-external evidence in ways that are consistent with the originally planned design to avoid such inconsistencies.

Lifetime-Limited Interrogation of Two Independent

Laser decoherence limits the stability of optical clocks by broadening the observable resonance linewidths and adding noise during the dead time between clock probes. Correlation spectroscopy avoids these limitations by measuring correlated atomic transitions between two ensembles, which provides a frequency difference measurement independent of laser noise. Here, we apply this technique to perform stability measurements between two independent clocks based on the ^{1}S_{0}↔^{3}P_{0} transition in ^{27}Al^{+}. By stabilizing the dominant sources of differential phase noise between the two clocks, we observe coherence between them during synchronous Ramsey interrogations as long as 8 s at a frequency of 1.12×10^{15} Hz. The observed contrast in the correlation spectroscopy signal is consistent with the 20.6 s ^{3}P_{0} state lifetime and represents a measurement instability of (1.8±0.5)×10^{-16}/sqrt[τ/s] for averaging periods longer than the probe duration when dead time is negligible.

Including non-concurrent control patients in the analysis of platform trials: is it worth it?

BACKGROUND: Platform trials allow adding new experimental treatments to an on-going trial. This feature is attractive to practitioners due to improved efficiency. Nevertheless, the operating characteristics of a trial that adds arms have not been well-studied. One controversy is whether just the concurrent control data (i.e. of patients who are recruited after a new arm is added) should be used in the analysis of the newly added treatment(s), or all control data (i.e. non-concurrent and concurrent). METHODS: We investigate the benefits and drawbacks of using non-concurrent control data within a two-stage setting. We perform simulation studies to explore the impact of a linear and a step trend on the inference of the trial. We compare several analysis approaches when one includes all the control data or only concurrent control data in the analysis of the newly added treatment. RESULTS: When there is a positive trend and all the control data are used, the marginal power of rejecting the corresponding hypothesis and the type one error rate can be higher than the nominal value. A model-based approach adjusting for a stage effect is equivalent to using concurrent control data; an adjustment with a linear term may not guarantee valid inference when there is a non-linear trend. CONCLUSIONS: If strict error rate control is required then non-concurrent control data should not be used; otherwise it may be beneficial if the trend is sufficiently small. On the other hand, the root mean squared error of the estimated treatment effect can be improved through using non-concurrent control data.

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.

D-optimal designs for multiarm trials with dropouts.

Multiarm trials with follow-up on participants are commonly implemented to assess treatment effects on a population over the course of the studies. Dropout is an unavoidable issue especially when the duration of the multiarm study is long. Its impact is often ignored at the design stage, which may lead to less accurate statistical conclusions. We develop an optimal design framework for trials with repeated measurements, which takes potential dropouts into account, and we provide designs for linear mixed models where the presence of dropouts is noninformative and dependent on design variables. Our framework is illustrated through redesigning a clinical trial on Alzheimer's disease, whereby the benefits of our designs compared with standard designs are demonstrated through simulations.

Design of experiments for a confirmatory trial of precision medicine.

Precision medicine, aka stratified/personalized medicine, is becoming more pronounced in the medical field due to advancement in computational ability to learn about patient genomic backgrounds. A biomaker, i.e. a type of biological process indicator, is often used in precision medicine to classify patient population into several subgroups. The aim of precision medicine is to tailor treatment regimes for different patient subgroups who suffer from the same disease. A multi-arm design could be conducted to explore the effect of treatment regimes on different biomarker subgroups. However, if treatments work only on certain subgroups, which is often the case, enrolling all patient subgroups in a confirmatory trial would increase the burden of a study. Having observed a phase II trial, we propose a design framework for finding an optimal design that could be implemented in a phase III study or a confirmatory trial. We consider two elements in our approach: Bayesian data analysis of observed data, and design of experiments. The first tool selects subgroups and treatments to be enrolled in the future trial whereas the second tool provides an optimal treatment randomization scheme for each selected/enrolled subgroups. Considering two independent treatments and two independent biomarkers, we illustrate our approach using simulation studies. We demonstrate efficiency gain, i.e. high probability of recommending truly effective treatments in the right subgroup, of the optimal design found by our framework over a randomized controlled trial and a biomarker-treatment linked trial.

Exploring issues and strengths of cross-cultural marriage among Korean immigrants.

Cross-cultural marriages have continuously increased in the United States. In spite of this increase, further research is needed to address the paucity of literature on cross-cultural marriage, particularly, between immigrants and their indigenous spouses. In this study, we have focused on the cross-cultural marriages between female Korean immigrants who have married Americans, aiming to identify the positive and/or negative aspects of cross-cultural marriage from the Korean women themselves. For this purpose, semi-structured interviews were conducted on a total of 14 participants. Their ages ranged from 45 to 66 years (M D 52.5 years) and the average length of time since their immigration was 25 years. Each interview lasted between 45 and 120 min and, with participants' permission, were recorded and transcribed. Based on the participants' life experiences and personal statements, we divided our findings into two sections: (a) issues and problems of cross-cultural marriages, and (b) strengths of cross-cultural marriages. With regard to the issues and problems of cross-cultural marriages experienced by participants, three major themes were identified: (a) communication barriers, (b) cultural conflicts and misunderstandings, and (c) unclear cultural identities. The strengths of cross-cultural marriages were identified as: (a) development of coping strategies, and (b) improving cultural understanding. It appears that participants developed their own coping strategies and improved their cultural understanding in order to deal with the various stressors associated with cross-cultural marriage.

The Role of Leisure Engagement for Health Benefits Among Korean Older Women.

This qualitative study was designed to examine the benefits of leisure to older Korean women. Using a constructive grounded theory methodology, in this study we identified three categories of benefits from leisure activities: (a) developing social connections, (b) enhancing psychological well-being, and (c) improving physical health. The findings of this study demonstrate that involvement in leisure activities offers substantial physical, psychological, and social benefits for older Korean women. The results also suggest that these benefits can provide an opportunity for older Korean adults to improve their health and well-being, which, in turn, may help promote successful aging.

Exploratory examination of the relationship between acculturation and personal growth among Korean immigrants.

Korean immigrants are motivated to accept new cultural perspectives and/or transform their own cultural values into those of their new country. During this acculturation process, they encounter cultural differences, make adaptations, and thus may experience positive changes in social relationships, coping resources, personal strength, and cultural knowledge. The purpose of this study was to investigate the relationship between the dimensions of acculturation and personal growth. The results indicated that two dimensions of acculturation (e.g., self-control and collectivism), age, and length of stay were predictors of personal growth that involves social relationships, personal resources, life philosophy, and coping skills. This study suggests that high scores on two acculturation dimensions indicated lower acculturation, which predicts personal growth.

Clinical trials with mechanism evaluation of intervention(s): mind the power and sample size calculation.

BACKGROUND: Mediation analysis, often completed as secondary analysis to estimating the main treatment effect, investigates situations where an exposure may affect an outcome both directly and indirectly through intervening mediator variables. Although there has been much research on power in mediation analyses, most of this has focused on the power to detect indirect effects. Little consideration has been given to the extent to which the strength of the mediation pathways, i.e., the intervention-mediator path and the mediator-outcome path respectively, may affect the power to detect the total effect, which would correspond to the intention-to-treat effect in a randomized trial. METHODS: We conduct a simulation study to evaluate the relation between the mediation pathways and the power of testing the total treatment effect, i.e., the intention-to-treat effect. Consider a sample size that is computed based on the usual formula for testing the total effect in a two-arm trial. We generate data for a continuous mediator and a normal outcome using the conventional mediation models. We estimate the total effect using simple linear regression and evaluate the power of a two-sided test. We explore multiple data generating scenarios by varying the magnitude of the mediation paths whilst keeping the total effect constant. RESULTS: Simulations show the estimated total effect is unbiased across the considered scenarios as expected, but the mean of its standard error increases with the magnitude of the mediator-outcome path and the variability in the residual error of the mediator, respectively. Consequently, this affects the power of testing the total effect, which is always lower than planned when the mediator-outcome path is non-trivial and a naive sample size was employed. Analytical explanation confirms that the intervention-mediator path does not affect the power of testing the total effect but the mediator-outcome path. The usual effect size consideration can be adjusted to account for the magnitude of the mediator-outcome path and its residual error. CONCLUSIONS: The sample size calculation for studies with efficacy and mechanism evaluation should account for the mediator-outcome association or risk the power to detect the total effect/intention-to-treat effect being lower than planned.

Perceived racial/ethnic discrimination and antisocial behaviors among Asian American college students: testing the moderating roles of ethnic and American identity.

The present study tested the moderating roles of ethnic identity and American identity on the association between perceived racial/ethnic discrimination and antisocial behaviors among Asian American college students. Using data from the Multi-Site University Study of Identity and Culture (MUSIC) collaborative, the sample included 1,362 East Asian and South Asian American college students. Perceived discrimination was significantly associated with antisocial behaviors for both East Asians and South Asians. Ethnic identity was not a significant moderator of the discrimination-antisocial behavior link, but American identity exacerbated the association between perceived discrimination and antisocial behaviors for both East Asians and South Asians. Interestingly, the explanatory power of the regression model was greater for South Asians than for East Asians in predicting antisocial behaviors. The importance of attending to American identity as a potential source of risk for Asian American college students exposed to racial/ethnic discrimination is discussed.

Physical Activity and Health of Koreans with Spinal Cord Injury during COVID-19.

Objectives: The primary purpose of this study was to explore the mediating roles of resilience and physical activity (PA) levels on the subjective health of people with spinal cord injury(SCI) during the COVID-19 pandemic.Methods: A total of 201 Koreans with SCI completed a survey between February and April 2021. The questionnaire measured participants' PA levels before and during the COVID-19 pandemic, resilience, and subjective health assessment. The data were analyzed using SPSS, and PROCESS macro (Model 6) was used to determine the dual mediation effects. Results: PA levels before COVID-19 positively affected resilience and PA levels during COVID-19, and resilience positively affected PA levels during COVID-19 and subjective health. PA levels during COVID-19 had a positive influence on subjective health. Moreover, resilience and PA levels during COVID-19 were independent mediators of the relationship between PA levels before COVID-19 and subjective health. PA levels before COVID-19 indirectly affected subjective health through a dual-mediated pathway of resilience and PA levels during COVID-19. Conclusion: We suggest that it is necessary to promote regular PA for people with physical disabilities to enhance resilience, and thus, maintain a healthy life even during a public health crisis.