Applying Exercise Capacity and Physical Activity as Single vs Composite Endpoints for Trials of Cardiac Rehabilitation Interventions: Rationale, Use-case, and a Blueprint Method for Sample Size Calculation.

OBJECTIVE: To conceptualize a composite primary endpoint for parallel-group RCTs of exercise-based cardiac rehabilitation (CR) interventions and to explore its application and statistical efficiency. DESIGN: We conducted a statistical exploration of sample size requirements. We combined exercise capacity and physical activity for the composite endpoint (CE), both being directly related to reduced premature mortality in patients with cardiac diseases. Based on smallest detectable and minimal clinically important changes (change in exercise capacity of 15 W and change in physical activity of 10 min/day), the CE combines 2 dichotomous endpoints (achieved/not achieved). To examine statistical efficiency, we compared sample size requirements based on the CE to single endpoints using data from 2 completed CR trials. SETTING: Cardiac rehabilitation phase III. PARTICIPANTS: Patients in cardiac rehabilitation. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): Exercise capacity (Pmax assessed by incremental cycle ergometry) and physical activity (daily minutes of moderate to vigorous physical activity assessed by accelerometry). RESULTS: Expecting, for example, a 10% between-group difference and improvement in the clinical outcome, the CE would increase sample size by up to 21% or 61%, depending on the dataset. When expecting a 10% difference and designing an intervention with the aim of non-deterioration, the CE would allow to reduce the sample size by up to 55% or 70%. CONCLUSIONS: Trialists may consider the utility of the CE for future studies in exercise-based CR to reduce sample size requirements. However, perhaps surprisingly at first, the CE could also lead to an increased sample size needed, depending on the observed baseline proportions in the trial population and the aim of the intervention.

The need for robust critique of arts and health research: the treatment of the Gene Cohen et al. (2006) paper on singing, wellbeing and health in subsequent evidence reviews.

BACKGROUND: This paper considers weaknesses in a study by Cohen et al. (2006) on the impacts of community singing on health. These include high demand characteristics, lack of attention to attrition, flawed statistical analysis, and measurement. Nevertheless, the study is uncritically cited, in evidence reviews, with findings taken at face value. METHODS: Google Scholar, SCOPUS and BASE citation functions for Cohen et al. identified 32 evidence reviews in peer-reviewed journals. Eleven of these reviews, published between 2010 and 2023, focused on creative arts interventions. RESULTS: We demonstrate limitations in the Cohen et al. research which undermine the conclusions they reach regarding the health benefits of group singing. Subsequent evidence reviews take the findings at face value and offer little critical commentary. DISCUSSION: We consider what is needed to improve evidence reviews in the field of creative arts and health research. CONCLUSIONS: A more robust approach is needed in reviewing research evidence in the field of arts and health. The Cohen et al. paper is not suitable for inclusion in future evidence reviews.

A neutral comparison of statistical methods for analyzing longitudinally measured ordinal outcomes in rare diseases.

Ordinal data in a repeated measures design of a crossover study for rare diseases usually do not allow for the use of standard parametric methods, and hence, nonparametric methods should be considered instead. However, only limited simulation studies in settings with small sample sizes exist. Therefore, starting from an Epidermolysis Bullosa simplex trial with the above-mentioned design, a rank-based approach using the R package nparLD and different generalized pairwise comparisons (GPC) methods were compared impartially in a simulation study. The results revealed that there was not one single best method for this particular design, because a trade-off exists between achieving high power, accounting for period effects, and for missing data. Specifically, nparLD as well as the unmatched GPC approaches do not address crossover aspects, and the univariate GPC variants partly ignore the longitudinal information. The matched GPC approaches, on the other hand, take the crossover effect into account in the sense of incorporating the within-subject association. Overall, the prioritized unmatched GPC method achieved the highest power in the simulation scenarios, although this may be due to the specified prioritization. The rank-based approach yielded good power even at a sample size of N = 6 $N=6$ , whereas the matched GPC method could not control the type I error.

Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials.

BACKGROUND: Recommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians. RESULTS: It was found that there is no uniformly best method for the aforementioned types of outcome variables, but in particular situations, there are methods that perform better than others. Especially if maximizing power is the primary goal, the prioritized unmatched GPC method was able to achieve particularly good results, besides being appropriate for prioritizing clinically relevant time points. Model averaging led to favorable results in some scenarios especially within the binary outcome setting and, like the GEE-like semiparametric method, also allows for considering period and carry-over effects properly. Inference based on the nonparametric marginal model was able to achieve high power, especially in the ordinal outcome scenario, despite small sample sizes due to separate testing of treatment periods, and is suitable when longitudinal and interaction effects have to be considered. CONCLUSION: Overall, a balance has to be found between achieving high power, accounting for cross-over, period, or carry-over effects, and prioritizing clinically relevant time points.

How to analyze continuous and discrete repeated measures in small-sample cross-over trials?

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.

The need for robust critique of arts and health research: Dance-movement therapy, girls, and depression.

We examine a highly cited randomized controlled trial on dance-movement therapy with adolescent girls with mild depression and examine its treatment in 14 evidence reviews and meta-analyses of dance research. We demonstrate substantial limitations in the trial which seriously undermine the conclusions reached regarding the effectiveness of dance movement therapy in reducing depression. We also show that the dance research reviews vary substantially in their treatment of the study. Some reviews provide a positive assessment of the study and take its findings at face value without critical commentary. Others are critical of the study, identifying significant limitations, but showing marked differences in Cochrane Risk of Bias assessments. Drawing on recent criticisms of systematic reviewing and meta-analysis, we consider how reviews can be so variable and discuss what is needed to improve the quality of primary studies, systematic reviews, and meta-analyses in the field of creative arts and health.

Third dose of SARS-CoV-2 vaccination in hemato-oncological patients and health care workers: immune responses and adverse events - a retrospective cohort study.

BACKGROUND: Due to potentially immune-escaping virus variants and waning immunity, a third SARS-CoV-2 vaccination dose is increasingly recommended. However, data in patients with cancer are limited. PATIENTS AND METHODS: We measured anti-SARS-CoV-2 spike protein antibody levels after the third vaccination dose in 439 patients with cancer and 41 health care workers (HCW) at an academic centre in Austria and a rural community hospital in Italy. Adverse events were retrieved from questionnaires. RESULTS: Overall, 439 patients and 41 HCW were included. SARS-CoV-2 infections were observed in 62/439 (14.1%) patients before vaccination and in 5/439 (1.1%) patients after ≥1 dose. Longitudinal analysis revealed a decrease of antibody levels between 3 and 6 months after second vaccination in patients with solid tumours (p < 0.001) and haematological malignancies without anti-B cell therapies (p < 0.001). After the third dose, anti-S levels increased compared to the first/second dose. Patients receiving B cell-targeted agents had lower antibody levels than patients with haematological malignancies undergoing other treatments (p < 0.001) or patients with solid tumours (p < 0.001). Moreover, anti-S levels correlated with CD19+ (B cell) and CD56+ (NK cell) counts in peripheral blood. The most frequent adverse events after the third dose were local pain (75/160, 46.9%), fatigue (25/160, 15.6%) and fever/chills (16/160, 10.0%). Patients with cancer had lower anti-S levels than HCW (p = 0.015). CONCLUSIONS: This study in patients with cancer shows improved antibody levels after the third vaccination dose at an acceptable side-effect profile. Lower antibody levels than in controls underline the need for further follow-up studies and dedicated trials.

The Need for Robust Critique of Arts and Health Research: Young People, Art Therapy and Mental Health.

We describe work in progress to conduct a systematic review of research on effects of arts-based programs for mental health in young people. We are at the stage of searching for relevant studies through major databases and screening extant systematic reviews for additional research which meet our inclusion criteria. At this stage, however, concerns have arisen regarding both the quality of existing primary studies and of recently published systematic reviews in this area of arts and health. As a case in point, in this paper we focus on one research report on art therapy with adolescent girls and its inclusion in three systematic reviews. We demonstrate that the reviews fail to undertake a robust critique of the Bazargan and Pakdaman paper and that the paper and reviews are flawed. Drawing on recent criticisms of systematic reviewing, we consider the value of proceeding with our systematic review as initially planned.

Testing for equality of distributions using the concept of (niche) overlap.

In this paper, we propose a new non-parametric test for equality of distributions. The test is based on the recently introduced measure of (niche) overlap and its rank-based estimator. As the estimator makes only one basic assumption on the underlying distribution, namely continuity, the test is universal applicable in contrast to many tests that are restricted to only specific scenarios. By construction, the new test is capable of detecting differences in location and scale. It thus complements the large class of rank-based tests that are constructed based on the non-parametric relative effect. In simulations this new test procedure obtained higher power and lower type I error compared to two common tests in several settings. The new procedure shows overall good performance. Together with its simplicity, this test can be used broadly. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00362-021-01239-y.

Macroclimatic conditions as main drivers for symbiotic association patterns in lecideoid lichens along the Transantarctic Mountains, Ross Sea region, Antarctica.

Lecideoid lichens as dominant vegetation-forming organisms in the climatically harsh areas of the southern part of continental Antarctica show clear preferences in relation to environmental conditions (i.e. macroclimate). 306 lichen samples were included in the study, collected along the Ross Sea coast (78°S-85.5°S) at six climatically different sites. The species compositions as well as the associations of their two dominant symbiotic partners (myco- and photobiont) were set in context with environmental conditions along the latitudinal gradient. Diversity values were nonlinear with respect to latitude, with the highest alpha diversity in the milder areas of the McMurdo Dry Valleys (78°S) and the most southern areas (Durham Point, 85.5°S; Garden Spur, 84.5°S), and lowest in the especially arid and cold Darwin Area (~ 79.8°S). Furthermore, the specificity of mycobiont species towards their photobionts decreased under more severe climate conditions. The generalist lichen species Lecanora fuscobrunnea and Lecidea cancriformis were present in almost all habitats, but were dominant in climatically extreme areas. Carbonea vorticosa, Lecidella greenii and Rhizoplaca macleanii were confined to milder areas. In summary, the macroclimate is considered to be the main driver of species distribution, making certain species useful as bioindicators of climate conditions and, consequently, for assessing the consequences of climate change.

SARS-CoV-2 screening in cancer outpatients during the second wave of the COVID-19 pandemic : Conclusions for crisis response at a high-volume oncology center.

BACKGROUND: During the second wave of the coronavirus disease 2019 (COVID-19) pandemic Austria suffered one of the highest severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rates worldwide. We report performance parameters of a SARS-CoV­2 screening program established for cancer outpatients at our center. METHODS: Institutional policy recommended routine biweekly SARS-CoV­2 testing. Adherence to the testing recommendation during the second wave of the COVID-19 pandemic between 1 October and 30 November 2020 was analyzed. The SARS-CoV­2 infection rate during first wave period (21 March to 4 May 2020) was compared to the one during second wave. RESULTS: A total of 1577 cancer patients were seen at our outpatient clinic during the second wave. In 1079/1577 (68.4%) patients, at least 1 SARS-CoV2 test was performed. Overall 2833 tests were performed, 23/1577 (1.5%, 95% confidence interval, CI 1.0-2.2%) patients were tested positive for SARS-CoV­2, which indicates a significant increase compared to the first wave (4/1016; 0.4%, 95% CI 0.1-1.0%) with an odds ratio of 3.9 (95% CI 1.5-10.1; p < 0.005). Patients undergoing active anticancer treatment (172/960; 17.9% not tested) were more likely to have undergone a SARS-CoV­2 test than patients in follow-up or best supportive care (326/617; 52.8% not tested p < 0.001). Furthermore, patients with only 1 visit within 4 weeks were more likely to not have undergone a SARS-CoV­2 test (386/598; 64.5%) compared to patients with 2 or more visits (112/979; 11.4%; p < 0.001). The projected number of patients with undetected SARS-CoV­2 infection during the study period was 5. CONCLUSION: We identified clinical patient parameters influencing SARS-CoV­2 testing coverage in cancer outpatients. Our data can provide information on generation of standard operating procedures and resource allocation during subsequent infection waves.

Are High Frequency Oscillations in Scalp EEG Related to Age?

BACKGROUND: High-frequency oscillations (HFOs) have received much attention in recent years, particularly in the clinical context. In addition to their application as a marker for pathological changes in patients with epilepsy, HFOs have also been brought into context with several physiological mechanisms. Furthermore, recent studies reported a relation between an increase of HFO rate and age in invasive EEG recordings. The present study aimed to investigate whether this relation can be replicated in scalp-EEG. METHODS: We recorded high-density EEG from 11 epilepsy patients at rest as well as during motor performance. Manual detection of HFOs was performed by two independent raters following a standardized protocol. Patients were grouped by age into younger (<25 years) and older (>50 years) participants. RESULTS: No significant difference of HFO-rates was found between groups [U = 10.5, p = 0.429, r = 0.3]. CONCLUSIONS: Lack of replicability of the age effect of HFOs may be due to the local propagation patterns of age-related HFOs occurring in deep structures. However, limitations such as small sample size, decreased signal-to-noise ratio as compared to invasive recordings, as well as HFO-mimicking artifacts must be considered.

Automatic vs. Manual Detection of High Frequency Oscillations in Intracranial Recordings From the Human Temporal Lobe.

Background: High frequency oscillations (HFOs) have attracted great interest among neuroscientists and epileptologists in recent years. Not only has their occurrence been linked to epileptogenesis, but also to physiologic processes, such as memory consolidation. There are at least two big challenges for HFO research. First, detection, when performed manually, is time consuming and prone to rater biases, but when performed automatically, it is biased by artifacts mimicking HFOs. Second, distinguishing physiologic from pathologic HFOs in patients with epilepsy is problematic. Here we automatically and manually detected HFOs in intracranial EEGs (iEEG) of patients with epilepsy, recorded during a visual memory task in order to assess the feasibility of the different detection approaches to identify task-related ripples, supporting the physiologic nature of HFOs in the temporal lobe. Methods: Ten patients with unclear seizure origin and bilaterally implanted macroelectrodes took part in a visual memory consolidation task. In addition to iEEG, scalp EEG, electrooculography (EOG), and facial electromyography (EMG) were recorded. iEEG channels contralateral to the suspected epileptogenic zone were inspected visually for HFOs. Furthermore, HFOs were marked automatically using an RMS detector and a Stockwell classifier. We compared the two detection approaches and assessed a possible link between task performance and HFO occurrence during encoding and retrieval trials. Results: HFO occurrence rates were significantly lower when events were marked manually. The automatic detection algorithm was greatly biased by filter-artifacts. Surprisingly, EOG artifacts as seen on scalp electrodes appeared to be linked to many HFOs in the iEEG. Occurrence rates could not be associated to memory performance, and we were not able to detect strictly defined "clear" ripples. Conclusion: Filtered graphoelements in the EEG are known to mimic HFOs and thus constitute a problem. So far, in invasive EEG recordings mostly technical artifacts and filtered epileptiform discharges have been considered as sources for these "false" HFOs. The data at hand suggests that even ocular artifacts might bias automatic detection in invasive recordings. Strict guidelines and standards for HFO detection are necessary in order to identify artifact-derived HFOs, especially in conditions when cognitive tasks might produce a high amount of artifacts.

SARS-CoV-2 Testing in Patients With Cancer Treated at a Tertiary Care Hospital During the COVID-19 Pandemic.

PURPOSE: To analyze the prevalence of SARS-CoV-2 infection in patients with cancer in hospital care after implementation of institutional and governmental safety measurements. METHODS: Patients with cancer routinely tested for SARS-CoV-2 RNA by nasal swab and real-time polymerase chain reaction between March 21 and May 4, 2020, were included. The results of this cancer cohort were statistically compared with the SARS-CoV-2 prevalence in the Austrian population as determined by a representative nationwide random sample study (control cohort 1) and a cohort of patients without cancer presenting to our hospital (control cohort 2). RESULTS: A total of 1,688 SARS-CoV-2 tests in 1,016 consecutive patients with cancer were performed. A total of 270 of 1,016 (26.6%) of the patients were undergoing active anticancer treatment in a neoadjuvant/adjuvant and 560 of 1,016 (55.1%) in a palliative setting. A total of 53 of 1,016 (5.2%) patients self-reported symptoms potentially associated with COVID-19. In 4 of 1,016 (0.4%) patients, SARS-CoV-2 was detected. At the time of testing at our department, all four SARS-CoV-2-positive patients were asymptomatic, and two of them had recovered from symptomatic COVID-19. Viral clearance was achieved in three of the four patients 14-56 days after testing positive. The estimated odds ratio of SARS-CoV-2 prevalence between the cancer cohort and control cohort 1 was 1.013 (95% CI, 0.209 to 4.272; P = 1), and between control cohort 2 and the cancer cohort it was 18.333 (95% CI, 6.056 to 74.157). CONCLUSION: Our data indicate that continuation of active anticancer therapy and follow-up visits in a large tertiary care hospital are feasible and safe after implementation of strict population-wide and institutional safety measures during the current COVID-19 pandemic. Routine SARS-CoV-2 testing of patients with cancer seems advisable to detect asymptomatic virus carriers and avoid uncontrolled viral spread.

Prediction of Cognitive Decline in Temporal Lobe Epilepsy and Mild Cognitive Impairment by EEG, MRI, and Neuropsychology.

Cognitive decline is a severe concern of patients with mild cognitive impairment. Also, in patients with temporal lobe epilepsy, memory problems are a frequently encountered problem with potential progression. On the background of a unifying hypothesis for cognitive decline, we merged knowledge from dementia and epilepsy research in order to identify biomarkers with a high predictive value for cognitive decline across and beyond these groups that can be fed into intelligent systems. We prospectively assessed patients with temporal lobe epilepsy (N = 9), mild cognitive impairment (N = 19), and subjective cognitive complaints (N = 4) and healthy controls (N = 18). All had structural cerebral MRI, EEG at rest and during declarative verbal memory performance, and a neuropsychological assessment which was repeated after 18 months. Cognitive decline was defined as significant change on neuropsychological subscales. We extracted volumetric and shape features from MRI and brain network measures from EEG and fed these features alongside a baseline testing in neuropsychology into a machine learning framework with feature subset selection and 5-fold cross validation. Out of 50 patients, 27 had a decline over time in executive functions, 23 in visual-verbal memory, 23 in divided attention, and 7 patients had an increase in depression scores. The best sensitivity/specificity for decline was 72%/82% for executive functions based on a feature combination from MRI volumetry and EEG partial coherence during recall of memories; 95%/74% for visual-verbal memory by combination of MRI-wavelet features and neuropsychology; 84%/76% for divided attention by combination of MRI-wavelet features and neuropsychology; and 81%/90% for increase of depression by combination of EEG partial directed coherence factor at rest and neuropsychology. Combining information from EEG, MRI, and neuropsychology in order to predict neuropsychological changes in a heterogeneous population could create a more general model of cognitive performance decline.

Sample size calculation and blinded recalculation for analysis of covariance models with multiple random covariates.

When testing for superiority in a parallel-group setting with a continuous outcome, adjusting for covariates is usually recommended. For this purpose, the analysis of covariance is frequently used, and recently several exact and approximate sample size calculation procedures have been proposed. However, in case of multiple covariates, the planning might pose some practical challenges and pitfalls. Therefore, we propose a method, which allows for blinded re-estimation of the sample size during the course of the trial. Simulations confirm that the proposed method provides reliable results in many practically relevant situations, and applicability is illustrated by a real-life data example.

Multivariate permutation tests for two sample testing in presence of nondetects with application to microarray data.

Very often, data collected in medical research are characterized by censored observations and/or data with mass on the value zero. This happens for example when some measurements fall below the detection limits of the specific instrument used. This type of left censored observations is called "nondetects". Such a situation of an excessive number of zeros in a data set is also referred to as zero-inflated data. In the present work, we aim at comparing different multivariate permutation procedures in two-sample testing for data with nondetects. The effect of censoring is investigated with regard to the different values that may be attributed to nondetected values, both under the null hypothesis and under alternative. We motivate the problem using data from allergy research.

Sample sizes and statistical methods in interventional studies on individuals with spinal cord injury: A systematic review.

AIM: Prevalence and incidence of spinal cord injury (SCI) are low. However, sample sizes have not been systematically examined yet, although this might represent useful information for study planning and power considerations. Therefore, our objective was to determine the median sample size in clinical trials on SCI individuals. Moreover, within small-sample size studies, statistical methods and awareness of potential problems regarding small samples were examined. METHODS: We systematically reviewed all studies on human SCI individuals published between 2014 and 2015, where the effect of an intervention on one or more health-related outcomes was assessed by means of a hypothesis test. If at least one group had a size <20, the study was classified as a small sample size study. PubMed was searched for eligible studies; subsequently, data on sample sizes and statistical methods were extracted and summarized descriptively. RESULTS: Out of 8897 studies 207 were included. Median total sample size was 18 (range 4-582). Small sample sizes were found in 167/207 (81%) studies, resulting limitations and implications for statistical analyses were mentioned in 109/167 (65%) studies. CONCLUSIONS: Although most recent SCI trials have been conducted with small samples, the consequences on statistical analysis methods and the validity of the results are rarely acknowledged.