A new conditional performance score for the evaluation of adaptive group sequential designs with sample size recalculation

In standard clinical trial designs, the required sample size is fixed in the planning stage based on initial parameter assumptions. It is intuitive that the correct choice of the sample size is of major importance for an ethical justification of the trial. The required parameter assumptions should be based on previously published results from the literature. In clinical practice, however, historical data often do not exist or show highly variable results. Adaptive group sequential designs allow a sample size recalculation after a planned unblinded interim analysis in order to adjust the sample size during the ongoing trial. So far, there exist no unique standards to assess the performance of sample size recalculation rules. Single performance criteria commonly reported are given by the power and the average sample size; the variability of the recalculated sample size and the conditional power distribution are usually ignored. Therefore, the need for an adequate performance score combining these relevant performance criteria is evident. To judge the performance of an adaptive design, there exist two possible perspectives, which might also be combined: Either the global performance of the design can be addressed, which averages over all possible interim results, or the conditional performance is addressed, which focuses on the remaining performance conditional on a specific interim result. In this work, we give a compact overview of sample size recalculation rules and performance measures. Moreover, we propose a new conditional performance score and apply it to various standard recalculation rules by means of Monte-Carlo simulations

The adoptr Package: Adaptive Optimal Designs for Clinical Trials in R

Even though adaptive two-stage designs with unblinded interim analyses are becoming increasingly popular in clinical trial designs, there is a lack of statistical software to make their application more straightforward. The package adoptr fills this gap for the common case of two-stage one- or two-arm trials with (approximately) normally distributed outcomes. In contrast to previous approaches, adoptr optimizes the entire design upfront which allows maximal efficiency. To facilitate experimentation with different objective functions, adoptr supports a flexible way of specifying both (composite) objective scores and (conditional) constraints by the user. Special emphasis was put on providing measures to aid practitioners with the validation process of the package

Improving sample size recalculation in adaptive clinical trials by resampling

Sample size calculations in clinical trials need to be based on profound parameter assumptions. Wrong parameter choices may lead to too small or too high sample sizes and can have severe ethical and economical consequences. Adaptive group sequential study designs are one solution to deal with planning uncertainties. Here, the sample size can be updated during an ongoing trial based on the observed interim effect. However, the observed interim effect is a random variable and thus does not necessarily correspond to the true effect. One way of dealing with the uncertainty related to this random variable is to include resampling elements in the recalculation strategy. In this paper, we focus on clinical trials with a normally distributed endpoint. We consider resampling of the observed interim test statistic and apply this principle to several established sample size recalculation approaches. The resulting recalculation rules are smoother than the original ones and thus the variability in sample size is lower. In particular, we found that some resampling approaches mimic a group sequential design. In general, incorporating resampling of the interim test statistic in existing sample size recalculation rules results in a substantial performance improvement with respect to a recently published conditional performance score

Adverse drug reactions associated with amitriptyline - protocol for a systematic multiple-indication review and meta-analysis

Background: Unwanted anticholinergic effects are both underestimated and frequently overlooked. Failure to identify adverse drug reactions (ADRs) can lead to prescribing cascades and the unnecessary use of over-thecounter products. The objective of this systematic review and meta-analysis is to explore and quantify the frequency and severity of ADRs associated with amitriptyline vs. placebo in randomized controlled trials (RCTs) involving adults with any indication, as well as healthy individuals. Methods: A systematic search in six electronic databases, forward/backward searches, manual searches, and searches for Food and Drug Administration (FDA) and European Medicines Agency (EMA) approval studies, will be performed. Placebo-controlled RCTs evaluating amitriptyline in any dosage, regardless of indication and without restrictions on the time and language of publication, will be included, as will healthy individuals. Studies of topical amitriptyline, combination therapies, or including <100 participants, will be excluded. Two investigators will screen the studies independently, assess methodological quality, and extract data on design, population, intervention, and outcomes ((non-)anticholinergic ADRs, e.g., symptoms, test results, and adverse drug events (ADEs) such as falls). The primary outcome will be the frequency of anticholinergic ADRs as a binary outcome (absolute number of patients with/without anticholinergic ADRs) in amitriptyline vs. placebo groups. Anticholinergic ADRs will be defined by an experienced clinical pharmacologist, based on literature and data from Martindale: The Complete Drug Reference. Secondary outcomes will be frequency and severity of (non-)anticholinergic ADRs and ADEs. The information will be synthesized in meta-analyses and narratives. We intend to assess heterogeneity using metaregression (for indication, outcome, and time points) and I2 statistics. Binary outcomes will be expressed as odds ratios, and continuous outcomes as standardized mean differences. Effect measures will be provided using 95% confidence intervals. We plan sensitivity analyses to assess methodological quality, outcome reporting etc., and subgroup analyses on age, dosage, and duration of treatment. Discussion: We will quantify the frequency of anticholinergic and other ADRs/ADEs in adults taking amitriptyline for any indication by comparing rates for amitriptyline vs. placebo, hence, preventing bias from disease symptoms and nocebo effects. As no standardized instrument exists to measure it, our overall estimate of anticholinergic ADRs may have limitations

Pursuing More Aggressive Timelines in the Surgical Treatment of Traumatic Spinal Cord Injury (TSCI): A Retrospective Cohort Study with Subgroup Analysis

Background: The optimal timing of surgical therapy for traumatic spinal cord injury (TSCI) remains unclear. The purpose of this study is to evaluate the impact of “ultra-early” (<4 h) versus “early” (4–24 h) time from injury to surgery in terms of the likelihood of neurologic recovery. Methods: The effect of surgery on neurological recovery was investigated by comparing the assessed initial and final values of the American Spinal Injury Association (ASIA) Impairment Scale (AIS). A post hoc analysis was performed to gain insight into different subgroup regeneration behaviors concerning neurological injury levels. Results: Datasets from 69 cases with traumatic spinal cord injury were analyzed. Overall, 19/46 (41.3%) patients of the “ultra-early” cohort saw neurological recovery compared to 5/23 (21.7%) patients from the “early” cohort (p = 0.112). The subgroup analysis revealed differences based on the neurological level of injury (NLI) of a patient. An optimal cutpoint for patients with a cervical lesion was estimated at 234 min. Regarding the prediction of neurological improvement, sensitivity was 90.9% with a specificity of 68.4%, resulting in an AUC (area under the curve) of 84.2%. In thoracically and lumbar injured cases, the estimate was lower, ranging from 284 (thoracic) to 245 min (lumbar) with an AUC of 51.6% and 54.3%. Conclusions: Treatment within 24 h after TSCI is associated with neurological recovery. Our hypothesis that intervention within 4 h is related to an improvement in the neurological outcome was not confirmed in our collective. In a clinical context, this suggests that after TSCI there is a time frame to get the right patient to the right hospital according to advanced trauma life support (ATLS) guidelines

Optimal planning of adaptive two-stage designs.

Funder: RUPRECHT KARLS UNIVERSITAET HEIDELBERG ‐ Projekt DEALAdaptive designs are playing an increasingly important role in the planning of clinical trials. While there exists various research on the optimal determination of a two-stage design, non-optimal versions still are frequently applied in clinical research. In this article, we strive to motivate the application of optimal adaptive designs and give guidance on how to determine them. It is demonstrated that optimizing a trial design with respect to particular objective criteria can have a substantial benefit over the application of conventional adaptive sample size recalculation rules. Furthermore, we show that in many practical situations, optimal group-sequential designs show an almost negligible performance loss compared to optimal adaptive designs. Finally, we illustrate how optimal designs can be tailored to specific operational requirements by customizing the underlying optimization problem

Selenium Deficiency Is Associated with Mortality Risk from COVID-19

SARS-CoV-2 infections underlie the current coronavirus disease (COVID-19) pandemic and are causative for a high death toll particularly among elderly subjects and those with comorbidities. Selenium (Se) is an essential trace element of high importance for human health and particularly for a well-balanced immune response. The mortality risk from a severe disease like sepsis or polytrauma is inversely related to Se status. We hypothesized that this relation also applies to COVID-19. Serum samples (n = 166) from COVID-19 patients (n = 33) were collected consecutively and analyzed for total Se by X-ray fluorescence and selenoprotein P (SELENOP) by a validated ELISA. Both biomarkers showed the expected strong correlation (r = 0.7758, p < 0.001), pointing to an insufficient Se availability for optimal selenoprotein expression. In comparison with reference data from a European cross-sectional analysis (EPIC, n = 1915), the patients showed a pronounced deficit in total serum Se (mean ± SD, 50.8 ± 15.7 vs. 84.4 ± 23.4 µg/L) and SELENOP (3.0 ± 1.4 vs. 4.3 ± 1.0 mg/L) concentrations. A Se status below the 2.5th percentile of the reference population, i.e., [Se] < 45.7 µg/L and [SELENOP] < 2.56 mg/L, was present in 43.4% and 39.2% of COVID samples, respectively. The Se status was significantly higher in samples from surviving COVID patients as compared with non-survivors (Se; 53.3 ± 16.2 vs. 40.8 ± 8.1 µg/L, SELENOP; 3.3 ± 1.3 vs. 2.1 ± 0.9 mg/L), recovering with time in survivors while remaining low or even declining in non-survivors. We conclude that Se status analysis in COVID patients provides diagnostic information. However, causality remains unknown due to the observational nature of this study. Nevertheless, the findings strengthen the notion of a relevant role of Se for COVID convalescence and support the discussion on adjuvant Se supplementation in severely diseased and Se-deficient patients