scholarly journals Conditional power, predictive power and probability of success in clinical trials with continuous, binary and time-to-event endpoints

2021 ◽  
Author(s):  
Madan Gopal Kundu ◽  
Sandipan Samanta ◽  
Shoubhik Mondal
Keyword(s):  
Predictive Power ◽  
Clinical Investigation ◽  
Clinical Success ◽  
General Setting ◽  
Conditional Power ◽  
Time To Event ◽  
Shiny App ◽  
Probability Of Success ◽  
R Shiny ◽  
Distributed Test

Abstract Assessment of study success using conditional power (CP), the predictive power of success (PPoS) and probability of success (PoS) is becoming increasingly common for resource optimization and adaption of trials in clinical investigation. Determination of these measures is often a non-trivial mathematical task. Further, the terminologies used across the literature are not consistent, and there is no consolidated presentation on this. Lastly, certain types of trials received more attention where others (e.g., single-arm trial with time-to-event endpoints) were completely ignored. We attempted to fill these gaps. This paper first provides a detailed derivation of CP, PPoS and PoS in a general setting with normally distributed test statistics and normal prior. Subsequently, expressions for these measures are obtained for continuous, binary, and time-to-event endpoints in single-arm and two-arm trial settings. We have discussed both clinical success and trial success. Importantly, we have derived the expressions for CP, PPoS and PoS in a single-arm trial with a time-to-event endpoint that was never addressed in the literature to our knowledge. In that discussion, we have also shown that commonly recommended 1/d consistently under-estimates the variance of log(median) and alternative expression for variance was derived. We have also presented the PPoS calculation for the binomial endpoint with a beta prior. Examples are given along with the comparison of CP and PPoS. Expressions presented in this paper are implemented in LongCART package in R. An R shiny app is also available at https://ppos.herokuapp.com/ .

Unified exact design with early stopping rules for single arm clinical trials with multiple endpoints

2021 ◽  
pp. 096228022110130
Author(s):  
Wei Wei ◽  
Denise Esserman ◽  
Michael Kane ◽  
Daniel Zelterman
Keyword(s):  
Clinical Trials ◽  
Early Phase ◽  
Decision Rules ◽  
Stopping Rules ◽  
Multiple Endpoints ◽  
Shiny App ◽  
R Shiny ◽  
Early Phase Clinical Trials ◽  
User Friendly ◽  
Exact Design

Adaptive designs are gaining popularity in early phase clinical trials because they enable investigators to change the course of a study in response to accumulating data. We propose a novel design to simultaneously monitor several endpoints. These include efficacy, futility, toxicity and other outcomes in early phase, single-arm studies. We construct a recursive relationship to compute the exact probabilities of stopping for any combination of endpoints without the need for simulation, given pre-specified decision rules. The proposed design is flexible in the number and timing of interim analyses. A R Shiny app with user-friendly web interface has been created to facilitate the implementation of the proposed design.

Initial Clinical Experience Using the Low-Profile Altura Endograft System With Double D-Shaped Proximal Stents for Endovascular Aneurysm Repair

2018 ◽  
Vol 25 (3) ◽  
pp. 379-386 ◽  
Author(s):  
Dainis Krievins ◽  
Albrecht Krämer ◽  
Janis Savlovskis ◽  
Georgij Oszkinis ◽  
E. Sebastian Debus ◽  
...  
Keyword(s):  
Clinical Investigation ◽  
Clinical Success ◽  
Endovascular Aneurysm Repair ◽  
Clinical Results ◽  
Type I ◽  
Midterm Outcome ◽  
Early Results ◽  
Low Profile ◽  
Type I Endoleak ◽  
Aneurysm Repair

Purpose: To report the initial clinical results of endovascular aneurysm repair (EVAR) using the low-profile (14-F) Altura Endograft System, which features a double “D-shaped” stent design with suprarenal fixation and modular iliac components that are deployed from distal to proximal. Methods: From 2011 to 2015, 90 patients (mean age 72.8±8.3 years; 79 men) with abdominal aortic aneurysm (AAA; mean diameter 53.8±5.7 mm) were treated at 10 clinical sites in 2 prospective, controlled clinical studies using the Altura endograft. Outcomes evaluated included mortality, major adverse events (MAEs: all-cause death, stroke, paraplegia, myocardial infarction, respiratory failure, bowel ischemia, and blood loss ≥1000 mL), and clinical success (freedom from procedure-related death, type I/III endoleak, migration, thrombosis, and reintervention). Results: Endografts were successfully implanted in 89 (99%) patients; the single failure was due to delivery system malfunction before insertion in the early-generation device. One (1%) patient died and 4 patients underwent reinterventions (1 type I endoleak, 2 iliac limb stenoses, and 1 endograft occlusion) within the first 30 days. During a median follow-up of 12.5 months (range 11.5–50.9), there were no aneurysm ruptures, surgical conversions, or AAA-related deaths. The cumulative MAE rates were 3% (3/89) at 6 months and 7% (6/89) at 1 year. Two patients underwent coil embolization of type II endoleaks at 6.5 months and 2.2 years, respectively. Clinical success was 94% (84/89) at 30 days, 98% (85/87) at 6 months, and 99% (82/83) at 1 year. Conclusion: Early results suggest that properly selected AAA patients can be safely treated using the Altura Endograft System with favorable midterm outcome. Thus, further clinical investigation is warranted to evaluate the role of this device in the treatment of AAA.

A Conditional Power Approach to the Evaluation of Predictive Power

2009 ◽  
Vol 1 (2) ◽  
pp. 131-136 ◽  
Author(s):  
K.K. Gordon Lan ◽  
Peter Hu ◽  
Michael A. Proschan
Keyword(s):  
Predictive Power ◽  
Conditional Power

scholarly journals Transcriptional Differences for COVID-19 Disease Map Genes between Males and Females Indicate a Different Basal Immunophenotype Relevant to the Disease

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1447
Author(s):  
Tianyuan Liu ◽  
Leandro Balzano-Nogueira ◽  
Ana Lleo ◽  
Ana Conesa
Keyword(s):  
Gene Expression ◽  
Disease Incidence ◽  
Tissue Expression ◽  
Matrix Metalloproteases ◽  
Sex And Gender ◽  
Demographic Groups ◽  
Shiny App ◽  
R Shiny ◽  
And Gender ◽  
High Level

Worldwide COVID-19 epidemiology data indicate differences in disease incidence amongst sex and gender demographic groups. Specifically, male patients are at a higher death risk than female patients, and the older population is significantly more affected than young individuals. Whether this difference is a consequence of a pre-existing differential response to the virus, has not been studied in detail. We created DeCovid, an R shiny app that combines gene expression (GE) data of different human tissue from the Genotype-Tissue Expression (GTEx) project along with the COVID-19 Disease Map and COVID-19 related pathways gene collections to explore basal GE differences across healthy demographic groups. We used this app to study differential gene expression of COVID-19 associated genes in different age and sex groups. We identified that healthy women show higher expression-levels of interferon genes. Conversely, healthy men exhibit higher levels of proinflammatory cytokines. Additionally, young people present a stronger complement system and maintain a high level of matrix metalloproteases than older adults. Our data suggest the existence of different basal immunophenotypes amongst different demographic groups, which are relevant to COVID-19 progression and may contribute to explaining sex and age biases in disease severity. The DeCovid app is an effective and easy to use tool for exploring the GE levels relevant to COVID-19 across demographic groups and tissues.

Comparison of extraction methods for intracellular metabolomics

2021 ◽  
Author(s):  
Carolin Andresen ◽  
Tobias Boch ◽  
Hagen M. Gegner ◽  
Nils Mechtel ◽  
Andreas Narr ◽  
...  
Keyword(s):  
Limit Of Detection ◽  
Extraction Methods ◽  
Biological Information ◽  
Global Estimate ◽  
Regulatory Processes ◽  
Online Resource ◽  
Human Sample ◽  
Shiny App ◽  
R Shiny ◽  
Comprehensive Study

Measurements of metabolic compounds inside cells or tissues are of high informative potential since they represent the endpoint of biological information flow and a snapshot of the integration of many regulatory processes. However, it requires careful extraction to quantify their abundance. Here we present a comprehensive study using ten extraction protocols on four human sample types (liver tissue, bone marrow, HL60 and HEK cells) targeting 630 metabolites of different chemical classes. We show that the extraction efficiency and stability is highly variable across protocols and tissues by using different quality metrics including the limit of detection and variability between replicates as well as the sum of concentration as a global estimate of extraction stability. The profile of extracted metabolites depends on the used solvents - an observation which has implications for measurements of different sample types and metabolic compounds of interest. To identify the optimal extraction method for future metabolomics studies, the benchmark dataset was implemented in an easy-to-use, interactive and flexible online resource (R/shiny app MetaboExtract).

Recent applications of QCM-D for the design, synthesis, and characterization of bioactive materials

2021 ◽  
pp. 088391152110142
Author(s):  
Robert J Mosley ◽  
Matthew V Talarico ◽  
Mark E Byrne
Keyword(s):  
Clinical Investigation ◽  
Clinical Success ◽  
Biological Response ◽  
Analytical Techniques ◽  
Soft Materials ◽  
Acoustic Resonator ◽  
Label Free ◽  
Bioactive Materials ◽  
Novel Technologies

The clinical translation of bioactive technologies is lacking compared to the number of novel technologies reported in the literature. This is in part due to the difficulties in characterizing bioactive materials to understand and predict their biological response. To progress the field and increase clinical success, more robust analytical techniques must be utilized when investigating novel bioactive materials. The quartz crystal microbalance with dissipation (QCM-D), a label-free sensing instrument based on an acoustic resonator, is used to quantify mass change and viscoelastic parameters from soft materials at the nanoscale, in situ, with precise temporal resolution and operation in both liquid and gaseous environments. The versatility of QCM-D has enhanced the characterization of bioactive polymers and sensing arrays for advanced applications of novel biotechnologies. In this review, we highlight exciting, recent applications of QCM-D for the investigation of bioactive materials. Attention is given to the dynamic mechanical properties of bioactive materials, discerning protein structure on surfaces, probing cell adhesion and cytoskeletal changes, and biosensing applications. We conclude that QCM-D has untapped utility in the pre-clinical investigation of bioactive materials and further utilization can improve the clinical success of novel technologies.

scholarly journals methylscaper: an R/Shiny app for joint visualization of DNA methylation and nucleosome occupancy in single-molecule and single-cell data

2020 ◽  
Author(s):  
Parker Knight ◽  
Marie-Pierre L. Gauthier ◽  
Carolina E. Pardo ◽  
Russell P. Darst ◽  
Alberto Riva ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Single Molecule ◽  
Nucleosome Occupancy ◽  
Chromatin Accessibility ◽  
Biologically Relevant ◽  
Shiny App ◽  
R Shiny ◽  
Long Read ◽  
Cell Data

AbstractDifferential DNA methylation and chromatin accessibility are associated with disease development, particularly cancer. Methods that allow profiling of these epigenetic mechanisms in the same reaction and at the single-molecule or single-cell level continue to emerge. However, a challenge lies in jointly visualizing and analyzing the heterogeneous nature of the data and extracting regulatory insight. Here, we developed methylscaper, a visualization framework for simultaneous analysis of DNA methylation and chromatin landscapes. Methylscaper implements a weighted principle component analysis that orders sequencing reads, each providing a record of the chromatin state of one epiallele, and reveals patterns of nucleosome positioning, transcription factor occupancy, and DNA methylation. We demonstrate methylscaper’s utility on a long-read, single-molecule methyltransferase accessibility protocol for individual templates (MAPit) dataset and a single-cell nucleosome, methylation, and transcription sequencing (scNMT-seq) dataset. In comparison to other procedures, methylscaper is able to readily identify chromatin features that are biologically relevant to transcriptional status while scaling to larger datasets.Availability and implementationMethylscaper, is available on GitHub at https://github.com/rhondabacher/[email protected]

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