Oliver Kuss,Annika Hoyer
Oliver Kuss
Background: Reporting treatment effects from clinical trials on both relative and absolute scales is crucial. While absolute measures like the Number Needed to Treat (NNT) are well-established for binary outcomes, their c...
A novel statistical feature selection framework for biomarker discovery and cancer classification via multiomics integration [0.03%]
一种新颖的统计特征选择框架，用于通过多组学整合发现生物标志物和分类癌症
Moshira S Ghaleb,Maryam N Al-Berry,Hala M Ebied et al.
Moshira S Ghaleb et al.
Background: Early cancer diagnosis is essential for improving prognosis and guiding treatment. However, the high dimensionality and complexity of omics data present major challenges. Computational approaches that extract ...
A clustering-stratified cross-validation framework for validating omics survival models: application to head and neck cancer [0.03%]
一种用于验证头颈癌组学生存模型的聚类分层交叉验证框架
Antoine Dubray-Vautrin,Olivier Choussy,Constance Lamy et al.
Antoine Dubray-Vautrin et al.
Background: This study tackles the challenge of developing reliable prognostic models for time-to-event (TTE) outcomes using high-dimensional omics data in head and neck cancers. Resampling methods, particularly nested cr...
Enhancing interpretability for Bayesian basket trial designs by effective sample size [0.03%]
有效样本量在贝叶斯篮子试验设计中的作用以增强其可解释性
Xin Chen,Jingyi Zhang,Wenyun Yang et al.
Xin Chen et al.
Background: There is growing interest in utilizing Bayesian approaches to borrow information across tumor types in basket trials. Several innovative designs, primarily extensions of the Bayesian hierarchical model (BHM), ...
Weighting strategy and selection analysis in the panel 'Health in Germany': methods and results for the 2024 annual survey [0.03%]
德国健康面板调查《德国健康》加权策略和选择分析：2024年度调查的方法与结果分析
Stefan Damerow,Ronny Kuhnert,Angelika Schaffrath Rosario et al.
Stefan Damerow et al.
Background: The panel `Health in Germany` has been established to gather nationwide health-related information, replacing cross-sectional surveys as primary data sources. However, panel designs involve multiple selection ...
Demystifying inconsistent two-sample mendelian randomization estimations using selection diagram [0.03%]
用选择图解释不一致的两样本孟德尔随机化估计结果
Lei Hou,Yuanyuan Yu,Zhi Geng et al.
Lei Hou et al.
Two-Sample Mendelian Randomization (TSMR) analysis is a widely used method for inferring causal effect in the presence of unmeasured confounding. However, causal inferences may be biased if the distributions of key variables (e.g., exposure...
Identifying, handling and impact of immortal time bias on addressing treatment effects in observational studies using routinely collected data [0.03%]
利用常规收集数据处理观察性研究中永生时间偏倚的识别、控制及影响
Shuangyi Xie,Jiayue Xu,Qiao He et al.
Shuangyi Xie et al.
Background: Immortal time bias (ITB) represents a methodological challenge in evaluating treatment effects in observational studies using routinely collected data (RCD). However, the prevalence of ITB, the strategies used...
Qualitative dyadic analysis in care partnership research: a scoping review [0.03%]
护理伙伴关系研究中的二元定性分析：系统综述
Andrea S E Parks,Lesley Gotlib Conn,Bahar Aria et al.
Andrea S E Parks et al.
Background: Chronic illness impacts not only individuals affected by it, but also those who care for them. Care partnerships recognize that health conditions are often shared, dyadic experiences. Qualitative dyadic analys...
Inclusive methodological awareness for equity and diversity in biomedical research [0.03%]
包容性方法意识在生物医学研究中的公平性和多样性问题上的应用
Elochukwu Ezenwankwo,Rosemary M Caron
Elochukwu Ezenwankwo
Applications of survival analysis and learning curves methods in neurosurgical stroke data and simulations to account for provider heterogeneity [0.03%]
生存分析和学习曲线方法在神经外科卒中数据和模拟中的应用，以考虑提供者异质性的影响
Usha S Govindarajulu,Rivera Daniel,Reynolds Eric et al.
Usha S Govindarajulu et al.