Statistical methods for cost-effectiveness analysis of left-truncated and right-censored survival data with treatment delays [0.03%]
具有治疗延迟的左截断和右删失生存数据的成本效果分析统计方法
Polyna Khudyakov,Li Xu,Ce Yang et al.
Polyna Khudyakov et al.
The incremental cost-effectiveness ratio (ICER) and incremental net benefit (INB) are widely used for cost-effectiveness analysis. We develop methods for estimation and inference for the ICER and INB which use the semiparametric stratified ...
A patient similarity-embedded Bayesian approach to prognostic biomarker inference with application to thoracic cancer immunity [0.03%]
一种基于患者相似性的贝叶斯方法在胸腔癌症免疫学中预测预后生物标志物的推断中的应用研究
Duo Yu,Meilin Huang,Michael J Kane et al.
Duo Yu et al.
This paper introduces a novel statistical methodology integrating machine learning (ML) and Bayesian modelling to facilitate personalized prognostic predictions with application to oncology. Utilizing power priors, we construct 'patient-sim...
Correcting for bias due to mismeasured exposure in mediation analysis with a survival outcome [0.03%]
纠正暴露测量误差引起的偏差在生存结果的中介分析中的应用
Chao Cheng,Donna Spiegelman,Fan Li
Chao Cheng
We investigate the impact of exposure measurement error on assessing mediation with a survival outcome modelled by Cox regression. We first derive the bias formulas of natural indirect and direct effects with a rare outcome and no exposure-...
Synergistic self-learning approach to establishing individualized treatment rules from multiple benefit outcomes in a calcium supplementation trial [0.03%]
一种协同的自我学习方法，可从钙补充试验的多个获益结果中建立个体化治疗方案
Yiwang Zhou,Peter X K Song
Yiwang Zhou
In utero lead exposure poses risks to children's neurobehavioral development. The Early Life Exposure in Mexico to ENvironmental Toxicants' calcium supplementation trial studies the effect of calcium supplement in reducing maternal lead exp...
Building absolute breast cancer risk prediction models for women treated with chest radiation for Hodgkin lymphoma [0.03%]
霍奇金淋巴瘤胸部放疗女性患者乳腺癌绝对风险预测模型的建立
Sander Roberti,Flora E van Leeuwen,Michael Hauptmann et al.
Sander Roberti et al.
We built models to predict absolute breast cancer (BC) risk in women treated with radiotherapy for Hodgkin lymphoma (HL). We first estimated relative risks (RRs) for risk factors, including radiation dose to 10 breast segments to accommodat...
Multivariate Bayesian variable selection for multi-trait genetic fine mapping [0.03%]
多性状遗传精细定位的多变量贝叶斯变量选择方法
Travis Canida,Hongjie Ke,Shuo Chen et al.
Travis Canida et al.
Genome-wide association studies (GWAS) have identified thousands of single-nucleotide polymorphisms (SNPs) associated with complex traits, but determining the underlying causal variants remains challenging. Fine mapping aims to pinpoint the...
Inferring bivariate associations with continuous data from studies using respondent-driven sampling [0.03%]
使用应答者驱动抽样研究从连续数据中推断二元关联关系
Samantha Malatesta,Karen R Jacobson,Tara Carney et al.
Samantha Malatesta et al.
Respondent-driven sampling (RDS) is a link-tracing sampling design that was developed to sample from hidden populations. Although associations between variables are of great interest in epidemiological research, there has been little statis...
Estimating disease onset distribution functions in mutation carriers with censored mixture data [0.03%]
利用截尾混合数据估计突变携带者发病分布函数
Yanyuan Ma,Yuanjia Wang
Yanyuan Ma
We consider non-parametric estimation of disease onset distribution functions in multiple populations by using censored data with unknown population identifiers. The problem is motivated from studies aiming at estimating the age-specific di...
Glenn Heller,Sean M Devlin
Glenn Heller
Survival is poor for patients with metastatic cancer, and it is vital to examine new biomarkers that can improve patient prognostication and identify those who would benefit from more aggressive therapy. In metastatic prostate cancer, 2 new...
tdCoxSNN: Time-dependent Cox survival neural network for continuous-time dynamic prediction [0.03%]
tdCoxSNN：用于连续时间动态预测的时间依赖Cox生存神经网络
Lang Zeng,Jipeng Zhang,Wei Chen et al.
Lang Zeng et al.
The aim of dynamic prediction is to provide individualized risk predictions over time, which are updated as new data become available. In pursuit of constructing a dynamic prediction model for a progressive eye disorder, age-related macular...