跳到正文
← 返回论文列表与筛选
阅读说明

本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。

引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。

关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。

分类依据与纠错

AI 根据所提供的论文材料归类:摘要以患者长期重复测量及个体随机效应为核心,直接对应纵向数据方法。

反馈分类问题

正在核对关联版本…

代码、数据与补充材料

正在核对对应版本的资源…

关注这篇论文的作者
Jay D. Pearson
Larry J. Brant

用分段非线性混合效应模型估计前列腺癌患者的未知转变时间

研究问题
如何从前列腺癌患者确诊前的长期 PSA 重复测量中,估计指标由线性增长转为指数增长的个体时间及疾病组间差异?
方法与思路
作者对十八名患者采用分段非线性混合效应模型,以随机项允许个体转变时间不同,并允许组间参数不同后作向后删减。
材料陈述的贡献
摘要称拟合模型显示局部或区域性癌与晚期或转移癌的 PSA 进展速率相近,而后者确诊较晚,并提出未知事件时间建模用途。
阅读关注点
应核对分段函数的衔接、随机效应与转变时间识别,检查小样本及向后选模对组间比较和时间估计不确定性的影响。
阅读边界
依据版本未注明的 OpenAlex 索引摘要,不能推断刊本变化;结论来自十八名患者的模型拟合,摘要未说明外部验证或因果解释。

原文摘要

It may be clinically useful to know when prostate-specific antigen (PSA) levels first begin to rise rapidly and to determine if the natural history of PSA progression is different in men with locally confined prostate cancers compared to men with metastatic tumors. This article uses a nonlinear mixed-effects model to describe longitudinal changes in PSA in men before their prostate cancers were detected clinically. Repeated measurements of PSA are available for 18 subjects with a diagnosis of prostate cancer based on prostate biopsy. PSA measurements were determined on repeated frozen serum samples collected from subjects with at least 10.0 years and up to 25.6 years of observation before the cancer was detected. A piecewise model is used to describe this data. The model is linear long before the cancer was detected and exponential nearer the time the cancer was detected. The time at which the PSA levels change from linear to exponential PSA progression is unknown but can be estimated by including random terms that allow each subject to have his own transition time. The model also accounts for two groups of patients—those with local or regional cancer and those with advanced cancer or whose cancer has metastasized. Various parameters are allowed to differ between these two groups. By backward elimination of statistically nonsignificant parameters, a model is found that adequately describes the data. The model represents a situation where local/regional and advanced/metastatic cancers have similar rates of PSA progression, but advanced/metastatic cancers are diagnosed later. Piecewise mixed-effects models may be useful in a variety of research settings where it is necessary to estimate the unknown time of an event.

笔记与分组
相关领域论文