Commentary: On measurement error, PSA doubling time, and prostate cancer

Lawrence L. Kupper , Sandra L. Martin , Christopher J. Wretman
{"title":"Commentary: On measurement error, PSA doubling time, and prostate cancer","authors":"Lawrence L. Kupper ,&nbsp;Sandra L. Martin ,&nbsp;Christopher J. Wretman","doi":"10.1016/j.gloepi.2023.100129","DOIUrl":null,"url":null,"abstract":"<div><p>Exposure measurement error is a pervasive problem for epidemiology research projects designed to provide valid and precise statistical evidence supporting postulated exposure-disease relationships of interest. The purpose of this commentary is to highlight an important real-life example of this exposure measurement error problem and to provide a simple and useful diagnostic tool for physicians and their patients that corrects for the exposure measurement error. More specifically, prostate-specific antigen doubling time (PSADT) is a widely used measure for guiding future treatment options for patients with biochemically recurrent prostate cancer. Numerous papers have been published claiming that a low calculated PSADT value (denoted <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span>) is predictive of metastasis and premature death from prostate cancer. Unfortunately, none of these papers have adjusted for the measurement error in <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span>, an estimator that is typically computed using the popular Memorial Sloan Kettering website very often visited by both physicians and their patients. For this website, the estimator <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> of the true (but unknown) PSADT for a patient (denoted PSADT<sup>∗</sup>) is computed as the natural log of 2 (i.e., 0.6931) divided by the estimated slope of the straight-line regression of the natural log of PSA (in ng/mL) on time. We utilize <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> to derive an expression for the probability that the unknown PSADT<sup>∗</sup> for a patient is below a specified value C (<span><math><mo>&gt;</mo><mn>0</mn></math></span>) of concern to both the physician and the patient. This probability is easy to interpret and takes into account the fact that <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> is a statistical estimator with variability. This variability introduces measurement error, namely, the difference between a computed value <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> and the true, but unknown, value PSADT<sup>∗</sup>. We have developed an Excel calculator that, once the [time, ln(PSA)] values are entered, outputs both the value of <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> and the desired probability. In addition, we discuss problematic statistical issues attendant with PSADT<sup>∗</sup> estimation typically based on at most three or four PSA values. We strongly recommend the use of this probability when physicians are discussing <span><math><mover><mtext>PSADT</mtext><mo>̂</mo></mover></math></span> values and associated treatment options with their patients. And, we stress that future epidemiology research projects involving PSA doubling time should take into account the measurement error problem highlighted in this Commentary.</p></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590113323000329/pdfft?md5=71d5903249a9e080067e9347ec66ce2c&pid=1-s2.0-S2590113323000329-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590113323000329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Exposure measurement error is a pervasive problem for epidemiology research projects designed to provide valid and precise statistical evidence supporting postulated exposure-disease relationships of interest. The purpose of this commentary is to highlight an important real-life example of this exposure measurement error problem and to provide a simple and useful diagnostic tool for physicians and their patients that corrects for the exposure measurement error. More specifically, prostate-specific antigen doubling time (PSADT) is a widely used measure for guiding future treatment options for patients with biochemically recurrent prostate cancer. Numerous papers have been published claiming that a low calculated PSADT value (denoted PSADT̂) is predictive of metastasis and premature death from prostate cancer. Unfortunately, none of these papers have adjusted for the measurement error in PSADT̂, an estimator that is typically computed using the popular Memorial Sloan Kettering website very often visited by both physicians and their patients. For this website, the estimator PSADT̂ of the true (but unknown) PSADT for a patient (denoted PSADT) is computed as the natural log of 2 (i.e., 0.6931) divided by the estimated slope of the straight-line regression of the natural log of PSA (in ng/mL) on time. We utilize PSADT̂ to derive an expression for the probability that the unknown PSADT for a patient is below a specified value C (>0) of concern to both the physician and the patient. This probability is easy to interpret and takes into account the fact that PSADT̂ is a statistical estimator with variability. This variability introduces measurement error, namely, the difference between a computed value PSADT̂ and the true, but unknown, value PSADT. We have developed an Excel calculator that, once the [time, ln(PSA)] values are entered, outputs both the value of PSADT̂ and the desired probability. In addition, we discuss problematic statistical issues attendant with PSADT estimation typically based on at most three or four PSA values. We strongly recommend the use of this probability when physicians are discussing PSADT̂ values and associated treatment options with their patients. And, we stress that future epidemiology research projects involving PSA doubling time should take into account the measurement error problem highlighted in this Commentary.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
评论:关于测量误差,PSA倍增时间,和前列腺癌
对于流行病学研究项目来说,暴露测量误差是一个普遍存在的问题,流行病学研究项目旨在提供有效和精确的统计证据来支持感兴趣的假定暴露-疾病关系。这篇评论的目的是强调这个暴露测量误差问题的一个重要的现实例子,并为医生和他们的病人提供一个简单而有用的诊断工具来纠正暴露测量误差。更具体地说,前列腺特异性抗原倍增时间(PSADT)是一种广泛使用的指标,用于指导生化复发前列腺癌患者未来的治疗选择。已发表的许多论文声称,低计算的PSADT值(表示PSADT³)可预测前列腺癌的转移和过早死亡。不幸的是,这些论文都没有对PSADT的测量误差进行调整,PSADT是一个估计量,通常是通过医生和病人经常访问的流行的Memorial Sloan Kettering网站来计算的。对于本网站,患者真实(但未知)PSADT(记为PSADT *)的估计量PSADT³计算为2的自然对数(即0.6931)除以PSA(以ng/mL为单位)自然对数随时间的直线回归的估计斜率。我们利用PSADT³来推导出患者的未知PSADT *低于医生和患者都关心的规定值C(>0)的概率表达式。这个概率很容易解释,并且考虑到PSADT³是一个具有可变性的统计估计量。这种可变性引入了测量误差,即计算值PSADT³与真实但未知的值PSADT *之间的差异。我们开发了一个Excel计算器,一旦输入[时间,ln(PSA)]值,就会输出PSADT的值和期望的概率。此外,我们还讨论了通常最多基于三个或四个PSA值的PSADT *估计所伴随的有问题的统计问题。我们强烈建议医生在与患者讨论PSADT值和相关治疗方案时使用该概率。并且,我们强调,未来涉及PSA加倍时间的流行病学研究项目应考虑到本评论中强调的测量误差问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Global Epidemiology
Global Epidemiology Medicine-Infectious Diseases
CiteScore
5.00
自引率
0.00%
发文量
22
审稿时长
39 days
期刊最新文献
A note on handling conditional missing values Tailored guidance to apply the Estimand framework to Trials within Cohorts (TwiCs) studies Improving the timeliness of birth registration in Fiji through a financial incentive Predicting adolescent psychopathology from early life factors: A machine learning tutorial Challenging unverified assumptions in causal claims: Do gas stoves increase risk of pediatric asthma?
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1