基于临床实践的数据估计前列腺切除术患者进行前列腺特异性膜抗原正电子发射断层扫描的最佳时间

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Martina Amongero, Gianluca Mastrantonio, Stefano De Luca, Mauro Gasparini
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引用次数: 0

摘要

前列腺切除术患者有复发的风险,因此,在随访期间,他们被监测前列腺特异性抗原(PSA)的生长,这是肿瘤进展的一个指标。肿瘤的存在可以通过昂贵的检查来评估,称为前列腺特异性膜抗原正电子发射断层扫描(PET-PSMA)。为了证明PET-PSMA的高成本是合理的,同时,为了控制患者的风险,只有当肿瘤进展的证据很明显时,才应该推荐这项检查。为了根据患者的病史和收集的数据估计推荐检查的最佳时间,我们建立了一个分层贝叶斯模型,该模型共同描述了PSA生长曲线和PET-PSMA阳性的概率。根据我们的建议,我们处理所有关于患者PSA测量和PET-PSMA结果的过去和现在的信息,以便给出最佳时间的知情估计,改进当前的实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the Optimal Time to Perform a Positron Emission Tomography With Prostate-Specific Membrane Antigen in Prostatectomized Patients, Based on Data From Clinical Practice

Prostatectomized patients are at risk of resurgence, and for this reason, during a follow-up period, they are monitored for prostate-specific antigen (PSA) growth, an indicator of tumor progression. The presence of tumors can be evaluated with an expensive exam, called positron emission tomography with prostate-specific membrane antigen (PET-PSMA). To justify the high cost of the PET-PSMA and, at the same time, to contain the risk for the patient, this exam should be recommended only when the evidence of tumor progression is strong. With the aim of estimating the optimal time to recommend the exam based on the patient's history and collected data, we build a hierarchical Bayesian model that describes, jointly, the PSA growth curve and the probability of a positive PET-PSMA. With our proposal, we process all past and present information about the patients PSA measurement and PET-PSMA results, in order to give an informed estimate of the optimal time, improving current practice.

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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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