Reliability of Systematic and Targeted Biopsies versus Prostatectomy

被引:0
|
作者
Guan, Tianyuan [1 ]
Sidana, Abhinav [2 ]
Rao, Marepalli B. [3 ]
机构
[1] Kent State Univ, Coll Publ Hlth, Kent, OH 44240 USA
[2] Univ Chicago, Div Biol Sci, 5841 S Maryland Ave, Chicago, IL 60637 USA
[3] Univ Cincinnati, Div Biostat & Bioinformat, Cincinnati, OH 45219 USA
来源
BIOENGINEERING-BASEL | 2023年 / 10卷 / 12期
关键词
prostate cancer; systematic biopsy; targeted biopsy; ROC curve; area under the curve; sensitivity; specificity; logistic regression; biomarker; machine learning methods;
D O I
10.3390/bioengineering10121395
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Systematic Biopsy (SBx) has been and continues to be the standard staple for detecting prostate cancer. The more expensive MRI guided biopsy (MRITBx) is a better way of detecting cancer. The prostatectomy can provide an accurate condition of the prostate. The goal is to assess how reliable SBx and MRITBx are vis a vis prostatectomy. Graded Gleason scores are used for comparison. Cohen's Kappa index and logistic regression after binarization of the graded Gleason scores are some of the methods used to achieve our goals. Machine learning methods, such as classification trees, are employed to improve predictability clinically. The Cohen's Kappa index is 0.31 for SBx versus prostatectomy, which means a fair agreement. The index is 0.34 for MRITBx versus prostatectomy, which again means a fair agreement. A direct comparison of SBx versus prostatectomy via binarized graded scores gives sensitivity 0.83 and specificity 0.50. On the other hand, a direct comparison of MRITBx versus prostatectomy gives sensitivity 0.78 and specificity 0.67, putting MRITBx on a higher level of accuracy. The SBx and MRITBx do not yet match the findings of prostatectomy completely, but they are useful. We have developed new biomarkers, considering other pieces of information from the patients, to improve the accuracy of SBx and MRITBx. From a clinical point of view, we provide a prediction model for prostatectomy Gleason grades using classification tree methodology.
引用
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页数:14
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