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Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort

机译：经验证的临床和基因组风险分层工具的组合价值可预测高危前列腺切除术队列中的前列腺癌死亡率

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BackgroundRisk prediction models that incorporate biomarkers and clinicopathologic variables may be used to improve decision-making post radical prostatectomy (RP). We compared two previously validated post-RP classifiers—the Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) and the Decipher genomic classifier (GC)—to predict prostate cancer-specific mortality (CSM) in a contemporary cohort of RP patients.

机译：背景结合生物标志物和临床病理变量的风险预测模型可用于改善根治性前列腺切除术（RP）后的决策。我们比较了两个先前经过验证的RP后分类器-手术后前列腺癌风险评估（CAPRA-S）和Decipher基因组分类器（GC）-以预测当代RP中前列腺癌特异性死亡率（CSM）耐心。

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期刊名称 other
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Matthew R. Cooperberg; Elai Davicioni; Anamaria Crisan; Robert B. Jenkins; Mercedeh Ghadessi; R. Jeffrey Karnes;
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年(卷),期 -1(67),2
年度 -1
页码 326–333
总页数 16
原文格式 PDF
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专利

1. Combined Value of Validated Clinical and Genomic Risk Stratification Tools for Predicting Prostate Cancer Mortality in a High-risk Prostatectomy Cohort [J] . Cooperberg Matthew R., Davicioni Elai, Crisan Anamaria, European urology . 2015,第2期

机译：经验证的临床和基因组风险分层工具的组合价值，可预测高危前列腺切除术队列中的前列腺癌死亡率
2. Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort [J] . Matthew R. Cooperberg, Robert B. Jenkins, Mercedeh Ghadessi, Indian heart journal . 2015,第2期

机译：验证临床和基因组风险分层工具的综合价值预测高危前列腺切除术队列前列腺癌死亡率
3. Re: A Genomic Classifier Improves Prediction of Metastatic Disease within 5 Years after Surgery in Node-Negative High-Risk Prostate Cancer Patients Managed by Radical Prostatectomy without Adjuvant Therapy - Re: Tissue-Based Genomics Augments Post-Prostatectomy Risk Stratification in a Natural History Cohort of Intermediate- and High-Risk Men Editorial Comment [J] . Taneja Samir S. The Journal of Urology . 2016,第1期

机译：回复：基因组分类器可改善经根治性前列腺切除术无辅助治疗的淋巴结阴性高危前列腺癌患者手术后5年内转移性疾病的预测-回复：自然历史队列中基于组织的基因组学增强前列腺切除术后的风险分层和高风险男人的社论编辑评论
4. Combining machine learning and clinical rules to build an algorithm for predicting ICU mortality risk [C] . Krajnak Michael, Xue Joel, Kaiser Willi, Computing in Cardiology 2012.;vol. 39. . 2012

机译：结合机器学习和临床规则以构建可预测ICU死亡风险的算法
5. Factors in Pi-Rads 3 and 4 Prostate Lesions that Predict The Risk of Clinically Significant Cancer [D] . Swallow, Matthew. 2019

机译：Pi-rads 3和4前列腺病变中的因素预测临床显着癌症的风险
6. Time to Disease Recurrence Is a Predictor of Metastasis and Mortality in Patients with High-risk Prostate Cancer Who Achieved Undetectable Prostate-specific Antigen Following Robot-assisted Radical Prostatectomy [O] . Do Kyung Kim, Kyo Chul Koo, Kwang Suk Lee, 2018

机译：疾病复发的时间是高危前列腺癌患者的转移和死亡率的预测因素这些患者在机器人辅助的根治性前列腺切除术后获得了无法检测的前列腺特异性抗原
7. Combined Value of Validated Clinical and Genomic Risk Stratification Tools for Predicting Prostate Cancer Mortality in a High-risk Prostatectomy Cohort [O] . Matthew R. Cooperberg, Elai Davicioni, Anamaria Crisan, 2015

机译：验证临床和基因组风险分层工具的综合价值预测高危前列腺切除术队列前列腺癌死亡率

Combined value of validated clinical and genomic risk stratification tools for predicting prostate cancer mortality in a high-risk prostatectomy cohort

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