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Validation of a Genomic Risk Classifier to Predict Prostate Cancer-specific Mortality in Men with Adverse Pathologic Features

机译:验证基因组风险分类器,以预测具有不良病理特征的男性前列腺癌特异性死亡率

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Abstract Background Risk of prostate cancer-specific mortality (PCSM) is highly variable for men with adverse pathologic features at radical prostatectomy (RP); a majority will die of other causes. Accurately stratifying PCSM risk can improve therapy decisions. Objective Validate the 22 gene Decipher genomic classifier (GC) to predict PCSM in men with adverse pathologic features after RP. Design, setting, and participants Men with adverse pathologic features: pT3, pN1, positive margins, or Gleason score >7 who underwent RP in 1987–2010 at Johns Hopkins, Cleveland Clinic, Mayo Clinic, and Durham Veteran's Affairs Hospital. We also analyzed subgroups at high risk (prostate-specific antigen >20 ng/ml, RP Gleason score 8–10, or stage >pT3b), or very high risk of PCSM (biochemical recurrence in Outcome measurements and statistical analysis Logistic regression evaluated the association of GC with PCSM within 10 yr of RP (PCSM10), adjusted for the Cancer of the Prostate Risk Assessment Postsurgical Score (CAPRA-S). GC performance was evaluated with area under the receiver operating characteristic curve (AUC) and decision curves. Results and limitations Five hundred and sixty-one men (112 with PCSM10), median follow-up 13.0 yr (patients without PCSM10). For high GC score (> 0.6) versus low-intermediate (≤ 0.6), the odds ratio for PCSM10 adjusted for CAPRA-S was 3.91 (95% confidence interval: 2.43–6.29), with AUC=0.77, an increase of 0.04 compared with CAPRA-S. Subgroup odds ratios were 3.96, 3.06, and 1.95 for high risk, BCR2, or MET, respectively (all p Conclusions In a large cohort with the longest follow-up to date, Decipher GC demonstrated clinically important prediction of PCSM at 10 yr, independent of CAPRA-S, in men with adverse pathologic features, BCR2, or MET after RP. Patient summary Decipher genomic classifier may improve treatment decision-making for men with adverse or high risk pathology after radical prostatectomy. Take Home Message In men with adverse pathology or early disease progression after prostatectomy, the Decipher 22 gene genomic classifier predicts risk of prostate cancer death. When combined with the Cancer of the Prostate Risk Assessment Postsurgical Score it further stratifies risk, which may be useful for decisions about postprostatectomy treatment.
机译:摘要前列腺癌特异性死亡率(PCSM)的背景风险对于受激菌前列腺切除术(RP)具有不良病理特征的男性是高度可变的;大多数人将死于其他原因。准确分层PCSM风险可以改善治疗决策。目的验证22基因破译基因组分类器(GC),以预测RP后具有不良病理特征的男性的PCSM。具有不良病理特征的设计,设置和参与者男性:PT3,PN1,正边缘或GLEASIN得分> 7世卫组织于1987 - 2010年在约翰霍普金斯,克利夫兰诊所,梅奥诊所和达勒姆退伍军人事务医院接受了RP。我们还分析了高风险(前列腺特异性抗原> 20ng / ml,RP Gleason评分8-10或阶段> Pt3b)的亚组,或者PCSM的风险非常高(结果测量中的生物化学复发和统计分析逻辑回归评估GC与PCSM在RP(PCSM10)中的10年内的关联,调整了前列腺风险评估后的前列评分(CAPRA-S)。GC性能在接收器操作特征曲线(AUC)和决策曲线下用面积进行评估。结果与限制五百六十一人(112带PCSM10),中位随访13.0 YR(没有PCSM10的患者)。对于高中GC分数(> 0.6)而低中间(≤0.6),PCSM10的差距比率Capra-S调整为3.91(95%置信区间:2.43-6.29),AUC = 0.77,与CAPRA-S相比增加0.04。亚组差比率为3.96,3.06和1.95,用于高风险,BCR2,或分别遇到(所有P在大型队列中的结论,随访最长迄今为止,破译GC在10年以10年的临床上重要预测,独立于Capra-S,在具有不良病理特征,BCR2或RP之后满足的男性。患者摘要破译基因组分类器可以改善自由基前列腺切除术后具有不良或高风险病理学的治疗决策。在前列腺切除术后患有不良病理学或早期疾病进展的男性中的家庭信息,破译22基因基因组分类器预测前列腺癌死亡的风险。当与前列腺风险评估的癌症结合后,它进一步分层风险,这可能对后产后切除治疗的决定可能是有用的。

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