Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance
Validation of the Decipher Test for predicting adverse pathology in candidates for prostate cancer active surveillance
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DOI：
10.1038/s41391-018-0101-6
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发表时间：
2019-09-01
影响因子：
4.8
通讯作者：
Bismar, Tarek A.
中科院分区：
文献类型：
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作者：
Kim, Hyung L.;Li, Ping;Bismar, Tarek A.
背景：许多诊断为前列腺癌的男性都是主动监测（AS）的候选者。然而，由于延迟治疗，AS可能与疾病进展和转移的风险增加有关。基因组分类器，如破译，可能允许更好的风险分层新诊断的前列腺癌AS。方法首先在前列腺切除术的前瞻性队列中评估Decipher，以探讨其与临床有意义的生物学特征的相关性，然后在266名患有国家综合癌症网络（NCCN）极低/低和中危前列腺癌的男性的回顾性多中心队列中评估其诊断活检。我们比较了Decipher和前列腺癌风险评估（CAPRA）作为不良病理（AP）的预测指标，普遍认为预期寿命长的患者不适合作为as（原发性模式4或5、局部晚期[pT3b或更高]或淋巴结受累）的候选人。结果前列腺切除术后出现的不良病理特征显著相关（p值< 0.001）。266例诊断活检（64.7%为nccn -极低/低，35.3%为有利-中间）是AP的独立预测因子（优势比为1.29 / 10%，95%可信区间[CI] 1.03-1.61， p值0.025）。CAPRA曲线下面积（AUC）为0.57,（95% CI 0.47-0.68）。在CAPRA中加入Decipher使AUC增加到0.65 （95% CI 0.58-0.70）。在破译阈值为0.45和0.2时，NPV（决定患者无AP的置信度）分别为91% （95% CI 87-94%）和96% （95% CI 90-99%）。使用0.2的阈值，当调整CAPRA时，破译是AP的显著预测因子（p值0.016）。结论破译技术可应用于nccn -极低/低及有利-中等风险患者的前列腺活检，预测无不良病理特征。预计这些患者是积极监测的良好候选者。
Background Many men diagnosed with prostate cancer are active surveillance (AS) candidates. However, AS may be associated with increased risk of disease progression and metastasis due to delayed therapy. Genomic classifiers, e.g., Decipher, may allow better risk-stratify newly diagnosed prostate cancers for AS.Methods Decipher was initially assessed in a prospective cohort of prostatectomies to explore the correlation with clinically meaningful biologic characteristics and then assessed in diagnostic biopsies from a retrospective multicenter cohort of 266 men with National Comprehensive Cancer Network (NCCN) very low/low and favorable-intermediate risk prostate cancer. Decipher and Cancer of the Prostate Risk Assessment (CAPRA) were compared as predictors of adverse pathology (AP) for which there is universal agreement that patients with long life-expectancy are not suitable candidates for AS (primary pattern 4 or 5, advanced local stage [pT3b or greater] or lymph node involvement).Results Decipher from prostatectomies was significantly associated with adverse pathologic features (p-values < 0.001). Decipher from the 266 diagnostic biopsies (64.7% NCCN-very-low/low and 35.3% favorable-intermediate) was an independent predictor of AP (odds ratio 1.29 per 10% increase, 95% confidence interval [CI] 1.03-1.61, p-value 0.025) when adjusting for CAPRA. CAPRA area under curve (AUC) was 0.57, (95% CI 0.47-0.68). Adding Decipher to CAPRA increased the AUC to 0.65 (95% CI 0.58-0.70). NPV, which determines the degree of confidence in the absence of AP for patients, was 91% (95% CI 87-94%) and 96% (95% CI 90-99%) for Decipher thresholds of 0.45 and 0.2, respectively. Using a threshold of 0.2, Decipher was a significant predictor of AP when adjusting for CAPRA (p-value 0.016).Conclusion Decipher can be applied to prostate biopsies from NCCN-very-low/low and favorable-intermediate risk patients to predict absence of adverse pathologic features. These patients are predicted to be good candidates for active surveillance.