Decipher correlation patterns post prostatectomy: initial experience from 2342 prospective patients
Decipher correlation patterns post prostatectomy: initial experience from 2342 prospective patients
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DOI：
10.1038/pcan.2016.38
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发表时间：
2016-12-01
影响因子：
4.8
通讯作者：
Shah, N. L.
中科院分区：
文献类型：
--
作者：
Den, R. B.;Santiago-Jimenez, M.;Shah, N. L.
背景技术背景：目前，有多种市售的基于RNA的生物标志物被Medicare批准并建议由国家综合癌症网络指南使用。有不确定性，哪些患者受益于基因组检测，这些测试应该下令。在这里，我们检查了Decipher检测的相关模式，以了解Decipher和患者肿瘤特征之间的关系。方法：对2015年1月至9月期间接受检测的2 342例连续根治性乳腺癌切除术（RP）患者的Decipher检测结果（包括Decipher风险评分和临床病理数据）进行分析。对于临床测试，使用1.5mm组织穿孔器对来自最高Gleason等级的肿瘤标本进行取样。解密分数是根据先前锁定的模型计算的。使用斯皮尔曼等级相关计算Decipher评分和临床病理变量之间的相关性。混合效应线性模型被用来研究实践类型和Decipher得分的关联。结果：解密评分与病理Gleason评分呈正相关（PGS; r = 0.37，95%置信区间（CI）0.34-0.41），病理T分期（r = 0.31，95% CI 0.28-0.35）、CAPRA-S（r = 0.32，95% CI 0.28-0.37）和患者年龄（r = 0.09，95% CI 0.05-0.13）。Decipher将52%、76%和40%的患者重新分类为CAPA-S低、中、高风险组。我们通过Decipher评分检测到pT 2患者中28%的高危疾病发生率和pT 3b/pT 4患者中7%的低风险，PGS 8-10患者。社区中心和学术中心患者的Decipher评分无显著差异（P = 0.82）。结论：尽管Decipher评分与2000多例患者的基线肿瘤特征相关，但与临床参数相比，肿瘤侵袭性有显著的重新分类。Decipher基因组分类器的使用可能对术后风险评估产生重大影响，这些风险可能影响医生-患者决策和最终患者管理。
BACKGROUND: Currently, there are multiple commercially available RNA-based biomarkers that are Medicare approved and suggested for use by the National Comprehensive Cancer Network guidelines. There is uncertainty as to which patients benefit from genomic testing and for whom these tests should be ordered. Here, we examined the correlation patterns of Decipher assay to understand the relationship between the Decipher and patient tumor characteristics.METHODS: De-identified Decipher test results (including Decipher risk scores and clinicopathologic data) from 2 342 consecutive radical prostatectomy (RP) patients tested between January and September 2015 were analyzed. For clinical testing, tumor specimen from the highest Gleason grade was sampled using a 1.5 mm tissue punch. Decipher scores were calculated based on a previously locked model. Correlations between Decipher score and clinicopathologic variables were computed using Spearman's rank correlation. Mixed-effect linear models were used to study the association of practice type and Decipher score. The significance level was 0.05 for all tests.RESULTS: Decipher score had a positive correlation with pathologic Gleason score (PGS; r = 0.37, 95% confidence interval (CI) 0.34-0.41), pathologic T-stage (r = 0.31, 95% CI 0.28-0.35), CAPRA-S (r = 0.32, 95% CI 0.28-0.37) and patient age (r = 0.09, 95% CI 0.05-0.13). Decipher reclassified 52%, 76% and 40% of patients in CAPRA-S low-, intermediate-and high-risk groups, respectively. We detected a 28% incidence of high-risk disease through the Decipher score in pT2 patients and 7% low risk in pT3b/pT4, PGS 8-10 patients. There was no significant difference in the Decipher score between patients from community centers and those from academic centers (P = 0.82).CONCLUSIONS: Although Decipher correlated with baseline tumor characteristics for over 2 000 patients, there was significant reclassification of tumor aggressiveness as compared to clinical parameters alone. Utilization of the Decipher genomic classifier can have major implications in assessment of postoperative risk that may impact physician-patient decision making and ultimately patient management.