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Combining Prostate Health Index density, magnetic resonance imaging and prior negative biopsy status to improve the detection of clinically significant prostate cancer

机译:结合前列腺健康指数密度,磁共振成像和现有的负活检地位,提高临床显着前列腺癌的检测

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摘要

Objectives To determine the performance of Prostate Health Index ( PHI ) density ( PHID ) combined with MRI and prior negative biopsy ( PNB ) status for the diagnosis of clinically significant prostate cancer ( PC a). Patients and Methods Patients without a prior diagnosis of PC a, with elevated prostate‐specific antigen and a normal digital rectal examination who underwent PHI testing prospectively prior to prostate biopsy were included in this study. PHID was calculated retrospectively using prostate volume derived from transrectal ultrasonography at biopsy. Univariable and multivariable logistic regression modelling, along with receiver‐operating characteristic ( ROC ) curve analysis, was used to determine the ability of serum biomarkers to predict clinically significant PC a (defined as either grade group [ GG ] ≥2 disease or GG 1 PC a detected in 2 cores or 50% of any one core) on biopsy. Age, PNB status and Prostate Imaging Reporting and Data System ( PI ‐ RADS ) score were incorporated into the regression models. Results Of the 241 men who qualified for the study, 91 (37.8%) had clinically significant PC a on biopsy. The median (interquartile range) PHID was 0.74 (0.44–1.24); it was 1.18 (0.77–1.83) and 0.55 (0.38–0.89) in those with and without clinically significant PC a on biopsy, respectively ( P 0.001). On univariable logistic regression, age and PNB status were associated with clinically significant cancer. Of the tested biomarkers, PHID demonstrated the highest discriminative ability for clinically significant disease (area under the ROC curve [ AUC ] 0.78 for the univariable model). That continued to be the case in multivariable logistic regression models incorporating age and PNB status ( AUC 0.82). At a threshold of 0.44, representing the 25th percentile of PHID in the cohort, PHID was 92.3% sensitive and 35.3% specific for clinically significant PC a; the sensitivity and specificity were 93.0% and 32.4% and 97.4% and 29.1% for GG ≥2 and GG ≥3 disease, respectively. In the 104 men who underwent MRI , PI ‐ RADS score was complementary to PHID , with a PI ‐ RADS score ≥3 or, if PI ‐ RADS score ≤2, a PHID ≥0.44, detecting 100% of clinically significant disease. For that subgroup, of the biomarkers tested, PHID ( AUC 0.90) demonstrated the highest discriminative ability for clinically significant disease on multivariable logistic regression incorporating age, PNB status and PI ‐ RADS score. Conclusions In this contemporary cohort of men undergoing prostate biopsy for the diagnosis of PC a, PHID outperformed PHI and other PSA derivatives in the diagnosis of clinically significant cancer. Incorporating age, PNB status and PI ‐ RADS score led to even further gains in the diagnostic performance of PHID . Furthermore, PI ‐ RADS score was found to be complementary to PHID . Using 0.44 as a threshold for PHID , 35.3% of unnecessary biopsies could have been avoided at the cost of missing 7.7% of clinically significant cancers. Despite these encouraging results, prospective validation is needed.
机译:目的是确定前列腺健康指数(PHI)密度(PHID)的性能与MRI和现有的负活检(PNB)状态相结合,用于诊断临床显着的前列腺癌(PC A)。患者和方法没有先前诊断的PC A,具有升高的前列腺特异性抗原和正常的数字直肠检查,患者在本研究中纳入前列腺活检之前前瞻性地进行了PHI测试。通过在活组织检查中使用从经癌超声检查的前列腺体积来回顾性地计算pHID。与接收器操作特征(ROC)曲线分析一起使用不可变化和多变量的逻辑回归建模,用于确定血清生物标志物预测临床上显着的PC A的能力(定义为≥2级≥2疾病或GG 1 PC在活检中检测到& 2核或任何一个核心的50%的核心。年龄,PNB状态和前列腺成像报告和数据系统(PI-RADS)得分被纳入回归模型。 241名合格研究的男性的结果91(37.8%)在活检中具有临床显着的PC A.中位数(四分位数)phid为0.74(0.44-1.24);在活检中分别为1.18(0.77-1.83)和0.55(0.38-0.89),分别没有临床显着的PC A(P <0.001)。在单一的逻辑回归,年龄和PNB状态与临床显着癌症有关。在测试的生物标志物中,PHID展示了临床显着疾病的最高鉴别能力(ROC曲线下的区域[AUC] 0.78,为单变种模型)。在包含年龄和PNB状态的多变量逻辑回归模型中继续如此(AUC 0.82)。在0.44的阈值下,代表群组中的第25%的phid,phID为92.3%敏感,35.3%,对于临床显着的PC a具体;敏感性和特异性分别为93.0%和32.4%和97.4%,分别为GG≥2和GG≥3次疾病。在接受MRI的104名男性中,PI - RADS评分与PHID互补,PI-RADS得分≥3或者如果PI-RADS得分≤2,则检测100%的临床显着疾病。对于那个测试的生物标志物的亚组,Phid(AUC 0.90)阐述了临床显着性疾病的最高鉴别能力,这些疾病在包含年龄,PNB状态和PI - RADS分数的多变量逻辑回归上。结论在这种当代队伍中,接受前列腺活检,用于诊断PC A,PhID表现优于PHI和其他PSA衍生物在临床上显着癌症的诊断中。加入年龄,PNB状态和PI - RADS分数导致PHID诊断性能进一步提升。此外,发现PI-RADS得分与phid互补。使用0.44作为PhID的阈值,可以以缺少7.7%的临床显着癌症的成本来避免35.3%的不必要的活组织检查。尽管这些令人鼓舞的结果,但需要预期验证。

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