Loeb Stacy, Shin Sanghyuk S, Broyles Dennis L, Wei John T, Sanda Martin, Klee George, Partin Alan W, Sokoll Lori, Chan Daniel W, Bangma Chris H, van Schaik Ron H N, Slawin Kevin M, Marks Leonard S, Catalona William J
Department of Urology and Population Health, NYU Langone Medical Center, New York, NY, USA.
Beckman Coulter Incorporated, Carlsbad, CA, USA.
BJU Int. 2017 Jul;120(1):61-68. doi: 10.1111/bju.13676. Epub 2016 Nov 22.
To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study.
The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram.
Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis.
Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.
在美国一项大型多中心研究中，检验前列腺健康指数（PHI）作为连续变量在侵袭性前列腺癌多变量风险评估中的应用。
研究人群包括728名男性，其前列腺特异性抗原（PSA）水平为2 - 10 ng/mL且直肠指检阴性，这些男性参与了一项前瞻性、多中心早期检测试验。主要终点为侵袭性前列腺癌，定义为活检Gleason评分≥7。首先，我们评估添加PHI是否能改善现有风险计算器（前列腺癌预防试验[PCPT]和欧洲前列腺癌筛查随机研究[ERSPC]风险计算器）的性能。我们还设计并在内部验证了一个基于PHI的新多变量预测模型，并创建了一个列线图。
在接受活检的728名男性中，118名（16.2%）患有侵袭性前列腺癌。PHI在整个数值范围内预测了侵袭性前列腺癌的风险。添加PHI显著提高了PCPT和ERSPC风险计算器对侵袭性疾病的预测准确性。使用年龄、既往活检、前列腺体积、PSA和PHI创建了一个新模型，曲线下面积为0.746。经自展校正的模型显示与侵袭性前列腺癌的观察风险具有良好的校准，并且在决策曲线分析中有净效益。
将PHI用作多变量风险评估的一部分可显著改善侵袭性前列腺癌的检测，有可能减少不必要的前列腺活检和过度诊断带来的危害。
