Martini-Clinic, Prostate Cancer Center Hamburg-Eppendorf, Hamburg, Germany.
BJU Int. 2010 Mar;105(5):636-41. doi: 10.1111/j.1464-410X.2009.08744.x. Epub 2009 Jul 7.
To improve the ability of our previously reported saturation biopsy nomogram quantifying the risk of prostate cancer, as the use of office-based saturation biopsy has increased.
Saturation biopsies of 540 men with one or more previously negative 6-12 core biopsies were used to develop a multivariable logistic regression model-based nomogram, predicting the probability of prostate cancer. Candidate predictors were used in their original or stratified format, and consisted of age, total prostate-specific antigen (PSA) level, percentage free PSA (%fPSA), gland volume, findings on a digital rectal examination, cumulative number of previous biopsy sessions, presence of high-grade prostatic intraepithelial neoplasia on any previous biopsy, and presence of atypical small acinar proliferation (ASAP) on any previous biopsy. Two hundred bootstraps re-samples were used to adjust for overfit bias.
Prostate cancer was diagnosed in 39.4% of saturation biopsies. Age, total PSA, %fPSA, gland volume, number of previous biopsies, and presence of ASAP at any previous biopsy were independent predictors for prostate cancer (all P < 0.05). The nomogram was 77.2% accurate and had a virtually perfect correlation between predicted and observed rates of prostate cancer.
We improved the accuracy of the saturation biopsy nomogram from 72% to 77%; it relies on three previously included variables, i.e. age, %fPSA and prostate volume, and on three previously excluded variables, i.e. PSA, the number of previous biopsy sessions, and evidence of ASAP on previous biopsy. Our study represents the largest series of saturation biopsies to date.
提高我们之前报告的饱和活检列线图量化前列腺癌风险的能力，因为基于诊室的饱和活检的使用有所增加。
使用 540 名先前有一次或多次阴性 6-12 核心活检的男性的饱和活检，建立了一个基于多变量逻辑回归模型的列线图，预测前列腺癌的概率。候选预测因子以其原始或分层形式使用，包括年龄、总前列腺特异性抗原（PSA）水平、游离 PSA 百分比（%fPSA）、腺体体积、直肠指检结果、先前活检次数的累积数、任何先前活检中存在高级别前列腺上皮内瘤变（HGPIN）以及任何先前活检中存在不典型小腺泡增生（ASAP）。使用 200 次 bootstrap 重采样来调整过度拟合偏差。
在 39.4%的饱和活检中诊断出前列腺癌。年龄、总 PSA、%fPSA、腺体体积、先前活检次数以及任何先前活检中 ASAP 的存在是前列腺癌的独立预测因子（均 P < 0.05）。列线图的准确率为 77.2%，预测和观察到的前列腺癌发生率之间存在近乎完美的相关性。
我们将饱和活检列线图的准确性从 72%提高到 77%；它依赖于三个以前包含的变量，即年龄、%fPSA 和前列腺体积，以及三个以前排除的变量，即 PSA、先前活检次数和先前活检中的 ASAP 证据。我们的研究代表了迄今为止最大的饱和活检系列。
