Mehta Vikas, Rycyna Kevin, Baesens Bart M M, Barkan Güliz A, Paner Gladell P, Flanigan Robert C, Wojcik Eva M, Venkataraman Girish
Department of Pathology, Loyola University Medical Center, Maywood, IL 60153, USA.
Int J Clin Exp Pathol. 2012;5(6):496-502. Epub 2012 Jul 29.
Biopsy Gleason score (bGS) remains an important prognostic indicator for adverse outcomes in Prostate Cancer (PCA). In the light of recent studies purporting difference in prognostic outcomes for the subgroups of GS7 group (primary Gleason pattern 4 vs. 3), upgrading of a bGS of 6 to a GS≥7 has serious implications. We sought to identify pre-operative factors associated with upgrading in a cohort of GS6 patients who underwent prostatectomy.
We identified 281 cases of GS6 PCA on biopsy with subsequent prostatectomies. Using data on pre-operative variables (age, PSA, biopsy pathology parameters), logistic regression models (LRM) were developed to identify factors that could be used to predict upgrading to GS≥7 on subsequent prostatectomy. A decision tree (DT) was constructed.
92 of 281 cases (32.7%) were upgraded on subsequent prostatectomy. LRM identified a model with two variables with statistically significant ability to predict upgrading, including pre-biopsy PSA (Odds Ratio 8.66; 2.03-37.49, 95% CI) and highest percentage of cancer at any single biopsy site (Odds Ratio 1.03, 1.01-1.05, 95% CI). This two-parameter model yielded an area under curve of 0.67. The decision tree was constructed using only 3 leave nodes; with a test set classification accuracy of 70%.
A simplistic model using clinical and biopsy data is able to predict the likelihood of upgrading of GS with an acceptable level of certainty. External validation of these findings along with development of a nomogram will aid in better stratifying the cohort of low risk patients as based on the GS.
活检 Gleason 评分(bGS)仍然是前列腺癌(PCA)不良预后的重要预测指标。鉴于最近有研究表明 GS7 组的亚组(主要 Gleason 模式 4 与 3)在预后结果上存在差异,将 bGS 为 6 升级为 GS≥7 具有严重影响。我们试图在接受前列腺切除术的 GS6 患者队列中确定与升级相关的术前因素。
我们确定了 281 例活检为 GS6 PCA 且随后接受前列腺切除术的病例。利用术前变量(年龄、前列腺特异性抗原、活检病理参数)的数据,建立了逻辑回归模型(LRM)以确定可用于预测后续前列腺切除术中升级为 GS≥7 的因素。构建了决策树(DT)。
281 例病例中有 92 例(32.7%)在后续前列腺切除术中升级。LRM 确定了一个包含两个具有统计学显著预测升级能力变量的模型,包括活检前前列腺特异性抗原(比值比 8.66;2.03 - 37.49,95%置信区间)和任何单个活检部位癌症的最高百分比(比值比 1.03,1.01 - 1.05,95%置信区间)。这个双参数模型的曲线下面积为 0.67。决策树仅使用 3 个叶节点构建;测试集分类准确率为 70%。
一个使用临床和活检数据的简单模型能够以可接受的确定水平预测 GS 升级的可能性。对这些发现进行外部验证以及开发列线图将有助于根据 GS 更好地对低风险患者队列进行分层。