Risk-group dependence of dose-response for biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer
Risk-group dependence of dose-response for biopsy outcome after three-dimensional conformal radiation therapy of prostate cancer
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DOI：
10.1016/s0167-8140(02)00062-2
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发表时间：
2002-04-01
影响因子：
5.7
通讯作者：
Ling, CC
中科院分区：
文献类型：
--
作者：
Levegrün, S;Jackson, A;Ling, CC
背景和目的：我们将现象学肿瘤控制概率（TCP）模型拟合到前列腺癌患者的三维适形放射治疗（3D-CRT）后的活检结果，以量化前列腺癌的局部剂量反应。材料和方法：我们分析了在纪念斯隆-凯特琳癌症中心（MSKCC）接受光子束3D-CRT治疗的103例T1 c-T3期前列腺癌患者的结局。（处方目标剂量在64.8和81戈伊之间），在治疗结束后大于或等于2.5年进行了前列腺活检。基于D均值（每例患者计划靶区的平均剂量）的单变量logistic回归模型适用于整个数据集，并分别适用于亚组，其特征在于肿瘤相关预后因素T分期（6）和治疗前前列腺特异性抗原（PSA）（小于或等于10 ng/ml vs.> 10 ng/ml）的低值和高值。此外，我们根据两个或三个预后因素的所有可能组合，评估了将患者分为三个风险组的五种不同分类，并将双变量logistic回归模型与D均值和风险组类别拟合到所有患者。剂量-反应曲线的特征是TCD 50，即控制肿瘤的剂量γ（50）%，和γ（50），在TCD 50剂量-反应曲线的标准化斜率。结果：D-均值与活检结果在所有患者亚组中显著相关，并且观察到与有利预后因素相比，不利预后因素患者的TCD 50值较大。例如，高T分期患者的TCD 50比低T分期患者高7戈伊。对于所有评估的风险组定义，D均值和风险组类别是双变量分析中活检结果的独立预测因子。TCD 50的拟合值显示低风险和高风险患者之间的9-10.6戈伊的明显分离。相应的剂量-反应曲线（γ（50）= 3.4-5.2）比当所有患者一起分析时获得的曲线（γ（50）= 2.9）更陡。结论：通过TCD 50和γ（50）量化的前列腺癌的剂量-反应随预后亚组而变化。我们的观察结果与以下假设一致：临床观察到的局部控制剂量-反应曲线的浅性来自患者人群，该患者人群是具有更陡峭剂量-反应曲线和不同TCD 50值的亚群的异质混合物。这些结果最终可能有助于根据患者个体的治疗前预后因素来识别从剂量递增中获益最大的患者，并指导剂量处方。(C)2002爱思唯尔科学爱尔兰有限公司保留所有权利。
Background and purpose: We fit phenomenological tumor control probability (TCP) models to biopsy outcome after three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer patients to quantify the local dose-response of prostate cancer.Materials and methods: We analyzed the outcome after photon beam 3D-CRT of 103 patients with stage T1c-T3 prostate cancer treated at Memorial Sloan-Kettering Cancer Center (MSKCC) (prescribed target doses between 64.8 and 81 Gy) who had a prostate biopsy performed greater than or equal to2.5 years after end of treatment. A univariate logistic regression model based on D-mean (mean dose in the planning target volume of each patient) was fit to the whole data set and separately to subgroup, characterized by low and high values of tumor-related prognostic factors T-stage (6), and pre-treatment prostate-specific antigen (PSA) (less than or equal to10 ng/ml vs. > 10 ng/ml). In addition, we evaluated five different classifications of the patients into three risk groups, based on all possible combinations of two or three prognostic factors, and fit bivariate logistic regression models with D-mean and the risk group category to all patients. Dose-response curves were characterized by TCD50, the dose to control gamma(50)% of the tumors, and gamma(50), the normalized slope of the dose-response curve at TCD50.Results: D-mean correlates significantly with biopsy outcome in all patient subgroups and larger values of TCD50 are observed for patients with unfavorable compared to favorable prognostic factors. For example, TCD50 for high T-stage patients is 7 Gy higher than for low T-stage patients, For all evaluated risk group definitions, D-mean and the risk group category are independent predictors of biopsy outcome in bivariate analysis. The fit values of TCD50 show a clear separation of 9-10.6 Gy between low and high risk patients. The corresponding dose-response curves are steeper (gamma(50) = 3.4-5.2) than those obtained when all patients are analyzed together (gamma(50) = 2.9).Conclusions: Dose-response of prostate cancer, quantified by TCD50 and gamma(50), varies by prognostic subgroup. Our observations are consistent with the hypothesis that the shallow nature of clinically observed dose-response curves for local control result from a patient population that is a heterogeneous mixture of sub-populations with steeper dose-response curves and varying values of TCD50. Such results may eventually hell) to identify patients, based on their individual pro-treatment prognostic factors, that would benefit most from dose-escalation, and to guide dose prescription. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.