Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden.
Br J Radiol. 2013 May;86(1025):20130015. doi: 10.1259/bjr.20130015. Epub 2013 Mar 11.
The aim of this study was to compare patient-specific radiobiological parameters with population averages in predicting the clinical outcome after radiotherapy (RT) using a tumour control probability (TCP) model based on the biological effective dose (BED).
A previously published study of 46 head and neck carcinomas with individually identified radiobiological parameters, radiosensitivity and potential doubling time (Tpot), and known tumour size was investigated. These patients had all been treated with external beam RT, and the majority had also received brachytherapy. The TCP for each individual based on the BED using patient-specific radiobiological parameters was compared with the TCP based on the BED using average radiobiological parameters (α=0.3 Gy(-1), Tpot=3 days).
43 patients remained in the final analysis. There was only a weak trend for increasing local tumour control with increasing BED in both groups. However, when the TCP was calculated, the use of patient-specific parameters was better for identifying local control correctly. The sensitivity and specificity for tumour-specific parameters were 63% and 80%, respectively. The corresponding values for population-based averages were 0% and 91%, respectively. The positive predictive value was 92% when tumour-specific parameters were used compared with 0% for population-based averages. A receiver operating characteristic curve confirmed the superiority of patient-specific parameters over population averages in predicting local control.
Individual radiobiological parameters are better than population-derived averages when used in a mathematical model to predict TCP after curative RT in head and neck carcinomas.
TCP based on individual radiobiological parameters is better than TCP based on population-based averages for identifying local control correctly.
本研究旨在通过基于生物有效剂量（BED）的肿瘤控制概率（TCP）模型，比较患者特异性放射生物学参数与群体平均值，预测放疗（RT）后的临床结果。
研究了 46 例头颈部癌患者的一项先前发表的研究，这些患者具有单独确定的放射生物学参数、放射敏感性和潜在倍增时间（Tpot）以及已知的肿瘤大小。这些患者均接受了外照射 RT，大多数患者还接受了近距离治疗。使用患者特异性放射生物学参数的 BED 计算每个个体的 TCP，并与使用平均放射生物学参数（α=0.3 Gy(-1)，Tpot=3 天）的 BED 计算的 TCP 进行比较。
43 例患者仍纳入最终分析。两组患者的局部肿瘤控制率均随 BED 的增加而呈微弱上升趋势。然而，当计算 TCP 时，使用患者特异性参数更能正确识别局部控制。肿瘤特异性参数的敏感性和特异性分别为 63%和 80%。基于群体平均值的相应值分别为 0%和 91%。与基于群体平均值的 0%相比，使用肿瘤特异性参数时，阳性预测值为 92%。受试者工作特征曲线证实，在预测头颈部癌根治性 RT 后 TCP 时，患者特异性参数优于群体平均值。
在数学模型中，个体放射生物学参数比基于群体的平均值更能准确预测头颈部癌根治性 RT 后的 TCP。
基于个体放射生物学参数的 TCP 比基于群体平均值的 TCP 更能正确识别局部控制。
