Zaider M, Zelefsky M J, Hanin L G, Tsodikov A D, Yakovlev A Y, Leibel S A
Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA.
Phys Med Biol. 2001 Oct;46(10):2745-58. doi: 10.1088/0031-9155/46/10/315.
This paper explores the applicability of a mechanistic survival model, based on the distribution of clonogens surviving a course of fractionated radiation therapy, to clinical data on patients with prostate cancer. The study was carried out using data on 1,100 patients with clinically localized prostate cancer who were treated with three-dimensional conformal radiation therapy. The patients were stratified by radiation dose (group 1: <67.5 Gy; group 2: 67.5-72.5 Gy; group 3: 72.5-77.5 Gy; group 4: 77.5-87.5 Gy) and prognosis category (favourable, intermediate and unfavourable as defined by pre-treatment PSA and Gleason score). A relapse was recorded when tumour recurrence was diagnosed or when three successive prostate specific antigen (PSA) elevations were observed from a post-treatment nadir PSA level. PSA relapse-free survival was used as the primary end point. The model, which is based on an iterated Yule process, is specified in terms of three parameters: the mean number of tumour clonogens that survive the treatment, the mean of the progression time of post-treatment tumour development and its standard deviation. The model parameters were estimated by the maximum likelihood method. The fact that the proposed model provides an excellent description both of the survivor function and of the hazard rate is prima facie evidence of the validity of the model because closeness of the two survivor functions (empirical and model-based) does not generally imply closeness of the corresponding hazard rates. The estimated cure probabilities for the favourable group are 0.80, 0.74 and 0.87 (for dose groups 1-3, respectively); for the intermediate group: 0.25, 0.51, 0.58 and 0.78 (for dose groups 1-4, respectively) and for the unfavourable group: 0.0, 0.27, 0.33 and 0.64 (for dose groups 1-4, respectively). The distribution of progression time to tumour relapse was found to be independent of prognosis group but dependent on dose. As the dose increases the mean progression time decreases (41, 28.5, 26.2 and 14.7 months for dose groups 1-4, respectively). This analysis confirms that, in terms of cure rate, dose escalation has a significant positive effect only in the intermediate and unfavourable groups. It was found that progression time is inversely proportional to dose, which means that patients recurring in higher dose groups have shorter recurrence times, yet these groups have better survival, particularly long-term. The explanation for this seemingly illogical observation lies in the fact that less aggressive tumours, potentially recurring after a long period of time, are cured by higher doses and do not contribute to the recurrence pattern. As a result, patients in higher dose groups are less likely to recur; however, if they do, they tend to recur earlier. The estimated hazard rates for prostate cancer pass through a clear-cut maximum, thus revealing a time period with especially high values of instantaneous cancer-specific risk; the estimates appear to be nonproportional across dose strata.
本文探讨了一种基于分次放射治疗过程中存活的克隆原细胞分布的机械生存模型对前列腺癌患者临床数据的适用性。该研究使用了1100例接受三维适形放射治疗的临床局限性前列腺癌患者的数据。患者按放射剂量(第1组:<67.5 Gy;第2组:67.5 - 72.5 Gy;第3组:72.5 - 77.5 Gy;第4组:77.5 - 87.5 Gy)和预后类别(根据治疗前前列腺特异性抗原(PSA)和 Gleason 评分定义为有利、中等和不利)进行分层。当诊断出肿瘤复发或从治疗后最低PSA水平观察到连续三次PSA升高时记录复发情况。无PSA复发存活时间用作主要终点。该模型基于迭代尤尔过程,由三个参数指定:治疗后存活的肿瘤克隆原细胞的平均数、治疗后肿瘤发展的进展时间的均值及其标准差。模型参数通过最大似然法估计。所提出的模型对生存函数和风险率都提供了出色的描述,这一事实初步证明了模型的有效性,因为两个生存函数(经验性的和基于模型的)的接近并不通常意味着相应风险率的接近。有利组的估计治愈概率分别为0.80、0.74和0.87(分别对应剂量组1 - 3);中等组:0.25、0.51、0.58和0.78(分别对应剂量组1 - 4),不利组:0.0、0.27、0.33和0.64(分别对应剂量组1 - 4)。发现肿瘤复发的进展时间分布与预后组无关,但与剂量有关。随着剂量增加,平均进展时间减少(剂量组1 - 4分别为41、28.5、26.2和14.7个月)。该分析证实,就治愈率而言,剂量递增仅在中等和不利组中有显著的积极影响。发现进展时间与剂量成反比,这意味着在高剂量组中复发的患者复发时间较短,但这些组的生存率更高,尤其是长期生存率。对这一看似不合逻辑的观察结果的解释在于,侵袭性较小的肿瘤可能在较长时间后复发,会被更高剂量治愈,并且不会对复发模式产生影响。因此,高剂量组的患者复发可能性较小;然而,如果他们复发,往往会更早复发。前列腺癌估计风险率通过一个明确的最大值,从而揭示了一个瞬时癌症特异性风险值特别高的时间段;估计值在不同剂量层之间似乎不成比例。