Ataman Ozlem Uruk, Barrett Ann, Filleron Thomas, Kramar Andrew
Dokuz Eylul University Oncology Institute, Inciralti, Izmir, Turkey.
Radiother Oncol. 2006 Jan;78(1):95-100. doi: 10.1016/j.radonc.2005.09.012. Epub 2005 Oct 26.
The European Society for Therapeutic Radiology and Oncology was funded by the EU for a project on Recording providing Education, and Ameliorating the Consequences of Treatment (REACT). An important aim of follow-up (FU) after treatment for cancer is to detect various events associated with disease recurrence or metastatic spread or severe treatment-related complications as early as possible. Each tumour type may show a specific pattern and timing of these events related to different prognostic factors. The aim of this study was to propose a way of defining an optimal timing schedule for follow-up after treatment based on the analysis of failure patterns determined from follow-up data from prospective clinical trials.
Cox proportional hazards model was used to identify prognostic factors associated with each failure type (loco-regional recurrence (LR), distant metastasis (DM) or side effects (SE)). Competing risks methods were applied to estimate the cumulative incidence functions (CIF), adjusted on the significant prognostic factors. Equally spaced quantiles of the CIF were then used to estimate the corresponding optimised follow-up times depending on a pre-specified total number of visits. Follow-up data from the CHART bronchus clinical trial were used to analyse the pattern of time to first failure.
A significantly higher risk of failure was observed for males (SE), stage III (DM) and conventional treatment (LR). Overall, patients treated with CHART needed 1 fewer visit in each category of patients compared to the Conventional group. For example, stage III male patients treated with CHART would need 8 visits during the first two years at 7, 11, 16, 24, 37, 52, 64 and 104 weeks rather than the 9 follow-up visits planned in the protocol. Similar patients treated with Conventional radiotherapy would need 8 visits at 3, 5, 7, 11, 15, 24, 52 and 104 weeks.
Use of these methods would allow timing of follow-up visits to be adapted according to tumour site and prognostic factors determined previously from audit or clinical trials. Application of this approach could optimize the timing of follow-up visits by placing them closer to the times when failures are expected to occur. It does not address the wider issues of follow-up such as who should do it or what should be done for which further studies are required.
欧洲放射治疗与肿瘤学治疗学会由欧盟资助开展了一项关于记录、提供教育及改善治疗后果（REACT）的项目。癌症治疗后随访的一个重要目标是尽早发现与疾病复发、转移扩散或严重治疗相关并发症有关的各种事件。每种肿瘤类型可能会呈现出与不同预后因素相关的这些事件的特定模式和时间规律。本研究的目的是基于对来自前瞻性临床试验随访数据所确定的失败模式的分析，提出一种确定治疗后随访最佳时间安排的方法。
采用Cox比例风险模型来识别与每种失败类型（局部区域复发（LR）、远处转移（DM）或副作用（SE））相关的预后因素。应用竞争风险方法来估计累积发病率函数（CIF），并根据显著的预后因素进行调整。然后，根据预先指定的访视总次数，使用CIF的等间距分位数来估计相应的优化随访时间。来自CHART支气管临床试验的随访数据用于分析首次失败时间的模式。
男性（副作用）、Ⅲ期（远处转移）和传统治疗（局部区域复发）的失败风险显著更高。总体而言，与传统治疗组相比，接受CHART治疗的患者在各患者类别中每次所需的访视次数少1次。例如，接受CHART治疗的Ⅲ期男性患者在头两年需要在第7、11、16、24、37、52、64和104周进行8次访视，而不是方案中计划的9次随访。接受传统放疗的类似患者需要在第3、5、7、11、15、24、52和104周进行8次访视。
使用这些方法可以根据肿瘤部位和先前通过审核或临床试验确定的预后因素来调整随访访视时间。应用这种方法可以通过将随访访视时间安排得更接近预期失败发生的时间来优化随访时间。它没有解决随访的更广泛问题，例如谁应该进行随访或针对此需要进一步研究应该做什么。
