Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA.
Department of Radiation Oncology, Massachusetts General Hospital & Harvard Medical School, Boston, USA.
Radiother Oncol. 2020 Jun;147:8-14. doi: 10.1016/j.radonc.2020.02.022. Epub 2020 Mar 27.
The goal of this study was to assess whether a model-based approach applied retrospectively to a completed randomized controlled trial (RCT) would have significantly altered the selection of patients of the original trial, using the same selection criteria and endpoint for testing the potential clinical benefit of protons compared to photons.
A model-based approach, based on three widely used normal tissue complication probability (NTCP) models for radiation pneumonitis (RP), was applied retrospectively to a completed non-small cell lung cancer RCT (NCT00915005). It was assumed that patients were selected by the model-based approach if their expected ΔNTCP value was above a threshold of 5%. The endpoint chosen matched that of the original trial, the first occurrence of severe (grade ≥3) RP.
Our analysis demonstrates that NTCP differences between proton and photon therapy treatments may be too small to support a model-based trial approach for lung cancer using RP as the normal tissue endpoint. The analyzed lung trial showed that less than 19% (32/165) of patients enrolled in the completed trial would have been enrolled in a model-based trial, prescribing photon therapy to all other patients. The number of patients enrolled was also found to be dependent on the type of NTCP model used for evaluating RP, with the three models enrolling 3%, 13% or 19% of patients. This result does show limitations in NTCP models which would affect the success of a model-based trial approach. No conclusion regarding the development of RP in patients randomized by the model-based approach could statistically be made.
Uncertainties in the outcome models to predict NTCP are the inherent drawback of a model-based approach to clinical trials. The impact of these uncertainties on enrollment in model-based trials depends on the predicted difference between the two treatment arms and on the set threshold for patient stratification. Our analysis demonstrates that NTCP differences between proton and photon therapy treatments may be too small to support a model-based trial approach for specific treatment sites, such as lung cancer, depending on the chosen normal tissue endpoint.
本研究旨在评估在使用相同选择标准和终点来测试质子相对于光子的潜在临床获益的情况下，回顾性地将基于模型的方法应用于已完成的随机对照试验（RCT），是否会显著改变原始试验患者的选择。
回顾性地将基于三种广泛使用的放射性肺炎（RP）正常组织并发症概率（NTCP）模型的基于模型的方法应用于已完成的非小细胞肺癌 RCT（NCT00915005）。假设如果患者的预期ΔNTCP 值高于 5%的阈值，则通过基于模型的方法选择患者。选择的终点与原始试验匹配，即首次发生严重（等级≥3）RP。
我们的分析表明，质子和光子治疗之间的 NTCP 差异可能太小，无法支持使用 RP 作为正常组织终点的肺癌基于模型的试验方法。分析的肺部试验表明，在已完成的试验中，只有不到 19%（32/165）的患者将被纳入基于模型的试验中，所有其他患者均接受光子治疗。还发现纳入的患者数量取决于用于评估 RP 的 NTCP 模型的类型，三个模型分别纳入了 3%、13%或 19%的患者。该结果确实表明 NTCP 模型存在局限性，这将影响基于模型的试验方法的成功。不能对通过基于模型的方法随机分组的患者的 RP 发展做出统计学结论。
用于预测 NTCP 的结果模型中的不确定性是临床试验基于模型方法的固有缺点。这些不确定性对基于模型试验纳入的影响取决于两个治疗臂之间的预测差异以及用于患者分层的设定阈值。我们的分析表明，取决于所选的正常组织终点，质子和光子治疗之间的 NTCP 差异可能太小，无法支持特定治疗部位（如肺癌）的基于模型的试验方法。
