Research in cancer care increasingly focuses on survivorship issues, e.g. managing disease- and treatment-related morbidity and mortality occurring during and after treatment. This necessitates innovative approaches that consider treatment side effects in addition to tumor cure. Current treatment-planning methods rely on constrained iterative optimization of dose distributions as a surrogate for health outcomes. The goal of this study was to develop a generally applicable method to directly optimize projected health outcomes. We developed an outcome-based objective function to guide selection of the number, angle, and relative fluence weight of photon and proton radiotherapy beams in a sample of ten prostate-cancer patients by optimizing the projected health outcome. We tested whether outcome-optimized radiotherapy (OORT) improved the projected longitudinal outcome compared to dose-optimized radiotherapy (DORT) first for a statistically significant majority of patients, then for each individual patient. We assessed whether the results were influenced by the selection of treatment modality, late-risk model, or host factors. The results of this study revealed that OORT was superior to DORT. Namely, OORT maintained or improved the projected health outcome of photon- and proton-therapy treatment plans for all ten patients compared to DORT. Furthermore, the results were qualitatively similar across three treatment modalities, six late-risk models, and 10 patients. The major finding of this work was that it is feasible to directly optimize the longitudinal (i.e. long- and short-term) health outcomes associated with the total (i.e. therapeutic and stray) absorbed dose in all of the tissues (i.e. healthy and diseased) in individual patients. This approach enables consideration of arbitrary treatment factors, host factors, health endpoints, and times of relevance to cancer survivorship. It also provides a simpler, more direct approach to realizing the full beneficial potential of cancer radiotherapy.

癌症护理的研究越来越关注生存问题，例如管理治疗期间和治疗后发生的与疾病和治疗相关的发病率和死亡率。这需要创新方法，除了肿瘤治愈外，还要考虑治疗副作用。当前的治疗计划方法依赖于剂量分布的约束迭代优化作为健康结果的替代。本研究的目标是开发一种普遍适用的方法来直接优化预计的健康结果。我们开发了一个基于结果的目标函数，通过优化预测的健康结果来指导在 10 名前列腺癌患者样本中选择光子和质子放疗束的数量、角度和相对能量密度。我们首先测试了结果优化放疗 (OORT) 与剂量优化放疗 (DORT) 相比是否改善了预期的纵向结果，首先是针对统计学上显着的大多数患者，然后是每个患者。我们评估了结果是否受到治疗方式选择、晚期风险模型或宿主因素的影响。这项研究的结果表明，OORT 优于 DORT。也就是说，与 DORT 相比，OORT 维持或改善了所有 10 名患者的光子和质子治疗计划的预期健康结果。此外，三种治疗方式、六种晚期风险模型和 10 名患者的结果在性质上相似。这项工作的主要发现是直接优化纵向（即 与个体患者所有组织（即健康和患病）的总（即治疗和杂散）吸收剂量相关的长期和短期）健康结果。这种方法可以考虑任意治疗因素、宿主因素、健康终点以及与癌症存活相关的时间。它还提供了一种更简单、更直接的方法来实现癌症放射治疗的全部有益潜力。