早期预测免疫疗法的反应可能有助于通过识别治疗耐药性并允许调整疗法来指导患者管理。该分析评估了免疫治疗反应的数学模型，该模型使用标准成像扫描中肿瘤大小/负担从基线到第一次随访的初始变化来提供患者特异性结果预测。我们将该模型应用于 600 名晚期晚期患者在研究 1108（一项 I/II 期试验）中接受 durvalumab 的实体瘤，并将结果预测性能与基于大小的标准与 RECIST 1.1 版最佳总体缓解 (BOR)、基线循环肿瘤 (ct)DNA 水平和其他临床/免疫治疗反应的病理预测因子。在多个实体瘤中，在开始 durvalumab (α1) 后约 6 周评估的代表第一次治疗计算机断层扫描 (CT) 扫描时的净肿瘤生长率的数学参数具有预测总生存期的一致性指数（多变量分析的 OS）为 0.66-0.77。这种早期肿瘤动态测量显着改善了多变量 OS 模型，其中包括标准 RECIST v1.1 标准、基线 ctDNA 水平以及预测 OS 的其他临床/病理因素。此外，α1 在第一次治疗 CT 扫描时得到一致评估，而所有传统 RECIST BOR 组仅在此时间后得到确认。这些结果支持进一步探索 α1 作为免疫治疗反应的整体生物标志物。该生物标志物可以预测进一步的益处，并且可以在分配 RECIST 反应组之前进行评估，从而可能提供个性化肿瘤管理的机会。

Early prediction of response to immunotherapy may help guide patient management by identifying resistance to treatment and allowing adaptation of therapies. This analysis evaluated a mathematical model of response to immunotherapy that provides patient-specific prediction of outcome using the initial change in tumor size/burden from baseline to the first follow-up visit on standard imaging scans.We applied the model to 600 patients with advanced solid tumors who received durvalumab in Study 1108, a phase I/II trial, and compared outcome prediction performance versus size-based criteria with RECIST version 1.1 best overall response (BOR), baseline circulating tumor (ct)DNA level, and other clinical/pathologic predictors of immunotherapy response.In multiple solid tumors, the mathematical parameter representing net tumor growth rate at the first on-treatment computed tomography (CT) scan assessed around 6 weeks after starting durvalumab (α1) had a concordance index to predict overall survival (OS) of 0.66-0.77 on multivariate analyses. This measurement of early tumor dynamics significantly improved multivariate OS models that included standard RECIST v1.1 criteria, baseline ctDNA levels, and other clinical/pathologic factors in predicting OS. Furthermore, α1 was assessed consistently at the first on-treatment CT scan, whereas all traditional RECIST BOR groups were confirmed only after this time.These results support further exploring α1 as an integral biomarker of response to immunotherapy. This biomarker may be predictive of further benefit and can be assessed before RECIST response groups can be assigned, potentially providing an opportunity to personalize oncologic management.