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超越剂量:利用治疗前生物标志物提高非霍奇金淋巴瘤放射免疫治疗结局的剂量预测。

Beyond Dose: Using Pretherapy Biomarkers to Improve Dose Prediction of Outcomes for Radioimmunotherapy of Non-Hodgkin Lymphoma.

机构信息

1 Department of Radiation Oncology, University of Michigan , Ann Arbor, Michigan.

2 Department of Pathology, University of Michigan , Ann Arbor, Michigan.

出版信息

Cancer Biother Radiopharm. 2017 Nov;32(9):309-319. doi: 10.1089/cbr.2017.2182. Epub 2017 Oct 30.

Abstract

INTRODUCTION

Non-Hodgkin Lymphoma patients respond differently to therapy according to inherent biological variations. Pretherapy biomarkers may improve dose-response prediction.

MATERIALS AND METHODS

Hybrid single-photon emission computed tomography (SPECT)/computed tomography (CT) three-dimensional imaging at multiple time points plus follow-up positron emission tomography (PET)/CT or CT at 2 and 6 months post therapy were used to fit tumor response to combined biological effect and cell clearance models from which three biological effect response parameters (radiosensitivity, cold effect sensitivity, and proliferation potential) were determined per patient. A correlation of biological effect parameters and pretherapy biomarker data (ki67, p53, and phospho-histone H3) allowed a dose-based equivalent biological effect (EBE) to be calculated for each patient.

RESULTS

Significant correlations were found between biological effect parameters and pretherapy biomarkers. Optimum correlations were found by splitting the patient data according to p53 status. Response correlation of progression free survival (PFS) and EBE were significantly improved compared with PFS and absorbed dose alone.

CONCLUSIONS

It is possible and desirable to use pretherapy biomarkers to enhance the predictive potential of dose calculations for patient-specific treatment planning.

摘要

简介

非霍奇金淋巴瘤患者对治疗的反应因固有生物学差异而不同。治疗前的生物标志物可以改善剂量反应预测。

材料和方法

在多个时间点进行混合单光子发射计算机断层扫描(SPECT)/计算机断层扫描(CT)三维成像,加治疗后 2 个月和 6 个月的正电子发射断层扫描(PET)/CT 或 CT,以拟合肿瘤对联合生物效应和细胞清除模型的反应,从而确定每个患者的三个生物效应反应参数(辐射敏感性、冷效应敏感性和增殖潜能)。生物效应参数与治疗前生物标志物数据(ki67、p53 和磷酸化组蛋白 H3)的相关性允许为每个患者计算基于剂量的等效生物效应(EBE)。

结果

发现生物效应参数与治疗前生物标志物之间存在显著相关性。根据 p53 状态对患者数据进行分割,可获得最佳相关性。与单独的进展无事件生存率(PFS)和吸收剂量相比,EBE 的 PFS 相关性得到了显著改善。

结论

使用治疗前生物标志物增强剂量计算对患者特异性治疗计划的预测潜力是可能的,也是可取的。

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