• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

VELOUR 研究二线结直肠癌数据中肿瘤生长抑制-总生存期模型中肿瘤大小评估的比较。

Comparison of tumor size assessments in tumor growth inhibition-overall survival models with second-line colorectal cancer data from the VELOUR study.

机构信息

Pharsight Consulting Services, Pharsight, a Certara™ Company, Marseille, France.

Genentech/Roche, Marseille, France.

出版信息

Cancer Chemother Pharmacol. 2018 Jul;82(1):49-54. doi: 10.1007/s00280-018-3587-7. Epub 2018 Apr 26.

DOI:10.1007/s00280-018-3587-7
PMID:29700575
Abstract

PURPOSE

To compare lesion-level and volumetric measures of tumor burden with sum of the longest dimensions (SLD) of target lesions on overall survival (OS) predictions using time-to-growth (TTG) as predictor.

METHODS

Tumor burden and OS data from a phase 3 randomized study of second-line FOLFIRI ± aflibercept in metastatic colorectal cancer were available for 918 patients out of 1216 treated (75%). A TGI model that estimates TTG was fit to the longitudinal tumor size data (nonlinear mixed effect modeling) to estimate TTG with: SLD, sum of the measured lesion volumes (SV), individual lesion diameters (ILD), or individual lesion volumes (ILV). A parametric OS model was built with TTG estimates and assessed for prediction of the hazard ratio (HR) for survival.

RESULTS

Individual lesions had consistent dynamics within individuals. Between-lesion variability in rate constants was lower (typically < 27% CV) than inter-patient variability (typically > 50% CV). Estimates of TTG were consistent (around 12 weeks) across tumor size assessments. TTG was highly significant in a log-logistic parametric model of OS (median over 12 months). When individual lesions were considered, TTG of the fastest progressing lesions best predicted OS. TTG obtained from the lesion-level analyses were slightly better predictors of OS than estimates from the sums, with ILV marginally better than ILD. All models predicted VELOUR HR equally well and all predicted study success.

CONCLUSION

This analysis revealed consistent TGI profiles across all tumor size assessments considered. TTG predicted VELOUR HR when based on any of the tumor size measures.

摘要

目的

比较使用生长时间(TTG)作为预测因子时,肿瘤负担的病变水平和体积测量值与目标病变最长径(SLD)总和在总生存(OS)预测中的表现。

方法

在转移性结直肠癌二线 FOLFIRI±aflibercept 的 3 期随机研究中,有 1216 例患者(75%)中有 918 例可获得肿瘤负担和 OS 数据。采用非线性混合效应模型拟合纵向肿瘤大小数据,建立 TGI 模型,以估计 TTG:SLD、测量病变体积总和(SV)、单个病变直径(ILD)或单个病变体积(ILV)。建立了一个包含 TTG 估计值的参数 OS 模型,并评估其对生存风险比(HR)的预测能力。

结果

个体病变在个体内具有一致的动力学。与个体间变异性(通常>50% CV)相比,速率常数的病变间变异性较低(通常<27% CV)。在各种肿瘤大小评估中,TTG 估计值是一致的(约 12 周)。在 OS 的对数逻辑参数模型中,TTG 具有高度显著性(中位数超过 12 个月)。当考虑个体病变时,进展最快的病变的 TTG 最好地预测了 OS。从病变水平分析中获得的 TTG 是 OS 的略优预测指标,而总和的估计值则略逊一筹,其中 ILV 比 ILD 略好。所有模型对 VELOUR HR 的预测能力均相当,且均预测了研究成功。

结论

本分析揭示了在所有考虑的肿瘤大小评估中,TGI 具有一致的特征。基于任何肿瘤大小测量值,TTG 均能预测 VELOUR HR。

相似文献

1
Comparison of tumor size assessments in tumor growth inhibition-overall survival models with second-line colorectal cancer data from the VELOUR study.VELOUR 研究二线结直肠癌数据中肿瘤生长抑制-总生存期模型中肿瘤大小评估的比较。
Cancer Chemother Pharmacol. 2018 Jul;82(1):49-54. doi: 10.1007/s00280-018-3587-7. Epub 2018 Apr 26.
2
Aflibercept Plus FOLFIRI vs. Placebo Plus FOLFIRI in Second-Line Metastatic Colorectal Cancer: a Post Hoc Analysis of Survival from the Phase III VELOUR Study Subsequent to Exclusion of Patients who had Recurrence During or Within 6 Months of Completing Adjuvant Oxaliplatin-Based Therapy.阿柏西普联合 FOLFIRI 对比安慰剂联合 FOLFIRI 二线治疗转移性结直肠癌:排除辅助奥沙利铂治疗完成后 6 个月内或期间复发的患者后,III 期 VELOUR 研究的生存事后分析。
Target Oncol. 2016 Jun;11(3):383-400. doi: 10.1007/s11523-015-0402-9.
3
Observed benefit and safety of aflibercept in elderly patients with metastatic colorectal cancer: An age-based analysis from the randomized placebo-controlled phase III VELOUR trial.在转移性结直肠癌老年患者中观察到阿柏西普的获益和安全性:来自随机安慰剂对照 III 期 VELOUR 试验的基于年龄的分析。
J Geriatr Oncol. 2018 Jan;9(1):32-39. doi: 10.1016/j.jgo.2017.07.010. Epub 2017 Aug 12.
4
Prognostic Nomogram and Patterns of Use of FOLFIRI-Aflibercept in Advanced Colorectal Cancer: A Real-World Data Analysis.预测列线图和 FOLFIRI-阿柏西普在晚期结直肠癌中的应用模式:真实世界数据分析。
Oncologist. 2019 Aug;24(8):e687-e695. doi: 10.1634/theoncologist.2018-0824. Epub 2019 May 30.
5
Evaluation of tumor-size response metrics to predict overall survival in Western and Chinese patients with first-line metastatic colorectal cancer.评估肿瘤大小反应指标,以预测一线转移性结直肠癌中西方和中国患者的总生存期。
J Clin Oncol. 2013 Jun 10;31(17):2110-4. doi: 10.1200/JCO.2012.45.0973. Epub 2013 May 6.
6
Aflibercept versus placebo in combination with fluorouracil, leucovorin and irinotecan in the treatment of previously treated metastatic colorectal cancer: prespecified subgroup analyses from the VELOUR trial.阿柏西普联合氟尿嘧啶、亚叶酸钙和伊立替康治疗既往治疗的转移性结直肠癌:VELOUR 试验的预先指定亚组分析。
Eur J Cancer. 2014 Jan;50(2):320-31. doi: 10.1016/j.ejca.2013.09.013. Epub 2013 Oct 16.
7
[The inhibition of angiogenic pathway in second line treatment of metastatic colorectal cancer.].
Recenti Prog Med. 2018 Nov;109(11):15e-19e. doi: 10.1701/3031.30301.
8
Resampling the N9741 trial to compare tumor dynamic versus conventional end points in randomized phase II trials.重新抽样N9741试验,以比较随机II期试验中肿瘤动力学终点与传统终点。
J Clin Oncol. 2015 Jan 1;33(1):36-41. doi: 10.1200/JCO.2014.57.2826. Epub 2014 Oct 27.
9
Aflibercept for metastatic colorectal cancer: safety data from the Spanish named patient program.阿柏西普用于转移性结直肠癌:来自西班牙指定患者项目的安全性数据。
Expert Opin Drug Saf. 2015 Aug;14(8):1171-9. doi: 10.1517/14740338.2015.1057495. Epub 2015 Jun 16.
10
Randomized phase III study of panitumumab with fluorouracil, leucovorin, and irinotecan (FOLFIRI) compared with FOLFIRI alone as second-line treatment in patients with metastatic colorectal cancer.一项比较帕尼单抗联合氟尿嘧啶、亚叶酸钙和伊立替康(FOLFIRI)与单独 FOLFIRI 二线治疗转移性结直肠癌患者的随机 III 期研究。
J Clin Oncol. 2010 Nov 1;28(31):4706-13. doi: 10.1200/JCO.2009.27.6055. Epub 2010 Oct 4.

引用本文的文献

1
Oral Delivery of Gemcitabine-Loaded Glycocholic Acid-Modified Micelles for Cancer Therapy.载吉西他滨的糖基化胆酸修饰胶束的口服递药用于癌症治疗。
ACS Nano. 2023 Sep 26;17(18):18074-18088. doi: 10.1021/acsnano.3c04793. Epub 2023 Sep 17.
2
Prediction of overall survival in patients across solid tumors following atezolizumab treatments: A tumor growth inhibition-overall survival modeling framework.预测接受阿特珠单抗治疗的各类实体瘤患者的总生存期:一种肿瘤生长抑制-总生存期建模框架。
CPT Pharmacometrics Syst Pharmacol. 2021 Oct;10(10):1171-1182. doi: 10.1002/psp4.12686. Epub 2021 Aug 4.
3
Which factors matter the most? Revisiting and dissecting antibody therapeutic doses.
哪些因素最重要?重新审视和剖析抗体治疗剂量。
Drug Discov Today. 2021 Aug;26(8):1980-1990. doi: 10.1016/j.drudis.2021.04.022. Epub 2021 Apr 22.
4
Tumor growth inhibition modeling of individual lesion dynamics and interorgan variability in HER2-negative breast cancer patients treated with docetaxel.HER2 阴性乳腺癌患者经多西紫杉醇治疗的个体病灶动态和器官间变异性的肿瘤生长抑制建模。
CPT Pharmacometrics Syst Pharmacol. 2021 May;10(5):511-521. doi: 10.1002/psp4.12629. Epub 2021 May 2.
5
Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models.利用肿瘤动态模型推进癌症临床治疗的进展和机遇。
Clin Cancer Res. 2020 Apr 15;26(8):1787-1795. doi: 10.1158/1078-0432.CCR-19-0287. Epub 2019 Dec 23.
6
Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach.基于机器学习方法的结肠癌分期及生存期预测
Cancers (Basel). 2019 Dec 12;11(12):2007. doi: 10.3390/cancers11122007.