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Erschienen in: Cancer Chemotherapy and Pharmacology 1/2018

26.04.2018 | Original Article

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

verfasst von: Laurent Claret, Christina Pentafragka, Sanja Karovic, Binsheng Zhao, Lawrence H. Schwartz, Michael L. Maitland, Rene Bruno

Erschienen in: Cancer Chemotherapy and Pharmacology | Ausgabe 1/2018

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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.
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Literatur
1.
Zurück zum Zitat Bruno R, Mercier F, Claret L (2014) Evaluation of tumor-size response metrics to predict survival in oncology clinical trials. Clin Pharmacol Ther 95:386–393CrossRefPubMed Bruno R, Mercier F, Claret L (2014) Evaluation of tumor-size response metrics to predict survival in oncology clinical trials. Clin Pharmacol Ther 95:386–393CrossRefPubMed
2.
Zurück zum Zitat Venkatakrishnan K, Friberg LE, Ouellet D et al (2015) Optimizing oncology therapeutics through quantitative clinical pharmacology: challenges and opportunities. Clin Pharmacol Ther 97:37–54CrossRefPubMed Venkatakrishnan K, Friberg LE, Ouellet D et al (2015) Optimizing oncology therapeutics through quantitative clinical pharmacology: challenges and opportunities. Clin Pharmacol Ther 97:37–54CrossRefPubMed
3.
Zurück zum Zitat Claret L, Girard P, Hoff PM et al (2009) Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J Clin Oncol 27:4103–4108CrossRefPubMed Claret L, Girard P, Hoff PM et al (2009) Model-based prediction of phase III overall survival in colorectal cancer on the basis of phase II tumor dynamics. J Clin Oncol 27:4103–4108CrossRefPubMed
4.
Zurück zum Zitat Claret L, Gupta M, Han K et al (2013) Evaluation of tumor size response metrics to predict overall survival in western and Chinese patients with first line metastatic colorectal cancer. J Clin Oncol 31:2110–2114CrossRefPubMed Claret L, Gupta M, Han K et al (2013) Evaluation of tumor size response metrics to predict overall survival in western and Chinese patients with first line metastatic colorectal cancer. J Clin Oncol 31:2110–2114CrossRefPubMed
5.
Zurück zum Zitat Sharma MR, Gray E, Goldberg RM et al (2015) Resampling the N9741 trial to compare tumor dynamic versus conventional end points in randomized phase II trials. J Clin Oncol 33:36–41CrossRefPubMed Sharma MR, Gray E, Goldberg RM et al (2015) Resampling the N9741 trial to compare tumor dynamic versus conventional end points in randomized phase II trials. J Clin Oncol 33:36–41CrossRefPubMed
6.
Zurück zum Zitat Venook AP, Tabernero J (2015) Progression-free survival: helpful biomarker or clinically meaningless end point? J Clin Oncol 33:4–6CrossRefPubMed Venook AP, Tabernero J (2015) Progression-free survival: helpful biomarker or clinically meaningless end point? J Clin Oncol 33:4–6CrossRefPubMed
7.
Zurück zum Zitat Therasse P, Arbuck SG, Eisenhauer EA et al (2000) New guidelines to evaluate the response to treatment in solid tumors. J Natl Cancer Inst 92:205–216CrossRefPubMed Therasse P, Arbuck SG, Eisenhauer EA et al (2000) New guidelines to evaluate the response to treatment in solid tumors. J Natl Cancer Inst 92:205–216CrossRefPubMed
8.
Zurück zum Zitat Li CH, Bies RR, Wang Y et al (2016) Comparative effects of CT imaging measurement on RECIST end points and tumor growth kinetics modeling. Clin Transl Sci 9(1):43–50CrossRefPubMedPubMedCentral Li CH, Bies RR, Wang Y et al (2016) Comparative effects of CT imaging measurement on RECIST end points and tumor growth kinetics modeling. Clin Transl Sci 9(1):43–50CrossRefPubMedPubMedCentral
9.
Zurück zum Zitat Zhao B, Lee SM, Lee HJ et al (2014) Variability in assessing treatment response: metastatic colorectal cancer as a paradigm. Clin Cancer Res 20(13):3560–3568CrossRefPubMedPubMedCentral Zhao B, Lee SM, Lee HJ et al (2014) Variability in assessing treatment response: metastatic colorectal cancer as a paradigm. Clin Cancer Res 20(13):3560–3568CrossRefPubMedPubMedCentral
10.
Zurück zum Zitat Van Cutsem E, Tabernero J, Lakomy R et al (2012) Addition of aflibercept to fluorouracil, leucovorin, and irinotecan improves survival in a phase III randomized trial in patients with metastatic colorectal cancer previously treated with an oxaliplatin-based regimen. J Clin Oncol 30:3499–3506CrossRefPubMed Van Cutsem E, Tabernero J, Lakomy R et al (2012) Addition of aflibercept to fluorouracil, leucovorin, and irinotecan improves survival in a phase III randomized trial in patients with metastatic colorectal cancer previously treated with an oxaliplatin-based regimen. J Clin Oncol 30:3499–3506CrossRefPubMed
11.
Zurück zum Zitat Tabernero J, Van Cutsem E, Lakomý R et al (2014) 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. Eur J Cancer 50:320–331CrossRefPubMed Tabernero J, Van Cutsem E, Lakomý R et al (2014) 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. Eur J Cancer 50:320–331CrossRefPubMed
12.
Zurück zum Zitat Yang H, Schwartz LH, Zhao B (2016) A response assessment platform for development and validation of imaging biomarkers in oncology. Tomography 2(4):406–410CrossRefPubMedPubMedCentral Yang H, Schwartz LH, Zhao B (2016) A response assessment platform for development and validation of imaging biomarkers in oncology. Tomography 2(4):406–410CrossRefPubMedPubMedCentral
13.
Zurück zum Zitat Tan Y, Schwartz LH, Zhao B (2013) Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. Med Phys 40(4):043502CrossRefPubMedPubMedCentral Tan Y, Schwartz LH, Zhao B (2013) Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. Med Phys 40(4):043502CrossRefPubMedPubMedCentral
14.
16.
17.
Zurück zum Zitat Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723CrossRef Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723CrossRef
18.
Zurück zum Zitat Schindler E, Krishnan SM, Mathijssen RHJ et al (2017) Pharmacometric modeling of liver metastases’ diameter, volume, and density and their relation to clinical outcome in imatinib-treated patients with gastrointestinal stromal tumors. CPT Pharmacomet Syst Pharmacol 6:449–457CrossRef Schindler E, Krishnan SM, Mathijssen RHJ et al (2017) Pharmacometric modeling of liver metastases’ diameter, volume, and density and their relation to clinical outcome in imatinib-treated patients with gastrointestinal stromal tumors. CPT Pharmacomet Syst Pharmacol 6:449–457CrossRef
19.
Zurück zum Zitat Zheng Y, Narwal R, Jin C, Baverel PG et al (2018) Population modeling of tumor kinetics and overall survival to identify prognostic and predictive biomarkers of efficacy for durvalumab in patients with urothelial carcinoma. Clin Pharmacol Ther 103:643–652CrossRefPubMedPubMedCentral Zheng Y, Narwal R, Jin C, Baverel PG et al (2018) Population modeling of tumor kinetics and overall survival to identify prognostic and predictive biomarkers of efficacy for durvalumab in patients with urothelial carcinoma. Clin Pharmacol Ther 103:643–652CrossRefPubMedPubMedCentral
20.
Zurück zum Zitat Desmée S, Mentré F, Veyrat-Follet C, Guedj J (2015) Nonlinear mixed-effect models for prostate-specific antigen kinetics and link with survival in the context of metastatic prostate cancer: a comparison by simulation of two-stage and joint approaches. AAPS J 17:691–699CrossRefPubMedPubMedCentral Desmée S, Mentré F, Veyrat-Follet C, Guedj J (2015) Nonlinear mixed-effect models for prostate-specific antigen kinetics and link with survival in the context of metastatic prostate cancer: a comparison by simulation of two-stage and joint approaches. AAPS J 17:691–699CrossRefPubMedPubMedCentral
Metadaten
Titel
Comparison of tumor size assessments in tumor growth inhibition-overall survival models with second-line colorectal cancer data from the VELOUR study
verfasst von
Laurent Claret
Christina Pentafragka
Sanja Karovic
Binsheng Zhao
Lawrence H. Schwartz
Michael L. Maitland
Rene Bruno
Publikationsdatum
26.04.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Cancer Chemotherapy and Pharmacology / Ausgabe 1/2018
Print ISSN: 0344-5704
Elektronische ISSN: 1432-0843
DOI
https://doi.org/10.1007/s00280-018-3587-7

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