958P - Tumor growth rate analysis of progression-free survival (PFS) and overall survival (OS) for thyroid cancer patients receiving placebo or sorafenib...

Date 09 October 2016
Event ESMO 2016 Congress
Session Poster display
Topics Anti-Cancer Agents & Biologic Therapy
Thyroid Cancer
Presenter Christian Kappeler
Citation Annals of Oncology (2016) 27 (6): 328-350. 10.1093/annonc/mdw376
Authors C. Kappeler1, G. Meinhardt2, R. Elisei3, M. Brose4, M. Schlumberger5
  • 1Clinical Statistics Eu, Bayer Pharma Aktiengesellschaft, 13353 - Berlin/DE
  • 2Global Clinical Development Oncology, Bayer HealthCare Pharmaceuticals, Whippany/US
  • 3Endocrine Unit, Department Of Clinical And Experimental Medicine, University of Pisa, Pisa/IT
  • 4Department Of Otorhinolaryngology, Abramson Cancer Center, University of Pennsylvania, Perelman School of Medicine, Philadelphia/US
  • 5Nuclear Medicine And Endocrinology, Institut Gustave Roussy, Villejuif/FR

Abstract

Background

In the randomized, controlled phase 3 DECISION trial (NCT00895674), sorafenib (SOR) significantly improved progression-free survival (PFS) vs placebo (PLC) in patients with radioactive iodine refractory differentiated thyroid cancer (HR, 0.587; p 

Methods

The primary endpoint of DECISION was PFS and OS was a secondary endpoint. Target lesions were assessed by central radiologic review every 8 weeks based on RECIST 1.0 criteria. Changes in target lesions over time were approximated by a parabola-like 3-parametric model. TGR was defined as % change per month of sum of target lesion diameters (SLD). To explore the association between TGR and PFS and OS, values of early TGR were split into quartiles separately by treatment arm. PFS (cutoff in 2012) and OS (cutoff 2015) were compared in each subgroup population by median times derived from KM curves and from modeling with a Weibull distribution. Correlation of TGR with maximum reduction in SLDs was examined.

Results

TGR subgroup statistics and median times of PFS and OS are shown in table 1. For these endpoints there is no simple proportional relation between TGR and median PFS or OS times. Better prognosis for PFS and OS is associated with Q2 or Q3 TGR quartiles. Early TGR values close to zero indicate a better prognosis. TGR and SLD show a high correlation.

Conclusions

In this exploratory analysis, stabilization of tumor lesions at treatment start seems to be associated with better PFS and OS outcomes than a pronounced early reduction of tumor lesion sizes. TGR may be an additional efficacy parameter to consider when monitoring SOR treatment.

Weibull model of KM curves; durations in months

PLC SOR
Quartile 1 Quartile 2 Quartile 3 Quartile 4 Quartile 1 Quartile 2 Quartile 3 Quartile 4
Med early TGR - 0.082 0.003 0.026 0.079 - 0.106 - 0.047 - 0.021 0.019
Med PFS 7.9 13.9 6.7 2.8 7.9 12.3 17.6 10.1
Med OS 46.3 47.6 48.2 27.8 34.3 45.4 60.5 35.8

Clinical trial identification

NCT00895674

Legal entity responsible for the study

N/A

Funding

Bayer Healthcare Pharmaceuticals

Disclosure

C. Kappeler: Employee of Bayer Pharma AG. G. Meinhardt: Employee of Bayer Healthcare Pharmaceuticals. R. Elisei: Consultancy fees/honorarium and research support from Bayer Healthcare Pharmaceuticals; and consultancy fees/honorarium from AstraZeneca and Genzyme. M. Brose: Consultancy fees/honorarium/research support from Bayer HealthCare Pharmaceuticals; consultancy fees/research support from Exelixis; consultancy fees from Onyx Pharmaceuticals; and research support from Eisai, Novartis, and Roche/Genentech. M. Schlumberger: Consultancy fees/research support from Bayer Healthcare Pharmaceuticals and Eisai; consultancy fees/honorarium and research support from AstraZeneca and Genzyme-Sanofi; consultancy fees from Exelixis; and consultancy fees/honorarium from Sobi.