Journal
ONCOLOGIST
Volume 20, Issue 7, Pages 798-805Publisher
ALPHAMED PRESS
DOI: 10.1634/theoncologist.2014-0429
Keywords
Dabrafenib; Dacarbazine; BRAF V600E mutation-positive melanoma; Overall survival; Survival analysis
Categories
Funding
- GlaxoSmithKline [NCT01227889]
- GlaxoSmithKline
- National Institute for Health Research Senior Investigator Award [NI-SI-0508-10061]
- National Institute for Health Research [NF-SI-0512-10159] Funding Source: researchfish
Ask authors/readers for more resources
Background. Patients with previously untreated BRAF V600E mutation-positive melanoma in BREAK-3 showed a median overall survival (OS) of 18.2 months for dabrafenib versus 15.6 months for dacarbazine (hazard ratio [HR], 0.76; 95% confidence interval, 0.48-1.21). Because patients receiving dacarbazine were allowed to switch to dabrafenib at disease progression, we attempted to adjust for the confounding effects on OS. Materials and Methods. Rank preserving structural failure time models (RPSFTMs) and the iterative parameter estimation (IPE) algorithm were used. Two analyses, treatment group (assumes treatment effect could continue until death) and on-treatment observed (assumes treatment effect disappears with discontinuation), were used to test the assumptions around the durability of the treatment effect. Results. A total of 36 of 63 patients (57%) receiving dacarbazine switched to dabrafenib. The adjusted OS HRs ranged from 0.50 to 0.55, depending on the analysis. The RPSFTM and IPE treatment group and on-treatment observed analyses performed similarly well. Conclusion. RPSFTM and IPE analyses resulted in point estimates for the OS HR that indicate a substantial increase in the treatment effect compared with the unadjusted OS HR of 0.76. The results are uncertain because of the assumptions associated with the adjustment methods. The confidence intervals continued to cross 1.00; thus, the adjusted estimates did not provide statistically significant evidence of a treatment benefit on survival. However, it is clear that a standard intention-to-treat analysis will be confounded in the presence of treatment switching-a reliance on unadjusted analyses could lead to inappropriate practice. Adjustment analyses provide useful additional information on the estimated treatment effects to inform decision making.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available