Poster Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2017

Utility values across lines of therapy in immuno-oncology treatments: an example from advanced melanoma (#220)

Dominic Tilden 1 , Will Sierakowski 1 , Suzi Cottrell 1 , Hansoo Kim 2
  1. Thema, Sydney
  2. BMS, Melbourne

Aim:

Cost utility analyses of oncology treatments are most commonly performed using partitioned survival models, applying health state utilities to progression-free and progressive disease and relative to a specific line of therapy. The objective of this study was to assess utility values across treatments and lines of treatment using data in advanced melanoma for two immuno-oncology agents, nivolumab and ipilimumab.

Methods:

Utility values from 1st line (1L) and 2nd line (2L) advanced melanoma populations treated with nivolumab and ipilimumab were extracted from three randomised controlled clinical trials: CheckMate-067 (1L nivolumab and 1L ipilimumab), CheckMate-037 (2L nivolumab) and MDX010-20 (2L ipilimumab). Visual assessment of QoL over time as well as comparisons of baseline and change from baseline values were performed using summary statistics.

Results:

Baseline values for 1L and 2L were similar for nivolumab (0.80 vs 0.75, p=0.001) and ipilimumab (0.79 vs 0.81, p=0.123). Across all lines of therapy nivolumab use resulted in improvements in utility whilst patients remained progression free. Ipilimumab treatment regimens showed initial declines in utilities in the first 3 months followed by improvements over the remainder of time on treatment.

The change in utility from baseline to 12 months was similar for 1L and 2L nivolumab (0.050 v 0.047, p=0.930). Both these changes were greater than that observed for 1L ipilimumab at 12 months (0.035, p=0.533 v 1L nivolumab and p=0.767 v 2L nivolumab). 2L ipilimumab results were limited to short term follow-up, however utility values were comparable to 1L ipilimumab at 5 months (-0.023 v 0.014, p=0.091).

Conclusions:

The quality of life of patients on immune-based therapies appears to be independent of therapy line. Furthermore, economic modelling in an immune-oncology setting should reflect that quality of life looks to be a function of time on treatment.