In my previous analysis of the top five Asian cancers , I did not delve deeply into the relationship between primary endpoints for later-stage oncology trials (phase II, II/III and III), outcomes and pharmacogenomic biomarkers. In this blog series, I will do just that – first by sponsor type, then by disease and finally by start year. The methodology I used in my analysis is listed below.
- In early January 2015, 3,277 completed and terminated, phase II-III, Asian trials in Lung, Gastric, Breast, Colorectal and Liver cancers were exported from Trialtrove.
- A subset of 681 trials had one of five clearly positive (Completed, Positive outcome or Terminated, Early positive outcome) or clearly negative (Completed, Negative outcome, Terminated, Lack of efficacy or Terminated, Safety/adverse effects) outcomes.
- Of this group, 440 trials, which had one of four efficacy primary endpoints common to later-stage oncology trials, Disease Free Survival (DFS) – 13%, Progression Free Survival (PFS) – 44%, Overall Survival (OS) – 45% and Time to Progression (TTP) – 3%, were analyzed for this blog.
- This subset was coded to differentiate between those trials that used a pharmacogenomic (PGX) biomarker to select or stratify patients (DFS-PGX, PFS-PGX, OS-PGX and TTP-PGX) and those that did not (DFS, PFS, OS and TTP).
- PGX biomarkers were used for selection or stratification with 17% (DFS), 34% (PFS), 10% (OS) and 8% (TTP) of trials.
Overall, the number of trials with positive outcomes for primary endpoints was about equal to the number of trials with negative outcomes. This parity held true if trials were jointly sponsored, but not if trials had only one type of sponsor. Industry sponsored trials were completed or terminated with more negative than positive primary outcomes; while non-industry sponsored trials resulted in the opposite. Only four of the top ten industry sponsors, Eli Lilly, Otsuka/Taiho, Roche and Sanofi, had more positive than negative primary outcomes (data not shown).
Besides sponsor type, the choice of primary endpoints also influenced the primary trial outcome. Overall, trials with DFS, PFS or TTP as the primary endpoint resulted in more positive than negative outcomes while trials with OS resulted in the opposite. Industry sponsored trials resulted in more positive than negative primary outcomes with just DFS while non-industry sponsored trials resulted in more positive primary outcomes with PFS and TTP.
Finally, the use of PGX biomarkers to select or stratify patients was more likely to be associated with a positive than negative primary outcome only with PFS as the primary endpoint, regardless of sponsor type. However, this difference was noticeable with just completed rather than terminated trials. Outcomes for trials using a PGX biomarker to select or stratify patients with the other three primary endpoints were almost equal in their outcomes. As mentioned earlier in this blog, the subset of trials using a PGX biomarker to select or stratify patients was very small. Therefore, the correlation of PGX biomarker selection or stratification to outcomes would benefit from a more select pool of trials in which the use of PGX biomarkers was greater.
For my next blog, I will continue my analysis of the outcomes, endpoints and the use of PGX biomarkers for selection or stratification in this set of later-stage trials for each of the top five Asian cancers.