Poster Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2017

Can time to progression on last line treatment inform us about post-progression survival time in advanced gastric cancer? (#204)

Anuradha Vasista 1 , Andrew Martin 2 , Nick Pavlakis 3 , Katrin M Sjoquist 2 , David Goldstein 4 , Jeremy Shapiro 5 , Chris Karapetis 6 , Sanjeev Gill 7 , Vikram Jain 8 , Geoffrey Liu 9 , George Kannourakis 10 , Yeul Hong Kim 11 , Louise Wigston (Nott) 12 , Stephanie Snow 13 , Dean Harris 14 , Derek Jonker 15 , Yu Jo Chua 16 , Martin Stockler 2 , Belinda Kiely 2
  1. NMHRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia
  2. NHMRC Clinical Trials Centre, University of Sydney, Camperdown, NSW, Australia
  3. Medical Oncology, Royal North Shore Hospital, Sydney, NSW, Australia
  4. Prince of Wales Hospital, Sydney, NSW, Australia
  5. Cabrini Hospital, Melbourne, VIC, Australia
  6. Flinders Medical Centre, Adelaide, SA, Australia
  7. The Alfred, Melbourne, VIC
  8. ICON Cancer Foundation, Brisbane, QLD
  9. University Health Network, Princess Margaret Hospital, Toronto, Canada
  10. Ballarat Oncology and Haematology Services, Ballarat
  11. Korea University Hospital, Seoul, South Korea
  12. Royal Hobart Hospital, Hobart, TAS
  13. Queen Elizabeth II Health Sciences Centre, Halifax, Canada
  14. Christchurch Hospital, Christchurch, New Zealand
  15. Medical Oncology, Ottawa Health Research Institute, Ottawa, Canada
  16. Canberra Hospital, Canberra, ACT, Australia


We aimed to determine if an individual’s time to progression on their most recent line of anticancer treatment (TTPi) could be used to predict their subsequent post-progression survival time (PPSTi) and construct scenarios for survival time. 


Patients with refractory, advanced gastric cancer allocated regorafenib in the INTEGRATE trial were eligible if they had a documented date of progression. We hypothesized that in each individual, TTPi would be a significant predictor of their subsequent PPSTi. For each patient we calculated the ratio of PPSTi:TTPi.  Based on our previous research we determined if simple multiples of the median PPSTi:TTPi ratio could be used to estimate bounds for an individual’s PPSTi based on their TTPi - worst case (shortest 10% of PPSTi ≤ 1/4 x ratio x TTPi), typical (middle 50% of PPSTi = 1/2 to 2 x ratio x TTPi) and best case (longest 10% of PPSTi ≥ 3 x ratio x TTPi) scenarios. 


Median TTP was 1.8 months and median PPST 3.6 months, giving a ratio of 2. The median of the 62 PPSTi:TTPi ratios was similar at 1.9. TTPi was not a strong predictor of PPSTi (HR 0.89, p=0.08), but scenarios for PPSTi based on simple multiples were remarkably accurate: as hypothesised, 10% died within 1/4 of their estimated survival time, 50% had a survival time from half to double their estimated survival time; however, 23% had a survival time ≥3 times their estimated survival time, higher than our hypothesised 10%. 


The relationship between TTP on the last line of therapy and subsequent PPST was modest, but scenarios for survival time based on simple multiples of an estimated survival time based on 2xTTPi provided accurate estimates for worst and typical case scenarios, but underestimated the best case scenario.