Prognostic Significance, Accuracy and Usefulness of Oncologists Estimates of Survival Time for Patients Starting First Line Chemotherapy for Advanced Non-Small Cell Lung Cancer (ANSCLC) — ASN Events
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Prognostic Significance, Accuracy and Usefulness of Oncologists Estimates of Survival Time for Patients Starting First Line Chemotherapy for Advanced Non-Small Cell Lung Cancer (ANSCLC) (#49)

Belinda E Kiely 1 , Anne-Sophie Veillard 1 , John A Davidson 2 , Mateya E Trinkaus 3 , Karen P Briscoe 4 , Brett GM Hughes 5 , Stephen Begbie 6 , Nick Pavlakis 7 , Michael Millward 8 , Michael Boyer 9 , Chris Brown 1 , Nick Muljadi 1 , Xanthi Coskinas 1 , Martin Stockler 1 9 10
  1. NHMRC Clinical Trials Centre, Camperdown, NSW, Australia
  2. Medical Oncology, Royal Perth Hospital, Perth, WA, Australia
  3. Medical Oncology, Markham Stouffville Hospital, University of Toronto, Markham, ON, Canada
  4. Medical Oncology, Coffs Harbour Health Campus, Coffs Harbour, NSW, Australia
  5. Medical Oncology, The Prince Charles Hospital, Brisbane, QLD, Australia
  6. Medical Oncology, Port Macquarie Base Hospital, Port Macquarie, NSW, Australia
  7. Royal North Shore Hospital, University of Sydney, Sydney, NSW, Australia
  8. Medical Oncology, Sir Charles Gardner Hospital, Perth, WA, Australia
  9. Medical Oncology, Sydney Cancer Centre, Sydney, NSW, Australia
  10. Sydney Medical School, University of Sydney, Sydney, NSW, Australia

Aim: To determine the accuracy and prognostic significance of oncologists’ estimates of survival time for patients with ANSCLC.
Methods: Medical oncologists recorded the “expected survival time in months” for individual patients with ANSCLC prior to randomisation in a trial of first-line platinum-based chemotherapy. Estimates within 0.75-1.33 times observed survival were deemed precise. We expected 50% of patients to live longer (or shorter) than their oncologist’s estimate (calibration), 50% to live from half to double their estimate (typical scenario); 5-10% to live ≤¼ of their estimate (worst-case scenario); and, 5-10% to live ≥3 times their estimate (best-case scenario). Associations between estimated and observed survival times were assessed with Cox proportional hazards regression.
Results: Estimates of survival were available for 244 (98%) of the first 250 patients randomised. After a median follow-up of 21 months there were 172 deaths (69%). The median (interquartile range) for observed survival was 10 months (5-20) and for estimated survival was 11 months (9-12). Oncologists’ estimates were imprecise (22% from 0.75-1.33 times observed) but well calibrated (53% lived longer than expected). The proportion of patients with an observed survival time: ≤1/4 of their estimated survival time was 10%; half to double their estimated survival time was 53%; and ≥3 times their estimated survival time was 13%. The oncologist’s estimate of survival time at baseline was the strongest predictor of observed survival in both univariate analysis (HR 0.90, 95% CI 0.86-0.95, p<0.001) and multivariate analysis (HR 0.90, 95% CI 0.86-0.95, p<0.001) accounting for all other independent significant predictors, namely: estimated neutrophil-lymphocyte ratio >5 (HR 3.15, 95% CI 1.76-5.64, p<0.001); haemoglobin <120g/L (HR 1.93, 95% CI 1.3-2.9, p=0.001) and total white cell count >11x109/L (HR 1.55, 95% CI 1.05-2.27, p=0.03).
Conclusions: Oncologists’ estimates of survival time were well-calibrated, independently associated with observed survival and a reasonable basis for estimating worst-case, typical and best-case scenarios for survival.