TY - JOUR
T1 - Accuracy and Prognostic Significance of Oncologists' Estimates and Scenarios for Survival Time in A Randomised Phase II Trial of Regorafenib in Advanced Gastric Cancer
AU - Vasista, A
AU - Martin, Andrew
AU - Pavlakis, N.
AU - Sjoquist, Katrin
AU - Snow, Stephanie
AU - Jonker, Derek J
AU - Chua, YuJo
AU - Epstein, Richard
AU - Bonaventura, Antonino
AU - Khasraw, M
AU - Varma, Suresh
PY - 2017
Y1 - 2017
N2 - Background: We have proposed that best, worst and typical scenarios for survival, based on simple multiples of an individual's expected survival time (EST) estimated by their oncologist, are a useful way of formulating and explaining prognosis in advanced cancer. We aimed to determine the accuracy and prognostic significance of such estimates in a multicentre, randomised trial. Methods: Sixtysix oncologists estimated the EST at baseline for each of 152 participants in the INTEGRATE trial. We expected oncologists estimates of EST to be well calibrated (∼50% of patients living longer than their EST) and imprecise (<33% living within 0.671.33 times their EST), but to provide accurate scenarios for survival time (∼10% dying within a quarter of their EST, ∼10% living longer than three times their EST and ∼50% living for half to double their EST). We hypothesised that oncologists estimates of EST would be independently predictive of overall survival in a Cox model including conventional prognostic factors. Results: Oncologists estimates of EST were well calibrated (45% shorter than observed), imprecise (29% lived within 0.671.33 times observed), and moderately discriminative (Harrell Cstatistic 0.62, P = 0.001). Scenarios derived from oncologists estimates were remarkably accurate: 9% of patients died within a quarter of their EST, 12% lived longer than three times their EST and 57% lived within half to double their EST. Oncologists estimates of EST were independently significant predictors of overall survival (HR = 0.89; 95% CI, 0.830.95; P = 0.001) in a Cox model including conventional prognostic factors. Conclusions: Oncologists estimates of survival time were well calibrated, moderately discriminative and independently significant predictors of overall survival. Best, worst and typical scenarios for survival based on simple multiples of the EST were remarkably accurate and would provide a useful method for estimating and explaining prognosis in this setting.
AB - Background: We have proposed that best, worst and typical scenarios for survival, based on simple multiples of an individual's expected survival time (EST) estimated by their oncologist, are a useful way of formulating and explaining prognosis in advanced cancer. We aimed to determine the accuracy and prognostic significance of such estimates in a multicentre, randomised trial. Methods: Sixtysix oncologists estimated the EST at baseline for each of 152 participants in the INTEGRATE trial. We expected oncologists estimates of EST to be well calibrated (∼50% of patients living longer than their EST) and imprecise (<33% living within 0.671.33 times their EST), but to provide accurate scenarios for survival time (∼10% dying within a quarter of their EST, ∼10% living longer than three times their EST and ∼50% living for half to double their EST). We hypothesised that oncologists estimates of EST would be independently predictive of overall survival in a Cox model including conventional prognostic factors. Results: Oncologists estimates of EST were well calibrated (45% shorter than observed), imprecise (29% lived within 0.671.33 times observed), and moderately discriminative (Harrell Cstatistic 0.62, P = 0.001). Scenarios derived from oncologists estimates were remarkably accurate: 9% of patients died within a quarter of their EST, 12% lived longer than three times their EST and 57% lived within half to double their EST. Oncologists estimates of EST were independently significant predictors of overall survival (HR = 0.89; 95% CI, 0.830.95; P = 0.001) in a Cox model including conventional prognostic factors. Conclusions: Oncologists estimates of survival time were well calibrated, moderately discriminative and independently significant predictors of overall survival. Best, worst and typical scenarios for survival based on simple multiples of the EST were remarkably accurate and would provide a useful method for estimating and explaining prognosis in this setting.
M3 - Meeting Abstract
SN - 1743-7555
SP - 138
EP - 138
JO - Asia-Pacific Journal of Clinical Oncology
JF - Asia-Pacific Journal of Clinical Oncology
T2 - COSA's 44th Annual Scientific Meeting, Immunotherapy: Molecules and Mountains
Y2 - 1 January 2017
ER -