Individualised Predictions of the Survival Benefit Due to Adjuvant Therapy in a Randomised Trial of Sorafenib after Nephrectomy for Localised Renal Cell Carcinoma

BACKGROUND: Little has been published regarding how doctors think and talk about prognosis and the potential benefits of adjuvant therapy. OBJECTIVE: We sought predictions of survival rates and survival times, for patients with and without adjuvant therapy, from the clinicians of patients participating in a randomised trial of adjuvant sorafenib after nephrectomy for renal cell carcinoma. METHODS: A subset of medical oncologists and urologists in the SORCE trial completed questionnaires eliciting their predictions of survival rates and survival times, with and without adjuvant sorafenib, for each of their participating patients. To compare predictions elicited as survival times versus survival rates, we transformed survival times to survival rates. To compare predicted benefits elicited as absolute improvements in rates and times, we transformed them into hazard ratios (HR), a measure of relative benefit.We postulated that a plausible benefit in overall survival (OS) should be smaller than that hypothesized for disease–free survival (DFS) in the trials original sample size justification (i.e. HR for OS should be ≥ 0.75). RESULTS: Sixty–one medical oncologists and 17 urologists completed questionnaires on 216 patients between 2007 and 2013. Predictions of survival without adjuvant sorafenib were similar whether elicited as survival rates or survival times (median 5–year survival rate of 61% vs 60%, p = 0.6). Predicted benefits of sorafenib were larger when elicited as improvements in survival rates than survival times (median HR 0.76 vs 0.83, p < 0.0001). The proportion of HR for predicted OS with sorafenib that reflected a plausible benefit (smaller effect of sorafenib on OS than hypothesized on DFS, i.e. HR ≥ 0.75) was 51% for survival rates, and 65% for survival times. CONCLUSIONS: The predicted benefits of adjuvant sorafenib were larger when elicited as improvements in survival rates than as survival times, and were often larger than the sample size justification for the trial. These potential biases should be considered when thinking and talking about individual patients in clinical practice, and when designing clinical trials