Effects of Prognostic Communication Strategies on Prognostic Perceptions, Treatment Decisions and End-Of-Life Anticipation in Advanced Cancer: An Experimental Study among Analogue Patients

Evidence-based guidance for oncologists on how to communicate prognosis is scarce. To investigate the effects of prognostic communication strategies (prognostic disclosure vs. communication of unpredictability vs. non-disclosure; standard vs. standard and best-case vs. standard, best- and worst-case survival scenarios; numerical vs. word-based estimates) on prognostic perceptions, treatment decision-making and end-of-life anticipation in advanced cancer. This experimental study used eight videos of a scripted oncological consultation, varying only in prognostic communication strategies. Cancer-naive individuals, who imagined being the depicted patient, completed surveys before and after watching one video (n = 1036). Individuals generally perceived dying within 1 year as more likely after prognostic disclosure, compared to communication of unpredictability or non-disclosure (P < 0.001), and after numerical versus word-based estimates (P < 0.001). Individuals felt better informed about prognosis to decide about treatment after prognostic disclosure, compared to communication of unpredictability or non-disclosure (P < 0.001); after communication of unpredictability versus non-disclosure (P < 0.001); and after numerical versus word-based estimates (P = 0.017). Chemotherapy was more often favored after prognostic disclosure versus non-disclosure (P = 0.010), but less often after numerical versus word-based estimates (P < 0.001). Individuals felt more certain about the treatment decision after prognostic disclosure, compared to communication of unpredictability or non-disclosure (P < 0.001). Effects of different survival scenarios were absent. No effects on end-of-life anticipation were observed. Evidence for moderating individual characteristics was limited. If and how oncologists discuss prognosis can influence how individuals perceive prognosis, which treatment they prefer, and how they feel about treatment decisions. Communicating numerical estimates may stimulate prognostic understanding and informed treatment decision-making.