An online randomised controlled trial of prognosticating imminent death in advanced cancer patients: Clinicians give greater weight to advice from a prognostic algorithm than from another clinician with a different profession.

Abstract

A second opinion or a prognostic algorithm may increase prognostic accuracy. This study assessed the level to which clinicians integrate advice perceived to be coming from another clinician or a prognostic algorithm into their prognostic estimates, and how participant characteristics and nature of advice received affect this. An online double-blind randomised controlled trial was conducted. Palliative doctors, nurses and other types of healthcare professionals were randomised into study arms differing by perceived source of advice (algorithm or another clinician). In fact, the advice was the same in both arms (emanating from the PiPS-B14 prognostic model). Each participant reviewed five patient summaries. For each summary, participants: (1) provided an initial probability estimate of two-week survival (0% 'certain death'-100% 'certain survival'); (2) received advice (another estimate); (3) provided a final estimate. Weight of Advice (WOA) was calculated for each summary (0 '100% advice discounting' - 1 '0% discounting') and multilevel linear regression analyses were conducted. NCT04568629. A total of 283 clinicians were included in the analysis. Clinicians integrated advice from the algorithm more than advice from another clinician (WOA difference=-0.12 [95% CI -0.18, -0.07], p< 0.001). There was no interaction between study arm and participant profession, years of palliative care or overall experience. Advice of intermediate strength (75%) was given a lower WOA (0.31) than advice received at either the 50% (WOA 0.40) or 90% level (WOA 0.43). The overall interaction between strength of advice and study arm on WOA was significant (p< 0.001). Clinicians adjusted their prognostic estimates more when advice was perceived to come from a prognostic algorithm than from another clinician. Research is needed to understand how clinicians make prognostic decisions and how algorithms are used in clinical practice.