Physician uncertainty aversion impacts medical decision making for older patients with acute myeloid leukemia: results of a national survey

Elderly patients with acute myeloid leukemia can be treated with intensive chemotherapy, low-intensity therapy such as low-dose aracytine or hypomethylating agents, or best supportive care. The choice between these treatments is a function of many patient-related and disease-related factors. We investigated how physicians’ behavioral characteristics affect medical decision-making between intensive and non-intensive therapy in this setting. A nationwide cross-sectional online survey of hematologists collected data on medical decision-making for 6 clinical vignettes involving older acute myeloid leukemia patients that were representative of routine practice. Questionnaires elicited physicians’ demographic and occupational characteristics along with their individual behavioral characteristics according to a decision theory framework. From the pattern of responses to the vignettes, a K-means clustering algorithm was used to distinguish those who were likely to prescribe more intensive therapy and those who were likely to prescribe less intensive or no therapy. Multivariate analyses were used to identify physician’s characteristics predictive of medical decision-making. We obtained 230 assessable answers, which represented an adjusted response rate of 45.4%. A multivariate model (n=210) revealed that physicians averse to uncertainty recommend significantly more intensive chemotherapy: Odds Ratio (OR) [95% Confidence Interval (CI)]: 1.15 [1.01;1.30]; P=0.039. Male physicians who do not conform to the expected utility model (assumed as economically irrational) recommend more intensive chemotherapy [OR (95% CI) = 3.45 (1.34; 8.85); P=0.01]. Patient volume per physician also correlated with therapy intensity [OR (95% CI)=0.98 (0.96; 0.99); P=0.032]. The physicians’ medical decision-making was not affected by their age, years of experience, or hospital facility. The significant association between medical decision and individual behavioral characteristics of the physician identifies a novel non-biological factor that may affect acute myeloid leukemia patients’ outcomes and explain variations in clinical practice. It should also encourage the use of validated predictive models and the description of novel bio-markers to best select patients for intensive chemotherapy or low-intensity therapy.