Factors associated with distinct prognostic-awareness-transition patterns over cancer patients' last 6 months of life

Cancer patients may develop prognostic awareness (PA) heterogeneously, but predictors of PA-transition patterns have never been studied. We aimed to identify transition patterns of PA and their associated factors during cancer patients' last 6 months.

For this secondary-analysis study, PA was assessed among 334 cancer patients when they were first diagnosed as terminally ill and monthly till they died. PA was categorized into four states: (a) unknown and not wanting to know; (b) unknown but wanting to know; (c) inaccurate awareness; and (d) accurate awareness. The first and last PA states estimated by hidden Markov modeling were examined to identify their change patterns. Factors associated with distinct PA-transition patterns were determined by multinomial logistic regressions focused on modifiable time-varying variables assessed in the wave before the last PA assessment to ensure a clear time sequence for associating with PA-transition patterns.

Four PA-transition patterns were identified: maintaining accurate PA (56.3%), gaining accurate PA (20.4%), heterogeneous PA (7.8%), and still avoiding PA (15.6%). Reported physician-prognostic disclosure increased the likelihood of belonging to the maintaining-accurate-PA group than to other groups. Greater symptom distress predisposed patients to be in the still-avoiding-PA than the heterogeneous PA group. Patients with higher functional dependence and more anxiety/depressive symptoms were more and less likely to be in the heterogeneous PA group and in the still-avoiding-PA group, respectively, than in the maintaining- and gaining-accurate PA groups.

Cancer patients heterogeneously experienced PA-transition patterns over their last 6 months. Physicians' prognostic disclosure, and patients' symptom distress, functional dependence, and anxiety/depressive symptoms, all modifiable by high-quality end-of-life care, were associated with distinct PA-transition patterns.