The impact of prognosis without treatment on doctors' and patients' resource allocation decisions and its relevance to new drug recommendation processes.

What Is Already Known About This Subject: The dominant health economic units upon which new treatment funding decisions are made are the incremental cost per life year gained (LYG) or the cost per quality-adjusted life year (QALY) gained. Neither of these units modifies the amount of health gained, by the amount of health patients would have had if they had not been given the treatment under consideration, which may unfairly undervalue the treatments for poor prognosis conditions. How certain patients make decisions about their own treatment has previously been explored, but not how they, or doctors, would allocate hypothetical resource within a healthcare system given information on disease-treatment scenarios' prognoses with and without treatment.

What This Study Adds: Information on prognosis without treatment is used within the resource allocation strategies of many doctors and most patients. Individuals use this information in a variety of different ways and a single dominant strategy for quantitative modification of health units is not apparent. Information on prognosis without treatment, or prognosis with standard treatment, is available from the control arm of randomized controlled clinical trials and should be used qualitatively to facilitate decision-making around the second inflexion point on cost per QALY/LYG acceptability curves.

Aims: Health economic assessments increasingly contribute to funding decisions on new treatments. Treatments for many poor prognosis conditions perform badly in such assessments because of high costs and modest effects on survival. We aimed to determine whether underlying shortness of prognosis should also be considered as a modifier in such assessments.

Methods: Two hundred and eighty-three doctors and 201 oncology patients were asked to allocate treatment resource between hypothetical patients with unspecified life-shortening diseases. The prognoses with and without treatment were varied such that consistent use of one of four potential allocation strategies could be deduced: life years gained (LYGs) - which did not incorporate prognosis without treatment information; percentage increase in life years (PILY); life expectancy with treatment (LEWT) or immediate risk of death (IRD).

Results: Random choices were rare; 47% and 64% of doctors and patients, respectively, used prognosis without treatment in their strategies; while 50% and 32%, respectively, used pure LYG-based strategies. Ranking orders were LYG > PILY > IRD > LEWT (doctors) and LEWT > LYG > IRD > PILY (patients). When LYG information alone could not be used, 76% of doctors prioritized shorter prognoses, compared with 45% of patients.

Conclusions: Information on prognosis without treatment is used within the resource allocation strategies of many doctors and most patients, and should be considered as a qualitative modifier during the health economic assessments of new treatments for life-shortening diseases. A single dominant strategy incorporating this information for any quantitative modification of health units is not apparent.