Inaccuracies in estimates of life expectancies of patients with bronchial cancer in clinical decision making

Approximations of life expectancy in clinical decision making frequently assume constant disease-specific ("excess") mortality hazards over age at diagnosis and over time from diagnosis. This assumption is inconsistent with the longer relative survival of younger patients with bladder cancer and with the declines in mortality hazards from bladder and breast cancers over time from diagnosis. To estimate the error that may result from these assumptions, the authors derived excess mortality hazards from the Surveillance, Epidemiology and End Result (SEER) tumor registry for bronchial cancers stratified by age at diagnosis and time from diagnosis. They compared the life expectancies calculated by a model using an average constant annual cancer-specific mortality hazard over time from diagnosis with those calculated using data-derived cancer-specific annual mortality hazards that varied as a function of time from diagnosis. For younger patients with less advanced disease, the constant-average-mortality model underestimated life expectancies by up to 50% relative to those predicted by the time-variant model. For those over 75 years old at diagnosis, and for all patients with advanced disease, the constant-average-mortality model overestimated life expectancies by up to 65% relative to those predicted by the time-variant model. The authors conclude that predictions of life expectancy with bronchial cancer, and probably with other neoplasms, are limited by the widespread use of oversimplified methods of calculation and by the lack of data describing mortality hazards as a function of time from diagnosis.(ABSTRACT TRUNCATED AT 250 WORDS)

Decision analysis as a synthetic tool for achieving consensus in technology assessment

Over the past decade the Office of Medical Application of Research (OMAR) of the National Institutes of Health has developed the consensus development conference (18) to assess technologies in cases where the scientific community has been unable, or unwilling, to reach a firm position as to efficacy but which require some better form of assessment than expert opinion (8). Another paper in this issue describes the principles that underlie such conferences (9).

A clinical decision analysis program for the Apple computer

A computer program written in BASIC and implemented on a 48K RAM Apple II computer was developed to assist physicians in using decision analysis to solve clinical problems. Clinicians familiar with decision analysis can easily enter, modify, store, and retrieve decision trees. Probabilities and utilities can be calculated and a sensitivity analysis can be performed and printed. An entire decision tree can be listed, and a graphic display of any node with its branches, branch probabilities, and node utilities can be viewed and printed. The program is easy to use and can be learned in a few hours. Its flexibility and power will facilitate the application of decision analysis to a wide variety of clinical problems.