Analysis of three decision-making methods: a breast cancer patient as a model.

Purpose: To compare three decision making techniques using a common clinical problem.

Methods: Two recently developed methods, the analytic hierarchy process (AHP) and the analytic network process (ANP), were compared with a Markov process in the evaluation of the optimal post-lumpectomy treatment strategy for an elderly woman with a mammographically detected, nonpalpable early-stage breast cancer. The following treatment alternatives were considered: observation, radiation, tamoxifen, combination radiation and tamoxifen, and simple mastectomy. All three decision methods incorporated patient preferences.

Results: The models agreed on the ranking of the preferred treatment, radiation and tamoxifen, but there were variations in the rankings of the other treatment choices. Individual differences between the three models were uncovered. The Markov process provided estimates of quality-adjusted life expectancy and distribution of health events. Both AHP and ANP required less development time than the Markov process.

Conclusion: All three methods may be useful tools to the clinician in analyzing complex medical problems. The Markov is the most labor-intensive method but provides detailed results, whereas the AHP and the ANP give only rank orders of the alternatives. The most important considerations in choosing between these methods are time to project completion and the detail of information sought.