The impact and indications for Oncotype DX on adjuvant treatment recommendations when third-party funding is unavailable.

OBJECTIVES: Industry-supported decision impact studies demonstrate that Oncotype Dx (ODX) changes treatment recommendations (TR) in 24-40% of hormone receptor+/HER2- patients. ODX is not reimbursed by third-party payers in Australia, potentially resulting in more selective use. We sought to evaluate the impact of self-funded ODX on TRs. METHODS: Data collected included demographics, tumor characteristics, indication for ODX and pre- and post-recurrence score (RS) TR. Primary endpoint was frequency of TR change and associations with TR change were sought. RESULTS: Eighteen physicians contributed 382 patients (median age 54). A total of 232 (61%) of tumors were T1 and were grade 1, 2 and 3 in 49 (13%), 252 (66%) and 79 (21%). A total of 257 (67%) were node negative. Assay indications were: confirm need for chemotherapy (CT) (36%), confirm omission of CT (40%) and genuine equipoise (24%). RS was low (≤17) in 55%, intermediate (18-31) in 36% and high (≥32) in 9%. Thirty-eight percent of patients had TR change post-ODX. Sixty-five percent of patients recommended CT pre-ODX changed to hormone therapy alone (HT)-more likely if lower grade and if ER and/or PR > 10%. Fourteen percent of patients with pre-ODX TR for HT added CT-more likely if ER and/or PR ≤10% and if Ki67 > 15% Overall, TR for CT decreased from 47% to 24%. CONCLUSION: Patient-funded ODX changed TRs in 38% of patients, de-escalating 65% from CT to HT and adding CT to 14% of those recommended HT. These changes were greater than an industry-funded study suggesting that physicians can identify situations where the assay may influence decisions.

Benefit-cost and cost-effectiveness analysis: theory and application.

Benefit-cost analysis and cost-effectivensss analysis are terms used with increasing frequency by health planners and those concerned with review and evaluation of specific programs. The economic bases for these formal techniques are however often obscured by adaptations of convenience or misapplications of the concepts by biological scientists (and others). This paper reviews briefly the theory of benefit-cost analysis and its potential as a tool in choosing programs of optimum size, of maximum economic efficiency as a given size, and in choosing amongst worthwhile alternative projects. Because of the difficulties of quantification of necessary data and the political nature of many policy decisions, the technique of benefit-cost analysis seldom finds application but cost-effectiveness emerges as a calculus of more practical use and acceptability. Examples are drawn from WHO papers and the medical literature to illustrate the "benefits and risks" of these techniques.