DOES BIOMARKER INFORMATION IMPACT BREAST CANCER PATIENTS' PREFERENCES FOR THERAPY?

Purpose: Biomarker information can risk stratify patients based on potential for benefit/toxicity from therapy. Ideally, a biomarker will identify those who benefit with limited or no toxicity. However, for some medicines, such as bevacizumab, early biomarker studies suggest that patients who may benefit also have increased toxicity.  The purpose of this study was to examine how biomarker information would impact patients' preferences for therapy in this situation.

Method:  We surveyed participants at the 18 month follow-up assessment in a large, international double blind randomized controlled trial, ECOG5103. For this trial, participants with breast cancer were randomized to receive adjuvant chemotherapy with either placebo or bevacizumab.  We asked patients for their preferred treatment (either chemotherapy A alone or chemotherapy A+B) in two hypothetical scenarios: 1) baseline without biomarker information; and 2) after learning that they tested positive for a “B-receptor” which increased both the benefit and toxicity of chemotherapy A+B. The risk information was given in both numerical (table) and graphical (100-person pictograph) format. We asked participants for the main reason for their choice. McNemar’s test was used to examine changes in treatment preferences.

Result: 439 patients completed both scenarios on 18-month survey. Table 1 shows the participants’ treatment preferences in each scenario. The increase in benefit and toxicity associated with the positive biomarker information in scenario 2 led 60/439 (14%) participants to switch their preference. Among participants who changed preference, those randomized to receive bevacizumab were more likely to switch to chemotherapy A in scenario 2. Among all participants, the main reason reported for their treatment preference in scenario 2 was greater benefits of chemotherapy A+B (64%), the lower risks with chemotherapy A (20%) and positive biomarker (10%). 

Table 1: Participants’ treatment preferences in scenario 1 and 2 (chemo=chemotherapy)

		Scenario 2: With “positive B-receptor”
		Preferred chemo A	Preferred chemo A+B	Total
Scenario 1: Without biomarker information	Preferred chemo A	73	28	101
	Preferred chemo A+B	32	306	338
	Total	105	334	439

Conclusion:  Information about a positive biomarker indicating increased benefit and increased toxicity from additional chemotherapy did not change many participants’ preferred treatment. The majority (70%) preferred the most aggressive course of treatment in both scenarios. Whether patients not enrolled in the trial would be more sensitive to the increased toxicity information is unclear.