Decreased Use of Adjuvant Breast Cancer Therapy in a Randomized Controlled Trial of a Decision Aid with Individualized Risk Information

Abstract

This study illustrates the important impact of medical decision aids on treatment choices, particularly for patients for whom treatment has little benefit. In the case of adjuvant therapy for breast cancer, providing individualized, evidence-based risk information for shared decision making resulted in fewer women with low tumor severity choosing adjuvant treatment.

Contextual factors in shared decision making: a randomised controlled trial in women with a strong suspicion of breast cancer

“…30% of patients with early breast cancer decided for adjuvant treatment. Although one study reported no effect on adjuvant treatment decision making either (Whelan et al, 2003), a decrease in adjuvant chemotherapy uptake in the group of patients who received a decision aid has been reported (Peele et al, 2005;Siminoff et al, 2006). Owing to the size of the subsample results on uptake rates of preoperative chemotherapy decision making have to be considered as preliminary.…”

“…Although not all studies showed benefits (Goel et al, 2001), intervention studies in patients with newly diagnosed breast cancer found that decision aids increase patient knowledge (Sawka et al, 1998;Whelan et al, 2003Whelan et al, , 2004 and affect surgical (Street et al, 1995;Molenaar et al, 2001;Katz et al, 2005;Lantz et al, 2005) as well as adjuvant treatment decision making (Peele et al, 2005;Siminoff et al, 2006).…”

Conditional survival in head and neck squamous cell carcinoma

“…Additionally, we must remind ourselves that risk stratification based on large-scale population data such as SEER must always be interpreted clinically for individual patients, whose specific risk factors must be carefully weighed. Other anatomical cancer sites have publicly available risk-assessment tools such as the downloadable MSKCC Prediction Tools, 34 Numeracy, 36 or Adjuvant!, 17,18,[35][36][37][38] whereas at present no such tool is widely accessible for head and neck cancers. Similarly, using datasets with greater treatment-related and staging specificity, 25,26 as well as accounting for competing causes of mortality and comorbidities, would only improve assessment of real-time risk.…”

“…Using the publicly available download of the most recent release of the SEER 17 as well as SEERStat 6.2.3, 18 we analyzed survival data from all patients diagnosed with HNSCC between 1973 and 1998. Cases diagnosed until 1998 were included to ensure at least 5 years of follow-up data (through December, 2003).…”

“…CS probabilities were calculated using the actuarial life table method included in the SEER*Stat software. 18 The calculations were then confirmed by product-limit calculation using JMP 6 (SAS Institute, Cary, NC) and graphics were generated using SPSS 11 (SPSS, Chicago, IL) and StatView 5.0.1 (SAS). We computed observed 5-year CS and stratified results by: age (>65 vs <65), historic SEER stage A, and specified subsites.…”