Ontology highlight
ABSTRACT: Purpose
To quantify the influence of RS assay on changing chemotherapy plans in a general practice setting using causal inference methods.Methods
We surveyed 3880 newly diagnosed breast cancer patients in Los Angeles and Georgia in 2013-14. We used inverse propensity weighting and multiple imputations to derive complete information for each patient about treatment status with and without testing.Results
A half of the 1545 women eligible for testing (ER+ or PR+, HER2-, and stage I-II) received RS. We estimate that 30% (95% confidence interval (CI) 10-49%) of patients would have changed their treatment selections after RS assay, with 10% (CI 0-20%) being encouraged to undergo chemotherapy and 20% (CI 10-30%) being discouraged from chemotherapy. The subgroups whose treatment selections would be changed the most by RS were patients with positive nodes (44%; CI 24-64%), larger tumor (43% for tumor size >2 cm; CI 23-62%), or younger age (41% for <50 years, CI 23-58%). The assay was associated with a net reduction in chemotherapy use by 10% (CI 4-16%). The reduction was much greater for women with positive nodes (31%; CI 21-41%), larger tumor (30% for tumor size >2 cm; CI 22-38%), or younger age (22% for <50 years; CI 9-35%).Conclusion
RS substantially changed chemotherapy treatment selections with the largest influence among patients with less favorable pre-test prognosis. Whether this is optimal awaits the results of clinical trials addressing the utility of RS testing in selected subgroups.
SUBMITTER: Li Y
PROVIDER: S-EPMC5243200 | biostudies-literature | 2017 Feb
REPOSITORIES: biostudies-literature
Li Yun Y Kurian Allison W AW Bondarenko Irina I Taylor Jeremy M G JMG Jagsi Reshma R Ward Kevin C KC Hamilton Ann S AS Katz Steven J SJ Hofer Timothy P TP
Breast cancer research and treatment 20161223 3
<h4>Purpose</h4>To quantify the influence of RS assay on changing chemotherapy plans in a general practice setting using causal inference methods.<h4>Methods</h4>We surveyed 3880 newly diagnosed breast cancer patients in Los Angeles and Georgia in 2013-14. We used inverse propensity weighting and multiple imputations to derive complete information for each patient about treatment status with and without testing.<h4>Results</h4>A half of the 1545 women eligible for testing (ER+ or PR+, HER2-, and ...[more]