scholarly journals Patient and physician factors associated with Oncotype DX and adjuvant chemotherapy utilization for breast cancer patients in New Hampshire, 2010–2016

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Thomas M. Schwedhelm ◽  
Judy R. Rees ◽  
Tracy Onega ◽  
Ronnie J. Zipkin ◽  
Andrew Schaefer ◽  
...  
2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e12014-e12014
Author(s):  
Sowmya Goranta ◽  
Tarek Haykal ◽  
Areeg Bala ◽  
Ragheed Al-Dulaimi ◽  
Ghassan Bachuwa ◽  
...  

e12014 Background: Oncotype-DX Assay is a 21-gene based recurrence score (RS) that helps stratify breast cancer patients based on their risk of recurrence. It is often used to help identify patients that may benefit from adjuvant chemotherapy (AC). Prior to the TAILORx Trial results, there were no guidelines for AC in patients with an intermediate score (18-30). Management of these patients was often at the clinical judgement of the provider. We sought to determine predictors of AC among these patients, and measure treatment effect on survival. Methods: We queried the Surveillance, Epidemiology, and End-Results database for breast cancer patients newly diagnosed between 2010-2015. We included patients with T1-T3, hormone receptor positive, HER2-negative, and lymph node-negative breast cancer with an intermediate RS. Male patients, those younger than 40 years, tumors 5 mm or less, and incomplete records were excluded. Univariate and multivariate analysis was performed to derive independent predictors of AC. Cox Proportional-Hazards Model was done to examine the effect of AC on survival. Results: We included 14,710 patients of whom 4,508 (30.6%) received AC. Patients that received AC were younger (55.4 years [8.8] vs 60.0 [9.7], p < 0.001), grade III or higher (29.8% vs 16.4%, p < 0.001), and had a higher RS (23.9 [3.6] vs 21.5 [3.1], p < 0.001). Higher T stage was associated with a higher rate of patients receiving AC (p < 0.001). Marital status was also associated with AC; a higher proportion of patients who received AC were married (67.9% vs 64.4%, p < 0.001). There was no significant association between race/ethnicity or insurance type with AC. Multivariate analysis showed that RS (OR: 1.24 [1.23-1.26], p < 0.001), T stage (OR: 1.67 [1.21-2.30], p < 0.001), and a grade III tumor (OR: 1.85 [1.64-2.09], p < 0.001) were the strongest predictors of AC. The age decile 80-89 years (OR: 0.05 [0.02-0.10], p < 0.001) was the most negative predictor of AC. AC did not have an effect on 5 year overall survival (97.6% vs 96.0%, p = 0.28). Conclusions: Between 2010-2015, our study shows 30.6% of breast cancers patients with an intermediate Oncotype-DX score were given AC. The decision to treat was largely based on tumor size, grade and age. AC had no effect on overall survival.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soo Youn Cho ◽  
Jeong Hoon Lee ◽  
Jai Min Ryu ◽  
Jeong Eon Lee ◽  
Eun Yoon Cho ◽  
...  

AbstractWe hypothesized that a deep-learning algorithm using HE images might be capable of predicting the benefits of adjuvant chemotherapy in cancer patients. HE slides were retrospectively collected from 1343 de-identified breast cancer patients at the Samsung Medical Center and used to develop the Lunit SCOPE algorithm. Lunit SCOPE was trained to predict the recurrence using the 21-gene assay (Oncotype DX) and histological parameters. The risk prediction model predicted the Oncotype DX score > 25 and the recurrence survival of the prognosis validation cohort and TCGA cohorts. The most important predictive variable was the mitotic cells in the cancer epithelium. Of the 363 patients who did not receive adjuvant therapy, 104 predicted high risk had a significantly lower survival rate. The top-300 genes highly correlated with the predicted risk were enriched for cell cycle, nuclear division, and cell division. From the Oncotype DX genes, the predicted risk was positively correlated with proliferation-associated genes and negatively correlated with prognostic genes from the estrogen category. An integrative analysis using Lunit SCOPE predicted the risk of cancer recurrence and the early-stage hormone receptor-positive breast cancer patients who would benefit from adjuvant chemotherapy.


2021 ◽  
Vol 503 ◽  
pp. 213-219
Author(s):  
Ran Cheng ◽  
Zhongzhao Wang ◽  
Xiangyi Kong ◽  
Jing Wang ◽  
Yi Fang ◽  
...  

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 599-599
Author(s):  
Jeffrey Gary Schneider ◽  
Lorna Ogden ◽  
Nosha Farhadfar ◽  
George Turi ◽  
Danny Khalil

599 Background: Oncotype DX (Genomic Health, Redwood City CA) and Mammostrat (Clarient, Aliso Viejo CA) are two distinct prognostic measures currently marketed to facilitate adjuvant chemotherapy decision making for ER+ breast cancer patients and their physicians. Both assays define three prognostic strata—favorable, intermediate, and unfavorable. Both assays were also validated in the same retrospective cohorts, but there is significant discordance between these assays, suggesting that assay selection may affect clinical decisions. Methods: We have previously reported that Oncotype DX significantly reduces adjuvant chemotherapy use in 89 consecutive ER+, N0 patients for whom this assay was ordered at our institution. Mammostrat assays were performed on 46 of these cases for which tumor blocks were available. Decision analysis was applied to determine changes in management that would have been most likely if Mammostrat had been substituted for Oncotype DX. Results: Oncotype DX and Mammostrat were concordant for prognostic strata in just 11 (24%) cases. Oncotype DX predicted a more favorable prognosis than Mammostrat in 27 (59%) cases, while Mammostrat predicted a more favorable prognosis in the remaining 8 (17%) cases. As shown in the Table, Oncotype DX reduced chemotherapy utilization whereas Mammostrat would have increased it. Conclusions: Despite being validated in identical patient cohorts, Oncotype DX and Mammostrat are frequently discordant and may often affect adjuvant treatment decisions in opposite directions. [Table: see text]


2015 ◽  
Vol 153 (1) ◽  
pp. 191-200 ◽  
Author(s):  
Megan C. Roberts ◽  
Morris Weinberger ◽  
Stacie B. Dusetzina ◽  
Michaela A. Dinan ◽  
Katherine E. Reeder-Hayes ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document