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The American Journal of Managed Care August 2014
Personalized Preventive Care Reduces Healthcare Expenditures Among Medicare Advantage Beneficiaries
Shirley Musich, PhD; Andrea Klemes, DO, FACE; Michael A. Kubica, MBA, MS; Sara Wang, PhD; and Kevin Hawkins, PhD
Impact of Hypertension on Healthcare Costs Among Children
Todd P. Gilmer, PhD; Patrick J. O’Connor, MD, MPH; Alan R. Sinaiko, MD; Elyse O. Kharbanda, MD, MPH; David J. Magid, MD, MPH; Nancy E. Sherwood, PhD; Kenneth F. Adams, PhD; Emily D. Parker, MD, PhD;
Tracking Spending Among Commercially Insured Beneficiaries Using a Distributed Data Model
Carrie H. Colla, PhD; William L. Schpero, MPH; Daniel J. Gottlieb, MS; Asha B. McClurg, BA; Peter G. Albert, MS; Nancy Baum, PhD; Karl Finison, MA; Luisa Franzini, PhD; Gary Kitching, BS; Sue Knudson,
Potential Role of Network Meta-Analysis in Value-Based Insurance Design
James D. Chambers, PhD, MPharm, MSc; Aaron Winn, MPP; Yue Zhong, MD, PhD; Natalia Olchanski, MS; and Michael J. Cangelosi, MA, MPH
Massachusetts Health Reform and Veterans Affairs Health System Enrollment
Edwin S. Wong, PhD; Matthew L. Maciejewski, PhD; Paul L. Hebert, PhD; Christopher L. Bryson, MD, MS; and Chuan-Fen Liu, PhD, MPH
Contemporary Use of Dual Antiplatelet Therapy for Preventing Cardiovascular Events
Andrew M. Goldsweig, MD; Kimberly J. Reid, MS; Kensey Gosch, MS; Fengming Tang, MS; Margaret C. Fang, MD, MPH; Thomas M. Maddox, MD, MSc; Paul S. Chan, MD, MSc; David J. Cohen, MD, MSc; and Jersey Che
Potential Benefits of Increased Access to Doula Support During Childbirth
Katy B. Kozhimannil, PhD, MPA; Laura B. Attanasio, BA; Judy Jou, MPH; Lauren K. Joarnt; Pamela J. Johnson, PhD; and Dwenda K. Gjerdingen, MD
Synchronization of Coverage, Benefits, and Payment to Drive Innovation
Annemarie V. Wouters, PhD; and Nancy McGee, JD, DrPH
The Effect of Depression Treatment on Work Productivity
Arne Beck, PhD; A. Lauren Crain, PhD; Leif I. Solberg, MD; Jürgen Unützer, MD, MPH; Michael V. Maciosek, PhD; Robin R. Whitebird, PhD, MSW; and Rebecca C. Rossom, MD, MSCR
Economic Implications of Weight Change in Patients With Type 2 Diabetes Mellitus
Kelly Bell, MSPhr; Shreekant Parasuraman, PhD; Manan Shah, PhD; Aditya Raju, MS; John Graham, PharmD; Lois Lamerato, PhD; and Anna D’Souza, PhD
Optimizing Enrollment in Employer Health Programs: A Comparison of Enrollment Strategies in the Diabetes Health Plan
Lindsay B. Kimbro, MPP; Jinnan Li, MPH; Norman Turk, MS; Susan L. Ettner, PhD; Tannaz Moin, MD, MBA, MSHS; Carol M. Mangione, MD; and O. Kenrik Duru, MD, MSHS
Does CAC Testing Alter Downstream Treatment Patterns for Cardiovascular Disease?
Winnie Chia-hsuan Chi, MS; Gosia Sylwestrzak, MA; John Barron, PharmD; Barsam Kasravi, MD, MPH; Thomas Power, MD; and Rita Redberg MD, MSc
Effects of Multidisciplinary Team Care on Utilization of Emergency Care for Patients With Lung Cancer
Shun-Mu Wang, MHA; Pei-Tseng Kung, ScD; Yueh-Hsin Wang, MHA; Kuang-Hua Huang, PhD; and Wen-Chen Tsai, DrPH
Currently Reading
Health Economic Analysis of Breast Cancer Index in Patients With ER+, LN- Breast Cancer
Gary Gustavsen, MS; Brock Schroeder, PhD; Patrick Kennedy, BE; Kristin Ciriello Pothier, MS; Mark G. Erlander, PhD; Catherine A. Schnabel, PhD; and Haythem Ali, MD

Health Economic Analysis of Breast Cancer Index in Patients With ER+, LN- Breast Cancer

Gary Gustavsen, MS; Brock Schroeder, PhD; Patrick Kennedy, BE; Kristin Ciriello Pothier, MS; Mark G. Erlander, PhD; Catherine A. Schnabel, PhD; and Haythem Ali, MD
This study projected that the breast cancer index assay is cost saving when used either at diagnosis or at 5 years post diagnosis.

Objectives

Breast Cancer Index (BCI) is a novel gene expression-based test for patients with estrogen receptor positive (ER+), lymph node negative (LN–) breast cancer that predicts risk of recurrence over 10 years, and also specifically predicts risk of late (≥5 y) recurrences and likelihood of benefit from extended (≥5 y) endocrine therapy. The objective of this study was to evaluate cost utility of BCI from a US third-party payer perspective.


Study Design

Two fact-based economic models were developed to project the cost and effectiveness of BCI in a hypothetical population of patients with ER+, LN– breast cancer compared with standard clinicopathologic diagnostic modalities.


Methods

Costs associated with adjuvant chemotherapy, toxicity, followup, endocrine therapy, and recurrence were modeled over 10 years. The models examined cost utility compared with standard practice when used at diagnosis and in patients disease-free at 5 years post diagnosis.


Results

Use of BCI was projected to be cost saving in both models. In the newly diagnosed population, net cost savings were $3803 per patient tested. In the 5 years post diagnosis population, BCI was projected to yield a net cost savings of $1803 per patient tested. Sensitivity analyses demonstrated that BCI was cost saving across a wide range of clinically relevant input assumptions.


Conclusions
 
BCI was projected to be cost saving when used either at diagnosis or at 5 years post diagnosis. Cost savings are achieved through projected impact on adjuvant chemotherapy use, extended endocrine therapy use, and endocrine therapy compliance. These findings require validation in additional cohorts, including studies of real-world clinical practice.


Am J Manag Care. 2014;20(8):e302-e310

This health economic analysis demonstrated that use of Breast Cancer Index in patients with estrogen receptor positive, lymph node negative early breast cancer is cost saving compared with standard management.

  • From a third-party payer perspective, use of this test may result in substantially lower overall medical costs.
     
  •  The test resulted in cost savings when used either at diagnosis or at 5 years post diagnosis.
     
  •  Cost savings were driven by a reduction in adjuvant chemotherapy in patients unlikely to derive benefit (when used at diagnosis), and optimization of extended endocrine therapy utilization in patients likely to receive substantial benefit (when used at either time point).

Each year more than 230,000 women are diagnosed with breast cancer in the United States.1 The clinical subset of patients with estrogen receptor positive (ER+), lymph node negative (LN–) breast cancer has a better overall prognosis than patients in other clinical subsets (eg, triple negative breast cancer, human epidermal growth factor receptor 2–positive [HER2+] breast cancer). However, one of the hallmarks of ER+ breast cancer is the persistent risk of recurrence that extends greater than 15 years after initial diagnosis and treatment.2 In addition to surgical intervention and 5 years of endocrine-based therapy, patients and physicians have 2 important therapeutic considerations: first, whether or not to receive adjuvant chemotherapy; and second, whether to extend endocrinebased therapy beyond 5 years. These difficult clinical decisions, which are multifactorial and must balance the potential risks and benefits of therapy, have led to the development of multiple prognostic and predictive tools to assist with clinical decision making.



Significant focus has been placed on supporting the adjuvant chemotherapy decision. Over the past decade, a number of molecular assays designed to predict risk of recurrence and chemotherapy benefit for ER+ patients have become commercially available. These molecular assays have been incorporated into clinical practice, have been shown to impact clinical decision making regarding the use of adjuvant chemotherapy,3-5 and have been incorporated into clinical guidelines.6,7 Finally, gene expression–based assays have been shown to be cost saving, through more appropriate patient stratification and utilization of adjuvant chemotherapy.



While significant progress has been made in the area of adjuvant chemotherapy guidance, little progress had been made, until recently, in assessing risk of late (post 5-year) recurrence and in determining the duration of endocrine therapy patients would receive. Focus on this area has grown, given the results of several randomized, prospective clinical trials (eg, MA.17, ATLAS, aTTom) demonstrating clinical benefit of extending endocrine-based therapy beyond 5 years.8-11 While statistically significant clinical benefit was observed in all 3 trials, the absolute benefits were relatively small (approximately 3%-6%); this suggests the need, so far unaddressed, to stratify patients based on risk of late recurrence and likelihood of benefit from extended endocrine therapy.



Breast Cancer Index (BCI; bioTheranostics, San Diego, California) is a gene expression-based biomarker with a novel mechanism of action. BCI was developed through the algorithmic combination of 2 complementary biomarkers: molecular grade index (MGI), which recapitulates tumor grade/proliferation status; and HOXB13:IL17BR ratio [BCI (H/I)], which interrogates estrogen-signaling pathways. In clinical validation studies, BCI has been demonstrated to significantly predict overall (10-year) risk of recurrence, and also specifically predict risk of early (0- to 5-year) and late (≥5-year) recurrence in ER+, LN– breast cancer patients.12,13 In addition, in a prospective-retrospective analysis of the randomized MA.17 trial, BCI (H/I) was shown to be predictive of extended endocrine therapy benefit. Letrozole treatment led to a reduction in the absolute risk of recurrence at 5 years of 16.5% in patients with high BCI (H/I) (P = .007) while there was no statistically significant benefit (P = .35) in patients with a low BCI (H/I) gene expression ratio.14



 
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