This study projected that the breast cancer index assay is cost saving when used either at diagnosis or at 5 years post diagnosis.
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.
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.
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.
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.
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.
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 extend
ing 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) (
= .007) while there
was no statistically significant benefit (
= .35) in patients
with a low BCI (H/I) gene expression ratio.14
Although BCI has been clinically validated in prospective
clinical trial cohorts, the health economic impact of
BCI has not been investigated, particularly with respect to
the novel functionality in predicting extended endocrine
therapy benefit. BCI can be ordered at initial diagnosis to
assess risk of overall, early, and late recurrence, and the
likelihood of extended endocrine therapy benefit. In addition,
BCI can be used in the prevalent population—those
patients who are recurrence-free after approximately 5 years
of endocrine-based therapy—to assess risk of late recurrence
and likelihood of benefit from continued endocrine
therapy. Therefore, the purpose of this study was to assess
the health economic impact associated with implementing
BCI at diagnosis or with utilizing BCI in patients who are
recurrence-free 5 years after diagnosis and who are considering
extended endocrine therapy.
A deterministic, decision-analytic model was developed
from the payer perspective to project cost and clinical outcomes
of using BCI compared with standard clinicopathologic
evaluation to guide ER+, LN— breast cancer patient
management for decisions of adjuvant chemotherapy and
duration of endocrine-based therapy. Treatment of a hypothetical
cohort of ER+, LN— breast cancer patients was
simulated with patient flow models, the structures of which
were developed according to the 2012 National Comprehensive
Cancer Network guidelines for management of
such patients.7 Branches represented patient management
under 2 scenarios: using standard clinicopathologic diagnostic
modalities alone versus incorporating BCI. The hypothetical
patient cohort was followed through the models
that tracked costs across a variety of possible health states
including adjuvant chemotherapy, complications, endocrine
therapy, observation, recurrence, and death over a
10-year follow-up. Two separate models were developed:
the first evaluated BCI ordered at diagnosis and included
impact on adjuvant chemotherapy decision making and
decision making regarding extended endocrine therapy;
the second evaluated BCI when ordered at 5 years post
diagnosis for the hypothetical population of patients who
were recurrence-free at 5 years post diagnosis, and included
impact on decision making for duration of endocrinebased
Clinical Decision Making. Key assumptions driving
adjuvant chemotherapy decision making are highlighted
. BCI risk categorization was derived from a
real-world clinical validation cohort in the indicated
patient population.11 Clinical decision making based
on risk categorization and estimates of disease-free survival
were estimated based on published studies evaluating
impact of Recurrence Score (21-gene assay).3,15 Key
assumptions driving use of extended endocrine-based
therapy are also highlighted in Table 1. In the scenario
without BCI, inputs were estimated based on interviews
with disease-state experts. In the scenario with BCI, the
model assumes that patients with high BCI (H/I) would
receive extended endocrine therapy, and patients with
low BCI (H/I) would stop endocrine therapy after 5
years based on the published outcomes from the MA.17
study.13 Disease-free survival in years 5 to 10 was modeled
based on BCI risk categorization status and utiliza
tion of extended endo crine therapy as reported in the
. To account for the potential effect of patient
compliance with endocrine therapy on the effect of
therapy and the likelihood of recurrence, compliance to
endocrine therapy and the associated impact on disease
recurrence was modeled according to previously observed
rates.16,17 The model also incorporated impact of a high
BCI (H/I) on patient compliance, based on a published
meta-analysis evaluating improvement in adherence following
information interventions.18,19 Compliance assumptions
are highlighted in Table 1.
A variety of sources were used to build cost assumptions
applied to patients as they moved through
health states within the models (
). Adjuvant chemotherapy
costs were derived from an observational study in
a Humana breast cancer population.3 Follow-up and recurrence
costs were based on breast cancer system economic
studies and considered total cost to the payer including
office visits, tumor-marker and imaging studies, systemic
treatments, complication management, and end-of-life
care.3,20 Adjuvant endocrine drug costs were based on a
RED BOOK analysis of average sale prices across various
manufacturers, factoring in generic drug pricing for both
tamoxifen and aromatase inhibitors.21 Alongside endocrine
therapy, additional costs associated with supportive
care (ie, bisphosphonate therapy) and complications (ie,
fractures) were included as well. Finally, the cost of the assay
was based on the manufacturer’s suggested retail pricing.
For each model, impact on total cost was evaluated
based on effect from adjuvant chemotherapy decision
making, extended endocrine-based therapy decision making,
and impact on compliance
. One-way sensitivity
analyses were conducted to evaluate the impact of
parameter input uncertainty on model outcomes. Probabilities
and cost parameters were varied over a range of
clinically relevant conservative and aggressive estimates.
Model: BCI at Diagnosis
The base case model representing treatments based
on standard clinicopathologic variables and 10 years of
follow-up resulted in mean costs of $45,437 per patient.
Use of BCI at diagnosis resulted in mean costs of $41,634,
resulting in an average savings of $3803 per patient tested
after accounting for the cost of the test. These savings
can be traced to individual contributing cost drivers including
targeted use of adjuvant chemotherapy, targeted
use of extended endocrine therapy, and increased patient
Key outputs of the sensitivity analysis are illustrated
. The model was most sensitive to the percentage
of patients classified as BCI (H/I) high, to BCI
test cost, and to the percentage of BCI (H/I) high patients
receiving extended endocrine therapy. None of the sensitivity
analyses resulted in cost savings of less than $2800
per patient tested, while more aggressive scenarios (eg,
percentage of patients classified as BCI (H/I) high, and
cost of recurrence) predicted cost savings of over $4000
per patient tested.
Model: BCI at 5 Years Post Diagnosis
In the second model, evaluating use of BCI in patients
who were recurrence-free at 5 years post diagnosis and
initial therapy, the base case resulted in mean costs of
$22,708 per patient without the use of BCI. Use of BCI at
this time point resulted in mean costs of $20,904, resulting
in a savings of $1803 per patient after accounting for
the cost of the test (
). The cost benefit was predominantly
driven by targeted use of extended endocrine
therapy ($5194 savings per patient).
Key outputs of the sensitivity analysis for this model
are illustrated in
. The model was most sensitive
to the percentage of patients classified as BCI (H/I)
high, to the percentage of BCI (H/I) high patients receiving
extended endocrine therapy, and to the total cost of
a recurrence. None of the sensitivity analyses resulted in
a cost savings under $300 per patient tested, while more
aggressive scenarios (eg, percentage of patients classified
as BCI (H/I) high, and cost of recurrence) predicted cost
savings of over $2300 per patient tested.
This health economic model projects the impact on
patient management and healthcare cost of a secondgeneration
molecular test for breast cancer recurrence
risk in patients with ER+, LN— breast cancer. The study
has 2 primary findings. First, the ability of BCI to predict
likelihood of benefit from extended endocrine therapy
adds additional cost savings on top of those cost savings
previously described for first-generation assays evaluating
the impact on adjuvant chemotherapy decision making
alone.3,19 BCI is projected to save an additional $2644 per
patient above the cost savings associated with optimizing
adjuvant chemotherapy alone. Second, the study demonstrated
that use of BCI in patients who are recurrence-free
after 5 years is cost saving as well. Optimizing the use of
extended endocrine therapy in these patients is projected
to save $1803 per patient tested after accounting for the
test cost in this setting.
As discussed, BCI has been estimated to save additional
costs beyond optimization of adjuvant chemotherapy,
the majority of which is driven by optimization of
extended endocrine therapy. Several large, randomized,
prospective clinical trials (eg, MA.17, ATLAS, aTTom)
have recently brought significant attention to the decision
of whether to extend endocrine therapy. While these trials
demonstrated treatment benefit, they showed only a
small absolute benefit in recurrence rates with extended
endocrine therapy in the unselected population.8-10 Given
the significant toxicities and side effects associated with
endocrine therapy, there exists an unmet need to identify
which patients should receive extended endocrine
therapy based on a higher risk of recurrence and likelihood
of benefit.22,23 BCI may be a tool to help address this
unmet need by stratifying patients based on their risk of
recurrence and likelihood of benefit, thereby increasing
extended endocrine therapy use in patients expected to
derive the most benefit while avoiding further treatment
and minimizing drug-related side effects in patients who
are unlikely to receive benefit. The results of this study
indicate that this additional clinical value proposition
translates into further system economic benefit for this
assay. With generic aromatase inhibitors now available,
extended endocrine therapy is highly cost effective and
substantially reduces recurrences in patients with high
The magnitude of the cost savings generated by optimization
of extended endocrine therapy depends on
when the assay is used over the course of diagnosis and
follow-up. When used at initial diagnosis, this clinical
value proposition adds an additional $2165 to the per patient
tested cost savings. When used for recurrence-free
patients at 5 years post diagnosis (the decision point for
extending endocrine therapy), this clinical value proposition
adds $5194 to the per patient cost savings. The per
patient tested cost benefit is greater when the test is used
at 5 years post diagnosis because it is only used in the
subset of women who are eligible for extended endocrine
therapy (ie, not including women who have a recurrence
or discontinuation within the first 5 years), and therefore
do not realize the additional savings due to this component
of the test.
This study has a number of limitations. First, as an
modeling study, many assumptions were based on
published clinical literature and expert interviews rather
than prospective real-world data of test economic impact.
As was the case with first-generation breast cancer
risk recurrence assays, future studies must assess the impact
of the assay in collaboration with third-party payers
to illustrate cost savings in a real-world setting. Second,
sensitivity analyses highlighted that cost savings were
most sensitive to the cost of the assay, to the proportion
of patients classified as high BCI (H/I), and to the percentage
of those patients following the recommendation
to receive extended endocrine therapy. The base scenario
of the model assumes optimal alignment between
test recommendation and physician/patient decision
on extended endocrine therapy. As has been observed
in real-world studies of first-generation assays, test recommendations
are incorporated with other clinical and
patient-specific factors, and thus are not followed in all
cases. Furthermore, it is important to note that the model
assumed that physicians may treat post menopausal patients
with extended aromatase inhibitor therapy following
an initial 5 years of aromatase inhibitor therapy. This
assumption was directly informed by interviews with disease-
state experts, per the study methodology. While definitive
data on the effectiveness of 10 years of aromatase
inhibitor treatment versus 5 years is not yet available,
the assumption is based on the effectiveness of extended
endocrine therapy demonstrated in 4 different randomized,
clinical trials.8-11 These assumptions and limitations
should be a focus for ongoing real-world studies. However,
it is important to note that the sensitivity analysis
reveals that even with a 20% discrepancy between test
recommendation and patient management, the test remains
highly cost-effective. Third, in a rapidly evolving
therapeutic landscape such as that of breast cancer treatment,
it is difficult to fully characterize the downstream
costs of recurrent cancer, as the treatment landscape
will likely involve new therapies by the time this patient
cohort experiences recurrences. With the emergence of
new higher-priced targeted therapy for metastatic disease,
costs for patients with recurrent breast cancer are
likely to rise.24,25 To examine this limitation, sensitivity
analyses revealed that as the cost of breast cancer recurrence
increases, BCI cost-effectiveness increases. Given
these trends, the base case assumes a relatively conservative
value for recurrence costs based on recent data,
leaving room for potential upside as treatment costs rise.
Finally, clinical data evaluating the benefit of adjuvant
chemotherapy based on BCI risk stratification are not
available, thus assumptions related to chemotherapy
utilization and patient outcomes are modeled based on
published RS studies. Notably, BCI has been investigated
in a neoadjuvant chemotherapy study, and demonstrated
ability to predict response to chemotherapy (as
assessed by pathologic complete response).26 In addition,
the sensitivity analyses demonstrate that a reduction in
chemotherapy benefit predictability of 25% results in
only a minor decrease in cost savings. Thus, while this
is an important limitation of the study, it is unlikely to
significantly alter the study’s conclusions.
In conclusion, this health economic analysis demonstrates
that use of BCI in patients with ER+, LN— early
breast cancer is cost saving compared with management
without the use of a molecular assay. From a third-party
payer perspective, use of this test may result in substantially
lower overall medical costs. These cost savings are
primarily driven by a reduction in adjuvant chemotherapy
in patients unlikely to derive benefit and an increase
in extended endocrine therapy utilization in patients
likely to receive substantial benefit. Additional studies on
clinical practice in real-world populations are needed to
validate these results.
Author Affiliations: Health Advances, LLC, Weston, MA (GG, PK,
KCP); bioTheranostics, Inc, San Diego, CA (BS, MGE, CAS); and Henry
Ford Health System, Detroit, MI (HA).
Funding Source: This study was funded by bioTheranostics, Inc.
Author Disclosures: bioTheranostics, Inc, markets the test described
in this manuscript.
Authorship Information: Concept and design (MGE, GG, PK, KCP,
BS, CAS); acquisition of data (PK, BS, CAS); analysis and interpretation
of data (HA, MGE, GG, PK, BS, CAS); drafting of the manuscript (GG,
BS, CAS); critical revision of the manuscript for important intellectual
content (HA, KCP, BS, CAS); administrative, technical, or logistic support
(MGE, BS, CAS); and supervision (HA, KCP).
Address correspondence to: Gary Gustavsen, MS, Health Advances,
LLC, 9 Riverside Rd, Weston, MA 02493. E-mail: ggustavsen@healthadvances.
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