NcXHF

STEPHEN T. SONIS
Defıning the clinical utility of a genomic test in the context of
supportive care may turn out to be complex. Toxicities rarely
occur as singular events. Rather, patients develop simultaneous
clusters of toxicities 43 often related by common biologic underpinnings.
This may be advantageous from the potential of testing
because there may be pathways (and genes) that are shared
by more than one toxicity. Compartmentalizing genomic risk
testing (i.e., toxicity by toxicity) ultimately is less attractive than
a comprehensive toxicity panel, especially with respect to adding
meaningful information for clinician-patient decision making.
A test’s true utility will be derived from cases in which
patients can select equally effective anticancer regimens based
on their toxicity preferences.
Economics play an increasing role in health care decision
making today. Aside from patients, health economic stakeholders
include providers, payers, and government. It initially appears
that a sound fıscal argument can be developed in favor of
genomic testing for supportive care indications, as long as it results
in an actionable outcome that affects toxicity risk, prevention,
or effective management. Numerous studies have
demonstrated increased costs and increased health resource use
attributable to specifıc toxicities. 44,45 However, these data might
be underestimates. In many cases, only severe forms of adverse
events have been evaluated, even though it is likely that toxicity
of any grade affects cost. 46 The incremental fınancial effect of
toxicities has also been differentially described for direct costs
(those costs associated with the costs of managing the toxicity)
or indirect costs (lost opportunity costs, caregiver costs, etc.).
For the most part, direct costs have been delineated for acute
toxicities, whereas indirect costs are often attributed to chronic
adverse events (i.e., the effect of cancer treatment–related fatigue
on inability to return to work).
As noted above, the fınding that patients most often develop
multiple, simultaneous toxicities mandates that true
cost assessment be done in a comprehensive way, rather
than toxicity by toxicity. It also places an obligation to develop
genomic assessments that, in a single test, capture
comprehensive toxicity risk and link those to alternative
regimens for the same cancer. The recent report by Hurvitz
et al 47 of a large number of patients with metastatic
breast cancer provides a rationale for such an approach.
Using an extensive claims database, they fırst identifıed the
22 most common adverse events associated with common
chemotherapy regimens. They computed and compared
the comprehensive monthly costs per number of adverse
events. The results were dramatic. Increases in average
monthly costs ranged from $854 to $5,320 depending on
chemotherapy regimen.
Consequently, even considering the additional costs of
testing (including test development), the prospective identifıcation
of risk that results in the avoidance of toxicity either
by guiding regimen selection, or by targeted toxicity prophylaxis,
certainly should provide overall cost savings. For example,
if an effective preventive agent were available for
radiation-induced mucositis in patients with head and neck
cancer, the projected savings could be calculated by deducting
the cost of the intervention from the incremental cost
(about $17,000) of mucositis. 48
Not surprisingly, third-party payers have been reluctant to
provide either coverage or reimbursement for genomic risk prediction,
often still considering such tests to be investigational.
Perhaps with broader test platforms—one test for multiple toxicities—and
increasing validation of clinical utility, this stance
will change. As the largest provider of health insurance in the
United States, the government has established several initiatives
to evaluate genomic tests and, in particular, to fıgure out ways to
provide reimbursement. Although multiple U.S. agencies are
involved in these efforts, those led by the National Human Genome
Research Institute are noteworthy. From the patients’
perspective, the value of genomic risk prediction seems recognized
as patients have expressed a willingness to pay for information
that better guides their treatment.
CONCLUSION
The application of genomics to cancer supportive care holds
multiple opportunities to improve our understanding of the biology
of regimen-related toxicities, to develop effective interventions,
and, most importantly, to guide treatment decisions.
A critical challenge to clinical implementation of this data will be
ensuring that providers and patients understand what the data
mean and how they can be used. Organizing and presenting
data in such a way that results are actionable will be key. Provider
education has been identifıed as a priority as genomics
moves from the laboratory to the clinic.
Disclosures of Potential Conflicts of Interest
Relationships are considered self-held and compensated unless otherwise noted. Relationships marked “L” indicate leadership positions. Relationships marked “I” are those held by an immediate
family member; those marked “B” are held by the author and an immediate family member. Institutional relationships are marked “Inst.” Relationships marked “U” are uncompensated.
Employment: None. Leadership Position: None. Stock or Other Ownership Interests: Stephen Sonis, Tenera, LLC, Theramech, Inform Genomics,
Biomodels, LLC. Honoraria: None. Consulting or Advisory Role: Stephen Sonis, Inform Genomics, Quintiles, Clinical Assistance Programs, LLC. Speakers’
Bureau: None. Research Funding: None. Patents, Royalties, or Other Intellectual Property: Stephen Sonis, Raman spectropscopy. Expert Testimony:
None. Travel, Accommodations, Expenses: None. Other Relationships: None.
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