Feng, Xiaodong_ Xie, Hong-Guang - Applying pharmacogenomics in therapeutics-CRC Press (2016)

274 Applying Pharmacogenomics in Therapeutics
such as life years saved by an alternative or intervention. In the case of the PGxbased
CEA study, costs and effects of the PGx assay are compared with that of
conventional clinical practice without using PGx information for decision making
of drug therapy, because this approach can answer the following basic question
9 : Does a PGx-based intervention provide a patient with improved healthcare
outcomes and quality of life at a reasonable additional cost when compared with
the conventional treatment strategies (standard care without PGx testing)? In general,
PGx-based treatment strategies would be likely to be cost-effective when
the following criteria can be met to a greater extent: (1) the genetic variant of
interest is relatively prevalent in the patient population; (2) there is a strong or
established genotype–phenotype association; (3) patients may face severe clinical
outcomes or life-threatening status and even death if the treatment strategy is not
appropriate; (4) severe adverse drug reactions would be minimized or avoided by
genotype-guided personalized medicine; and (5) genetic testing is highly specific,
sensitive, relatively cheap, and easy to use. 7,9,12,13 In short, PGx interventions
would be cost-effective when severe clinical and/or economic consequences could
be avoided after use of PGx testing. However, PGx-based therapies are not always
cost-effective in systematic review articles of eligible CEA studies about PGx
interventions for patient care. 7,14 More importantly, PGx interventions are often
applied to the drug with a narrow therapeutic window, or a drug with high variation
in drug response, not to all marketed drugs. 9,15
Cost-Utility Analysis
Cost-utility analysis (CUA) measures the benefit in patient-oriented (or clinical) terms
(such as cost per QALY saved by the intervention), and thus different interventions
used for patients can be directly compared by standardizing the denominator. 10 By
definition, CUA uses QALY only as its outcome. For example, an alternative or new
intervention can be compared with conventional clinical practice in an incremental
analysis. In other words, the new or alternative interventions would be believed to be
cost-effective if they produce health benefits at a certain cost comparable to or less
than that of other currently accepted drug therapies (or so-called conventional treatment
strategies) in clinical settings. Clearly, as a specific type of CEA, CUA has been
more accepted in healthcare than other types of economic evaluation, 14 due to more
emphases on use of the QALY in pharmacoeconogenomic studies.
The incremental cost-effectiveness (ICE) 9,10,16 ratio is defined as
ICE = (C2 − C1)/(E2 − E1)
where C2 and E2 denote the cost and effectiveness of the new intervention being
evaluated, and C1 and E1 refer to the cost and effectiveness of the standard care (or
current medical practice), respectively. For a CUA study of PGx, the ICE ratio also
represents the difference in costs between the two alternatives divided by the difference
in effectiveness between the same two alternatives, 8 such as cost per QALY
gained, where the quality values for the alternatives (also known as utility values) are
either estimated as part of the study or retrieved from the existing literature, and one