Biology Reference
In-Depth Information
false-positive candidates generated at the identifi-
-
BIOMARKER VALIDATION
cation phase, dif
culties of proceeding to
biomarker veri
cation and validation phases,
and shortage of academic grants that fund trans-
lation of discovery data into clinics.
Regardless of the specimen analyzed during
the protein identi
Biomarker validation is a multifaceted proce-
dure that requires collaboration of multiple clin-
ical centers and carries a signi
financial
burden. Ideally, only the most promising candi-
dates that have proven their potential at the veri-
cant
fication
should be performed with specimens that are
intended for clinical use and accurately re
cation phase, veri
ect
fication phase and for which robust quantitative
assays have been developed will enter the vali-
dation phase. The importance of high-quality
quantitative assays was demonstrated by the
Prostate Lung Colorectal Ovarian (PLCO)
Cancer Screening Trial in which multiple
ovarian cancer biomarker candidates were
tested.
124
As a result, it was shown that only
markers with analytical assays achieving a coeffi-
population.
119
the
target
Proper
control
subjects, as de
ned by the inclusion or exclu-
sion criteria, are essential for meaningful data
interpretation and should be matched for phys-
iologic factors such as age and gender to control
potential confounding factors. Preanalytical
sources of variation such as biases in sample
collection and storage should be also carefully
evaluated, especially given that veri
-
cient of variation less than 30% performed with
adequate diagnostic sensitivity.
Validation studies should be performed in
both a retrospective and prospective manner
using independent sample cohorts ideally
collected by multiple hospitals.
119
Unbiased
presentation of the results of validation studies
holds
fication
studies are performed with retrospectively
collected samples. Finally, the size of study pop-
ulation should be calculated to ensure adequate
statistical power,
119
and the results of the study
must undergo a rigorous statistical analysis.
Importance of an appropriate statistical anal-
ysis is sometimes overlooked in the biomarker
discovery
final assessment of
a biomarker performance.
125
Study population
should recapitulate the general population both
in terms of disease prevalence and disease stage
to allow for correct data interpretation and evalu-
ation of biomarker performance. Power calcula-
tions are necessary to de
the key for
the
field. At the initial steps of protein
biomarker discovery, thousands of proteins are
typically identi
ed and selected based on their
relative abundance in disease versus control
groups. Proper selection of candidates, however,
should include robust statistical analysis based
on statistical probability (
p
-values) of differenti-
ating groups of samples. Furthermore, because
thousands of proteins are tested simultaneously,
p
-values should be corrected for multiple testing
hypothesis.
120,121
Such correction should also be
performed when a set of biomarker candidates
is veri
ne the appropriate
study size and ensure statistical signi
cance. Vali-
dation phase requires large numbers of high-
quality specimens, availability of which may be
the bottleneck of biomarker development. Inter-
national multicenter collaborations and central-
ized registries of clinical samples are founded to
alleviate this limitation.
125
To minimize preana-
lytical biases, all samples should be collected,
stored, and processed using prede
ed by a multiplex SRM assay. Develop-
ment of multimarker diagnostic signatures
would require even more advanced statistical
algorithms.
122,123
By the end of the veri
ned standard
operating procedures. In
uence of preanalytical
parameters such as sample handling and sample
preparation, protein stability, intra- and interindi-
vidual variations need to be addressed prior to
the large-scale validation studies. The ultimate
cation phase, many
biomarker candidates are eliminated, resulting
in a small and manageable list of candidates that
will proceed to the biomarker validation phase.
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