Research
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OBSTETRICS
Karyotype versus genomic hybridization
for the prenatal diagnosis of chromosomal
abnormalities: a metaanalysis
Wilmar Saldarriaga, MD, MSc; Herney Andrés Garcı́a-Perdomo, MD, MSc, EdD, PhD;
Johanna Arango-Pineda, MD; Javier Fonseca, MD, MSc
OBJECTIVE: The aim of this study was to determine the diagnostic
accuracy of comparative genomic hybridization (CGH) compared with
karyotyping for the detection of numerical and structural chromosomal
alterations in prenatal diagnosis.
STUDY DESIGN: A metaanalysis was performed using searches of
PubMed, EMBASE, CENTRAL, Cochrane Register of Diagnostic Test
Accuracy Studies, Google Scholar, gray literature, and reference manuals. No language restriction was imposed. We included cross-sectional,
cohort, and case-control studies published from January 1980 through
March 2014 in the analysis. Studies of pregnant women who received
chorionic villus biopsies, amniocentesis, or cordocentesis and then underwent CGH and karyotype analysis were included. Two independent
reviewers assessed each study by title, abstract, and full text before its
inclusion in the analysis. Methodological quality was assessed using
QUADAS2, and a third reviewer resolved any disagreement. Conclusions
were obtained through tests (sensitivity, specificity, and likelihood ratios)
for the presence of numerical and structural chromosomal abnormalities.
The reference used for these calculations was the presence of any
abnormalities in either of the 2 tests (karyotype or CGH), although it
should be noted that in most cases, the karyotyping test had a lower yield
compared with CGH. Statistical analysis was performed in RevMan 5.2
and the OpenMeta[Analyst] program.
RESULTS: In all, 137 articles were found, and 6 were selected for
inclusion in the systematic review. Five were included in the
metaanalysis. According to the QUADAS2 analysis of methodology
quality, there is an unclear risk for selection bias and reference and
standard tests. In the other elements (flow, time, and applicability
conditions), a low risk of bias was found. CGH findings were as
follows: sensitivity 0.939 (95% confidence interval [CI],
0.838e0.979), I2 ¼ 82%; specificity 0.999 (95% CI,
0.998e1.000), I2 ¼ 0%; negative likelihood ratio 0.050 (95% CI,
0.015e0.173), I2 ¼ 0%; and positive likelihood ratio 1346.123
(95% CI, 389e4649), I2 ¼ 0%. Karyotype findings were as follows:
sensitivity 0.626 (95% CI, 0.408e0.802), I2 ¼ 93%; specificity
0.999 (95% CI, 0.998e1.000), I2 ¼ 0%; negative likelihood ratio
0.351 (95% CI, 0.101e1.220), I2 ¼ 0%; and positive likelihood
ratio 841 (95% CI, 226e3128), I2 ¼ 10%.
CONCLUSION: This systematic review provides evidence of the relative
advantage of using CGH in the prenatal diagnosis of chromosomal and
structural abnormalities over karyotyping, demonstrating significantly
higher sensitivity with similar specificity.
Key words: chromosomal abnormalities, comparative genomic
hybridization, karyotype, prenatal diagnosis
Cite this article as: Saldarriaga W, Garcı́a-Perdomo HA, Arango-Pineda J, et al. Karyotype versus genomic hybridization for the prenatal diagnosis of chromosomal
abnormalities: a metaanalysis. Am J Obstet Gynecol 2015;212:330.e1-10.
P
renatal studies include the detection of numerical and structural
chromosomal abnormalities. However,
sampling of fetal genetic material requires the use of invasive procedures that
pose risks for both the mother and
child.1 For this reason, a series of
screening tests is performed prior to fetal
chromosomal analysis to determine if
there is a probability 1% of finding a
From the Departments of Obstetrics and Gynecology (Drs Saldarriaga, Fonseca, and ArangoPineda), Urology (Dr García-Perdomo), and Morphology (Dr Saldarriaga), School of Medicine,
University of Valle, Cali, Colombia.
Received July 9, 2014; revised Aug. 19, 2014; accepted Oct. 3, 2014.
The authors report no conflict of interest.
Presented at the 29th Annual Scientific Meeting of the Colombian Obstetrical and Gynecologic
Society, Medellin, Colombia, May 28-31, 2014.
Corresponding author: Herney Andrés García-Perdomo, MD, MSc, EdD, PhD. Herney.garcia@
correounivalle.edu.co
0002-9378/$36.00 ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ajog.2014.10.011
330.e1 American Journal of Obstetrics & Gynecology MARCH 2015
chromosomal abnormality. Parameters
such as maternal age, biochemical test
results, and ultrasound markers, such as
fetal anatomy defects, justify performing
the more invasive procedure.2
The most common diagnostic test for
chromosomal abnormalities is G-banding karyotyping. Other tests include
fluorescent in situ hybridization (FISH)
or quantitative fluorescent polymerase
chain reaction. Karyotyping can detect
numerical chromosomal abnormalities
in chromosomes as well as structural
changes, such as the loss or gain of upwards of 5 megabases of genetic material.
Other techniques detect common trisomies and monosomies (13, 18, 21, X,
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bases that are not detected by karyotype.
In 2010, a consensus document4 and an
economic analysis5 were published that
suggested that CGH should be considered the first diagnostic test, replacing
karyotyping in patients with neurological problems, autism, and cognitive
deficits and in newborns with congenital
anomalies of unknown etiology.
In
prenatal
diagnosis,
studies
comparing different chromosomal alteration analysis techniques in high-risk
patients report diagnostic frequencies
between 2.5-4.2% with karyotyping,6
whereas frequencies of 5.3-15% have
been reported with CGH.7-10 The
detection increases significantly for
CGH (9.3-39%) when fetal anatomic
defects are indicated.8,9,11 The patient is
not subjected to additional risk, and
results are obtained more rapidly. However, there is an increase in the cost as
well as the probability of finding variants
of an uncertain nature.7,10
Given the advantages of CGH over
karyotyping in prenatal diagnosis, the
use of this molecular test has increased in
countries where the additional cost is
borne by health insurance as well as in
countries or states where abortion is
permitted. So far, there was only 1 metaanalysis12 suggesting that CGH increases the detection rate to diagnose
chromosomal abnormalities for prenatal
indications overall. That metaanalysis
focused on the agreement between both
tools and the detection rate of chromosomal abnormalities, however it was not
related to diagnostic accuracy.
The aim of this study was to determine
the diagnostic accuracy of CGH and karyotyping compared with the sum of the
results of the 2 tests for the detection of
numerical and structural chromosomal
abnormalities in prenatal diagnosis.
FIGURE 1
Flowchart
CGH, comparative genomic hybridization.
Saldarriaga. Karyotype vs genomic hybridization for the prenatal diagnosis of chromosomal abnormalities. Am J Obstet
Gynecol 2015.
and Y), in addition to fetal chromosomal
sex, but do not diagnose structural alterations.3 The aforementioned tests are
techniques often combined with karyotyping because results are available in
approximately a week, whereas karyotyping requires 2-3 weeks.
Research
Comparative genomic hybridization
(CGH) has emerged as a molecular test
for chromosomal analysis and it is used
in prenatal diagnosis, pediatric patients,
or adults with specific indications. CGH
detects microdeletions and microduplications sizing upwards of 500 pair-
M ATERIALS
AND
M ETHODS
This study was conducted according to
the recommendations of the Cochrane
Collaboration and is reported following
the PRISMA Statement. The protocol
was registered in the international prospective register of systematic reviews
(PROSPERO): CRD42014007627.
We designed a search strategy for
studies published in MEDLINE via
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TABLE 1
Characteristics of included studies
Sample
size, n
Study
Country
Array type
Sample type
Array indication
Van den Veyver
et al17 (2009),
prospective
(cross-sectional)
United
States
BAC chromosomal
microarray V5 or 6; V6 of
BCM oligonucleotide
chromosomal microarray
AF 254, CVS 53
Advanced maternal age (33.5%),
abnormal ultrasound finding (22.9%),
family history of genetic disease (23.7%),
abnormal fetal karyotype (7.6%), parental
anxiety (9%), altered serum screening
(2.5%), others (0.9%)
309
Maya et al15
(2010),
retrospective
(cross-sectional)
Israel
BAC using SignatureChip
whole genome or
oligonucleotide
microarrays
AF 243, CVS 16
Advanced maternal age (22.7%),
abnormal ultrasound finding (38%),
familial congenital disease (16%),
abnormal fetal karyotype (5.6%), parental
anxiety (17%), altered serum screening
(0.7%)
269
Fiorentino et al14
(2011),
prospective
(cross-sectional)
Italy
Whole-genome BAC
microarrayseCytoChip
Focus Constitutional
AF 938, CVS 99
Advanced maternal age 42.8%), altered
serum screening (1.3%), abnormal
ultrasound (4.6%), abnormal fetal
karyotype (0.8%), family history of genetic
disease (1.1%), parental anxiety (46.8%),
others (2.4%)
1037
Wapner et al16
(2012),
prospective
(cross-sectional)
United
States
Agilent 4-plex array and
Affymetrix genomewide
human SNP array 6.0
AF 1627, CVS
1910
Abnormal ultrasound finding (25.8%),
advanced maternal age (47.9%), altered
serum screening (19.3%), others (9.7%)
4282
Lee et al11 (2012),
prospective
(cross-sectional)
Taiwan
1-Mb resolution BAC from
2010, until 60-K
oligonucleotide
AF 2926, CVS 82,
fetal blood 93
Abnormal ultrasound findings (6.1%),
altered serum screening (0.8%),
advanced maternal age (60.2%), parental
anxiety (31.1%)
3171
Armengol et al7
(2012),
prospective
Spain
Not defined
AF 728, CVS 164,
fetal blood 14
Abnormal ultrasound finding (19%),
altered serum screening (25.9%), history
of congenital disease (16%), advanced
maternal age (30.1%), parental anxiety
(6.6%), other (2.2%)
906
AF, amniotic fluid; AMA, advanced maternal age (35 years old); BAC, bacterial artificial chromosome; CVS, chorionic villus sampling; SNP, single nucleotide polymorphism.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
PubMed, CENTRAL, Cochrane Register
of Diagnostic Test Accuracy Studies, and
EMBASE. The search strategy was specific for each database and included a
combination of the medical subject
headings and free-text terms for
“comparative genomic hybridization”
and “karyotype.” No language or publication status restrictions were imposed.
We included articles from Jan. 1, 1980,
through March 31, 2014. The full search
strategies are listed in the Appendix.
Other electronic sources were used to
find additional studies, such as conference
abstracts, Google Scholar, DARE, and
PROSPERO. We looked for additional
studies in the reference lists of selected
articles and contacted authors about their
knowledge of published or unpublished
articles. The results of searches were crosschecked to eliminate duplicates.
Eligibility criteria
Studies
We included cross-sectional, case-control, and cohort studies conducted from
Jan. 1, 1980, through March 31, 2014.
No language restrictions were imposed.
Studies were required to report at least
sensitivity and specificity or data to
calculate these parameters.
Participants
Pregnant women who underwent chorionic villus sampling, amniocentesis, or
cordocentesis to perform CGH and
karyotyping.
330.e3 American Journal of Obstetrics & Gynecology MARCH 2015
There were no preferences with
respect to any other demographic characteristics of the participants.
Comparisons
We intended to perform the following
comparisons:
Karyotype (reference standard) vs
CGH (index test).
Karyotype plus CGH vs karyotype.
Karyotype plus CGH vs CGH.
However, at the time of analysis, we
determined that CGH diagnosed abnormalities that the karyotype did not.
Therefore, we decided to create a reference standard according to the literature
(karyotype þ CGH).
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Research
could not agree, a third reviewer (W.S.)
made the final decision.
FIGURE 2
Risk of bias within studies
Data collection process
Relevant data were collected using a
standardized data extraction sheet,
which contained the following: study
design, methods, participants, index test,
standard of reference, and final outcome
details. Reviewers confirmed all data
entries and checked the entries at least
twice for completeness and accuracy. If
some information was missing, we contacted the authors to obtain the complete
data.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol
2015.
Outcomes
Outcomes were sensitivity, specificity,
and likelihood ratios for numeric and
structural chromosomal abnormalities.
Exclusions
We excluded studies using karyotype or
CGH independently, and those in which
data were unavailable to obtain sensitivity and specificity.
Study selection
Two investigators (H.A.G-P., J.A-P.)
independently and blindly screened the
titles and abstracts to determine the
potential usefulness of the articles. Two
assessors (H.A.G-P., J.A-P.) applied
eligibility criteria to the full-text articles
during the final selection. When discrepancies occurred, a final decision was
reached by consensus. If the 2 assessors
FIGURE 3
Risk of bias across studies
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol
2015.
Risk of bias in and across individual
studies
The risk of bias was assessed independently by at least 2 researchers (H.A.GP., J.A-P.) using the QUADAS2 tool,
which evaluates items related to the
patient selection, the index and reference
tests, the flow and timing, and the concerns about their applicability. We solved
disagreements by consensus. The risk of
bias table (within and across studies) was
edited using Review Manager Software
version 5.2 (RevMan; Cochrane Collaboration, Oxford, England) to illustrate
the judgments for each study.
Summary measures
Analyses were performed in RevMan 5.2,
OpenMeta[Analyst] (http://www.cebm.
brown.edu/open_meta), and Stata 10
(StataCorp, College Station, TX) as
needed. The sensitivity, specificity, likelihood ratios, and diagnostic odds ratios
were measured for comparisons with
95% confidence intervals (CIs). We
performed fixed effects or random effect
metaanalysis according to the heterogeneity or homogeneity among the studies.
We also performed forest plots and
summary receiver operating characteristic for comparisons.
Heterogeneity between trials was
assessed through the I2 statistic. A value
50% can represent heterogeneity according to Higgins and Green13 (2011).
We also intended to analyze heterogeneity according to the following: reference standard, clinical spectrum, type of
method used, and age of the patient.
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FIGURE 4
CGH vs gold standard (CGH D karyotype): sensitivity and specificity forest plot
CGH, comparative genomic hybridization.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
Additional analyses
We intended to perform the following
subgroup analysis: low- and high-risk
pregnancies, history of chromosomal
abnormalities, parents with chromosomal abnormalities, maternal age
>37 years, biochemical screening plus
maternal ultrasonography, and abnormalities detected on ultrasonography. However, the studies lacked
sufficient data to perform these types
of analyses.
Sensitivity analysis
We undertook a sensitivity analysis
based on unknown significance variables
considered important for analysis and
results.
Publication bias
Publication bias was not assessed due to
the number of studies found (<10
studies) according to Higgins and
Green.13
R ESULTS
Study selection
In all, 137 articles were found with the
described search strategies; after exclusions, 6 and 5 studies were included in
qualitative (general description of the
data) and metaanalysis, respectively
(Armengol et al7 [2012], Fiorentino
et al14 [2011], Maya et al15 [2010],
Wapner et al16 [2012], and Van den
Veyver et al17 [2009]) (Figure 1).
Characteristics of included studies
In all, 9974 pregnant patients were
identified in the studies, with a median
of 971 (interquartile range, 269e4282)
patients per study. With respect to the
array platform used in the various
studies, the majority of studies used 1 of
2 arrays for CGH: Lee et al11 (2012)
initially (until 2010) performed arrays
based on bacterial artificial chromosomes (BAC) with 1-Mb resolution and
later used oligonucleotide arrays. Van
den Veyver et al17 (2009) analyzed 190
samples using BAC, and the rest were
analyzed with oligonucleotides. Maya
et al15 (2010) followed a similar protocol, although they later used wholegenome coverage BAC. In contrast,
Fiorentino et al14 (2011) analyzed samples by means of a single platform. One
study did not describe the type of array
used7 (Table 1).
Characteristics of the excluded
studies
The reasons for excluding these articles
were as follows: postnatal diagnosis
(13%), unrelated topic or outcome
(60%), lack of comparison between the
tests (6%), and lack of platform assessment (1.5%).
Risk of bias within the studies
For the studies of Armengol et al7
(2012), Lee et al11 (2012), Maya et al15
(2010), Van den Veyver et al17 (2009),
and Wapner et al16 (2012), we observed
an unclear risk of bias for the assessment
of index and reference tests, mainly
because the authors did not describe the
blinding of the evaluation. The studies of
Lee et al11 (2012) and Wapner et al16
(2012) exhibited an unclear risk of bias
for the assessment of patient selection.
There was only 1 study associated with a
low risk of bias with respect to all
items.14 (Figure 2).
Risk of bias across the studies
Although we did not observe a high risk
of bias, it is important to notice an unclear risk of bias for the index and
reference test items. In addition, we
observed a low risk of bias related to
applicability concerns in all evaluated
items (Figure 3).
FIGURE 5
CGH vs gold standard (CGH D karyotype): NLR and PLR forest plot
CGH, comparative genomic hybridization; NLR, negative likelihood ratio; PLR, positive likelihood ratio.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
330.e5 American Journal of Obstetrics & Gynecology MARCH 2015
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TABLE 2
Summary of findings for comparative genomic hybridization and
karyotype including unknown significance variants
CGH (including USV)
Karyotype (including USV)
Item
Random effect analysis
Random effect analysis
Negative likelihood ratio
0.032
0.291
95% CI
0.017e0.058
0.0841e1.011
P value
Heterogeneity (P value)
I
2
< .001
.052
.02
.845
66%
0%
Positive likelihood ratio
71.898
866.365
95% CI
31.942e161.834
223.017e3365.650
P value
< .001
< .001
Heterogeneity (P value)
< .001
.315
I
2
81%
Sensitivity
0.945
95% CI
0.837e0.983
0.673
0351e0.886
< .001
.29
Heterogeneity (P value)
< .001
< .001
84%
96%
I
Specificity
0.987
0.99
95% CI
0.970e0.994
0.998e1
P value
< .001
< .001
Heterogeneity (P value)
< .001
.637
I
2
81%
0%
CGH, comparative genomic hybridization; CI, confidence interval; USV, unknown significance variants.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet
Gynecol 2015.
Results of individual studies
CGH vs gold standard (CGH D
karyotype) including unknown
significance variables
We observed a sensitivity of 94.5% (95%
CI, 83.7e98.3%) and a specificity of
31e161) including a high heterogeneity
(I2 ¼ 66-81%, respectively) (Figures 4
and 5, and Table 2).
Karyotype vs gold standard (CGH D
karyotype) including unknown
significance variables
We observed a sensitivity of 67.3% (95%
CI, 35.1e88.6%) and a specificity of
99% (95% CI, 99.8e100%) associated
with high (I2 ¼ 96%) and low (I2 ¼ 0%)
heterogeneity, respectively.
The negative likelihood ratio was 0.29
(95% CI, 0.084e1.011) and the positive
likelihood ratio was 866 (95% CI,
223e3365) associated with low heterogeneity (I2 ¼ 0-16%) (Figures 6 and 7,
and Table 2).
16%
P value
2
Research
98.7% (95% CI, 97e99.4%) associated
with high heterogeneity (I2 ¼ 84% and
81%, respectively).
The negative likelihood ratio was
0.032 (95% CI, 0.017e0.058) and the
positive likelihood ratio was 71 (95% CI,
Sensitivity analysis
We performed a sensitivity analysis for
the inclusion or exclusion of unknown
significance variables (Table 3). With
respect to CGH, we observed no differences in the sensitivity, specificity, or
negative likelihood ratio. However, increases in the positive likelihood ratio and
diagnostic odds ratios were associated
with CGH. It is important to note that I2
decreases for negative/positive likelihood
ratios and specificity (Table 3).
With respect to karyotype, we
observed no differences in sensitivity,
specificity, negative/positive likelihood
ratios, diagnostic odds ratios, or heterogeneity (Table 3).
C OMMENT
Summary of major findings
In summary, 6 studies were included in
the qualitative analysis,7,11,14-17 and one
of these studies was excluded from the
FIGURE 6
Karyotype vs gold standard (CGH D karyotype): sensitivity and specificity forest plot
CGH, comparative genomic hybridization.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
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FIGURE 7
Karyotype vs gold standard (CGH D karyotype): NLR and PLR forest plot
CGH, comparative genomic hybridization; NLR, negative likelihood ratio; PLR, positive likelihood ratio.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
quantitative analysis because it did not
contain the requisite data.11 A total of
9974 pregnant women were included in
the studies. The sensitivity and specificity were 94.5% and 98.7%, respectively, for CGH compared with the gold
standard. The sensitivity and specificity
values for karyotype alone were 67.3%
and 99%, respectively.
Generation of the gold standard
CGH is used in prenatal diagnosis for the
detection of numerical and structural
chromosomal alterations. Given that
CGH is more sensitive in detecting the
loss or gain of genetic material than
karyotyping and that karyotyping detects polyploidy and translocations more
frequently than CGH, we decided to use
the sum of the 2 tests as a reference
method for all cases instead of only for
TABLE 3
Sensitivity analysis
CGH (including USV)
Variable
CGH (not including USV) Karyotype (including USV) Karyotype (not including USV)
Random effect analysis Random effect analysis
Random effect analysis
Random effect analysis
Negative likelihood ratio
0.032
0.049
0.291
0.291
95% CI
0.017e0.058
0.014e0.170
0.0841e1.011
0.0841e1.011
P value
Heterogeneity (P value)
< .001
.02
I2
66%
Positive likelihood ratio
71.898
< .001
.052
.052
.826
.845
.845
0%
1340.42
0%
866.365
860.488
223.017e3365.650
223.805e3308.421
95% CI
31.942e161.834
P value
< .001
< .001
< .001
< .001
Heterogeneity (P value)
< .001
.587
.315
.323
I
2
Sensitivity
95% CI
81%
0.945
0.837e0.983
388.092e4629.641
0%
0%
0.942
0.837e0.981
16%
0.673
0351e0.886
14%
0.673
0351e0.886
P value
< .001
< .001
.29
.29
Heterogeneity (P value)
< .001
< .001
< .001
< .001
84%
83%
96%
96%
I
2
Specificity
95% CI
0.987
0.970e0.994
0.999
0.998e1
0.99
0.998e1
0.999
0.998e1
P value
< .001
< .001
< .001
< .001
Heterogeneity (P value)
< .001
.633
.637
.637
I
2
81%
0%
0%
CGH, comparative genomic hybridization; CI, confidence interval; USV, unknown significance variants.
Saldarriaga. Karyotype vs genomic hybridization for prenatal diagnosis of chromosomal abnormalities. Am J Obstet Gynecol 2015.
330.e7 American Journal of Obstetrics & Gynecology MARCH 2015
0%
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selected cases, as proposed by the
American Congress of Obstetricians and
Gynecologists.18
Sensitivity, specificity, and likelihood
ratios
This systematic review is consistent with
the findings of previous studies. CGH
performed better compared with karyotype, largely with respect to sensitivity
(94.5% vs 67.3%). False negatives were
reduced from 33% with karyotype alone
to 4.5% with CGH. There was no difference in the rates of false positives:
1.3% for CGH and 1% for karyotyping.
In prenatal diagnosis, karyotyping is
considered the gold standard because of
its greater diagnostic accuracy compared
with other molecular techniques, such as
FISH and quantitative fluorescent polymerase chain reaction, which do not
identify structural abnormalities and
only diagnose the most frequent aneuploidies (13, 18, 21, and X).19-21
The results of this metaanalysis
observed CGH and karyotype results
similar to those reported by Armengol
et al7 (2012), who reported a sensitivity
of 98.2% and a specificity of 99.7% for
CGH and a sensitivity of 76.3% and a
specificity of 99.8% for karyotyping.
However, in the study by Armengol
et al,7 the gold standard was not clearly
defined. In our metaanalysis, a gold
standard was the inclusion of both tests
(karyotype and CGH).
Regarding the previous metaanalysis,12 it concluded that CGH increases the detection rate to diagnose
chromosomal abnormalities for prenatal
indications overall. The focus was on
detection and agreement rate of chromosomal abnormalities but not related
to sensitivity, specificity, and likelihood
ratios. On the other hand, although this
metaanalysis included 10 studies, they
described how only 4 had complete data
for agreement and 6 had incomplete
data. This metaanalysis also showed high
clinical and statistical heterogeneity that
limit the generalizability of the results.
Unknown significance variants are a
topic of interest to the geneticist as well
as to the obstetrician in that they may
increase parental anxiety and lead to
problems in prenatal counseling.22 The
frequency of unknown significance variants increases if the parents’ samples are
unavailable for further analysis because
parental genetic information can reveal
whether the variation detected in the
fetus is inherited or de novo. However,
due to incomplete penetrance and variable expression, inherited variants are
not always benign.23 It is expected that
with the evolution of molecular techniques in CGH and the development
of databases comparing genomic
results and phenotypes, the number of
unknown significance variants will
decrease.24
After performing sensitivity analysis
including and excluding unknown significance variants, we observed that the
sensitivity and specificity were very
similar for both diagnostic tests
(Table 3). This result is in contrast to
other studies using CGH, such as Iafrate
et al25 (2004), in which the percent
agreement between techniques increased
as unknown significance variants were
eliminated.
It is clear that the balanced chromosomal rearrangements, such as balanced
translocations and inversions, are not
identified with CGH. Giardino et al26
(2009) reported de novo balanced
chromosomal rearrangement rates in
prenatal diagnosis to be 0.09% in amniotic fluid, 0.08% by chorionic villus
sampling, and 0.05% in cordocentesis
samples. Furthermore, the chromosomal phenotype in approximately 40%
of patients with a balanced translocation
identified by karyotype was determined
to be unbalanced or to exhibit loss of
genetic material and was therefore
detectable by CGH.27,28 This finding
strengthens the rationale by which
Fiorentino et al14 (2011) and Wapner
et al16 (2012) discarded these patients in
their analysis. In light of these findings,
CGH can provide important information in cases of balanced translocations.
However, karyotyping is key to identifying chromosomal structure and
microscopic location in such cases, and
the use of CGH is justified after
karyotyping.
Mosaicism is diagnosed more
frequently by karyotype than by CGH
depending on the percentage of cells
Research
exhibiting the abnormality via karyotype
or by FISH but not depending on
the CGH matrix used.29 Cases of prenatal diagnosis of mosaicism must be
confirmed after birth. For this reason,
Fiorentino et al14 (2011) and Wapner
et al16 (2012) do not include mosaicism
in the results of their literature analysis,
although Armengol et al7 (2012), Maya
et al15 (2010), and Van den Veyver et al17
(2009) do. In this metaanalysis, analyses
were performed with respect to the
methodologies used in each study, which
results in heterogeneity.
Strengths
The strengths of this study include the
following: the report of sensitivity,
specificity, and likelihood ratios; the
rigor with which this study was conducted; following the steps proposed by
Cochrane for systematic reviews of
studies of diagnostic accuracy; its previous protocol publication in the PROSPERO database at the University of York;
and its writing according to the PRISMA
methodology.
Limitations
The weaknesses of this metaanalysis arise
from the clinical heterogeneity between
the selected papers, the inclusion of
prospective and retrospective studies,
and the heterogeneity in the CGH arrays
used.
Additionally, it was found that the
likelihood ratios of the tests exhibited
low heterogeneity and high sensitivity
when likelihood ratios depend on the
sensitivity and specificity. This could be
due to power problems in the test, as
described by Higgins and Green13
(2011).
It is worth noting that the included
studies were found to be biased, primarily due to the lack of blindness in the
description, failure to describe the allocation method, and patient attrition
during follow-up.
Conclusion
This systematic review provides evidence for the relative advantage of
CGH over karyotype in prenatal diagnosis; CGH exhibits higher sensitivity
with similar specificity, although
MARCH 2015 American Journal of Obstetrics & Gynecology
330.e8
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Obstetrics
clinical heterogeneity is an important
issue to consider. The detection of the
loss and gain of genetic material by
array technology produces a combination of well-described pathological
findings and others of unknown significance. However, the advantages of
CGH over karyotype persisted even
when these results were removed from
the analysis.
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A PPENDIX
Search strategies
Search strategy for MEDLINE via
PubMed:
(‘Comparative genomic hybridization’ [mh] OR ‘a-CGH’ [tw] OR aCGH
[tw] OR CGH [tw]) AND
(Karyotype [mh] OR caryotype [tw]
OR ‘chromosomal arrangement’ [tw] OR
‘chromosomal configuration’ [tw] OR
‘chromosomal pattern’ [tw] OR ‘chromosome arrangement’ [tw] OR kariotype
[tw] OR karotype [tw] OR karytype [tw])
AND (‘Prenatal diagnosis’ [mh] OR ‘Fetal
aneuploidy’ [mh] OR ‘Maternal serum
screening’ [mh] OR ‘Chromosomal
anomalies’ [tw] OR ‘Chromosomal defects’ [tw]) AND (‘Diagnostic test, routine’
[mh] OR ‘Sensitivity and specificity’ [mh]
OR ‘Roc curve’ [mh] OR ‘Predictive value
of tests’ [mh] OR Sensitivity [tw] OR
Specificity [tw] OR Accuracy [tw] OR
‘Predictive value’ [tw] OR Likelihood
[tw])
Search strategy for EMBASE:
(comparative genomic hybridization [Emtree] OR ‘a-CGH’ [tw] OR
aCGH [tw] OR CGH [tw]) AND
(Karyotype [Emtree] OR caryotype
[tw] OR ‘chromosomal arrangement’
[tw] OR ‘chromosomal configuration’ [tw] OR ‘chromosomal pattern’
[tw] OR ‘chromosome arrangement’
[tw] OR kariotype [tw] OR karotype
[tw] OR karytype [tw]) AND (Prenatal diagnosis [Emtree] OR aneuploidy [Emtree] OR maternal serum
screening test [Emtree] OR chromosome aberration [Emtree]) AND
(Diagnostic accuracy [Emtree] OR
Sensitivity and specificity [Emtree]
OR receiver operating characteristic
Obstetrics
ajog.org
[Emtree] OR Predictive value [Emtree]
OR Likelihood [tw])
Search strategy for CENTRAL and
Cochrane Register of Diagnostic Test
Accuracy Studies:
(‘Comparative genomic hybridization’
[mh] OR ‘a-CGH’ [tw] OR aCGH [tw]
OR CGH [tw]) AND (Karyotype [mh] OR
caryotype [tw] OR ‘chromosomal arrangement’ [tw] OR ‘chromosomal
configuration’ [tw] OR ‘chromosomal
pattern’ [tw] OR ‘chromosome arrangement’ [tw] OR kariotype [tw] OR karotype
[tw] OR karytype [tw]) AND (‘Prenatal
diagnosis’ [mh] OR ‘Fetal aneuploidy’
[mh] OR ‘Maternal serum screening’
Research
[mh] OR ‘Chromosomal anomalies’ [tw]
OR ‘Chromosomal defects’ [tw]) AND
(‘Diagnostic test, routine’ [mh] OR
‘Sensitivity and specificity’ [mh] OR ‘Roc
curve’ [mh] OR ‘Predictive value of tests’
[mh] OR Sensitivity [tw] OR Specificity
[tw] OR Accuracy [tw] OR ‘Predictive
value’ [tw] OR Likelihood [tw])
MARCH 2015 American Journal of Obstetrics & Gynecology
330.e10