1 s2.0-s1525157820300106-main

Clinical Utility of a High-Resolution Melting
Test for Screening Numerical Chromosomal
Abnormalities in Recurrent Pregnancy Loss
Yulin Zhou,* Wenyan Xu,* Yancheng Jiang,y
Zhongmin Xia,* Haixia Zhang,* Xiaolu Chen,* Zengge Wang,* Yunsheng Ge,* and
Qiwei Guo*
From the United Diagnostic and Research Center for Clinical Genetics,* Women and Children’s Hospital, School of Medicine & School of Public Health,
Xiamen University, Xiamen; and the Department of Clinical Laboratory,y
Quanzhou First Hospital affiliated with Fujian Medical University, Quanzhou,
People’s Republic of China
Accepted for publication
January 12, 2020.
Address correspondence to
Qiwei Guo, M.S., United
Diagnostic and Research Center
for Clinical Genetics, Women
and Children’s Hospital, School
of Medicine & School of Public
Health, Xiamen University,
Xiamen, Fujian 361102,
People’s Republic of China.
E-mail: guoqiwei@xmu.edu.cn.
Recurrent pregnancy loss (RPL) occurs in approximately 5% of clinically identified pregnancies.
Determining the cause of RPL is essential. Genetic testing, accompanied by an evidence-based workup,
is the well-accepted process for evaluating RPL; however, current genetic tests have limitations in
clinical practice. We, thus, developed a high-resolution melting analysisebased test (HRM test) to
screen for the most common numerical chromosomal abnormalities present in the products of
conception. We examined 765 products-of-conception samples with known karyotypes retrospectively
using the HRM test, which showed high technical sensitivity (96.1%) and specificity (96.3%) as well as
a high positive predictive value (95.9%) for the screening of chromosomal abnormalities. The cost-
effectiveness of four RPL evaluation strategies that employ different genetic tests, karyotyping,
chromosomal microarray/next-generation sequencing, the HRM test, and a combination of the HRM test
and chromosomal microarray/next-generation sequencing, was then compared. The costs of diagnosing
an explained RPL using karyotyping or the HRM test alone were similar. Performance of the HRM
screening test before chromosomal microarray/next-generation sequencing analysis improved cost-
effectiveness by approximately 30%. Cost-effectiveness was more prominent in the advanced maternal
age group. Thus, the HRM test could be used as an initial screening tool, followed by other diagnostic
methods to improve the cost-effectiveness of RPL evaluation, or as an alternative genetic test when
other methods are unavailable or unaffordable. (J Mol Diagn 2020, 22: 523e531; https://doi.org/
10.1016/j.jmoldx.2020.01.005)
Recurrent pregnancy loss (RPL), which is defined as two or
more failed clinical pregnancies, affects approximately 5%
of reproductive-aged couples.1e3
Genetic defects, anatomic
and endocrine abnormalities, inherited thrombophilia, and
infections have been considered as definite or probable
causes of RPL.4,5
Genetic defects, particularly chromosomal
abnormalities (CAs), are involved in most RPLs.4
Identi-
fying the causes of miscarriages not only assists clinicians in
genetic counseling and therapeutic management but also
reduces the emotional distress and psychological burden in
affected couples.6,7
Therefore, careful evaluation of RPL is
a consensus practice, although the best evidence-based
workup (EBW) is still being debated. Generally, an
extensive workup includes an evaluation of parental kar-
yotypes, examination of the uterine cavity, and testing of
immunologic markers and hormone levels.2,8
However, the
diagnostic yield of explained RPLs, which are cases with
Supported by National Natural Science Foundation of China grant
81572084 (Y.Z.), Xiamen Science and Technology Bureau Major Project
grant 3502Z20171006 (Y.Z.), and Natural Science Foundation for Distin-
guished Young Scholars of Fujian Province project number 2015D012
(Q.G.).
Y.Z., W.X., and Y.J. contributed equally to this work.
Disclosures: None declared.
Copyright ª 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.
https://doi.org/10.1016/j.jmoldx.2020.01.005
jmd.amjpathol.org
The Journal of Molecular Diagnostics, Vol. 22, No. 4, April 2020

abnormal results on at least one test, is only 40% to 60%
with EBW.5,9
Considering the high prevalence of CAs in RPL, a
combination of genetic tests and EBW has been proposed
and has been shown to improve not only the diagnostic yield
but also the cost-effectiveness of RPL evaluation.10e13
Karyotyping, which can detect numerical CAs (NCAs)
and structural changes larger than 5 Mb, is the conventional
gold-standard genetic test for RPL evaluation. However,
karyotyping requires cell culture and frequently yields null
results due to culture failure caused by fetal demise or
macerated tissue or false results due to the preferential
growth of maternal cells. Recently, chromosomal micro-
array (CMA) and next-generation sequencing (NGS) have
shown promising technical and clinical utility in RPL ana-
lysis.13e17
Compared to karyotyping, CMA and NGS do not
require cell culture and yield more genetic information (eg,
submicroscopic deletions and duplications, and a loss of
heterozygosity) at the genome level, thus facilitating a
deeper understanding of the etiology of miscarriages. In
addition, the results of CMA and NGS are derived from a
standardized procedure combined with computational
analysis and are, thus, more objective than results of
karyotyping, which is susceptible to human error in terms of
both operation and interpretation. Therefore, CMA and
NGS are used as the de facto standards for the genetic
analysis of RPL in some clinical practices.
Although there is no controversy in the clinical use of ge-
netic testing for the evaluation of RPL, some issues remain in
its clinical practice, especially in underdeveloped regions with
large populations. For example, karyotyping of the product of
conception (POC) is labor-intensive, time-consuming, and
requires specialists, requirements that make it difficult to meet
the massive clinical demand for RPL detection. In addition,
CMA and NGS are relatively expensive tests that pose a
financial challenge to patients. In recent years, at our
institution, the Women and Children’s Hospital at the School
of Medicine of Xiamen University (Xiamen, China), the
cytogeneticists were frequently busy with second-trimester
prenatal diagnoses. Thus, CMA and NGS were used for POC
analysis. However, statistical analysis of data revealed that
although most patients expressed a desire for genetic testing,
<5% of POCs were examined, with the cost (440 USD per
case) being cited as the major barrier. The cost of CMA or NGS
is decreasing; however, the costs are likely to remain high
enough to hinder the acceptance of CMA and NGS as
affordable methods of RPL evaluation in underdeveloped
regions.
Inspired by the success of prenatal screening and diag-
nosis of Down syndrome, we hypothesized that a
well-accepted screening method combined with a diagnostic
method, such as CMA or NGS, would advance the clinical
practice of genetic testing for POCs. High-resolution
melting (HRM) analysis is one of the best screening
methods for detecting point mutations and aneuploidy.18e20
It has been used in the screening of trisomies 13, 18, 21, and
sex chromosome aneuploidies for prenatal diagnosis, and
47,XXY in infertile men.21,22
This method has displayed
high clinical sensitivity and specificity, as well as a
high-resolution detection of mosaicism. Therefore, we
developed a genetic test based on HRM and evaluated its
accuracy for NCA screening. The cost-effectiveness of four
different strategies of evaluating RPL was subsequently
compared to validate our hypothesis regarding the clinical
utility of the HRM screening test.
Materials and Methods
Establishment of the HRM Test
The technical basis of this test is the HRM analysis of
segmental duplication, which was described in our previous
study.18
Briefly, paired paralogous sequences located on two
chromosomes are simultaneously amplified by a primer pair,
and the melting-curve profiles of the resulting amplicons reveal
the numerical information of the target chromosomes. There-
fore, by analyzing melting-curve profiles with a proper
data-analysis procedure, NCAs could be identified.
Based on the previously reported frequency of NCAs in
POCs,4
five assays were designed to target chromosomes 13
and 15 (13 versus 15 assay), chromosomes 18 and 21 (18
versus 21 assay), chromosomes 16 and 22 (16 versus 22
assay), chromosomes 2 and X (2 versus X assay), and
chromosomes X and Y (X versus Y assay) (Figure 1). The
extreme value of the relative signal difference (E value) of
each sample was determined to evaluate the presence of
NCAs.
For the 13 versus 15, 18 versus 21, and 16 versus 22
assays, 46,XX and 46,XY samples (45 each, for a total of 90
samples) were analyzed. The E values of these 90 samples
were analyzed with a normality test, and the results showed
that they were not normally distributed. Therefore, the
ranges of the E values for these samples were defined as the
reference intervals for the unaffected samples (Figure 1).
Samples with E values within the defined reference intervals
were considered to be low risk for NCAs in the target
chromosomes. In contrast, samples with E values outside of
the reference intervals were considered to be high risk for
specific types of NCAs or mosaicism.
For the 2 versus X and X versus Y assays, each 90 46,XX
and 46,XY samples were analyzed. Similarly, the E values
of these samples were not normally distributed, and the
ranges of the E values for these samples were defined as the
reference intervals for 46,XX and 46,XY, respectively
(Figure 1). A sample with an E value within the 46,XY or
46,XX reference intervals in both assays was considered to
be low risk for NCAs, while a sample with E values within
the reference intervals for 46,XY in the 2 versus X assay
and 46,XX in the X versus Y assay was considered to be
high risk for 45,X. Samples outside of the reference
intervals were considered to be high risk for specific types
of NCAs or mosaicism.
Zhou et al
524 jmd.amjpathol.org - The Journal of Molecular Diagnostics

The DNA samples used in this study were derived from
peripheral blood lymphocytes with confirmed karyotypes,
which were obtained from the molecular diagnostics labo-
ratory of the Women and Children’s Hospital at the School
of Medicine of Xiamen University.
Retrospective Samples
During 2013 to 2016, 860 POCs from RPL patients were
sent to the cytogenetics laboratory of the Women and
Children’s Hospital at the School of Medicine of Xiamen
University, for G-banded karyotyping, of which 765 were
successfully analyzed. The remaining samples from these
765 uncultured POCs were collected to evaluate the
screening accuracy of the HRM test. The karyotypes of
these retrospective samples are summarized in Table 1,
Figure 2, and Supplemental Table S1. In brief, NCAs were
detected in approximately 60% of the tested POCs
(Figure 2A). Of the samples with NCA, 67.8% had
numerical changes in the chromosomes that were targeted
by the HRM test, and thus were theoretically detectable
(Figure 2B).
DNA was extracted from approximately 20 mg of uncul-
tured POC using the QIAamp Fast DNA Tissue Kit (Qiagen,
Valencia, CA) according to the manufacturer’s instructions.
The DNA concentration was determined by measuring the
absorbance at 260 nm using a NanoDrop 2000 spectropho-
tometer (Thermo Fisher Scientific, Waltham, MA).
PCR and HRM
PCR amplification and HRM analysis were performed on a
LightCycler 480 II Thermocycler (Roche Applied Science
Figure 1 Design of a high-resolution melting test including five assays. E value, the extreme value of the relative signal difference, which is a melting
profile derived from plotting the melting signal difference between the target and reference samples. Black line denotes melting profile of the reference
sample, which is indicated in the lower right corner of the image; colored lines are used to differentiate melting profiles among reference intervals without
specific meaning. NCA, numerical chromosomal abnormalities.
Table 1 Information on Retrospective POC Samples
Parameter
Value
MA
<35 years
MA
!35 years Total
Number of POC 601 164 765
Number of CA-POC 375 116 491
Number of NCA-POC 345 114 459
NCA-POC/CA-POC, % 92.0 98.3 93.5
NCA-POC/total POC, % 57.4 69.5 60.0
NCA-POC with detectable
changes for HRM test
(target NCA-POC)
235 76 311
Target NCA-POC/total NCA-POC, % 68.1 66.7 67.8
Target NCA-POC/total POC, % 39.1 46.3 40.7
CA, chromosomal abnormality; HRM, high-resolution melting; MA, maternal
age; NCA, numerical chromosomal abnormality; POC, product of conception.
Screening NCAs in RPL by HRM
The Journal of Molecular Diagnostics - jmd.amjpathol.org 525

GmbH, Mannheim, Germany). Each 25-mL reaction con-
tained 10 mmol/L Tris-HCl (pH 8.3), 50 mmol/L KCl, 1 U
TaqHS (Takara, Dalian, China), 2.5 mmol/L Mg2þ
,
0.8 Â LightCycler 480 ResoLight Dye (Roche Applied
Science GmbH), 0.2 mmol/L of each deoxy-nucleoside
triphosphate, 0.2 mmol/L of each forward and reverse
primer, and 25 ng of DNA template. The primers that were
used are listed in Table 2. The reaction conditions were as
follows: 95
C for 3 minutes followed by 40 cycles of 95
C
for 15 seconds, 60
C for 15 seconds, and 72
C for 15
seconds. The HRM analysis began with a denaturation step
at 95
C for 1 minute, and a renaturation step at 40
C for
1 minute, followed by melting (60
C to 90
C, with a
0.03
C/second ramp rate), and 20 fluorescence acquisitions
per degree centigrade were collected.
HRM Data Analysis
HRM data were analyzed as fluorescence-versus-
temperature graphs using Gene Scanning software version
1.5.0 (Roche Applied Science GmbH). The melting-curve
analysis comprised four steps: i) data normalization was
conducted by selecting the linear regions of the melting
curves before and after DNA dissociation, ii) data were
adjusted by shifting the temperature axes of the normalized
melting curves, iii) the relative signal difference versus
temperature was plotted using the reference sample as a
baseline, and iv) the E value was extracted for NCA eval-
uation (Figure 1).
Reference Samples
In the HRM data analysis, a reference sample was used as a
baseline to plot the relative signal difference and to obtain
the E value. For the 13 versus 15, 18 versus 21, and 16
versus 22 assays, the reference sample was prepared by
mixing 50 46,XX and 50 46,XY samples in equal amounts.
For the 2 versus X and X versus Y assays, the reference
sample was prepared by mixing equal amounts of 100
46,XY samples.
Cost-Effectiveness Analysis
A simplified decision-analytic model was developed using
TreeAge Pro 2011 software version 1.0.12.1 (TreeAge
Figure 2 Karyotypic profiles of retrospective product-of-conception
(POC) samples. A: Overall karyotypic profiles of 765 retrospective POC
samples. B: Karyotypic profiles of retrospective POC samples with numerical
chromosomal abnormalities. The percentages indicate the percentage of
samples with changes detectable on high-resolution melting test. Com-
bined aneuploidy: polyploidy defines a polyploid chromosome complement
with additional or missing chromosome(s), such as 70,XXY,þ21 or
91,XXYY,e18.
Table 2 Primer Sequences of HRM Test
Assay Amplicon location (GRch37/hg19) Primer sequence
13 vs 15 chr13:92921201-92921295 F: 50
-GTTTACATTTGTCTATTTGGTTGTT-30
chr15:23710072-23710166 R: 50
-GAAGAGTATAAACAGACCAAATGGT-30
18 vs 21 chr18:15053830-15053940 F: 50
-CACCACAGAGGTCAAGTAAG-30
chr21:29398456-29398566 R: 50
-CTCTCAGGCCTATGACTTCA-30
16 vs 22 chr16:55888175-55888244 F: 50
-TGCCCTTCCATTCCTCTT-30
chr22:23703154-23703223 R: 50
-GAGCAGAAGGACATTTCAAGTA-30
2 vs X chr2:173463301-173463380 F: 50
-GCAGTTAATGAATGTGCCAA-30
chrX:45387886-45387965 R: 50
-AAGCCAGCCAGTATTTTAACTA-30
X vs Y chrX:24228420-24228515 F: 50
-GAACACCTTGCCAAGAAGAA-30
chrY:2846961-2847056 R: 50
-CAGCTTGTGGCTCTCCA-30
F, forward; HRM, high-resolution melting; R, reverse.
Zhou et al

Software, Williamstown, MA) to compare the cost-
effectiveness of four strategies that included different
genetic tests (karyotyping, CMA/NGS, the HRM screening
test, and a combination of the HRM screening test and
CMA/NGS) followed by EBW to identify the definite or
probable causes of RPL (Figure 3). In general, the model
assumes that when the genetic test of the POC yielded a
normal- or low-risk result for an NCA or an inconclusive
result, the patient would undergo EBW, based on the rec-
ommendations of the American Society for Reproductive
Medicine (ASRM workup).2
In contrast, when genetic
testing of the POC showed CAs or high risk for an NCA,
there would be no further evaluation of the patient.
Using the literature, it was assumed that the diagnostic yield
of the ASRM workup was 42% when used alone and 85%
when used after karyotyping/CMA/NGS analysis.5,9,13
Based
on this assumption, it was also assumed that the diagnostic
yield of the ASRM workup was 63.5% (the mean of 42% and
85%)whenusedaftertheHRMtest.Moreover,a100%success
rate was assumed for POC analysis by CMA/NGS, which de-
tects 8.7% more CAs than does karyotyping.14,16,23
Although the self-pay costs of these tests would be slightly
differentbetweenprovincesinmainlandChinaaccordingtothe
level of economic development, they reflect the true costs (eg,
labor and materials) of the tests. Therefore, this study used the
median self-pay cost of each test as is currently used in three
provinces with different levels of economic development
(Fujian, Guangdong, and Jiangxi) (Table 3). The costs of all
tests are expressed in United States dollars (USD), with a hy-
pothetical exchange rate of 6.8 to the Chinese yuan.
Statistical Analyses
Normality testing was performed using OriginPro software
version 8.0 (OriginLabCorp.,Northampton,MA) to determine
whetherasetofEvaluesfollowedanormaldistribution.Thec2
test was performed using SPSS statistical software version 20.0
(IBM, Armonk, NY) to determine the significant differences
for HRM tests between different maternal age groups.
Ethics Statement
Signed informed consent had been obtained from patients
who received clinical POC karyotyping and agreed to the
use of the excess POC samples for research purposes. These
excess samples were used as the retrospective samples in
this study. No additional sampling or any other health-
related intervention was performed. Except for the karyo-
types and maternal ages, all other information, including the
names of the patients, was withheld from the study group.
Therefore, according to the ethics administration for clinical
study, issued by the China Food and Drug Administration,
Figure 3 Decision-analytic model for four
strategies including different genetic tests com-
bined with evidence-based workup (EBW) for
recurrent pregnancy loss (RPL) evaluation. In the
first strategy, karyotyping, the conventional gold
standard test, is used for genetic testing of the
product of conception (POC); in the second strat-
egy, chromosomal microarray (CMA) or
next-generation sequencing (NGS), the de facto
standard tests, is used for genetic testing of POC;
in the third strategy, high-resolution melting
(HRM) testing alone is used for genetic testing of
POC, assuming that other genetic tests are un-
available or unaffordable; and in the fourth strat-
egy, HRM screening is used before CMA/NGS
diagnosis for genetic testing of POC. Based on the
experimental or hypothetical diagnostic yields, the
numbers of cases with corresponding results are
listed, while hypothetical numbers are indicated in
parentheses. CA, chromosomal abnormality.
Table 3 Costs of Tests in Mainland China
Test Cost, USD
HRM screening test 30
POC karyotyping 100
POC-CMA or NGS 440
EBW (ASRM workup) 222
Parental karyotypes 118
Lupus anticoagulant 8.8
Antiphospholipid antibodies 10.2
Sonohysterogram 58.8
Thyroid stimulating hormone 7.6
Prolactin 7.6
Hemoglobin A1c 11
ASRM, American Society for Reproductive Medicine; CMA, chromosomal
microarray; EBW, evidence-based workup; HRM, high-resolution melting;
NGS, next-generation sequencing; POC, product of conception; USD, US
dollars.

additional informed consent was not required for this study.
The study protocol was approved by the research ethics
committees of the Women and Children’s Hospital at the
School of Medicine of Xiamen University.
Results
Screening Accuracy of the HRM Test
A total of 765 retrospective samples were examined using
the HRM test, and the results were compared to those ob-
tained using karyotyping. Using the HRM test, samples
were classified as either low or high risk for NCAs, without
specification of their possible karyotypes. In total, 316
samples were high risk for NCA, and the results from 297 of
these correlated well with the karyotyping results. The
remaining 449 samples were considered as low risk for
NCA, and the results from 437 of these correlated well with
the karyotyping results. The accuracy data are summarized
in Table 4. In terms of detecting target NCAs, the HRM test
showed high technical sensitivity (96.1%) and specificity
(96.3%) (Supplemental Table S2). In terms of screening for
CAs in all POCs, the HRM test showed a 61.7% screening
sensitivity and a 95.3% screening specificity as well as a
high positive predictive value (PPV; 95.9%) (Supplemental
Table S3). When grouped by maternal age, the screening
accuracy of the HRM test was higher in the advanced
maternal age group (age !35 years) than that in the younger
age group (age 35 years) (Supplemental Tables S4eS7).
The c2
test revealed that the accuracy differences on the
HRM test between the two age groups were not statistically
significant (Supplemental Table S8).
Thirty-one discordant samples, including 17 false-positive,
12 false-negative, and two discordant positive results were
found in the accuracy study. These discordant samples were
further analyzed with a commercial NGS assay (BGI,
Shenzhen, China), as described previously.16
The results are
provided in Supplemental Tables S9eS11. NGS supported
the HRM results in eight of 17 false-positive cases, eight of 12
false-negative cases, and one of the two discordant positive
cases.
Cost-Effectiveness Analysis
For each strategy, the cost per case was derived from the
total cost, which was the sum of the costs of the genetic tests
and EBW, divided by the number of total cases that un-
derwent RPL evaluation (Figure 3). The effectiveness of a
strategy was calculated by dividing the total number of
explained cases by the total number of cases that underwent
RPL evaluation. Specifically, an explained case was defined
as a CA case for karyotyping or CMA/NGS, or an abnormal
case for EBW. In terms of the HRM test, the number of
explained cases was calculated by multiplying the number
of high-risk cases by the screening PPV. The results of the
cost-effectiveness analysis of different maternal age groups
are summarized in Table 5. The threshold costs, represent-
ing the points at which the costs of the two strategies (CMA/
NGS versus HRM screening þ CMA/NGS) would be
equivalent, were also estimated. The results showed that
when the cost of CMA/NGS decreased to 68.3 USD or the
cost of the HRM screening test increased to 178.0 USD,
the addition of the HRM screening test was no longer cost-
effective.
Discussion
Compared to screening samples from second-trimester
amniocentesis and infertile men,22,23
the screening of
POCs is more challenging because they contain more
types of CAs and are more susceptible to maternal
Table 4 Accuracy of the HRM Assay
Accuracy MA 35 years MA !35 years Total
In terms of target NCAs
Technical sensitivity 95.7 97.4 96.1
Technical specificity 95.6 98.9 96.3
Positive predictive value 93.4 98.7 94.6
Negative predictive value 97.2 97.8 97.3
In terms of total CAs
Screening sensitivity 61.1 63.8 61.7
Screening specificity 94.7 97.9 95.3
Positive predictive value 95.0 98.7 95.9
Negative predictive value 59.4 52.8 58.1
Data are expressed as %.
CA, chromosomal abnormality; HRM, high-resolution melting; MA,
maternal age; NCA, numerical chromosomal abnormality.
Table 5 Cost-Effective Analysis of Different Strategies of Evaluating Recurrent Pregnancy Loss at Different MAs
Strategy
MA 35 years MA !35 years Total
C, USD E C/E C, USD E C/E C, USD E C/E
Karyotyping þ EBW 198.8 0.886 224.4 182.0 0.897 202.9 195.3 0.888 219.9
CMA/NGS þ EBW 511.3 0.952 537.1 491.4 0.963 510.3 507.0 0.954 531.4
HRM þ EBW 163.0 0.765 213.1 150.5 0.786 191.5 160.3 0.769 208.5
HRM þ CMA/NGS þ EBW 361.2 0.938 385.1 316.2 0.951 332.5 351.5 0.940 373.9
C, cost per case; CMA, chromosomal microarray; E, effectiveness; EBW, evidence-based workup; HRM, high-resolution melting; MA, maternal age; NGS,
next-generation sequencing; USD, US dollars.
Zhou et al

contamination. To address these issues, the HRM test in
this study was designed to target seven autosomes and the
sex chromosomes, which are most frequently affected in
POCs, to attain a relatively high screening yield. More-
over, only reference intervals for unaffected samples were
defined. As long as the numerical changes were clear
enough to be differentiated by the defined reference in-
tervals, various types of CAs, including mosaicisms and
maternally contaminated samples, were classified as high
risk, without the need for specifying their karyotypes. This
strategy simplifies the data analysis of POCs with
complicated backgrounds. When 765 clinical POCs with
variously representative CAs were comprehensively eval-
uated, the established HRM test displayed high technical
sensitivity (96.1%) and specificity (96.3%), as well as a
high PPV (95.9%) for NCA screening (Table 3). In
accordance with previous studies,10,11
the percentage of
NCA-containing POCs was higher in the advanced age
group (age !35 years) than in the younger age group (age
35 years; 69.5% versus 57.4%) (Table 1). Similarly, the
percentage of target NCAs was also higher in the
advanced age group (46.3% versus 39.1%) (Table 1).
Therefore, as expected, the screening accuracy of the
HRM test was higher in the advanced maternal age group,
although the difference was not statistically significant
(Table 4 and Supplemental Table S8). Notably, NGS
supported the HRM results in more than half of the
discordant cases (17 of 31), indicating that the authentic
specificity and PPV of the HRM test may be higher
(Supplemental Tables S9eS11). Therefore, the HRM test
is highly accurate when screening for NCAs in the eval-
uation of RPLs.
The HRM test is also inexpensive because the reagent
costs of this test are low. In an era of globally contracting
health care resources, the cost and cost-effectiveness of
diagnostic strategies are crucial concerns. Several clinical
scenarios were assessed in our decision-analytic model
based on the accuracy data on the HRM test (Figure 3).
Recently, Popescu et al13
reported a high diagnostic yield
(95%) with the combined use of CMA and ASRM workup.
Based on their findings, the use of CMA/NGS as the first
genetic test could achieve the highest diagnostic yield
(0.954) among those of the four strategies used in our
model; when HRM screening is added, the diagnostic yield
would decrease by approximately 1.4%, while the
cost-effectiveness would improve by approximately 30%
(373.9 versus 531.4 USD). When the patients were grouped
by maternal age, the cost-effectiveness was more evident
(improved by approximately 35%) in the advanced age
group due to the increased screening sensitivity and PPV
resulting from the higher prevalence of target NCAs
(Tables 1 and 3). Therefore, alterations that increase the
screening sensitivity or PPV of the HRM test could further
improve its clinical utility; for example, the prevalence of
target NCAs can be increased by adding assays with
more target chromosomes to the test. Although the costs of
CMA/NGS are decreasing, which could limit the cost
advantage of the HRM test, their further decrease to the
threshold cost (68.3 USD) would be unlikely due to the high
cost of supportive hardware. Moreover, the
cost-effectiveness of the HRM test has much room for
improvement. This improvement could be achieved by
further decreasing the test price or increasing the effec-
tiveness by, for example, adding additional assays including
other target chromosomes. Finally, when the conventional
or de facto gold-standard genetic tests are unavailable or
unaffordable, the combined use of HRM screening and an
ASRM workup provides a predicted diagnostic yield of
76.9% in the evaluation of RPL, and the cost of diagnosing
an explained RPL case using this method is similar to that of
diagnosing it through karyotyping (208.5 versus 219.9
USD), which is 60.8% lower than that of CMA or NGS
(208.5 versus 531.4 USD) (Table 5). However, the
decreased effectiveness due to missing abnormalities (eg,
structural abnormalities and nontargeted NCAs) should be
considered when using the HRM test alone.
Although no corresponding cost-effectiveness analyses
have been reported, quantitative fluorescent PCR and multi-
plex ligationedependent amplification (MLPA) have also
been used for the genetic testing of POCs.24e29
Previous
studies using quantitative fluorescent PCR targeted chromo-
somes 13, 18, 21,X, and Y, which cover a limited range of the
CA spectrum in RPL and thus showed lower diagnostic
yields.25e27
Recently, Donaghue et al24
reported the use of
quantitative fluorescent PCR in the screening of target chro-
mosomes similar to those in our study. However, the cost of
this assay was relatively high due to the use of 31 pairs of
fluorophore-labeled primers and the need for capillary
electrophoresis analysis. Based on our model, the cost
advantage of the screening assay will be lost when its price
reaches 178.0 USD. In MLPA, all chromosomes can be tar-
geted in a single reaction, which suggests a higher diagnostic
yield than that of the HRM test. In our group of POCs, 420
cases had relative chromosome dosage differences, which are
theoretically detectable by MLPA. Therefore, the technical
sensitivity, specificity, and screening PPV of MLPA were
assumed to be 100%, and a cost-effectiveness analysis was
performed in which MLPA was used as a screening test before
CMA/NGS detection. In comparison with the HRM test, an
extra 58.5 USD was added for an explained RPL when using
MLPA as the screening method (432.4 vs 373.9 USD)
(Supplemental Table S12). The threshold cost analysis indi-
cated that only when the price of MLPA is low (91.2 USD)
will MLPA and the HRM test have comparable cost-
effectiveness. Similar to quantitative fluorescent PCR, the
cost of MLPA would be relatively high due to the complex
reaction components and the need for capillary electropho-
resis analysis. However, even if the threshold price of MLPA
can be achieved, the HRM test is still competitive in terms of
turnaround time, labor, and test capacity. In addition, starting
with a lower-cost genetic test is more psychologically
acceptable to patients.

It should be noted that the cost-effectiveness of the HRM
test was based on the price system in mainland China and
could be distinct from that in other districts. Therefore, the
model was tested based on a reported cost (Supplemental
Table S13) of RPL analysis in the United States.13
The re-
sults showed that the addition of the HRM screening test is
still cost-effective (Supplemental Table S14). However, due
to the variation in the price system, the cost-effectiveness
benefit of the HRM test should be reevaluated in each
clinical practice.
The results of 31 POCs were discordant between the
HRM test and karyotyping. There are several possible
causes, with maternal contamination as a notable cause of
false-positive results. The sex chromosome content
derived from karyotyping was XX in most of the false-
positive cases (15 of 17), with eight of these discordant to
those of HRM and NGS tests, suggesting a high possi-
bility of the existence of maternal contamination due to
careless sampling or the preferential growth of maternal
cells in karyotyping (Supplemental Table S9). Therefore,
some of the false positives from the culture-free HRM test
could have been true positives, which was supported by
NGS validation. In addition, some positive results in the 2
versus X and X versus Y assays could have been induced
by mixed-template DNA derived from male POC and
maternal contaminants. With regard to the false-negative
results, the relative numerical changes in the target chro-
mosomes were mild and beyond the resolution capability
of the HRM test, for example, numerical changes in cases
with low-degree mosaicism, combined aneuploidy-
polyploidy, or maternal contamination (Supplemental
Table S10). Our previous studies used DNA derived
from amniocytes or peripheral blood lymphocytes as
quantitative NCA standards to evaluate the resolution of
corresponding HRM assays.18,21,22
The NCA status of
these standard samples was nonmosaic and was validated
by their karyotypes. However, the NCA standard DNA
derived from POC could be mosaic per se; therefore, in
this study, we were unable to accurately evaluate the
resolution of these five HRM assays using serial dilutions
of the standard DNA. However, high resolution has been
validated for the 2 versus X and X versus Y assays in
previous studies.21,22
Based on these previous findings, we
speculate that samples containing 50% of NCA cells are
detectable for the three remaining HRM assays. None-
theless, false negatives caused by mild relative numerical
changes could also be missed by other methods, for
example, MLPA, CMA, or NGS (Supplemental Table
S10). In addition, sporadic false results may be associ-
ated with the defined reference intervals. However, the
reference intervals can be adjusted or optimized with more
clinical practice based on the expected sensitivity and
specificity. It should also be noted that NCAs with no
relative numerical changes in the target chromosomes
would be missed by the HRM test, such as 69,XXX,
92,XXYY, 48,XY,þ13,þ15, and 48,XXX,þ2. Finally, in
rare cases, sporadic copy number variations in the target
sequences pose a finite risk for the screening accuracy of
the HRM assay.
Conclusions
Inthe current study,anHRM testwas developed and its clinical
utility was validated for the screening of NCAs in the evalua-
tion of RPL. The developed HRM test is accurate, rapid,
inexpensive, and easy to perform. It could be used as an initial
screening tool, combined with other diagnostic methods
(eg, CMA or NGS), to improve the cost-effectiveness of RPL
evaluation or as an alternative genetic test when other methods
are unavailable or unaffordable.
Acknowledgment
We thank the cytogenetic laboratories of the Women and
Children’s Hospital, School of Medicine, Xiamen Univer-
sity, for providing POC samples and their corresponding
information.
Supplemental Data
Supplemental material for this article can be found at
http://doi.org/10.1016/j.jmoldx.2020.01.005.
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