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Journal of Microbiology Research and Reviews Vol. 3(4): 43-55, August, 2015 ISSN: 2350-1510 www.resjournals.org/JMR Accuracy of Reverse Transcription Loop-Mediated Isothermal Amplification Technique for Detecting Dengue Virus Guo-Ming Su, Jia-Min Wang, Wei-Xi Yuan, Chun-Cai Hu, Zu-Guo Zhao and Wei-Qing Yang* Department of Clinical Microbiology Laboratory, Institute of Medical Laboratory, Guangdong Medical College, Dongguan, Guangdong Province, China. Email for Correspondence: [email protected] Abstract In recent years, researchers have developed a reverse transcription loop-mediated isothermal amplification (RT-LAMP) test as a sensitive and specific technique. But the results of these studies were conflicting. The aim of this meta-analysis was to assess the accuracy of RT-LAMP technique for detecting dengue virus. We systematically searched PUBMED, EMBASE, Web of Science, and the Cochrane Library up to June 2015. Data from included studies were pooled to yield the summary sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve. All statistical analyses were performed using STATA VERSION 12.0 software. A total of 7 studies including 1263 clinical samples fulfilled the inclusion criteria. Our results showed that the pooled sensitivity and specificity were 0.99 and 0.96, respectively. The pooled DOR was 564.94 and the area under the curve (AUC) of SROC was 0.99, indicating a high level of overall accuracy. Besides, heterogeneity was statistically significant but was not caused by the threshold effect. Our study validates that RT-LAMP is an alternative molecular diagnostic method for the diagnosis of dengue virus infection. Keywords: Dengue virus, reverse transcription loop-mediated isothermal amplification (RT-LAMP), accuracy. INTRODUCTION Dengue virus, a member of genus Flavivirus of the family Flavivirus, is transmitted by Aedes aegypti and Aedes albopictus mosquitoes (Kyle and Harris, 2008). There are four antigenically related but distinct serotypes of dengue virus
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Page 1: Accuracy of reverse transcription loop-mediated isothermal ... · Accuracy of Reverse Transcription Loop-Mediated Isothermal Amplification Technique for Detecting Dengue Virus Guo-Ming

Journal of Microbiology Research and Reviews

Vol. 3(4): 43-55, August, 2015

ISSN: 2350-1510

www.resjournals.org/JMR

Accuracy of Reverse Transcription Loop-Mediated

Isothermal Amplification Technique for Detecting

Dengue Virus

Guo-Ming Su, Jia-Min Wang, Wei-Xi Yuan, Chun-Cai Hu, Zu-Guo Zhao and Wei-Qing Yang*

Department of Clinical Microbiology Laboratory, Institute of Medical Laboratory, Guangdong Medical College, Dongguan,

Guangdong Province, China.

Email for Correspondence: [email protected]

Abstract

In recent years, researchers have developed a reverse transcription loop-mediated isothermal

amplification (RT-LAMP) test as a sensitive and specific technique. But the results of these studies were

conflicting. The aim of this meta-analysis was to assess the accuracy of RT-LAMP technique for

detecting dengue virus. We systematically searched PUBMED, EMBASE, Web of Science, and the

Cochrane Library up to June 2015. Data from included studies were pooled to yield the summary

sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds

ratio (DOR), and summary receiver operating characteristic (SROC) curve. All statistical analyses were

performed using STATA VERSION 12.0 software. A total of 7 studies including 1263 clinical samples

fulfilled the inclusion criteria. Our results showed that the pooled sensitivity and specificity were 0.99

and 0.96, respectively. The pooled DOR was 564.94 and the area under the curve (AUC) of SROC was

0.99, indicating a high level of overall accuracy. Besides, heterogeneity was statistically significant but

was not caused by the threshold effect. Our study validates that RT-LAMP is an alternative molecular

diagnostic method for the diagnosis of dengue virus infection.

Keywords: Dengue virus, reverse transcription loop-mediated isothermal amplification (RT-LAMP), accuracy.

INTRODUCTION

Dengue virus, a member of genus Flavivirus of the family Flavivirus, is transmitted by Aedes aegypti and Aedes

albopictus mosquitoes (Kyle and Harris, 2008). There are four antigenically related but distinct serotypes of dengue virus

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(dengue virus 1, 2, 3, and 4) (Russell and Nisalak, 1967), and each serotype contains several phylogenetically distinct

genotypes (Holmes and Burch, 2000). The virus dengue virus infection induces a lifelong protective immunity to the

homologous serotype, but it gives only a short time cross protective immunity against subsequent infection with any of the

other three serotypes (Neeraja et al., 2015). Therefore, people may have multiple and sequential infections with the four

dengue virus serotypes in a region where the infection is hyper endemic due to the lack of cross-protective neutralizing

antibodies (Neeraja et al., 2015).

It is estimated that 390 million dengue virus infections are believed to occur each year, of which 96 million are clinically

symptomatic (Bhatt et al., 2013). Prior dengue virus infection is a major risk factor for the subsequent development of

fatal dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) through antibody-dependent enhancement

(Maves et al., 2010). Timely and accurate diagnosis of dengue virus infection can reduce the number of cases of DHF

and DSS. Obviously, diagnosing dengue virus infection is vitally important for guiding appropriate supportive care and for

preventing potential dengue outbreak. However, dengue fever presents clinical characteristics similar to other febrile

illness (Ferraz et al., 2013). Therefore, a laboratory method for the rapid and accurate diagnosis of early dengue virus

infection is highly needed.

Molecular techniques to detect virus genomic RNA sequence by the reverse transcription polymerase chain reaction

(RT-PCR) and the real-time quantitative (qRT-PCR) have been accepted as the new standard method for the detection of

dengue virus (Melo et al., 2006), which enable diagnosis during the acute phase of dengue virus infection (Lanciotti et al.,

1992; Shu et al., 2003). However, these PCR-based methods require either high-precision instruments for the

amplification or elaborate methods for detection of the amplified products (Neeraja et al., 2015; Parida et al., 2007). In

recent years, reverse transcription loop-mediated isothermal amplification (RT-LAMP) as a novel nucleic acid

amplification method has the potential to replace the RT-PCR owing to its rapidity, sensitivity, specificity and

cost-effectiveness without the need of specialized equipment (Tomita et al., 2008).

To facilitate needed diagnosis, we performed a systematic review and meta-analysis to investigate the performance of

RT-LAMP assay for diagnosis of dengue virus infection when compared with RT-PCR or qRT-PCR.

MATERIALS AND METHODS

This systematic literature review was performed according to the PRISMA Statement (Moher et al., 2009) and Cochrane

Collaboration guidelines (http://handbook.cochrane.org/). Study validity was assessed on the basis of the Standards for

Reporting of Diagnostic Accuracy Initiative and the Review of Methodological Standards (Bossuyt et al., 2003).

Search strategy

We conducted a systematical search of the PUBMED, EMBASE, Web of Science, and the Cochrane Library using

the following terms: ("Dengue Virus" OR “Dengue Viruses” OR “Breakbone Fever Virus” OR “Breakbone Fever Viruses”)

AND (“loop-mediated isothermal amplification method” OR “RT-LAMP” OR “LAMP”) AND (“diagnosis” OR “detection” OR

“accuracy” OR “screening” OR “sensitivity” OR “specificity”). No language or publication date restrictions were applied to

the search. This search was performed in June 2015. Searching was conducted independently by two reviewers

(Guo-Ming Su and Wei-Xi Yuan), and discrepancies were resolved by consensus opinion. To ensure comprehensive

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acquisition of literature, the reference lists of retrieved studies were scanned to identify additional relevant article.

Inclusion and exclusion criteria

Studies evaluating RT-LAMP as a diagnostic test for dengue virus infection were eligible for inclusion if the studies 1)

used RT-PCR or qRT-PCR as the reference standard; 2) performed clinical samples analyses from patients clinically

suspected with dengue virus infection; 3) contained no less than ten specimens; 4) provided sufficient data that allowed

calculation of true positive (TP), false positive (FP), false negative (FN), and true negative (TN). Relevant studies were

excluded if they were review articles, meta-analysis, opinions, editorials, commentaries, or conference abstracts. Two

reviewers (Guo-Ming Su and Chun-Cai Hu) independently screened studies according to eligibility criteria. Any

discrepancies were resolved by consensus or by correspondence with study authors.

Data extraction

Two reviewers (Guo-Ming Su and Wei-Xi Yuan) independently extracted information from the selected papers, and then

another reviewer verified them (Zu-Guo Zhao). Disagreements between reviewers were resolved by discussion with the

involvement of an arbitrator if necessary. The following information was collected from each study: the first author,

publication year, study location, reference standard, sample size, and data for two by two tables (TP, FP, FN, and TN),

respectively. For each study, these were summarized as sensitivity = TP / (TP + FN) × 100%; specificity = TN / (TN + FP)

× 100%; positive predictive value (PPV) = TP / (TP + FP) × 100%; negative predictive value (NPV) = TN / (TN + FN) ×

100%; and prevalence = (TP + FN) / (TP + FN + TN + FP) × 100%.

Data analysis

To determine the diagnostic accuracy of RT-LAMP, correlated diagnostic accuracy indexes were computed as follows:

sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR)

along with 95% confidence intervals (95% CI). The PLR represents the value by which the odds of the disease increase

when a test is positive; whereas NLR shows the value by which the odds of the disease decrease when a test is negative.

The DOR reflects the relationship between the result of the diagnostic test and the disease, the value of which ranges

from 0 to infinity-higher values indicating better discriminatory test performance (Glas et al., 2003). Summary receiver

operating characteristic (SROC) curve was also used to summarize overall test performance (Rosman and Korsten,

2007). The area under the curve (AUC) under the SROC curve is a measure of the overall performance of a diagnostic

test to accurately differentiate those with and those without the condition of interest (Walter, 2002).

Heterogeneity was assessed using the Cochran Q chi-square test and the I2 statistic (Higgins and Thompson, 2002;

Huedo-Medina et al., 2006). If there was no significant heterogeneity (p-value > 0.05 and I2 < 50%) among studies, the

fixed-effect model (Hedges, 1998) was performed for the meta-analysis; otherwise, the random-effect model (Schmidt,

Oh, and Hayes, 2009) was chosen. To address potential heterogeneity among studies, we also performed a subgroup

analysis based on reference standard. Spearman model was then applied to explore the threshold effect on the

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Figure 1. Flow chart of the selection process.

performance of the RT-LAMP assay. Fagan's nomogram, a two-dimensional graphical tool, was used to estimate how

much the result of a diagnostic test changes the probability that a patient has a disease (Fagan, 1975). Publication bias

was detected using Deeks' regression test of asymmetry (Deeks, Macaskill, and Irwig, 2005). All analyses were

undertaken using STATA VERSION 12.0 software (StataCorp, 2011).

RESULTS

Search results

A total of 74 titles and abstracts were retrieved after the primary search of the electronic databases for published work on

the subject. Sixty-eight potentially relevant citations were selected based on relevance to the study topic. After reviewing

the titles and abstracts, 57 citations were excluded as basic science studies, or detecting different viruses. Then 11 articles

were selected for full-text review. Subsequently, 4 studies were excluded (Dauner et al., 2010; Kwallah et al., 2013; Li et al.,

2011; Teoh et al., 2013a) (reasons for exclusion in Figure 1). Finally, seven articles reported the sensitivity and specificity

of RT-LAMP on clinical samples for the diagnosis of dengue virus infection and were selected in our data analysis

(Dauner et al., 2015; Lu et al., 2012; Neeraja et al., 2015; Parida et al., 2005; Sahni et al., 2013; Teoh et al., 2015;

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Figure 2. Forest plot of the sensitivity (left) and specificity (right) for studies using

RT-LAMP assay to detect dengue virus infection. The sensitivity and specificity are

represented by individual squares, and the horizontal lines represent the 95% CIs for

each included study. The diamonds represent the pooled summary estimates (95% CI)

Teoh et al., 2013b). The details of study selection flow are summarized in Figure 1.

Study characteristics

Our systematic review included 7 studies, 43% of which were published in 2015. Among the studies included in the

meta-analysis, there were a total of 1263 clinical samples. All samples (serum or plasma) were from patients suspected

dengue virus infection. As for reference standards, five studies used RT-PCR assay (Dauner et al., 2015; Lu et al., 2012;

Neeraja et al., 2015; Parida et al., 2005; Sahni et al., 2013), and two used qRT-PCR assay (Teoh et al., 2015; Teoh et al.,

2013b). Prevalence of dengue virus infection in each study was highly variable, ranging from 26.2% to 77.1%. The main

characteristics of the included studies are shown in Table 1.

Overall diagnostic performance of RT-LAMP

Using bivariate mixed–effects models, the combined results were as follows: sensitivity was 0.99 (95% CI, 0.84 - 1.00);

specificity was 0.96 (95% CI, 0.90 - 0.99); PLR was 27.3 (95% CI, 9.2 - 80.4); NLR was 0.01 (95% CI, 0.00 - 0.19). The

forest plot of sensitivity and specificity for RT-LAMP method in the detection of dengue virus infection was shown in

Figure 2. The NLR was 0.01, which suggested that if a RT-LAMP result was negative, the probability rate of the individual

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Figure 3. Overall diagnostic odds ratio (DOR) for all data sets describing the diagnostic

performance of RT-LAMP in detecting dengue virus infection.

having dengue virus infection was 1% in theory. In contrast, the PLR value was 27.3, suggesting that patients with a

positive RT-LAMP result had a about 27-fold chance of being diagnosed with dengue virus infection. Using random

effects analysis, the pooled DOR was 564.94 (95% CI, 127.29 – 2507.43) (Figure 3), with individual DORs ranging from

83.92 to 5041.47. As was shown in Figure 4, the AUC of SROC curve based on summary sensitivity and specificity

across all data sets were 0.99 (95% CI, 0.98 - 1.00), indicating a high level of overall accuracy.

Subgroup analysis by RT-PCR

We performed a subgroup analysis in five studies, which used RT-PCR as a reference standard. The pooled sensitivity,

specificity, PLR, NLR, and DOR were 1.00 (95% CI, 0.36 - 1.00), 0.94 (95% CI, 0.82 - 0.98), 17.3 (95% CI, 5.1 - 58.7),

0.00 (95% CI, 0.00 - 1.85), and 746.58 (95% CI, 102.57 - 5434.16), respectively. The SROC curve indicated that the area

under the curve (AUC) was 0.99 (95% CI, 0.98 - 1.00). The result of subgroup analysis also displayed a good diagnostic

accuracy.

Investigation of heterogeneity

We used the Cochran Q chi-square test and the I2 statistic to evaluate the presence of statistical heterogeneity.

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Figure 4. Summary receiver operating characteristic (SROC) curve for all data sets

describing the diagnostic performance of RT-LAMP in detecting dengue virus infection.

Significant heterogeneity was found for the pooled sensitivity, specificity, PLR, NLR, and DOR. So we performed an

analysis of diagnostic threshold to explore the effect on the performance of the RT-LAMP assay. Spearman correlation

coefficient was found to be 0.286 with a p value of 0.535, indicating that there was no statistically significant difference.

Posttest probability

The relationship between pretest probability and posttest probability was depicted by visual Fagan's nomogram (Figure 5).

We performed a simulation of an environment that had a prevalence of 20% for dengue virus infection, with base on the

included studies. As a result, the probability in this model of someone having the disease and not being detected by the

RT-LAMP test was 0.3%. In contrast, the posttest probability of sick patients with a positive test was 87%.

Publication bias

Deeks' funnel plot asymmetry test indicated that no significant bias was found (t = –0.83; p = 0.45). The shape of the

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Figure 5. Fagan's nomogram for the calculation of posttest probability.

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Table 1. Characteristics of the included studies.

First author Year Region Reference

standard

Sample

size TP FP FN TN Sensitivity Specificity PPV NPV Prevalence

B.T. Teoh 2015 Malaysia qRT-PCR 203 46 5 15 137 75.40% 96.50% 90.20% 90.10% 30%

M. Neeraja 2015 India RT-PCR 300 140 8 0 152 100% 95% 94.60% 100% 46.70%

A.L. Dauner 2015 USA RT-PCR 101 38 4 6 53 86.40% 93% 90.50% 89.80% 43.60%

B.T. Teoh 2013 Malaysia qRT-PCR 305 74 1 6 224 92.50% 99.60% 98.70% 97.40% 26.20%

X. Lu 2012 China RT-PCR 30 12 0 0 18 100% 100% 100% 100% 40%

M. Parida 2005 Japan RT-PCR 45 25 0 0 20 100% 100% 100% 100% 55.60%

A.K. Sahni 2013 India RT-PCR 279 215 17 0 47 100% 73.40% 92.70% 100% 77.10%

RT-PCR, reverse transcription polymerase chain reaction; TP, true-positive; FP, false-positive; FN, false-negative; TN, true-negative; NPV, negative predictive

value; PPV, positive predictive value.

funnel plot also did not show any evidence of obvious asymmetry (data not shown), suggesting that there was no

potential publication bias.

DISCUSSION

Dengue virus infection is a major public health problem causing serious morbidity and mortality in tropical and subtropical

developing countries (Sahni et al., 2013; Tavakoli et al., 2007). An excellent method for the rapid diagnosis of dengue

virus infection is highly needed. Regarding limitations of traditional techniques for detection of dengue virus, researchers

have developed a reversed transcription loop-mediated isothermal amplification (RT-LAMP) test as a sensitive and

specific technique (Dauner et al., 2010; Parida et al., 2005; Sahni et al., 2013). However, the results of these studies

showed that the sensitivity of RT-LAMP assay ranged from 75.4% to 100% (Neeraja et al., 2015; Sahni et al., 2013; Teoh

et al., 2015), and that the specificity ranged from 73.4% to 100% (Lu et al., 2012; Parida et al., 2005; Sahni et al., 2013).

Hence, a systematic review and meta-analysis that assessed the accuracy of RT-LAMP technique for detecting dengue

virus was highly needed.

The RT-LAMP assay is a novel method of gene amplification, which is based on the principle of a strand displacement

reaction and stem-loop structure that amplifies the target with high degrees of specificity and selectivity and with rapidity

under isothermal conditions (Nagamine, Hase, and Notomi, 2002; Notomi et al., 2000). As a matter of fact, the RT-LAMP

test has recently emerged as a powerful gene amplification tool for rapid identification of multiple viruses, such as the

rubella viruses (Abo et al., 2014), hepatitis D virus (Wang et al., 2013), and bovine rotavirus (Xie et al., 2012).

In our study, the RT-LAMP assay demonstrated high sensitivity and specificity in comparison to RT-PCR or qRT-PCR

as the reference standard for diagnosing dengue virus infection. Despite statistical heterogeneity, the diagnostic accuracy

was consistently similar in the direction of effect in the majority of the studies. To illustrate the overall performance of

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RT-LAMP test, we also counted the AUC of the SROC curve. In present meta-analysis, the data showed that the

pooled DOR was 564.94, suggesting a high level of overall accuracy. In addition, our result showed that the AUC was

0.99, also indicating very good ability to diagnose dengue virus infection. However, compared with the SROC curve and

DOR, the likelihood ratio is considered to be more clinically meaningful for our measures of diagnostic accuracy

(Gallagher, 1998). The likelihood ratios for the RT-LAMP assay indicated that the test is useful in determining posttest

probability of dengue virus infection.

To explore sources of heterogeneity, we used the Spearman correlation coefficient to analyze the threshold effect. The

result suggested that the heterogeneity was not caused by the threshold effect. However, statistically significant

heterogeneity was observed when we pooled sensitivity, specificity and DOR of included studies, implying that there

should be other factors rather than threshold effect resulting in variations among studies. Perhaps heterogeneity was

caused by the conditions of RT-LAMP such as nucleic acid isolation and primer design. But it was overwhelmingly difficult

to compare the success of each RT-LAMP condition due to diversity. To address potential heterogeneity among studies,

we performed a subgroup analysis based on RT-PCR. Results remained robust after subgroup analysis.

However, two limitations should be acknowledged in our study. On one hand, sample size after pooling the existing

studies was still relatively small. This meta-analysis only selected seven studies, though we performed a systematical

search of main electronic databases. On the other hand, there was substantial heterogeneity for all the statistical

measures. Although an effort was made, we failed to find a major source of heterogeneity due to insufficient data.

In conclusion, although several limitations exist, our findings suggest that RT-LAMP is a useful diagnostic tool with a

high sensitivity, specificity, likelihood ratios, and posttest probability in the detection of dengue virus. However, to better

investigate the possible sources of between-study heterogeneity, further systematic review involving more studies with

meta-regression analysis should be performed in the future.

ABBREVIATIONS

CI, confidence interval; FN, false-negative; FP, false-positive; TN, true-negative; TP, true-positive; RT-LAMP, reversed

transcription loop-mediated isothermal amplification; RT-PCR, reverse transcription polymerase chain reaction; DOR,

diagnostic odds ratio; PLR, positive likelihood ratio; NLR, negative likelihood ratio; NPV, negative predictive value; PPV,

positive predictive value; summary receiver operating curve; AUC, area under the curve.

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