| Literature DB >> 35030167 |
Meng-Tao Sun1, Man-Man Gu1, Jie-Ying Zhang1, Qiu-Fu Yu1, Poppy H L Lamberton2, Da-Bing Lu1.
Abstract
BACKGROUND: As China is moving onto schistosomiasis elimination/eradication, diagnostic methods with both high sensitivity and specificity for Schistosoma japonicum infections in humans are urgently needed. Microscopic identification of eggs in stool is proven to have poor sensitivity in low endemic regions, and antibody tests are unable to distinguish between current and previous infections. Polymerase chain reaction (PCR) technologies for the detection of parasite DNA have been theoretically assumed to show high diagnostic sensitivity and specificity. However, the reported performance of PCR for detecting S. japonicum infection varied greatly among studies. Therefore, we performed a meta-analysis to evaluate the overall diagnostic performance of variable-temperature PCR technologies, based on stool or blood, for detecting S. japonicum infections in humans from endemic areas.Entities:
Mesh:
Year: 2022 PMID: 35030167 PMCID: PMC8794272 DOI: 10.1371/journal.pntd.0010136
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Flow chart of studies on S. japonicum infections detected by PCR tests.
The chart shows numbers of titles and studies reviewed in preparation of this meta-analysis. N, the number of studies included in each stage of the process.
Characteristics of the eligible publications included in the analysis.
| Study | Sample size | Design | Biological sample | Index test | Population | Setting | Target gene |
|---|---|---|---|---|---|---|---|
| Fung 2012 [ | 106 | Cross-sectional | Stool | Conventional PCR | All ages | Endemic area in Sichuan, China | SjR2 |
| Gordon 2015 [ | 560 | Cross-sectional | Stool | Real-time PCR | All ages | Endemic area in Laoang and Palapag municipalities, Northern Samar, the Philippines | NADH 1 |
| Guan 2013 [ | 71 | Case-control | Serum | Real-time PCR | - | Endemic area in Hunan, China | SjR2 |
| Guo 2012 [ | 94 | Case-control | Serum | Nested PCR | - | Endemic areas in Hunan and Suzhou, Jiangsu, China | SjCHGCS19 |
| Kato-Hayashia 2015 [ | 23 | Cross-sectional | Serum | Conventional PCR | All ages | Endemic area in Sorsogon, the Philippines | COI |
| Lier 2009 [ | 1106 | Cross-sectional | Stool | Real-time PCR | - | Endemic area in the Yangtze River in Tongling, Anhui, China | NADH 1 |
| Mu 2020 | 78 | Cross-sectional | Serum | Real-time PCR | All ages | Endemic area in Laoang and Palapag, Northern Samar, the Philippines | Sja-miR-2b-5p/ Sja-miR-2c-5p |
| Wang 2009 [ | 75 | Case-control | Stool | Conventional PCR | - | Endemic area in Anqing, Anhui and non-endemic area in Hanshan, Anhui China | 14-3-3 protein mRNA |
| Weerakoon 2017 | 412 | Cross-sectional | Serum /Stool | Droplet digital PCR | All ages | Endemic area in Laoang and Palapag municipalities, Northern Samar, the Philippines | NADH 1 |
| Xu 2010 [ | 50 | Case-control | Serum | Conventional PCR | - | Endemic area in Hunan and Suzhou, Jiangsu, China | SjR2 |
| Xu 2011 | 215 | Case-control | Serum | Conventional PCR/Nested PCR | - | Endemic areas in Hunan and Wuxi, Jiangsu, China | SjR2 |
| Xu 2014 [ | 1371 | Cross-sectional | Serum | Conventional PCR | All ages | Endemic area of southeastern Poyang Lake, Jiangxi, China | SjR2 |
| Zeng 2017 [ | 107 | Case-control | Serum | Nested PCR | All ages | Endemic area in Hunan, China | SjR2 |
Note
a/b, two studies within the publication.
Raw data from included studies.
| Author | Tp | Fp | Fn | Tn | N |
|---|---|---|---|---|---|
| Fung 2012 [ | 14 | 2 | 8 | 82 | 106 |
| Gordon 2015 [ | 121 | 384 | 7 | 48 | 560 |
| Guan 2013 [ | 39 | 0 | 2 | 30 | 71 |
| Guo 2012 [ | 42 | 2 | 1 | 49 | 94 |
| Kato-Hayashi 2015 [ | 1 | 9 | 0 | 13 | 23 |
| Lier 2009 [ | 32 | 35 | 39 | 1000 | 1106 |
| Mu 2020_a [ | 36 | 8 | 17 | 17 | 78 |
| Mu 2020_b [ | 42 | 11 | 11 | 14 | 78 |
| Wang 2009 [ | 31 | 0 | 0 | 44 | 75 |
| Weerakoon 2017_a [ | 102 | 176 | 6 | 128 | 412 |
| Weerakoon 2017_b [ | 106 | 201 | 2 | 103 | 412 |
| Xu 2010 [ | 18 | 0 | 12 | 20 | 50 |
| Xu 2011_a [ | 96 | 7 | 14 | 98 | 215 |
| Xu 2011_b [ | 98 | 9 | 12 | 96 | 215 |
| Xu 2014 [ | 71 | 394 | 3 | 903 | 1371 |
| Zeng 2017 [ | 74 | 21 | 0 | 12 | 107 |
Tp = number of true positive samples; Fp = number of false positive samples; Fn = number of false negative samples; Tn = number of true negative samples; N = total number of samples tested.
Fig 2Paired forests of pooled sensitivity and specificity of all included studies.
Fig 3Bivariate boxplots of all included studies.
Fig 4Assessment of publication bias by Deek’s funnel plot asymmetry test.
Subgroup analysis of diagnostic accuracy.
| Sensitivity | Het. | Specificity | Het. | PLR | Het. | NLR | Het. | DOR | Het. | |
|---|---|---|---|---|---|---|---|---|---|---|
| (95% CI) | (I2%, P) | (95% CI) | (I2%, P) | (95% CI) | (I2%, P) | (95% CI) | (I2%, P) | (95% CI) | (I2/%, P) | |
|
| 0.91 | 97.3; <0.01 | 0.85 | 99.1; <0.01 | 5.90 | 99.4; <0.01 | 0.10 | 97.4; <0.01 | 58 | 100; <0.01 |
|
| ||||||||||
| Cross-sectional | 0.87 | 97.4; <0.01 | 0.67 | 99.4; <0.01 | 2.60 | 99.0; <0.01 | 0.20 | 96.7; <0.01 | 13 | 100; <0.01 |
| Case-control | 0.95 | 92.6; <0.01 | 0.96 | 96.1; <0.01 | 26.0 | 96.6; <0.01 | 0.05 | 92.9; <0.01 | 512 | 88.0; <0.01 |
|
| ||||||||||
| Stool | 0.91 | 99.6; <0.01 | 0.87 | 99.8; <0.01 | 7.20 | 99.9; <0.01 | 0.10 | 99.6; <0.01 | 69 | 100; <0.01 |
| Serum | 0.92 | 89.9; <0.01 | 0.83 | 96.2; <0.01 | 5.30 | 95.1; <0.01 | 0.10 | 88.2; <0.01 | 53 | 100; <0.01 |
|
| ||||||||||
| Conventional PCR | 0.86 | 86.5; <0.01 | 0.74 | 95.7; <0.01 | 11.37 | 97.1; <0.01 | 0.18 | 87.0; <0.01 | 73.76 | 38.2; 0.15 |
| Nested PCR | 0.94 | 86.0; <0.01 | 0.83 | 96.0; <0.01 | 7.06 | 97.5; <0.01 | 0.05 | 55.8; 0.10 | 158.62 (36.17, 695.63) | 43.1; 0.17 |
| Real-time PCR | 0.78 | 94.7; <0.01 | 0.72 | 99.7; <0.01 | 4.121 | 98.8; <0.01 | 0.39 | 74.2; <0.01 | 10.06 | 88.6; <0.01 |
| Droplet digital PCR | 0.96 | 53.9; 0.14 | 0.38 | 77.1; 0.04 | 1.55 | 47.9; 0.17 | 0.10 | 19.3; 0.27 | 15.24 | 0.0; 0.34 |
Abbreviations: Het = Heterogeneity; PLR = positive likelihood ratio; NLR = negative likelihood ratio; DOR = diagnostic odds ratio; I2 = I-square; CI = confidence interval; P = P value.
Fig 5HSROC curve of PCR tests used to diagnose S. japonicum infections.
Fig 6HSROC curves of subgroup analyses based on research design (A and B), biological samples (C and D) and PCR method (E-G). A) case-control design, B) cross-sectional design, C) based on blood samples, D) based on stool samples, E) conventional PCR, F) nested PCR, G) real-time PCR.