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Diagnostic utility of automated indirect immunofluorescence compared to manual indirect immunofluorescence for anti-nuclear antibodies in patients with systemic rheumatic diseases: A systematic review and meta-analysis
Authors:Jinmi Kim  Woonhyoung Lee  Geun-Tae Kim  Hyon-Suk Kim  Soyoung Ock  In-Soo Kim  Seri Jeong
Institution:1. Department of Statistics, Pusan National University Hospital, Gudeok-ro 179, Seo-gu, Busan 49241, Republic of Korea;2. Department of Laboratory Medicine, Hallym University College of Medicine, Kangnam Sacred Heart Hospital, Singil-ro 1, Yeongdeungpo-gu, Seoul 07441, Republic of Korea;3. Department of Rheumatology, Kosin University College of Medicine, Gamcheon-ro 262, Seo-gu, Busan 49267, Republic of Korea;4. Department of Laboratory Medicine, Severance Hospital, Yonsei University College of Medicine, Yonsei-ro 50, Seodaemun-gu, Seoul 03722, Republic of Korea;5. Department of Internal Medicine, Kosin University College of Medicine, Gamcheon-ro 262, Seo-gu, Busan 49267, Republic of Korea;6. Department of Internal Medicine, Yonsei University College of Medicine, Yonsei-ro 50, Seodaemun-gu, Seoul 03722, Republic of Korea
Abstract:

Objective

This study aimed to review and compare the analytical and clinical performance of automated indirect immunofluorescence (AIIF) and manual indirect immunofluorescence (MIIF) as anti-nuclear antibody screening assays for patients with systemic rheumatic diseases (SRDs), such as systemic lupus erythematosus (SLE) and systemic sclerosis (SSc).

Methods

A systematic literature search was performed in the Medline, Embase, Cochrane, Web of Science, and Scopus databases for studies published before August 2017. A bivariate random effects model was used to calculate the summary diagnostic values.

Results

Twenty-two studies involving 6913 positive and 1818 negative samples of MIIF, as well as 524 combined SRD, 132 SLE, and 104 SSc patients, and 520 controls were available for meta-analysis. The summary positive concordance (PC) of qualitative result between AIIF and MIIF was 93.7%, whereas PCs of total pattern (68.5%; homogeneous, 52.3%; speckled, 56.5%; nucleolar, 52.7%; centromere, 51.4%; nuclear dot, 11.7%) and titer (77.8%) exhibited significantly lower values. The summary clinical sensitivities of AIIF vs. MIIF were 84.7% vs 78.2% for combined SRDs, 95.5% vs. 93.9% for SLE, and 86.5% vs. 83.7% for SSc, respectively. Meanwhile, the summary specificities of AIIF vs. MIIF were 75.6% vs. 79.6% for combined SRDs, 74.2% vs. 83.3% for SLE, and 74.2% vs. 83.3% for SSc, respectively. Although the differences in sensitivity and specificity between AIIF and MIIF were not significant in most subgroups, the summary specificity of SLE and SSc showed statistically significant changes.

Conclusions

Our systematic meta-analysis demonstrates that AIIF is comparable to MIIF in distinguishing between the positive and negative results, and screening SRDs based on clinical sensitivities and standardization. However, improvements in the pattern and titer recognition and clinical specificities are necessary.
Keywords:ANAs  anti-nuclear antibodies  AIIF  automated immunofluorescence  AU  arbitrary unit  CI  confidence interval  DFS  dense fine speckled  DORs  diagnostic odds ratios  DM  dermatomyositis  FI  fluorescence index  FN  false negative  FP  false positive  HEp-2  human epithelial  hsROC  hierarchical summary receiver operating characteristics  ID  identification  LI  light intensity  LIU  light intensity unit  LR+  positive likelihood ratio  LR?  negative likelihood ratio  MCTD  mixed connective tissue disease  MIIF  manual indirect immunofluorescence  NC  negative concordance  NR  not reported  PC  positive concordance  PI  probability index  PM  polymyositis  SLE  systemic lupus erythematosus  SRDs  systemic rheumatic diseases  SROC  summary receiver operating characteristics  SS  Sjögren’s syndrome  SSc  systemic sclerosis  TN  true negative  TP  true positive  Anti-nuclear antibody  Automation  Indirect immunofluorescence  Systemic lupus erythematosus  Systemic rheumatic disease  Systemic sclerosis
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