A multi-centre study for standardization of antinuclear antibody indirect immunofluorescence screening with automated system

Li, Xin; Pan, Jie; Zhou, Hui; He, Ming; Li, WeiXuan; Zhanze, Chen; Wei-liang, Dai; Wang, Fang; Wei, Qiujing; Lao, Xiaobin; Zhang, Ling; Li, Ling; Hu, Honghai; Li, Min; Qiu, Yurong; Hou, Tieying

doi:10.1016/j.jim.2019.112701

Cited by 3 publications

(6 citation statements)

References 24 publications

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“…The AESKU ANA-IFA reagent kit and the fully automated HELIOS system are from AESKU.DIOGNOSTICS GmbH & Co. KG. HELIOS is a system which automatically takes over the complete pipetting and image capturing of IFA tests without manual interference (32). An ANA titer of 1:80 or greater was considered positive.…”

Section: Detection Of Serum Autoantibodiesmentioning

confidence: 99%

Anti-Ro52 Autoantibodies Are Related to Chronic Graft-vs.-Host Disease After Allogeneic Hematopoietic Stem Cell Transplantation

Yang

Chen

et al. 2020

Front. Immunol.

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Chronic graft-vs.-host disease (cGVHD) remains a major cause of morbidity and mortality after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Previous studies have shown that autoantibodies play an important role in the development of cGVHD. Anti-nuclear autoantibodies (ANA) is the most frequently detected autoantibodies in patients with cGVHD, but the role of anti-Ro52 autoantibodies (anti-Ro52) in cGVHD remains largely unknown. In this study, we analyzed autoantibodies from 84 patients after allo-HSCT, including 42 with active cGVHD and 42 without cGVHD. Autoantibodies were found in 36 (42.9%) patients. Among these autoantibody-positive patients, 28 (77.8%) patients had active cGVHD. The most frequent autoantibodies in patients with active cGVHD were ANA (50.0%), anti-Ro52 (28.6%) and anti-mitochondrial autoantibodies type 2 (4.8%). We further explored the association between anti-Ro52 and cGVHD. Patients with active cGVHD had higher anti-Ro52 levels than patients without cGVHD (P < 0.05). The increases of anti-Ro52 levels were more significant in patients with moderate/severe cGVHD compared to those of patients without cGVHD (P < 0.05). Stratified and multivariable logistic regression analysis demonstrated that moderate/severe cGVHD was an independent risk factor for the levels of anti-Ro52 (P < 0.01). ROC analysis confirmed anti-Ro52 as a risk factor for progression of skin cGVHD. Moreover, the anti-Ro52 levels were highly correlated with the levels of B cell-activating factor (BAFF) and IgG1 antibodies. Our study demonstrates that anti-Ro52 is associated with cGVHD. The increased levels of anti-Ro52 were associated with higher levels of BAFF and IgG1 antibodies, suggesting a mechanistic link between elevated anti-Ro52 levels and aberrant B cell homeostasis.

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Section: Detection Of Serum Autoantibodiesmentioning

confidence: 99%

Anti-Ro52 Autoantibodies Are Related to Chronic Graft-vs.-Host Disease After Allogeneic Hematopoietic Stem Cell Transplantation

Yang

Chen

et al. 2020

Front. Immunol.

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“…These studies were published between 2007 and 2022. Ten articles assessed the accuracy of the automated‐IIF for ANA detection 7,9,19–26 . The study characteristics of the included studies are shown in Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…During the evaluation process, it was found in the patient selection section that the first question of the domain was answered as “no”, the second question of the domain was answered as “yes”, and the third question of the domain was answered as “unclear”, so the level of risk of bias was judged as “unclear”, 26 and as for another study which was also judged as “unclear”, those were “yes”, “no,” and “unclear” respectively 9 . One study included a total of 230 participants and was judged as “high” in the flow and timing section because there were missing cases 26 . Among the patient selection to be evaluated, 2 articles included samples from patients with suspected autoimmune rheumatic disease, which were judged as “high” in the consideration of applicability.…”

Section: Resultsmentioning

confidence: 99%

“…Ten articles assessed the accuracy of the automated-IIF for ANA detection. 7,9,[19][20][21][22][23][24][25][26] The study characteristics of the included studies are shown in Table 1.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…9 One study included a total of 230 participants and was judged as "high" in the flow and timing section because there were missing cases. 26 Among the patient selection to be evaluated, 2 articles included samples from patients with suspected autoimmune rheumatic disease, which were judged as "high" in the consideration of applicability. Among the reference standard to be evaluated, 2 articles included negative test results of manual-IIF within a diseased individual (clinically), 3 articles included positive test results of manual-IIF in an individual without AARD, which were evaluated as "high" in the consideration of applicability.…”

Section: Quality Assessmentmentioning

confidence: 99%

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An indirect comparison of automated indirect immunofluorescence vs automated solid‐phase immunoassays for antinuclear antibody detection: A meta‐analysis and adjusted indirect comparison of diagnostic test accuracy

Zhang

2022

Int J of Rheum Dis

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Objective:The primary aim of this study was to conduct a meta-analysis to compare the diagnostic accuracy of automated indirect immunofluorescence (automated-IIF) and fully automated solid-phase immunoassays (solid-phase assays), compared with gold standard conventional manual indirect immunofluorescence (manual-IIF) for antinuclear antibody (ANA) detection.Methods: Indirect meta-comparison was performed using prospective studies reporting comparative data between automated-IIF and fully automated solid-phase assays individually to conventional manual-IIF. Diagnostic tests regarding different automated solid-phase assays and automated-IIF for ANA detection were retrieved from the Cochrane Library, PubMed, Embase, Web of Science, Chinese Biological Medicine Database (CBM), China National Knowledge Infrastructure (CNKI), and WANFANG electronic databases from their inception to January 2022. Assessment of the quality of the studies was undertaken using a second version of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The investigated diagnostic indices including pooled sensitivity, pooled specificity, pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (DOR), area under the summary receiver operating characteristic (AUC) of automated-IIF and solidphase assays, respectively. Relative diagnostic odds ratio (RDOR) was calculated to indirectly compare the diagnostic accuracy of automated-IIF and solid-phase assays.To visualize results, we provide forest plots showing the RDOR with 95% confidence intervals (CI) of the 2 methods against the "gold standard" manual-IIF by R software.Deeks' funnel was used to investigate the publication bias.Results: A total of 16 studies involving 6111 subjects were included in the analysis. The pooled sensitivity, pooled specificity, pooled PLR, pooled NLR, pooled DOR and the AUC were 0.85 (95% CI: 0.84-0.86), 0.82 (95% CI 0.81-0.84), 14.22 (95% CI 8.55-23.65), 0.06 (95% CI 0.03-0.12), 287.0 (95% CI 124.30-662.68) and 0.983 for automated-IIF respectively, and as for solid-phase assays those were 0.73 (95% CI 0.70-0.75), 0.87 (95% CI 0.85-0.89), 5.66 (95% CI 3.33-9.62), 0.30 (95% CI 0.20-0.47),

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Artificial intelligence for medicine: Progress, challenges, and perspectives

Huang,

Xu,

Wang

et al. 2023

TIME

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<p>Artificial Intelligence (AI) has transformed how we live and how we think, and it will change how we practice medicine. With multimodal big data, we can develop large medical models that enables what used to unimaginable, such as early cancer detection several years in advance and effective control of virus outbreaks without imposing social burdens. The future is promising, and we are witnessing the advancement. That said, there are challenges that cannot be overlooked. For example, data generated is often isolated and difficult to integrate from both perspectives of data ownership and fusion algorithms. Additionally, existing AI models are often treated as black boxes, resulting in vague interpretation of the results. Patients also exhibit a lack of trust to AI applications, and there are insufficient regulations to protect patients�� privacy and rights. However, with the advancement of AI technologies, such as more sophisticated multimodal algorithms and federated learning, we may overcome the barriers posed by data silos. Deeper understanding of human brain and network structures can also help to unravel the mysteries of neural networks and construct more transparent yet more powerful AI models. It has become something of a trend that an increasing number of clinicians and patients will implement AI in their life and medical practice, which in turn can generate more data and improve the performance of models and networks. Last but not the least, it is crucial to monitor the practice of AI in medicine and ensure its equity, security, and responsibility.</p>

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A multi-centre study for standardization of antinuclear antibody indirect immunofluorescence screening with automated system

Cited by 3 publications

References 24 publications

Anti-Ro52 Autoantibodies Are Related to Chronic Graft-vs.-Host Disease After Allogeneic Hematopoietic Stem Cell Transplantation

Anti-Ro52 Autoantibodies Are Related to Chronic Graft-vs.-Host Disease After Allogeneic Hematopoietic Stem Cell Transplantation

An indirect comparison of automated indirect immunofluorescence vs automated solid‐phase immunoassays for antinuclear antibody detection: A meta‐analysis and adjusted indirect comparison of diagnostic test accuracy

Artificial intelligence for medicine: Progress, challenges, and perspectives

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