Evidence map›Paper›PMID 32311947›Full record

SynthesisMedicine2020

Comparative diagnostic efficacy of serum Krebs von den Lungen-6 and surfactant D for connective tissue disease-associated interstitial lung diseases: A meta-analysis.

Danli Zhong, Chanyuan Wu, Jingjing Bai, Chaojun Hu, Dong Xu, Qian Wang, Xiaofeng Zeng

Open access · goldAbstract readComparative StudyMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
1.6field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 25 citations in OpenAlex.

  1. Pooled it
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  4. Review
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  12. Radiation-induced lung injury - what do we know in the era of modern radiotherapy?Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 3 countries.

Danli ZhongDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Chanyuan WuDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Jingjing BaiDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Chaojun HuDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Dong XuDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Qian WangDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Xiaofeng ZengDepartment of Rheumatology, Peking Union Medical College Hospital, Peking Union Medical College &Chinese Academy of Medical Sciences.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNNational Clinical Research · USMinistry of Education of the People's Republic of China · CNPeking Union Medical College Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of the study was to estimate and compare the diagnostic accuracy of serum Krebs von den Lungen-6 (KL-6) and surfactant protein D (SP-D) for identifying interstitial lung disease (ILD) from non-ILD among connective tissue disease (CTD) patients. MATERIALS AND

methodsOriginal articles on the diagnostic accuracy of serum KL-6 and SP-D in differentiating CTD-ILD from CTD-nonILD were identified from three public databases. The overall quality of evidence and methodologic quality of each eligible study were assessed by the Grading of Recommendations, Assessment, Development and Evaluation approach and Quality Assessment of Diagnostic Accuracy Studies, respectively. We used the bivariate model to calculate random-effect sensitivity, specificity, likelihood ratios, and area under curve. Furthermore, trial sequential analysis (TSA) was used to determine whether sample sizes incorporated in the meta-analysis were powerful for evaluating the diagnostic utility. Bayesian network analysis was performed to compare the diagnostic accuracy of 2 serum biomarkers in differentiating ILD among CTD patients and various subgroups.

resultsTwenty-nine studies were included in the quantitative synthesis. No threshold effects were observed (all P values >.05). For diagnosis of ILD among CTD patients, overall sensitivity and specificity of serum KL-6 were 0.76 (95% confidence interval [CI]: 0.68-0.82) and 0.89 (95% CI: 0.83-0.93), whereas those for serum SP-D were 0.65 (95% CI: 0.45-0.80) and 0.88 (95% CI: 0.80-0.93). Comprehensive comparison of 2 circulating biomarkers using back-calculated likelihood ratio (LR) demonstrated that serum KL-6 corresponded to a higher LR+ and a lower LR- in comparison to serum SP-D, as well as in SSc-ILD. TSA indicated that evidence for serum KL-6 and SP-D in identifying CTD-ILD is powerful; nonetheless, more trials were needed for validation of serum KL-6 and SP-D in differentiating CTD-ILD subtypes, including different CTD and ethnicities.

conclusionsThis meta-analysis suggested that serum KL-6 had superior diagnostic accuracy to SP-D for differentiating ILD from non-ILD among CTD patients, providing a convenient and non-invasive approach for screening and management of ILD among CTD patients.

Indexed as

BiomarkersConnective Tissue DiseasesDiagnosis, DifferentialHumansLung Diseases, InterstitialMucin-1Pulmonary Surfactant-Associated Protein DBiomarkersMUC1 protein, humanMucin-1Pulmonary Surfactant-Associated Protein D

Identifiers

PMID32311947
PMCPMC7220682
OpenAlexW3017280694

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.