Evidence map›Paper›PMID 33409795›Full record

SynthesisEuropean radiology2021

Diagnostic performance of Liver Imaging Reporting and Data System treatment response algorithm: a systematic review and meta-analysis.

Seo Yeon Youn, Dong Hwan Kim, Sang Hyun Choi, Bohyun Kim, Joon-Il Choi, Yu Ri Shin, Soon Nam Oh, Sung Eun Rha

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
  8. Up-to-Date Role of CT/MRI LI-RADS in Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2021
    Review
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

8 authors.

Seo Yeon YounDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.
Dong Hwan KimDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea. rhdwngkwk333@naver.com.ORCID http://orcid.org/0000-0002-2932-2367
Sang Hyun ChoiDepartment of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul, 05505, South Korea.
Bohyun KimDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.
Joon-Il ChoiDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.
Yu Ri ShinDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.
Soon Nam OhDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.
Sung Eun RhaDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo systematically determine the accuracy of Liver Imaging Reporting and Data System treatment response (LR-TR) algorithm for diagnosing the viability of hepatocellular carcinoma (HCC) treated with locoregional therapy (LRT).

methodsOriginal studies reporting the diagnostic accuracy of LR-TR algorithm on dynamic contrast-enhanced computed tomography or magnetic resonance imaging (MRI) were identified in MEDLINE and EMBASE up to June 1, 2020. The meta-analytic summary sensitivity and specificity of LR-TR algorithm were calculated using a bivariate random-effects model. Subgroup analyses and meta-regression analysis were performed to explore study heterogeneity.

resultsWe found six studies reporting the accuracy of LR-TR viable category (601 observations in 453 patients). The meta-analytic pooled sensitivity and specificity of LR-TR viable category were 63% (95% confidence interval [CI], 39-81%; I

conclusionsThe LR-TR viable category had high specificity but suboptimal sensitivity for diagnosing the viability of HCC after LRT. Substantial study heterogeneity was noted, and it was significantly associated with the type of reference standard and study design. KEY POINTS: • The meta-analytic pooled sensitivity and specificity of LR-TR viable category were 63% (95% CI, 39-81%) and 96% (95% CI, 91-99%), respectively. • The meta-analytic pooled sensitivity and specificity of LR-TR viable or equivocal category combined were 71% (95% CI, 55-84%) and 87% (95% CI, 73-94%), respectively. • The type of reference standard and study design were the factors significantly influencing study heterogeneity (p ≤ 0.01).

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAlgorithmsHumansMagnetic Resonance ImagingRetrospective StudiesSensitivity and SpecificityHepatocellular carcinomaLiverMeta-analysisSystematic reviewTreatment outcome

Identifiers

PMID33409795

What OpenQuestion holds

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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.