Evidence map›Paper›PMID 33163456›Full record

ArticleAnnals of surgical treatment and research2020

Development and validation of risk score for predicting spontaneous rupture of hepatocellular carcinoma.

Feng Ye, Di Ma, Xiao-Yong Gong, Yu-Chen Yang, Yong-Jun Chen

Open access · diamondAbstract read
In one paragraph

Article in Annals of surgical treatment and research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

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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

6 citing papers in PubMed, 8 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Feng YeDivision of Hepatobiliary Surgery, Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-2127-4604
Di MaDivision of Hepatobiliary Surgery, Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-2937-1839
Xiao-Yong GongDivision of Hepatobiliary Surgery, Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-0346-5677
Yu-Chen YangDivision of Hepatobiliary Surgery, Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-5962-0437
Yong-Jun ChenDivision of Hepatobiliary Surgery, Department of General Surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-6486-2000
Ruijin Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSpontaneous rupture is a potentially serious complication of liver cancer. A risk score was developed and validated for predicting spontaneous rupture based on a retrospective study.

methodsMultiple logistic regression analysis was used to study the relationship between clinical variables and spontaneous rupture. The independent rupture predictors were converted into a score based on the odds ratio. Predicted attributes of the developed scores were then verified using a dataset in 2019.

resultsThe incidence of spontaneous rupture was 5.5% from 2002 to 2019. A 10-point score (α-FP of ≥400 µg/L, 1; protrusion from liver surface, 2; ascites, 3; tumor size of >5 cm, 4) was derived for prediction of rupture and area under the receiver-operating characteristic curve was 0.9 (95% confidence interval, 0.87-0.92). When applying a cutoff value of 5 points or more, the specificity was 0.87 and the sensitivity was 0.84. A validation cohort consisting of 202 hepatocellular carcinoma patients reproduces the predictive, identification, and calibration characteristics. The observed rate of spontaneous rupture according to risk stratification of the score was 0.6% for those with a score of 0-4, 21.6% for a score of 5-7, and 36.4% for a score of 8-10 in the validation cohort.

conclusionHere, based on routine clinical data, we determine the factors that affect prognosis and propose an effective tool for predicting spontaneous rupture, which may be useful in guiding priority treatment of high-risk patients or clinical routine preventive treatment.

Indexed as

ForecastingLiver cancerPatient recruitmentRuptureScoring methods

Identifiers

PMID33163456
PMCPMC7606127
OpenAlexW3095426600

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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.