Evidence map›Paper›PMID 29391833›Full record

ArticleClinical epidemiology2018

A validation study of the CirCom comorbidity score in an English cirrhosis population using the Clinical Practice Research Datalink.

Colin J Crooks, Joe West, Peter Jepsen

Open access · goldAbstract read
In one paragraph

Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
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

3 authors at 2 institutions in 2 countries.

Colin J CrooksDivision of Epidemiology and Public Health, University of Nottingham, Nottingham, UK.
Joe WestDivision of Epidemiology and Public Health, University of Nottingham, Nottingham, UK.
Peter JepsenDepartment of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark.
University of Nottingham · GBAarhus University Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe CirCom score has been developed from Danish data as a specific measure of comorbidity for cirrhosis to predict all-cause mortality. We compared its performance with the Charlson Comorbidity Index (CCI) in an English cirrhosis population. PATIENTS AND

methodsWe used comorbidity scores in a survival model to predict mortality in a cirrhosis cohort in the Clinical Practice Research Datalink. The discrimination of each score was compared by age, gender, socioeconomic status, cirrhosis etiology, cirrhosis stage, and year after cirrhosis diagnosis. We also measured their ability to predict liver-related versus non-liver-related death.

resultsThere was a small improvement in the C statistic from the model using the CirCom score (C=0.63) compared to the CCI (C=0.62), and there was an overall improvement in the net reclassification index of 1.5%. The improvement was more notable in younger patients, those with an alcohol etiology, and those with compensated cirrhosis. Both scores performed better (C statistic >0.7) for non-liver-related deaths than liver-related deaths (C statistic <0.6), as comorbidity was only weakly predictive of liver-related death.

conclusionThe CirCom score provided a small improvement in performance over the CCI in the prediction of all-cause and non-liver mortality, but not liver-related mortality. Therefore, it is important to include a measure of comorbidity in studies of cirrhosis survival, alongside a measure of cirrhosis severity.

Indexed as

cause of deathcirrhosiscohortcomorbiditymortalityprognosis

Identifiers

PMID29391833
PMCPMC5774468
OpenAlexW2783519615

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.