Evidence map›Paper›PMID 31581237›Full record

ArticlePloS one2019

The Model of Mortality with Incident Cirrhosis (MoMIC) and the model of Long-term Outlook of Mortality in Cirrhosis (LOMiC).

Ellen R Berni, Bethan I Jones, Thomas R Berni, James Whitehouse, Mark Hudson, James Orr, Pete Conway, Bharat Amlani, Craig J Currie

Abstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Ellen R BerniGlobal Epidemiology, Pharmatelligence, Cardiff, United Kingdom.
Bethan I JonesGlobal Epidemiology, Pharmatelligence, Cardiff, United Kingdom.ORCID 0000-0003-1954-9362
Thomas R BerniGlobal Epidemiology, Pharmatelligence, Cardiff, United Kingdom.ORCID 0000-0001-5615-5528
James WhitehouseNorgine Pharmaceuticals Limited, Harefield, Uxbridge, United Kingdom.
Mark HudsonLiver Unit, Freeman Hospital, Newcastle upon Tyne, United Kingdom.
James OrrLiver Unit, Freeman Hospital, Newcastle upon Tyne, United Kingdom.
Pete ConwayGlobal Epidemiology, Pharmatelligence, Cardiff, United Kingdom.
Bharat AmlaniNorgine Pharmaceuticals Limited, Harefield, Uxbridge, United Kingdom.
Craig J CurrieGlobal Epidemiology, Pharmatelligence, Cardiff, United Kingdom.ORCID 0000-0002-6154-818X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to produce two statistical survival models in those with cirrhosis utilising only routine parameters, including non-liver-related clinical factors that influence survival. The first model identified and utilised factors impacting short-term survival to 90-days post incident diagnosis, and a further model characterised factors that impacted survival following this acute phase. Data were from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. Incident cases in patients ≥18 years were identified between 1998 and 2014. Patients that had prior history of cancer or had received liver transplants prior were excluded. Model-1 used a logistic regression model to predict mortality. Model-2 used data from those patients who survived 90 days, and used an extension of the Cox regression model, adjusting for time-dependent covariables. At 90 days, 23% of patients had died. Overall median survival was 3.7 years. Model-1: numerous predictors, prior comorbidities and decompensating events were incorporated. All comorbidities contributed to increased odds of death, with renal disease having the largest adjusted odds ratio (OR = 3.35, 95%CI 2.97-3.77). Model-2: covariables included cumulative admissions for liver disease-related events and admissions for infections. Significant covariates were renal disease (adjusted hazard ratio (HR = 2.89, 2.47-3.38)), elevated bilirubin levels (aHR = 1.38, 1.26-1.51) and low sodium levels (aHR = 2.26, 1.84-2.78). An internal validation demonstrated reliability of both models. In conclusion: two survival models that included parameters commonly recorded in routine clinical practice were generated that reliably forecast the risk of death in patients with cirrhosis: in the acute, post diagnosis phase, and following this critical, 90 day phase. This has implications for practice and helps better forecast the risk of mortality from cirrhosis using routinely recorded parameters without inputs from specialists.

Indexed as

Models, TheoreticalFemaleHumansIncidenceKaplan-Meier EstimateLiver CirrhosisLogistic ModelsMaleMiddle AgedProportional Hazards ModelsReproducibility of Results

Identifiers

PMID31581237
PMCPMC6776387

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LicenceCC BY
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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.