Evidence map›Paper›PMID 27001945›Full record

ArticleJournal of investigative medicine : the official publication of the American Federation for Clinical Research2016

Development and validation of a composite score for excessive alcohol use screening.

Wanzhu Tu, Chenghao Chu, Shanshan Li, Suthat Liangpunsakul

Abstract readValidation Study
In one paragraph

Article in Journal of investigative medicine : the official publication of the American Federation for Clinical Research, 2016. 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
1.7field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Article
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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

4 authors at 2 institutions in 1 country.

Wanzhu TuDepartment of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Chenghao ChuDepartment of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Shanshan LiDepartment of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Suthat LiangpunsakulDivision of Gastroenterology and Hepatology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA Roudebush veterans Administration Medical Center, Indianapolis, Indiana, USA.
Indiana University – Purdue University Indianapolis · USIndiana University School of Medicine

Funding

Translational Research and Evolving Alcoholic hepatitis Treatment (TREAT-IU)U01AA021840 · NIAAA · INDIANA UNIVERSITY INDIANAPOLIS · PI NAGA P CHALASANI, Olawale Ojo · 2012 to 2026
$8.1M
Effect of ethanol on Kupffer cell/hepatocyte interactions and lipid metabolismK08AA016570 · NIAAA · INDIANA UNIVERSITY INDIANAPOLIS · PI LIANGPUNSAKUL, SUTHAT · 2008 to 2012
$659k
Serum Proteomic Profiles as Biomarkers of Abusive Alcohol ConsumptionI01CX000361 · VA · RLR VA MEDICAL CENTER · PI LIANGPUNSAKUL, SUTHAT · 2012 to 2025
–
CSRD VA I01 CX000361NIAAA NIH HHS K08 AA016570NIAAA NIH HHS U01 AA021840
6 · The paper itself

Abstract

This study was undertaken to develop a composite measure that combines the discriminant values of individual laboratory markers routinely used for excessive alcohol use (EAU) for an improved screening performance. The training sample consisted of 272 individuals with known history of EAU and 210 non-alcoholic individuals. The validation sample included 100 EAU and 75 controls. We used the estimated regression coefficients and the observed marker values to calculate the individual's composite screening score; this score was converted to a probability measure for excessive drinking in the given individual. A threshold value for the screening score based on an examination of the estimated sensitivity and specificity associated with different threshold values was proposed. Using regression coefficients estimated from the training sample, a composite score based on the levels of aspartate aminotransferase, alanine aminotransferase, per cent carbohydrate-deficient transferrin and mean corpuscular volume was calculated. The areas under the receiver operating characteristic curve (AUC) value of the selected model was 0.87, indicating a strong discriminating power and the AUC was better than that of each individual test. The score >0.23 corresponded to a sensitivity of 90% and a specificity of nearly 60%. The AUC value remained at a respectable level of 0.83 with the sensitivity and specificity at 91% and 49%, respectively, in the validation sample. We developed a novel composite score by using a combination of commonly used biomakers. However, the development of the mechanism-based biomarkers of EAU is needed to improve the screening and diagnosis of EAU in clinical practice.

Indexed as

Mass ScreeningAdultAlcoholismCohort StudiesDemographyFemaleHumansMaleReproducibility of ResultsROC CurveSensitivity and SpecificityAlcohol DrinkingBiological Markers

Identifiers

PMID27001945
PMCPMC5495183
OpenAlexW2306302243

What OpenQuestion holds

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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.