ArticleGastroenterology and hepatology from bed to bench2012
Using statistical models to assess medical cost of hepatitis C virus.
Article in Gastroenterology and hepatology from bed to bench, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Real World Cost-of-Illness Evidence in Hepatitis C Virus: A systematic review.PharmacoEconomics · 2020Pooled it
- Lack of association between interleukin 28B gene polymorphisms (rs8099917G/T, rs12979860 C/T) and susceptibility to chronic hepatitis C virus infection, Tehran, Iran.Gastroenterology and hepatology from bed to bench · 2016Article
- Sofosbuvir has come out of the magic box.Hepatitis monthly · 2013Article
- Estimation of average diagnosis and treatment costs of hepatitis C.Gastroenterology and hepatology from bed to bench · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThis study compared PR and NB in predicting HCV patient costs. The objective of this study was to predict the direct cost of the HCV patient in Iran.
backgroundHepatitis C virus (HCV) is a common and expensive infectious disease in Iran. Cost associated with HCV and its complications has not been well characterized. Analysis of cost data is important in providing consistent information to aid budgeting decisions and certain statistical regression models need for prediction mean costs. Poisson regression (PR) and negative binomial regression (NB) are more common in cost prediction study. PATIENTS AND
methodsThis study designed as a cross-sectional clinic base from 2001 to 2010. First treatment period of each patient bring in study. We evaluated the doctor visiting, drugs, and hospitalization and laboratory tests of patients. Cost per person per one treatment period estimated in purchasing power parity dollars (PPP$). The PR is one of the models from general linear models (GLM) for describing count outcomes. The NB is another model from (GLM) as an alternative to the PR model.
resultsAccording to Likelihood ratio test NB was found to be more appropriate than PR (P < 0.001). Genotype, marriage, medication, and SVR were being significant. Genotype 3 versus 1 decreasing cost while marriage, consuming pegasys and SVR increasing.
conclusionChoosing best model in cost data is important because of specific feature of this data. After fitting the best model, analyzing and predicting future cost for patient in different situation is possible.
Indexed as
Identifiers
24834235PMC4017486What OpenQuestion holds
Registered trials
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.