ArticleHepatology international2013
Insulin resistance: mechanism and implications for carcinogenesis and hepatocellular carcinoma in NASH.
Article in Hepatology international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses 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
6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.
- Metabolic syndrome and survival of patients with hepatocellular carcinoma: A meta-analysis.Frontiers in oncology · 2023Pooled it
- Dietary Carbohydrate and Diverse Health Outcomes: Umbrella Review of 30 Systematic Reviews and Meta-Analyses of 281 Observational Studies.Frontiers in nutrition · 2021Pooled it
- Metabolic syndrome-related gene signature for prognosis and immune microenvironment prediction in hepatocellular carcinoma.Scientific reports · 2025Article
- Precision Strategy for Hepatocellular Carcinoma Surveillance after Hepatitis C Cure: Debates across Guidelines.Gut and liver · 2025Review
- Associations between "Cancer Risk", "Inflammation" and "Metabolic Syndrome": A Scoping Review.Biology · 2024Article
- Metabolic syndrome and the incidence of hepatocellular carcinoma: a meta-analysis of cohort studies.OncoTargets and therapy · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe effects of insulin resistance in human diseases are of paramount importance. Since the original proposal by the WHO indicating insulin resistance as the common substrate of the metabolic syndrome, large data are now available on its significance in cardiovascular diseases, nonalcoholic fatty liver disease and cancer risk. MATERIALS AND
methodsWe reviewed the evidence linking hyperinsulinemia to insulin resistance and ultimately to increased cancer risk. Insulin resistance, by reducing substrate flux along the PI3-K pathway, is followed by compensatory hyperinsulinemia, considered a potential stimulus for cancerogenesis along the MAP-K pathway. Adaptive mechanisms of fat storage, promoted by insulin resistance, chronically maintained in an obesiogenic environment, may lead to oxidative stress and inflammation and modify the immune responses, further increasing the carcinogenic potential. The increased cancer risk associated with obesity, type 2 diabetes and nonalcoholic fatty liver may thus be fueled by hyperinsulinemia. Insulin secretagogs and insulin treatment, by raising circulating insulin levels, further increase cancer risk, whereas insulin sensitizers are associated with decreased cancer risk (all sites) and specifically decrease hepatocellular carcinoma. Likewise, drugs related to the incretin system, which are weight neutral or even reduce whole-body and hepatic fat, improve insulin sensitivity and potentially reduce the cancer risk.
conclusionNew diabetes treatments might thus help decrease the future burden of diabetes-associated cancer and particularly of hepatocellular carcinoma.
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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.