ArticleTranslational cancer research2023
Identification of risk and prognostic factors for intrahepatic vascular invasion in patients with hepatocellular carcinoma: a population-based study.
Article in Translational cancer research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Article
- Article
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
Background: The aim of this study was to develop nomograms to predict the risk of intrahepatic vascular invasion (IVI) of hepatocellular carcinoma (HCC) patients and estimate the overall survival (OS) and cancer-specific survival (CSS) of HCC patients with IVI. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients with HCC from 2010 to 2015. Ultimately, 1,287 HCC patients with IVI were included in this study and randomly divided into training (n=901) and validation (n=386) cohorts. Multivariate logistic regression analysis and multivariate Cox proportional hazards regression analysis were performed to construct nomograms to visually quantify the risk of IVI in patients with HCC and predict the prognosis. The prediction effect of nomograms was evaluated using Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA), respectively. Results: The C-index of the nomogram for risk prediction was 0.730. The C-indices based on the nomogram were 0.762 [95% confidence interval (CI): 0.745-0.779] and 0.770 (95% CI: 0.753-0.787) for OS and CSS prediction in the training cohort, respectively. In the validation cohort, the C-indices were 0.779 (95% CI: 0.752-0.806) and 0.795 (95% CI: 0.768-0.822) for OS prediction and CSS prediction, respectively. Overall, the ROC curve, calibration plots, and DCA indicated the good performance of nomograms. Conclusions: We identified the relevant risk and prognostic factors for IVI in patients with HCC. The nomograms performed well on validation and may help to facilitate clinical decision-making.
Indexed as
Identifiers
What 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.