ArticleHeliyon2023
Nomogram of uveal melanoma as prediction model of metastasis risk.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 6 citations in OpenAlex.
- Development of a prognostic nomogram for ocular melanoma: a SEER population-based study (2000-2021).Frontiers in medicine · 2025Article
- Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.Cancer science · 2024Observational
- Protein Tyrosine Phosphatase PRL-3: A Key Player in Cancer Signaling.Biomolecules · 2024Review
- Integrating Single-cell and Bulk RNA-seq to Construct a Metastasis-related Model for Evaluating Immunotherapy and Chemotherapy in Uveal Melanoma.Current medicinal chemistry · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Since the poor prognosis of uveal melanoma with distant metastasis, we intended to screen out possible biomarkers for uveal melanoma metastasis risk and establish a nomogram model for predicting the risk of uveal melanoma (UVM) metastasis. Methods: Two datasets of UVM (GSE84976, GSE22138) were selected. Data was analyzed by R language, CTD database and GEPIA. Results: The co-upregulated genes of two datasets, HTR2B, CHAC1, AHNAK2, and PTP4A3 were identified using a Venn diagram. These biomarkers are combined with clinical characteristics, and Lasso regression was conducted to filter the metastasis-related biomarkers. HTR2B, CHAC1, AHNAK2, PTP4A3, tumor thickness, and retinal detachment (RD) were selected to establish the nomogram. Conclusion: Our study provides a comprehensive predictive model and personalized risk estimation tool for assessment of 3-year metastasis risk of UVM with a better accuracy.
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.