Evidence map›Paper›PMID 35814753›Full record

ArticleFrontiers in medicine2022

A Predictive Web-Based Nomogram for Elderly Patients Newly Diagnosed as Uveal Melanoma: A Population-Based Study.

Meng Lv, Xinhua Yan, Yuanxing Tu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

3 authors.

Meng LvDepartment of Ophthalmology, Lanxi People's Hospital, Jinhua, China.
Xinhua YanDepartment of Ophthalmology, Lanxi People's Hospital, Jinhua, China.
Yuanxing TuDepartment of Ophthalmology, Lanxi People's Hospital, Jinhua, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Uveal melanoma (UM) is the most frequent primary intraocular tumor in adults. This study aims to develop a nomogram and an individualized web-based calculator to predict the overall survival (OS) of elderly patients with UM. Methods: Patients aged more than 60 years and diagnosed with UM were derived from the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2015. The selected patients were randomly divided into training and validation cohorts. In the training cohort, the univariate and multivariate Cox analyses were carried out to determine the independent prognostic factors, and the predictors were integrated to establish a nomogram for predicting the 1-, 2-, and 3-year OS of elderly patients with UM. The discrimination of the nomogram was validated by receiver operating characteristic (ROC) curves and the area under the curve (AUC). The clinical practicability and accuracy of the nomogram were evaluated by the calibration curves and decision curve analysis (DCA). A web-based survival calculator was then constructed using a fitted survival prediction model (https://yuexinupup.shinyapps.io/DynNomapp/). Results: A total of 1,427 patients with UM were included in this study. Age, T stage, N stage, M stage, marital status, sex, and radiotherapy (RT) were identified as independent prognostic factors. Based on the abovementioned factors, the nomogram was then constructed. The AUC values of the nomogram predicting 1-, 2-, and 3-year OS were 0.841, 0.801, and 0.768 in the training cohort, and 0.745, 0.717, and 0.710 in the validation cohort, respectively. The calibration curves and DCA also indicated the good performance of the predictive model. Conclusion: This study established and validated a novel nomogram risk stratification model and a web-based survival rate calculator that can dynamically predict the long-term OS for elderly patients with UM.

Indexed as

elderlynomogramoverall survivalSEERuveal melanoma

Identifiers

PMID35814753
PMCPMC9259836
OpenAlexW4283331184

What OpenQuestion holds

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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.