Evidence map›Paper›PMID 39234506›Full record

ArticleFrontiers in endocrinology2024

Nomogram construction and evaluation for predicting non-remission after a single radioactive iodine therapy for Graves' hyperthyroidism: a retrospective cohort study.

Feng Yu, Wenhui Ma, Xue Li, Ruiguo Zhang, Fei Kang, Weidong Yang, Renfei Wang, Jing Wang

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Feng YuDepartment of Nuclear Medicine, Xijing Hospital, Air Force Military Medical University, Xi'an, China.
Wenhui MaDepartment of Nuclear Medicine, Xijing Hospital, Air Force Military Medical University, Xi'an, China.
Xue LiDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Ruiguo ZhangDepartment of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Fei KangDepartment of Nuclear Medicine, Xijing Hospital, Air Force Military Medical University, Xi'an, China.
Weidong YangDepartment of Nuclear Medicine, Xijing Hospital, Air Force Military Medical University, Xi'an, China.
Renfei WangDepartment of Nuclear Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, China.
Jing WangDepartment of Nuclear Medicine, Xijing Hospital, Air Force Military Medical University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Radioactive iodine (RAI) therapy is a widely used treatment for Graves' Hyperthyroidism (GH). However, various factors can impact the non-remission rate of GH after single RAI therapy. This study aimed to develop an online dynamic nomogram to assist physicians in providing personalized therapy for GH. Methods: Data from 454 GH patients who received RAI therapy were retrospectively reviewed and included in the present study. The univariate and multivariate analysis were conducted to investigate and identify independent influencing factors. The nomogram was developed based on the training cohort to explore non-remission rates. Finally, the reliability and accuracy of the constructed nomogram model were verified in the validation cohort via the calibration, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Results: 24-hours radioactive iodine uptake (RAIU Conclusion: An online nomogram was constructed with good predictive performance, which can be used as a practical approach to predict and assist physicians in making personalized therapy decisions for GH patients.

Indexed as

Graves DiseaseIodine RadioisotopesNomogramsAdultCohort StudiesFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesIodine RadioisotopesGraves’ hyperthyroidismnomogramnon-remissionprediction modelradioactive iodine therapy

Identifiers

PMID39234506
PMCPMC11371608

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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.