Evidence map›Paper›PMID 40969790›Full record

ArticleFrontiers in medicine2025

A clinical study incorporating multimodal

Zizhen Huang, Wanling Qi, Tian Rao, Qingyun Zeng, Ping Lu, Jie Zhang, Zhibin Qiu, Guihua Xiao, Qian Liu, Huan Fu and 1 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Zizhen Huang *Department of Psychosomatic Medicine, Jiangxi Provincal People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Wanling Qi *Department of Nuclear Medicine, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Tian RaoNanchang YiMai Sunshine Medical Imaging Diagnosis Co., Ltd., Nanchang, China.
Qingyun ZengDepartment of Nuclear Medicine, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Ping LuDepartment of Nuclear Medicine, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Jie ZhangNanchang YiMai Sunshine Medical Imaging Diagnosis Co., Ltd., Nanchang, China.
Zhibin QiuNanchang YiMai Sunshine Medical Imaging Diagnosis Co., Ltd., Nanchang, China.
Guihua XiaoDepartment of Cardiology, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Qian LiuDepartment of Pathology, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Huan FuDepartment of Hematology, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.
Fengxiang LiaoDepartment of Nuclear Medicine, Jiangxi Provincial People's Hospital (The First Affiliated Hospital of Nanchang Medical College), Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Langerhans cell histiocytosis (LCH) is a rare clonal proliferative disorder characterized by the infiltration of pathological Langerhans cells into multiple organs, exhibiting significant clinical heterogeneity. Although standard chemotherapy regimens have markedly improved patient survival rates, several challenges remain, such as low response rates, high recurrence rates, and long-term sequelae in certain patients. This study aimed to integrate multimodal 18F-FDG PET/CT metabolic parameters, genetic markers, and clinical characteristics to evaluate and predict treatment efficacy and prognosis in patients with LCH. Methods: A retrospective analysis was conducted on clinical data and Results: Patients with disease progression or recurrence exhibited significantly higher SUVmax, TLR, MTV, and TLG values compared to those who responded to treatment. ROC curve analysis identified optimal cutoff values for predicting disease remission as follows: SUVmax = 7.5, TLR = 5.2, MTV = 25.0, and TLG = 150. The remission rates in the high-value groups for SUVmax, MTV, and TLG were significantly lower than those in the corresponding low-value groups, with the most pronounced differences observed in the MTV and TLG groups ( Conclusion: Baseline metabolic parameters derived from

Indexed as

genetic markersLangerhans cell histiocytosismetabolic parametersprognosistreatment efficacy

Identifiers

PMID40969790
PMCPMC12442764

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.