Evidence map›Paper›PMID 36035279›Full record

ArticleComputational and mathematical methods in medicine2022

Clinical Data-CT Radiomics-Based Model for Predicting Prognosis of Patients with Gastrointestinal Pancreatic Neuroendocrine Neoplasms (GP-NENs).

Peng An, Junyan Zhang, Mingqun Li, Peng Duan, Zhibing He, Zhongq Wang, Guoyan Feng, Hongyan Guo, Xiumei Li, Ping Qin

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

10 authors.

Peng An *Department of Radiology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0002-0048-2738
Junyan Zhang *Department of Pharmacy and Laboratory, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0002-3486-6625
Mingqun Li *Department of Internal Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0001-8890-807X
Peng DuanDepartment of Oncology/Obstetrics and Gynecology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0001-6740-6687
Zhibing HeDepartment of Radiology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0001-9087-7006
Zhongq WangDepartment of Radiology, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0003-2871-7567
Guoyan FengDepartment of Pharmacy and Laboratory, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0002-2909-8430
Hongyan GuoDepartment of Internal Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0001-5894-2613
Xiumei LiDepartment of Internal Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0002-9672-9431
Ping QinDepartment of Internal Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China.ORCID https://orcid.org/0000-0001-7514-8809

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Based on computerized tomography (CT) radiomics and clinical data, a model was established to predict the prognosis of patients with gastrointestinal pancreatic neuroendocrine neoplasms (GP-NENs). Methods: In the data collection, the clinical imaging and survival follow-up data of 225 GP-NENs patients admitted to Xiangyang No.1 People's Hospital and Jiangsu Province Hospital of Chinese Medicine from August 2015 to February 2021 were collected. According to the follow-up results, they were divided into the nonrecurrent group ( Results: Our newly developed combined prediction model had high predictive efficacy. Univariate analysis showed that Radscore 1/2/3, age, Ki-67 index, tumor pathological type, tumor primary site, and TNM stage were risk factors for the prognosis of GP-NENs patients (all Conclusion: The prognosis of patients with GP-NENs is generally poor. The combined model based on clinical data and CT radiomics can help to early predict the prognosis of patients with GP-NENs, and then necessary interventions could be provided to improve the survival rate and quality of life of patients.

Indexed as

Neuroendocrine TumorsPancreatic NeoplasmsHumansPrognosisQuality of LifeRetrospective StudiesROC CurveTomography, X-Ray Computed

Identifiers

PMID36035279
PMCPMC9410919

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