Evidence map›Paper›PMID 35693082›Full record

ArticleAmerican journal of cancer research2022

A novel preoperative MRI-based radiomics nomogram outperforms traditional models for prognostic prediction in pancreatic ductal adenocarcinoma.

Hui Qiu, Muchen Xu, Yan Wang, Xin Wen, Xueting Chen, Wanming Liu, Nie Zhang, Xin Ding, Longzhen Zhang

Open access · greenAbstract read
In one paragraph

Article in American journal of cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

4 citing papers in PubMed, 5 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

9 authors at 2 institutions in 1 country.

Hui QiuCancer Institute, Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Muchen XuDepartment of Radiation Oncology, Dushu Lake Hospital Affilated to Soochow University, Medical Center of Soochow University Suzhou 215000, Jiangsu, China.
Yan WangDepartment of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Xin WenCancer Institute, Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Xueting ChenDepartment of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Wanming LiuDepartment of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Nie ZhangDepartment of Radiation Oncology, Affiliated Hospital of Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Xin DingCancer Institute, Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Longzhen ZhangCancer Institute, Xuzhou Medical University Xuzhou 221000, Jiangsu, China.
Xuzhou Medical College · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To develop an efficient prognostic model based on preoperative magnetic resonance imaging (MRI) radiomics for patients with pancreatic ductal adenocarcinoma (PDAC), the preoperative MRI data of PDAC patients in two independent centers (defined as development cohort and validation cohort, respectively) were collected retrospectively, and the radiomics features of tumors were then extracted. Based on the optimal radiomics features which were significantly related to overall survival (OS) and progression-free survival (PFS), the score of radiomics signature (Rad-score) was calculated, and its predictive efficiency was evaluated according to the area under receiver operator characteristic curve (AUC). Subsequently, the clinical-radiomics nomogram which incorporated the Rad-score and clinical parameters was developed, and its discrimination, consistency and application value were tested by calibration curve, concordance index (C-index) and decision curve analysis (DCA). Moreover, the predictive value of the clinical-radiomics nomogram was compared with traditional prognostic models. A total of 196 eligible PDAC patients were enrolled in this study. The AUC value of Rad-score for OS and PFS in development cohort was 0.724 and 0.781, respectively, and the value of Rad-score was negatively correlated with PDAC's prognosis. Moreover, the developed clinical-radiomics nomogram showed great consistency with the C-index for OS and PFS in development cohort was 0.814 and 0.767, respectively. In addition, the DCA demonstrated that the developed nomogram displayed better clinical predictive usefulness than traditional prognostic models. We concluded that the preoperative MRI-based radiomics signature was significantly related to the poor prognosis of PDAC patients, and the developed clinical-radiomics nomogram showed better predictive ability, it might be used for individualized prognostic assessment of preoperative patients with PDAC.

Indexed as

nomogramPancreatic ductal adenocarcinomaprognostic modelradiomics

Identifiers

PMID35693082
PMCPMC9185614
OpenAlexW4285741071

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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.