Evidence map›Paper›PMID 33902469›Full record

ArticleBMC medical imaging2021

Whole-tumour evaluation with MRI and radiomics features to predict the efficacy of S-1 for adjuvant chemotherapy in postoperative pancreatic cancer patients: a pilot study.

Liang Liang, Ying Ding, Yiyi Yu, Kai Liu, Shengxiang Rao, Yingqian Ge, Mengsu Zeng

Open access · goldAbstract read
In one paragraph

Article in BMC medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 13 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

7 authors at 2 institutions in 1 country.

Liang LiangDepartment of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Ying DingDepartment of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Yiyi YuDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Kai LiuDepartment of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Shengxiang RaoDepartment of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Yingqian GeSiemens Healthineers, No. 278 Zhou Zhu Road, Pudong New District, Shanghai, 201318, China.
Mengsu ZengDepartment of Radiology, Zhongshan Hospital, Fudan University, and Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. zengmengsu_zs@163.com.ORCID 0000-0002-5769-925X
Fudan University · CNSiemens (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultiple guidelines for pancreatic ductal adenocarcinoma (PDAC) suggest that all stages of patients need to receive postoperative adjuvant chemotherapy. S-1 is a recently emerged oral antitumour agent recommended by the guidelines. However, which population would benefit from S-1 needs to be determined, and predictors of chemotherapy response are needed for personalized precision medicine. This pilot study aimed to initially identify whether whole-tumour evaluation with MRI and radiomics features could be used for predicting the efficacy of S-1 and to find potential predictors of the efficacy of S-1 as evidence to assist personalized precision treatment.

methodsForty-six patients with PDAC (31 in the primary cohort and 15 in the validation cohort) who underwent curative resection and subsequently adjuvant chemotherapy with S-1 were included. Pre-operative abdominal contrast-enhanced MRI was performed, and radiomics features of the whole PDAC were extracted from the primary cohort. After univariable analysis and radiomics features selection, a multivariable Cox regression model for survival analysis was subsequently used to select statistically significant factors associated with postoperative disease-free survival (DFS). Predictive capacities of the factors were tested on the validation cohort by using Kaplan-Meier method.

resultsMultivariable Cox regression analysis identified the probability of T

conclusionsWhole-tumour radiomics feature of T

Indexed as

Analysis of VarianceAntimetabolites, AntineoplasticCarcinoma, Pancreatic DuctalChemotherapy, AdjuvantContrast MediaDisease-Free SurvivalDrug Administration ScheduleDrug CombinationsFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedOxonic AcidPancreatic NeoplasmsPilot ProjectsAntimetabolites, AntineoplasticContrast MediaDrug CombinationsOxonic AcidS 1 (combination)TegafurCarcinoma, Pancreatic DuctalDrug therapyMagnetic resonance imagingPersonalized medicineRadiomicsSurvival analysis

Identifiers

PMID33902469
PMCPMC8077911
OpenAlexW3158457961

What OpenQuestion holds

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Registered trials

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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.