Evidence map›Paper›PMID 40195140›Full record

SynthesisAbdominal radiology (New York)2025

Looking at or beyond the tumor - a systematic review and meta-analysis of quantitative imaging biomarkers predicting pancreatic cancer prognosis.

Zihe Wang, Liang Zhu, Yitan Wang, Xianlin Han, Qiang Xu, Menghua Dai

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

6 authors.

Zihe WangSchool of Medicine, Anhui Medical University, Hefei, China.ORCID 0009-0007-6518-7119
Liang ZhuDepartment of Radiology, Peking Union Medical College Hospital, Beijing, China. zhuliang_pumc@163.com.ORCID 0000-0003-3779-7853
Yitan WangDepartment of Statistics and Data Science, Yale University, New Haven, Connecticut, USA.
Xianlin HanDepartment of General Surgery, Peking Union Medical College Hospital, Beijing, China.
Qiang XuDepartment of General Surgery, Peking Union Medical College Hospital, Beijing, China.
Menghua DaiDepartment of General Surgery, Peking Union Medical College Hospital, Beijing, China.

Funding

National Natural Science Foundation of China 82371950
6 · The paper itself

Abstract

objectivesTo evaluate the prognostic value of quantitative imaging biomarkers derived from computed tomography (CT) and magnetic resonance imaging (MRI) for pancreatic cancer (PC), with a particular focus on body composition parameters beyond the traditional intrinsic features of the tumor.

methodsPubMed, EMBASE, and Cochrane Library databases were searched for articles on quantitative imaging biomarkers obtained from CT or MRI in predicting PC prognosis published between January 2014 and August 2024. The Newcastle-Ottawa scale was used to assess the quality of the included studies. Survival outcomes, such as overall survival (OS) and recurrence-free survival (RFS), were evaluated. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using a random-effects model. In case of high heterogeneity, subgroup analyses and sensitivity analyses were performed to identify potential sources of heterogeneity among the studies.

resultsWe performed a meta-analysis of ten imaging biomarkers investigated in 43 included studies. Larger tumor size, lower skeletal muscle radiodensity, lower skeletal muscle index (SMI), presence of sarcopenic obesity, lower psoas muscle index (PMI), higher visceral to subcutaneous adipose tissue area ratio, and lower visceral adipose tissue index were associated with significantly worse OS. In particular, lower SMI and lower PMI had relatively high HRs (1.65 for SMI, 95% CI 1.39-1.96, and 2.20 for PMI, 95% CI 1.74-2.78). Patients with lower SMI exhibited poorer RFS (HR 1.78, 95% CI 1.46-2.18). Subgroup analyses identified the origin region of the study and intervention type as potential factors of heterogeneity for SMI in predicting OS.

conclusionsImaging biomarkers indicating body composition at PC diagnosis may play an important role in predicting patient prognosis. Further prospective multi-center studies with large sample sizes are needed for validation and translation into clinical practice.

Indexed as

Magnetic Resonance ImagingPancreatic NeoplasmsTomography, X-Ray ComputedBiomarkers, TumorBody CompositionHumansPredictive Value of TestsPrognosisBiomarkers, TumorMagnetic resonance imagingMeta-analysisPancreatic neoplasmsPrognosisTomography, X-Ray computed

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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.