Evidence map›Paper›PMID 40667546›Full record

ArticleAmerican journal of cancer research2025

Imaging-guided SMART improves survival in locally advanced and borderline resectable pancreatic cancer: a comparative study.

Nianhui Jiao, Huiqin Qi, Xuejun Li, Yongjie Qi, Yanjie Sun

Abstract read
In one paragraph

Article in American journal of cancer research, 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
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0citing papers in PubMed
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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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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

5 authors.

Nianhui JiaoDepartment of Critical Care Medicine, People's Hospital Affiliated to Shandong First Medical University Jinan 271199, Shandong, China.
Huiqin QiDepartment of Critical Care Medicine, People's Hospital Affiliated to Shandong First Medical University Jinan 271199, Shandong, China.
Xuejun LiDepartment of Critical Care Medicine, People's Hospital Affiliated to Shandong First Medical University Jinan 271199, Shandong, China.
Yongjie QiDepartment of Critical Care Medicine, People's Hospital Affiliated to Shandong First Medical University Jinan 271199, Shandong, China.
Yanjie SunDepartment of Critical Care Medicine, People's Hospital Affiliated to Shandong First Medical University Jinan 271199, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer remains notoriously challenging to treat due to its aggressive nature and complex anatomic location. Late-stage diagnoses often result in high mortality rates. This study assesses the effectiveness of combining ablative stereotactic MRI-guided intensity-modulated radiation therapy (SMART) with chemotherapy for treating locally advanced and borderline resectable pancreatic cancer. We retrospectively analyzed 235 pancreatic cancer patients treated between 2020 and 2023. Patients were divided into chemoradiation (SMART + chemotherapy, n = 106) and chemotherapy-only (n = 129) groups. Key outcomes included progression-free survival, overall survival, margin-negative resection rates, lymphovascular invasion, and toxicities. The chemoradiation group demonstrated improved PFS (8.30 ± 1.20 vs. 7.90 ± 1.30 months, P = 0.015) and OS (14.30 ± 2.60 vs. 13.50 ± 2.40 months, P = 0.015), with higher rates of margin-negative resections (92.45% vs. 80.62%, P = 0.009) and reduced LVI (37.74% vs. 52.71%, P = 0.022) compared to chemotherapy alone. However, acute toxicities, including fatigue and abdominal pain, were more frequent in the chemoradiation group. Locoregional control and distant metastasis-free survival showed no significant group differences (P > 0.05). Overall, SMART enhances local tumor control and survival outcomes in severe pancreatic cancer, albeit with increased acute toxicity.

Indexed as

ablative radiation therapychemotherapyPancreatic cancerstereotactic MRIsurvival outcomestoxicity

Identifiers

PMID40667546
PMCPMC12256400

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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.