Evidence map›Paper›PMID 41444419›Full record

ArticleNPJ precision oncology2025

Higher local recurrence as the distinct failure pattern in early-onset rectal cancer: a tailored MRI score to guide therapy.

Yunrui Ye, Ke Zhao, Lili Feng, Yanfen Cui, Zhenhui Li, Minning Zhao, Lifen Yan, Haitao Huang, Yulin Liu, Kaibo Ouyang and 5 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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. Article
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

15 authors.

Yunrui Ye *Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Ke Zhao *Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Lili Feng *Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yanfen CuiDepartment of Radiology, Shanxi Cancer Hospital, Shanxi Medical University, Taiyuan, China.
Zhenhui LiDepartment of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, China.
Minning ZhaoDepartment of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Lifen YanDepartment of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Haitao HuangDepartment of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Yulin LiuDepartment of Radiology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Kaibo OuyangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
Weixiong XuDepartment of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Zaiyi LiuDepartment of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Yong LiDepartment of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. liyong@gdph.org.cn.
Changhong LiangGuangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. liangchanghong@gdph.org.cn.
Min-Er ZhongDepartment of Gastrointestinal Surgery, Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China. zhongminer@gdph.org.cn.

Funding

Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application No. 2022B1212010011Noncommunicable Chronic Diseases-National Science and Technology Major Project 2024ZD0531100, 2024ZD0531101Regional Innovation and Development Joint Fund of National Natural Science Foundation of China No.U22A20345Regional Innovation and Development Joint Fund of National Natural Science Foundation of China No.U23A20478Science and Technology Projects in Guangzhou 2024A04J4977the National Science Foundation for Young Scientists of China 82202267the Talent Introduction Supporting Funds of Guangdong Provincial People's Hospital KY0120230009
6 · The paper itself

Abstract

The unique biology of early-onset locally advanced rectal cancer (EOLARC) may drive distinct failure patterns, challenging current age-agnostic management. This multicenter retrospective study aimed to define these patterns compared to late-onset disease (LOLARC) and develop a tailored magnetic resonance imaging (MRI)-based risk score. We analyzed 1289 patients undergoing neoadjuvant chemoradiotherapy and surgery. After propensity score matching, EOLARC patients exhibited higher local recurrence rates (4.9% vs. 1.7%; P = 0.03) despite similar pathological complete response (pCR) rates (25.5% vs. 21.2%; P = 0.22). The novel mrTML score (incorporating tumor deposits, mesorectal fascia, and lateral lymph nodes) effectively predicted local recurrence (adjusted hazard ratio for score 3 vs. 0, 33.99). Notably, high pre-treatment risk persisted even among patients achieving pCR (HR 12.02; P = 0.003), highlighting failure patterns uncaptured by pathological response. The mrTML score is a robust tool to identify patients at high risk for local recurrence, providing an evidence-based framework for risk-adapted therapy.

Identifiers

PMID41444419
PMCPMC12847736

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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.