Evidence map›Paper›PMID 41567811›Full record

ArticleTherapeutic advances in medical oncology2026

A clinical-molecular nomogram for predicting early recurrence following resection of initially unresectable colorectal liver metastases.

Yu-Ting Lu, Xiao-Xia Huang, Wen-Chuan Chen, Qi-Yun Xiao, Jian-Li Duan, Zi-Jing Li, William Pat Fong, Feng-Hua Wang, Yu-Hong Li, De-Shen Wang

Abstract read
In one paragraph

Article in Therapeutic advances in medical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

10 authors.

Yu-Ting LuDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Xiao-Xia HuangDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Wen-Chuan ChenDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Qi-Yun XiaoDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Jian-Li DuanDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Zi-Jing LiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
William Pat FongDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Feng-Hua WangDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, China.
Yu-Hong LiDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China.ORCID https://orcid.org/0000-0002-5710-9096
De-Shen WangDepartment of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China.ORCID https://orcid.org/0000-0001-9657-4380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Postoperative early recurrence (PER) remains a major challenge to long-term survival after successful conversion therapy and curative resection for initially unresectable colorectal liver metastases (CRLM). Existing prediction models rely heavily on clinicopathological parameters and lack molecular biomarkers, limiting their predictive accuracy. Objectives: To define the optimal recurrence-free survival (RFS) cutoff for PER and develop a comprehensive predictive nomogram incorporating molecular and clinical variables to predict PER in patients with initially unresectable CRLM who undergo curative resection following conversion therapy. Design: Retrospective cohort study. Methods: Clinicopathological and molecular data from 411 patients with initially unresectable CRLM undergoing curative resection after conversion therapy were analyzed. The minimum Results: PER was defined as recurrence within 4 months postoperatively. Independent predictors included dual preoperative positivity for CEA and CA19-9 (odds ratio (OR) = 2.437, Conclusion: We identified 4 months as the optimal RFS threshold for PER and proposed a novel nomogram integrating molecular and clinical factors for perioperative decision-making in patients with initially unresectable CRLM.

Indexed as

early recurrenceinitially unresectable colorectal liver metastasesminimum p valuenomogram

Identifiers

PMID41567811
PMCPMC12816525

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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.