Evidence map›Paper›PMID 42656393›Full record

ArticleFrontiers in oncology2026

Integrating perioperative inflammation and pathological invasiveness to predict recurrence after curative colorectal cancer surgery: a multicenter cohort study.

Jian Deng, Qiang Gao, Jie Jiao, Baochuan Yang, Xunying Zhang, Jiayong Wang, Jinbo Jiang, Zhi Liu

Abstract read
In one paragraph

Article in Frontiers in oncology, 2026. 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
0cells of the map it votes in
0citing 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

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

8 authors.

Jian Deng *Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Qiang Gao *Department of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Jie JiaoDepartment of Gastrointestinal Surgery, Central Hospital Affiliatedo Shandong First Medical University, Jinan, Shandong, China.
Baochuan YangDepartment of Gastrointestinal Surgery, The Third Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China.
Xunying ZhangDepartment of Gastrointestinal Surgery, Jinan Fourth People's Hospital, Jinan, Shandong, China.
Jiayong WangDepartment of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Jinbo JiangDepartment of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.
Zhi LiuDepartment of General Surgery, Qilu Hospital of Shandong University, Jinan, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recurrence risk after curative surgery for non-metastatic colorectal cancer (CRC) remains heterogeneous within the same TNM stage. Pathological invasiveness and perioperative systemic inflammation may provide complementary prognostic information, but their combined value and the role of early postoperative inflammatory dynamics remain insufficiently defined. We aimed to develop and externally validate a multicenter prognostic model integrating invasive pathological features with perioperative inflammatory biomarkers to improve recurrence-free survival (RFS) prediction. Patients and methods: We retrospectively included 1,260 patients with stage I-III colorectal adenocarcinoma who underwent curative-intent resection between January 2017 and March 2023. The development cohort comprised 1,008 consecutive patients from Qilu Hospital of Shandong University, and the external validation cohort comprised 252 patients from three regional hospitals. Data extraction followed a prespecified case-report framework with harmonized definitions for pathology, perioperative laboratory timing, adjuvant treatment, surgical approach, MSI/MMR status, and follow-up. The final Cox model was evaluated against prespecified comparator models, with additional sensitivity analyses adjusting for adjuvant chemotherapy, surgical approach, and MSI status. Results: The reduced final pathology-inflammation model incorporated eight predictors: histological differentiation, pN stage, extramural venous invasion (EMVI), tumor budding (BD), tumor deposits (TD), preoperative CEA, preoperative systemic immune-inflammation index (preSII), and postoperative day-1 C-reactive protein-to-albumin ratio (postCAR). The final model used 9 effective parameters and 437 recurrence events in the development cohort, corresponding to an events-per-variable ratio of 48.6. Its apparent Harrell C-index was 0.786 in the development cohort and 0.793 in the external validation cohort; bootstrap-based internal validation showed minimal optimism (mean optimism 0.003; optimism-corrected C-index 0.783). Adding adjuvant chemotherapy, surgical approach, and MSI status did not materially change discrimination in either cohort. The development-derived cutoff retained clinically meaningful separation in the external validation cohort, with 3-year sensitivity of 78.0% and specificity of 72.5%. Conclusions: In this multicenter study, a reduced pathology-inflammation model improved postoperative recurrence prediction beyond conventional clinicopathologic assessment in stage I-III CRC and remained stable after adjustment for newly incorporated treatment, surgical approach, and MSI/MMR information. Because postoperative inflammatory markers may partly reflect operative and early postoperative factors, and because the study remains retrospective, the model should be interpreted as a risk-stratification aid requiring prospective validation before routine clinical implementation.

Indexed as

colorectal cancerexternal validationprognostic modelrecurrence-free survivalsystemic inflammationtumor-host interaction

Identifiers

PMID42656393
PMCPMC13506383

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.