Evidence map›Paper›PMID 36600277›Full record

ArticleBMC medicine2023

Survival outcomes of stage I colorectal cancer: development and validation of the ACEPLY model using two prospective cohorts.

Qingbin Wu, Pengju Chen, Chi Shu, Lin Chen, Zechuan Jin, Jun Huang, Xin Wang, Xue Li, Mingtian Wei, Tinghan Yang and 4 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

14 citing papers in PubMed, 15 citations in OpenAlex.

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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

14 authors at 6 institutions in 3 countries.

Qingbin Wu *Colorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Pengju Chen *Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Unit III & Ostomy Service, Gastrointestinal Cancer Centre, Peking University Cancer Hospital & Institute, Beijing, China.
Chi Shu *Department of Vascular Surgery, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China.
Lin ChenKey Laboratory of Ministry of Education for Gastrointestinal Cancer, Fujian Medical University, Fuzhou, China.
Zechuan JinColorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Jun HuangColorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Xin WangDepartment of Epidemiology and Medical Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xue LiDepartment of Big Data in Health Science, School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Mingtian WeiColorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Tinghan YangColorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Xiangbing DengColorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Aiwen WuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Unit III & Ostomy Service, Gastrointestinal Cancer Centre, Peking University Cancer Hospital & Institute, Beijing, China. wuaw@sina.com.
Yazhou He *Department of Oncology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China. yazhou.he@scu.edu.cn.
Ziqiang Wang *Colorectal Cancer Center, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China.
Sichuan University · CNPeking University Cancer Hospital · CNFujian Medical University · CNUniversity of Edinburgh · GBWest China Hospital of Sichuan University · CNWest China Medical Center of Sichuan University · CN

Funding

National Natural Science Foundation of China 82103541National Natural Science Foundation of China 82103918National Natural Science Foundation of China 82173156Sichuan Province Science and Technology Support Program 2021YFS0025Sichuan Province Science and Technology Support Program 2022NSFSC1314Sichuan Provincial Postdoctoral Science Foundation 2019HXBH041
6 · The paper itself

Abstract

backgroundApproximately 10% of stage I colorectal cancer (CRC) patients experience unfavorable clinical outcomes after surgery. However, little is known about the subset of stage I patients who are predisposed to high risk of recurrence or death. Previous evidence was limited by small sample sizes and lack of validation.

methodsWe aimed to identify early indicators and develop a risk stratification model to inform prognosis of stage I patients by employing two large prospective cohorts. Prognostic factors for stage II tumors, including T stage, number of nodes examined, preoperative carcinoma embryonic antigen (CEA), lymphovascular invasion, perineural invasion (PNI), and tumor grade were investigated in the discovery cohort, and significant findings were further validated in the other cohort. We adopted disease-free survival (DFS) as the primary outcome for maximum statistical power and recurrence rate and overall survival (OS) as secondary outcomes. Hazard ratios (HRs) were estimated from Cox proportional hazard models, which were subsequently utilized to develop a multivariable model to predict DFS. Predictive performance was assessed in relation to discrimination, calibration and net benefit.

resultsA total of 728 and 413 patients were included for discovery and validation. Overall, 6.7% and 4.1% of the patients developed recurrences during follow-up. We identified consistent significant effects of PNI and higher preoperative CEA on inferior DFS in both the discovery (PNI: HR = 4.26, 95% CI: 1.70-10.67, p = 0.002; CEA: HR = 1.46, 95% CI: 1.13-1.87, p = 0.003) and the validation analysis (PNI: HR = 3.31, 95% CI: 1.01-10.89, p = 0.049; CEA: HR = 1.58, 95% CI: 1.10-2.28, p = 0.014). They were also significantly associated with recurrence rate. Age at diagnosis was a prominent determinant of OS. A prediction model on DFS using Age at diagnosis, CEA, PNI, and number of LYmph nodes examined (ACEPLY) showed significant discriminative performance (C-index: 0.69, 95% CI:0.60-0.77) in the external validation cohort. Decision curve analysis demonstrated added clinical benefit of applying the model for risk stratification.

conclusionsPNI and preoperative CEA are useful indicators for inferior survival outcomes of stage I CRC. Identification of stage I patients at high risk of recurrence is feasible using the ACEPLY model, although the predictive performance is yet to be improved.

Indexed as

Colorectal NeoplasmsHumansNeoplasm StagingPrognosisProspective StudiesRetrospective StudiesColorectal cancerEarly stagePrediction modelPrognosisRisk factor

Identifiers

PMID36600277
PMCPMC9814451
OpenAlexW4313546453

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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.