Evidence map›Paper›PMID 36518985›Full record

ArticleGastroenterology report2022

Nomogram for predicting overall survival time of patients with stage IV colorectal cancer.

Min-Yi Lv, Xi-Jie Chen, Jun-Guo Chen, Bin Zhang, Yan-Yun Lin, Tian-Ze Huang, De-Gao He, Kai Wang, Zeng-Jie Chi, Jian-Cong Hu and 1 more

Abstract read
In one paragraph

Article in Gastroenterology report, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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  6. Effect ofGastroenterology report · 2023
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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

11 authors.

Min-Yi LvDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.ORCID https://orcid.org/0000-0003-0155-9204
Xi-Jie ChenDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Jun-Guo ChenDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Bin ZhangDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Yan-Yun LinDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Tian-Ze HuangDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
De-Gao HeDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Kai WangDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Zeng-Jie ChiDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Jian-Cong HuDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.
Xiao-Sheng HeDepartment of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Prognosis varies among stage IV colorectal cancer (CRC). Our study aimed to build a robust prognostic nomogram for predicting overall survival (OS) of patients with stage IV CRC in order to provide evidence for individualized treatment. Method: We collected the information of 16,283 patients with stage IV CRC in the Surveillance, Epidemiology, and End Results (SEER) database and then randomized these patients in a ratio of 7:3 into a training cohort and an internal validation cohort. In addition, 501 patients in the Sixth Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) database were selected and used as an external validation cohort. Univariate and multivariate Cox analyses were used to screen out significant variables for nomogram establishment. The nomogram model was assessed using time-dependent receiver-operating characteristic curve (time-dependent ROC), concordance index (C-index), calibration curve, and decision curve analysis. Survival curves were plotted using the Kaplan-Meier method. Result: The C-index of the nomogram for OS in the training, internal validation, and external validation cohorts were 0.737, 0.727, and 0.655, respectively. ROC analysis and calibration curves pronounced robust discriminative ability of the model. Further, we divided the patients into a high-risk group and a low-risk group according to the nomogram. Corresponding Kaplan-Meier curves showed that the prediction of the nomogram was consistent with the actual practice. Additionally, model comparisons and decision curve analysis proved that the nomogram for predicting prognosis was significantly superior to the tumor-node-metastasis (TNM) staging system. Conclusions: We constructed a nomogram to predict OS of the stage IV CRC and externally validate its generalization, which was superior to the TNM staging system.

Indexed as

nomogramoverall survivalprognosisSEERstage IV CRC

Identifiers

PMID36518985
PMCPMC9731212

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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.