Evidence map›Paper›PMID 35058717›Full record

ArticleCancer management and research2022

Development and Internal Validation of a Nomogram-Based Model to Predict Three-Year and Five-Year Overall Survival in Patients with Stage II/III Colon Cancer.

Dan Ren, Wen-Ling Wang, Gang Wang, Wei-Wei Chen, Xiao-Kai Li, Guo-Dong Li, Sai-Xi Bai, Hong-Min Dong, Wang-Hua Chen

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

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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

9 authors at 2 institutions in 1 country.

Dan RenOncology Department, Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Wen-Ling WangDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Gang WangDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Wei-Wei ChenDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Xiao-Kai LiDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Guo-Dong LiDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Sai-Xi BaiDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Hong-Min DongDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Wang-Hua ChenDepartment of Abdominal Oncology, Affiliated Hospital of Guizhou Medical University, Affiliated Tumor Hospital of Guizhou Medical University, Guiyang, Guizhou, 550000, People's Republic of China.
Guiyang Medical University · CNAffiliated Hospital of Guizhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe aim of this study was to develop a nomogram-based model to predict the three-year and five-year overall survival (OS) of patients with stage II/III colon cancer following radical resection.

methodsA total of 1156 patients with stage II/III colon cancer who underwent radical resection at the Affiliated Hospital of Guizhou Medical University between December 2012 and December 2018 were enrolled. Lasso regression was used to screen out 12 variables: age, prealbumin, albumin, degree of differentiation, total tumor-node-metastasis (TNM) stage, T stage, N stage, prognostic nutritional index (PNI), platelet/lymphocyte count, carcinoembryonic antigen, carbohydrate antigen 19-9 (CA19-9), and postoperative adjuvant chemotherapy. The data set was then randomly split into a modeling set and a validation set, and the bootstrap method was used to verify the internal validity of the final model. A nomogram was then used to present the model, and the risk groups were categorized according to the total score in the nomogram.

resultsThis study established and developed a simple, easy-to-use predictive model that included age, degree of differentiation, N stage, CA19-9, PNI, and postoperative chemotherapy as variables. In the multivariate Cox regression analysis, only postoperative chemotherapy was identified as an independent risk factor for death in patients with colon cancer. The receiver operating characteristic curve showed that the model demonstrated good resolution, with an area under the curve of 0.803. Decision curve analysis indicated that the model had a good positive net gain, and the bootstrap method was used to verify its stability. In the OS rate, the C-index was 0.78. According to the total score of the nomogram, the risk group was layered by drawing the Kaplan-Meier (K-M) curve. In the three-year OS K-M curve, the survival rates of the low-risk group, the medium-risk group, and the high-risk group were 96%, 93%, and 82%, respectively. In the five-year OS K-M curve, the survival rates of the low-risk group, the medium-risk group, and the high-risk group were 94%, 90%, and 73%, respectively.

conclusionThe nomogram-based prediction model developed in this study is stable and has good resolution, reliability, and net gain. It will therefore be useful for clinicians performing risk stratification and postoperative monitoring and in the development of personalized treatment options for patients with stage II/III colon cancer.

Indexed as

colon cancernomogramoverall survivalprognosis

Identifiers

PMID35058717
PMCPMC8765714
OpenAlexW4205943345

What OpenQuestion holds

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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.