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Predicting survival and prognosis in early-onset locally advanced colon cancer: a retrospective observational study

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International Journal of Colorectal Disease Aims and scope Submit manuscript

Abstract

Objective

To predict cancer-specific survival, a refined nomogram model and brand-new risk-stratifying system were established to classify the risk levels of patients with early-onset locally advanced colon cancer (LACC).

Methods

The clinical factors and survival outcomes of LACC cases from the SEER database from 2010 to 2019 were retrieved retrospectively. Early-onset and late-onset colon cancer were grouped according to the age (50 years old) at diagnosis. Differences between groups were compared to identify mutual significant variables. A multivariate Cox regression analysis was further performed and then constructed a nomogram. We compared it with the AJCC-TNM system. The external validation was performed for evaluation. Finally, a risk-stratifying system of patients with early-onset LACC was established.

Results

A total of 32,855 LACC patients were enrolled in, 4548 (13.84%) patients were included in the early-onset LACC group, and 28,307 (86.16%) patients were included in the late-onset LACC group. The external validation set included 228 early-onset LACC patients. Early-onset colon cancers had poorer prognosis (T4, N2, TNM stage III, CEA, tumor deposit, and nerve invasion), and a higher proportion received radiotherapy and systemic therapy (P<0.001). In the survival analysis, cancer-specific survival (CSS) was better in patients with early-onset LACC than in those with late-onset LACC (P <0.001). This nomogram constructed based on the results of COX analysis showed better accuracy in CSS prediction of early-onset LACC patients than AJCC-TNM system in the training set and external validation set (0.783 vs 0.728; 0.852 vs 0.773).

Conclusion

We developed a novel nomogram model to predict CSS in patients with early-onset LACC it provided a reference in prognosis prediction and selection of individualized treatment, helping clinicians in decision-making.

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Availability of data and materials

The data presented in this study are available on reasonable request.

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Funding

This study was sponsored by Yangzhou City Science and Technology Project (Funding No.YZ2020159).

Author information

Authors and Affiliations

  1. Northern Jiangsu People’s Hospital Affiliated to Yangzhou University, Yangzhou, 225001, China

    Bangquan Chen, Wenhao Yu, Yapeng Yang, Jun Ren & Daorong Wang

  2. General Surgery Institute of Yangzhou, Yangzhou University, Yangzhou, 225001, China

    Bangquan Chen, Yue Ma, Jiajie Zhou, Shuyang Gao, Wenhao Yu, Yapeng Yang, Yong Wang, Jun Ren & Daorong Wang

  3. Yangzhou Key Laboratory of Basic and Clinical Transformation of Digestive and Metabolic Diseases, Yangzhou, China

    Bangquan Chen, Yue Ma, Jiajie Zhou, Shuyang Gao, Wenhao Yu, Yapeng Yang, Yong Wang, Jun Ren & Daorong Wang

  4. Northern Jiangsu People’s Hospital, Medical School of Nanjing University, Yangzhou, 225001, China

    Yue Ma & Jiajie Zhou

  5. Northern Jiangsu People’s Hospital Affiliated to Dalian Medical University, Yangzhou, 225001, China

    Shuyang Gao

  6. Northern Jiangsu People’s Hospital, Yangzhou, 225001, China

    Yong Wang, Jun Ren & Daorong Wang

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  1. Bangquan Chen
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  5. Wenhao Yu
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Contributions

Bangquan Chen and Yue Ma organized the study data, assisted in data analysis, and wrote the first draft of the paper. Jiajie Zhou and Wenhao Yu conceptualized and designed the study. Shuyang Gao, Yapeng Yang, and Bangquan Chen collected the data and performed the statistical analysis. Jun Ren, Yong Wang and Daorong Wang revised the article. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Daorong Wang.

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Chen, B., Ma, Y., Zhou, J. et al. Predicting survival and prognosis in early-onset locally advanced colon cancer: a retrospective observational study. Int J Colorectal Dis 38, 250 (2023). https://doi.org/10.1007/s00384-023-04543-1

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