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A novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer

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Abstract

Introduction

This study aimed to develop a prognostic nomogram for patients with gastric cancer (GC) based on the levels of programmed death 1 ligand 1 (PDL1) and carcinoembryonic antigen (CEA).

Methods

The nomogram was developed using data from a primary cohort of 247 patients who had been clinicopathologically diagnosed with GC, as well as a validation cohort of 63 patients. Furthermore, the nomogram divided the patients into three different risk groups for overall survival (OS)—the low-risk, middle-risk, and high-risk groups. Univariate and multivariate Cox hazard analyses were used to determine all of the factors included in the model. Decision curve analysis and receiver operating characteristic (ROC) curves were used to assess the accuracy of the nomogram.

Results

The Kaplan–Meier survival analysis revealed that metastasis stage, clinical stage, and CEA and PDL1 levels were predictors for progress-free survival (PFS) and OS of patients with GC. Metastasis stage, clinical stage, and CEA and PDL1 levels were found to be independent risk factors for the PFS and OS of patients with GC in a multivariate analysis, and the nomogram was based on these factors. The concordance index of the nomogram was 0.763 [95% confidence interval (CI) 0.740–0.787]. The area under the concentration–time curve of the nomogram model was 0.81 (95% CI 0.780–0.900). According to the decision curve analysis and ROC curves, the nomogram model had a higher overall net efficiency in forecasting OS than clinical stage, CEA and PDL1 levels.

Conclusion

In conclusion, we proposed a novel nomogram that integrated PDL1 and CEA, and the proposed nomogram provided more accurate and useful prognostic predictions for patients with GC.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Not applicable.

Funding

This work was supported by the National Natural Science Foundation of China (Grant No.82003268); the Guangdong Province Natural Science Foundation (Grant No. 2018A030310260); the Sci-Tech Foundation of Guangdong Province (Grant No.2018YJ021); the Medical Science Foundation of Guangdong Province (Grant No.A2016023); the Natural science Foundation of Guangdong Province (Grant No.2016A030313280).

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Author notes

  1. Tian Di, Yue-rong Lai and Qiu-yun Luo have contributed equally to the manuscript.

Authors and Affiliations

  1. Department of Clinical Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China

    Tian Di, Yue-rong Lai, Qiu-yun Luo, Zhi-gang Chen, Yong Du, Run-duan Lin, Li-qiong Yang, Lin Zhang & Jian Sun

  2. Department of Experimental Research, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China

    Qiu-yun Luo & Lin Zhang

  3. Department of Clinical Laboratory, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China

    Run-duan Lin & Lin Zhang

  4. Department of Clinical Research, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China

    Tian Di & Li-qiong Yang

  5. Department of Gynecologic Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China

    Yue-rong Lai

  6. The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen, 518033, Guangdong, China

    Qiu-yun Luo

  7. Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China

    Zhi-gang Chen

  8. Department of Clinical Research, The Third Affiliated Hospital, Sun Yat-Sen University, Guangdong, 510630, China

    Jian Sun

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Contributions

Conceptualization: TD, QYL. Methodology: TD, QYL. Formal analysis and investigation: TD, QYL, YRL, ZGC, YD, RDL. Writing—original draft preparation: TD. Writing—review and editing: TD, QYL. Funding acquisition: JS, LZ. Resources: JS, LZ. Supervision: JS, LZ.

Corresponding authors

Correspondence to Lin Zhang or Jian Sun.

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The studies involving human participants were reviewed and approved by the Ethics Committee of The Sun Yat-sen University Cancer Center.

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Di, T., Lai, Yr., Luo, Qy. et al. A novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer. Clin Transl Oncol 25, 2472–2486 (2023). https://doi.org/10.1007/s12094-023-03132-6

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  • DOI: https://doi.org/10.1007/s12094-023-03132-6

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