Prognostic Significance of preoperative serum CA125, CA19-9, CA72-4, CEA, and AFP in Patients with Endometrial cancer

  1. Zi-hao Wang
  2. Yun-zheng Zhang
  3. Shu-wen Ge
  4. Luhe-Shan
  5. Bo Wang
  6. Zi-yu Zhang
  7. Qi-jun Wu
  8. Xiao-xin Ma

  • Curated by eLife

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    eLife assessment

    This study presents a valuable finding on prognostic values of serum CA125, CEA, and AFP for predicting patient outcomes of endometrial cancer. The evidence supporting the claims of the authors is solid, although inclusion of detailed discussion of present results with prior documented findings would have strengthened the study. The work will be of interest to scientists working on endometrial cancer.

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Abstract

Objective

To determine preoperative serum CA125, CA19-9, CA72-4, CEA, and AFP with prognostic value, and to establish a risk score based on CA125, CEA, AFP levels for predicting the overall survival (OS) and progression-free survival (PFS) of endometrial cancer (EC) patients.

Methods

A retrospective cohort study with 2081 EC patients was conducted at Shengjing Hospital of China Medical University. Patient baseline information, tumor characteristics, and data on five serum biomarkers (CA125, CA19-9, CA72-4, CEA, and AFP) were collected. Hazard ratios (HRs) and 95% confidence intervals (CIs) were determined using univariate or multivariate Cox proportional hazard models. log-rank test and Kaplan-Meier analysis were used to compared survival, Data were randomly divided into a training cohort (50%, N = 1041) and an external validation cohort (50%, n = 1040). the least absolute shrinkage and selection operator (Lasso)-Cox regression model was used to screen the independent factors for establishing risk score. And develop nomograms for survival rate prediction.

Results

Multivariate analysis showed Elevated CA125 (P<0.0001) AFP (P <0.0001) and CEA(P=0.037) were identified as independent biomarkers for PFS. Increased CA125 (P = 0.003) AFP (P <0.0001) and CEA(P=0.014) were independent factors associated with OS. CA125, AFP and CEA were thus incorporated in an innovative Risk score (RS) by Lasso-Cox regression model, The RS was also an independent indicator for PFS (P<0.0001) and OS (P<0.0001). Furthermore, we developed and validated nomogram based on Cox regression models. The discriminative ability and calibration of the nomograms revealed good predictive ability, as indicated by the calibration plots.

Conclusion

This study suggests that the risk score based on preoperative serum levels of CA125, CEA, and AFP was prognostic biomarkers for predicting progression-free survival and overall survival for EC patients. Nomograms based on the RS and clinicopathological features accurately predict Prognosis of EC patients.

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  1. eLife

    Author response:

    Reviewer #2 (Public Review):

    (1) The groups of patients with endometrial cancer in the manuscript are classified according to age greater than/less than 60. Please explain why 60 years old is chosen as the boundary value of age.

    Thanks for your Recommendation. We have modified the discussion section of the manuscript in accordance with your suggestion.

    (2) Among the patients with endometrial cancer selected in the manuscript, AFP outliers accounted for a relatively small proportion. The authors chose the clinical detection outliers of CA-125, CA19-9, AFP and CEA as the dividing line, instead of re-selecting the optimal cut-off value in thispopulation, which should be classified and the prognostic value explored.

    Thanks for your Recommendation. We have modified the discussion section of the manuscript in accordance with your suggestion.

    (3) In cancer research, stage is an important prognostic factor to guide the treatment of patients in clinical work. Patients with different stages of endometrial cancer have obvious prognostic differences. The authors constructed a new prognostic risk score based on serum level of AFP， CEA andCA125, the prognostic value of the risk score should be validated in patients with endometrial cancer at different stages。

    Thanks for your Recommendation. We have modified the discussion section of the manuscript in accordance with your suggestion.

  2. eLife

    eLife assessment

    This study presents a valuable finding on prognostic values of serum CA125, CEA, and AFP for predicting patient outcomes of endometrial cancer. The evidence supporting the claims of the authors is solid, although inclusion of detailed discussion of present results with prior documented findings would have strengthened the study. The work will be of interest to scientists working on endometrial cancer.

  3. eLife

    Reviewer #1 (Public Review):

    Article strengths:

    (1) Detailed data: The authors provided a large amount of clinical data as support, making the analysis results more persuasive and credible.
    (2) Scientific method: Appropriate statistical methods were used to analyze the data, which can accurately reflect the internal laws and trends of the data.
    (3) Clear conclusions: The conclusions drawn in the article are clear and explicit, easy for readers to understand and accept.
    (4) High practicality: The research results have important guiding significance for obstetrics and gynecology clinical practice, helping to improve patient treatment outcomes and quality of life.

    Article weaknesses:

    Limitations of research methods: Although the authors used statistical methods to analyze the data, they may be limited by factors such as data sources and sample size, leading to some limitations in the research results. It is recommended that the authors further expand the data sources and increase the sample size in subsequent studies to improve the accuracy and reliability of the research.

  4. eLife

    Reviewer #2 (Public Review):

    This prospective study advances our understanding of the predictive value of preoperative serum CA125, CA19-9, CA72-4, CEA, and AFP in endometrial cancer. The evidence supporting the conclusions is convincing with rigorous analysis of the association between prognostic values of several serum markers with the clinical data of endometrial cancer patients. However, there are a few areas in which the article may be improved through further validation of the prognostic value of the risk score in patients with endometrial cancer at different stages. Moreover, the authors should provide a more detailed explanation of the choice of statistical methods in the manuscript. The work will be of broad interest to clinicians, medical researchers and scientists working in endometrial cancer.

    (1) The groups of patients with endometrial cancer in the manuscript are classified according to age greater than/less than 60. Please explain why 60 years old is chosen as the boundary value of age.
    (2) Among the patients with endometrial cancer selected in the manuscript, AFP outliers accounted for a relatively small proportion. The authors chose the clinical detection outliers of CA-125, CA19-9, AFP and CEA as the dividing line, instead of re-selecting the optimal cut-off value in this population, which should be classified and the prognostic value explored.
    (3) In cancer research, stage is an important prognostic factor to guide the treatment of patients in clinical work. Patients with different stages of endometrial cancer have obvious prognostic differences. The authors constructed a new prognostic risk score based on serum level of AFP， CEA and CA125, the prognostic value of the risk score should be validated in patients with endometrial cancer at different stages。

  5. eLife

    Reviewer #3 (Public Review):

    The authors of this study aimed to enhance the prognostic assessment of endometrial cancer (EC) by identifying and validating a set of serum tumor markers (CA125, CEA, and AFP) that could reliably predict progression-free survival (PFS) and overall survival (OS) in patients. By employing a robust methodology that included the use of LASSO Cox regression analysis to construct a predictive model, the study sought to provide a more nuanced tool for clinical decision-making in the management of EC.

    Major Strengths:

    Methodological Rigor: The study's use of advanced statistical methods to analyze a large dataset of EC patients stands out. The inclusion of a validation cohort enhances the credibility of the prognostic model developed.
    Clinical Relevance: The identification of CA125, CEA, and AFP as independent prognostic factors and the creation of a risk score based on these markers offer valuable tools for clinicians. The predictive accuracy of this model could significantly impact patient management and treatment planning.
    Weaknesses:

    Generalizability: The study is based on a cohort from a single institution, which may limit the applicability of the findings across different populations and healthcare settings.
    Loss to Follow-Up: As acknowledged by the authors, the loss to follow-up of some patients introduces a potential source of bias, possibly affecting the study's conclusions.
    Achievement of Aims and Support for Conclusions:

    The study successfully achieves its aim of developing a prognostic model for EC that integrates serum levels of CA125, CEA, and AFP. The evidence presented supports the authors' conclusions that this model is a robust tool for predicting patient outcomes, evidenced by its performance in both the training and validation cohorts.

    Impact and Utility:

    This work is poised to make a significant contribution to the field of gynecological oncology, particularly in the management of endometrial cancer. The study's findings provide a practical approach to stratifying patients based on their risk, which could be instrumental in tailoring individualized treatment plans. Moreover, the model's ability to predict PFS and OS with considerable accuracy offers a promising avenue for further research and application in clinical settings.

    Additional Context:

    Understanding the role of tumor markers in cancer prognosis is a rapidly evolving area of oncology research. This study's focus on combining multiple serum markers into a comprehensive risk score model represents a significant step forward in the quest for more personalized cancer care. Future studies could expand on this work by exploring the integration of such markers with other clinical and molecular data to further refine prognostic models.

  6. Version published to 10.1101/2024.01.23.576857v1 on bioRxiv