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Nomograms for Predicting Overall Survival and Cancer-Specific Survival of Young Patients with Epithelial Ovarian Cancer: Analysis Based on SEER Program

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Abstract

Introduction

Currently, there is no clinical prediction model for young patients (≤ 45 years old) with epithelial ovarian cancer (EOC) based on large samples of clinical data. The purpose of this study was to construct nomograms using data extracted from the Surveillance, Epidemiology, and End Results (SEER) Program to predict the overall survival (OS) and cancer-specific survival (CSS) of patients and to further guide the choice of clinical treatment options.

Methods

Data from a total of 6376 young patients with EOC collected from 1998 to 2016 were selected from the SEER database. These patients were randomly divided (7:3) into a training cohort (n = 4465) and a validation cohort (n = 1911). Cox and least absolute shrinkage and selection operator (LASSO) analyses were used to select the prognostic factors affecting OS and CSS, and the nomograms of OS and CSS were established. The performance of the nomogram models was assessed by C-index, area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Sample were chosen from patients who underwent surgery in Shengjing Hospital to set external validation. Kaplan–Meier curves were plotted to compare survival outcomes between subgroups.

Results

Nomograms showed good predictive power and clinical practicality. The internal and external validation indicated better performance of the nomograms than the American Joint Committee on Cancer (AJCC) staging system and tumor grade system. Significant differences were observed in the survival curves of different risk subgroups.

Conclusions

We constructed predictive nomograms to evaluate the OS and CSS of young patients with EOC. The nomograms will provide an individualized evaluation of OS and CSS for suitable treatment of young patients with EOC.

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Acknowledgements

Funding

The present study was supported by 345 Talent Project of Shengjing Hospital. The Journal’s Rapid Service Fee was funded by the authors.

Authorship

All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Author Contributions

Liancheng Zhu, Jian Gao and Haoya Xu designed research. Jian Gao and Xianli Li wrote manuscript. Jian Gao, Haoya Xu, Xianli Li, Shengtan Wang, Limei Yan, Feifei Li and Liancheng Zhu involved in data collection and data statistical analysis. Liancheng Zhu provided fund support and critically reviewed the manuscript. All authors read and approved the final manuscript.

Compliance with Ethics Guidelines

The studies involving human participants were reviewed and approved by Shengjing Hospital of China Medical University and were conducted in accordance with the Declaration of Helsinki.

Disclosures

Jian Gao, Shengtan Wang, Feifei Li, Haoya Xu, Xianli Li, Limei Yan, and Liancheng Zhu confirm that they have no conflicts of interest to declare.

Data Availability

All of the material is owned by the corresponding authors. The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request (Liancheng Zhu, email: medecin@126.com).

Consent for Publication

The results/data/figures in this manuscript have not been published elsewhere, nor are they under consideration by another publisher.

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, 110004, Liaoning, China

    Jian Gao, Haoya Xu, Xianli Li, Limei Yan & Liancheng Zhu

  2. Department of Gynecology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570011, Hainan, China

    Shengtan Wang

  3. Department of Gynecology, Shandong Provincial Hospital Affiliated To Shandong First Medical University, Jinan, 250021, Shandong, China

    Feifei Li

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  1. Jian Gao
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Correspondence to Liancheng Zhu.

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Cite this article

Gao, J., Wang, S., Li, F. et al. Nomograms for Predicting Overall Survival and Cancer-Specific Survival of Young Patients with Epithelial Ovarian Cancer: Analysis Based on SEER Program. Adv Ther 39, 257–285 (2022). https://doi.org/10.1007/s12325-021-01955-9

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  • DOI: https://doi.org/10.1007/s12325-021-01955-9

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