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Incidence of and risk factors associated with lung metastases in newly diagnosed epithelial ovarian cancer with a look on prognosis after diagnosis: a population-based cohort study of the SEER database

Abstract

Purpose

Patients with lung metastases (LM) from epithelial ovarian cancer (EOC) (EOCLM) usually have a poor prognosis. However, there is no consensus on the optimal management of these patients. In this study, we aimed to take a look at the incidence of LM and factors associated with its occurrence as well as the prognosis in newly diagnosed EOC with LM on a population level.

Methods

EOC patients diagnosed between the years 2010 and 2016 were identified from the Surveillance, Epidemiology, and End Results (SEER) program database. Multivariable logistic regression and multivariable Cox regression were used to investigate the factors that could predict the occurrence of and prognosis after diagnosis of EOC with LM.

Results

Of the 33,418 qualified EOC patients, 2240 (6.7%) were noted to have LMs at the time of EOC diagnosis. Higher T stage, N1 stage, advanced tumor grade, and elevated cancer antigen-125 levels were found to be associated with a higher risk of having LM at the time of EOC diagnosis. The median survival time after diagnosis with EOCLM was found to be 13.0 months (interquartile range: 3.0–34.0 months). Being unmarried and having mucinous histology were both associated with increased all-cause death risk from EOCLM. However, the primary tumor originated from the midline of ovaries, surgical management, and whether patient received chemotherapy or not predicted improved overall survival. The median survival time of patients was significantly longer for EOCLM cases managed surgically (31.0 months) versus those who did not have surgery (4.0 months), as well as EOCLM cases received chemotherapy (23.0 months) versus those who did not have chemotherapy (2.0 months).

Conclusion

This retrospective cohort study showed that de novo LM was infrequent in EOC patients overall and when present predicted poor prognosis. The findings can be potentially useful in formulating for follow-up strategies, screening tools, and personalized interventions.

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Availability of data and materials

The data analyzed in the present study can be obtained from the SEER database using SEER*Stat software (https://seer.cancer.gov/data/) and can also be obtained by emailing the corresponding author.

Code availability

The code can be obtained by contacting the corresponding author.

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Funding

This study was funded by the Postgraduate Research & Practice Innovation Program of Harbin Medical University (YJSKYCX2019-72HYD) and National Natural Science Foundation of China (81773551).

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Authors

Contributions

XJQ protocol/project development, data analysis, manuscript writing and editing. IH data collection and management, data analysis, manuscript editing. WLY data analysis, manuscript correction and revision. DK protocol/project development, manuscript editing. ZL data analysis, manuscript correction and revision. ZKQ data analysis, manuscript correction. ZLC data analysis, manuscript correction. XZY data analysis, manuscript editing. LK protocol/project development, manuscript editing.

Corresponding author

Correspondence to Kang Li.

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Conflict of interest

The authors declare that they have no conflict of interest.

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All authors reviewed and approved the final version of the manuscript.

Ethics approval and consent to participate

The SEER database was publicly available and all patient-related information has been de-identified. Hence, we did not require Institutional Review Board approval or patient informed consent.

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Xu, J., Hussain, I., Wang, L. et al. Incidence of and risk factors associated with lung metastases in newly diagnosed epithelial ovarian cancer with a look on prognosis after diagnosis: a population-based cohort study of the SEER database. Arch Gynecol Obstet 304, 1007–1020 (2021). https://doi.org/10.1007/s00404-021-05997-w

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Keywords

  • Epithelial ovarian cancer
  • Lung metastases
  • SEER
  • Incidence
  • Risk factors
  • Prognosis