Evidence map›Paper›PMID 40244485›Full record

ArticleDiscover oncology2025

The impact of the COVID-19 pandemic on the diagnosis, treatment, and prognosis of ovarian cancer in the United States: a retrospective cohort study based on the SEER database.

Yuqin Wang, Lele Chang, Haixin He, Xuemei Zhang, Jing Liu, Lele Zang, Li Li, Tongyu Liu, Qin Xu

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yuqin Wang *Departments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Lele Chang *Departments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Haixin He *Departments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Xuemei ZhangDepartment of Radiation Oncology, Quzhou People's Hospital, Quzhou, 323000, Zhejiang, China.
Jing LiuDepartments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Lele ZangDepartments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Li LiDepartments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China.
Tongyu Liu *Departments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China. liu_tongyu@fjmu.edu.cn.
Qin Xu *Departments of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, 350014, Fujian, China. xuqin@fjmu.edu.cn.

Funding

Fujian Cancer Hospital High-Level Talent Training Program 2024YNG09Fujian Clinical Research Center for Radiation and Therapy of Digestive, Respiratory and Genitourinary Malignancies 2021Y2014Fujian Province Science and Technology Innovation Joint Fund Project 2023Y9449Innovative Medicine Subject of Fujian Provincial Health Commission 2022CXA029Natural Science Foundation of Fujian Province 2023J011273
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has significantly impacted cancer diagnosis, treatment, and prognosis; however, its effects on ovarian cancer remain unclear.

methodsThis multicenter retrospective study utilized the Surveillance, Epidemiology, and End Results database to compare changes in the diagnosis, treatment, prognosis, and risk factors among ovarian cancer patients pre- and post-COVID-19 pandemic. Patients diagnosed before the pandemic (pre-COVID-19 group) and those diagnosed during the pandemic (post-COVID-19 group) were matched through 1:1 propensity score matching. Kaplan-Meier analysis compared cancer-specific survival (CSS) and overall survival (OS). Factors associated with survival were identified by the Cox proportional hazards model, while a competing risks model was used to determine factors associated with cancer-specific death.

resultsA total of 9,112 ovarian cancer patients were included in the study, with 4,536 diagnosed before COVID-19 and 4576 diagnosed during COVID-19. The results showed that the post-COVID-19 group presented at a more advanced stage had lower tissue differentiation, experienced more delayed treatments, and received fewer surgical interventions. Although there was no significant difference in survival between the pre-COVID-19 group and the post-COVID-19 group, patients with delayed treatment had a worse prognosis than those without delayed treatment. Additionally, we identified independent factors associated with survival outcomes, including age, tumor grade, clinical stage, pathological stage, specific histology, treatment delays, surgical intervention, and systemic therapy.

conclusionsThe survival outcomes of the pre-COVID-19 group and the post-COVID-19 group were relatively consistent, likely due to the short follow-up. Future research is necessary to continue monitoring the outcomes of patients in the post-COVID-19 group to determine its long-term impact.

Indexed as

Cancer-specific survivalCOVID-19 pandemicDelayed treatmentOvarian cancerOverall survival

Identifiers

PMID40244485
PMCPMC12006593

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.