ArticleJournal of Korean medical science2021
Sarcopenia as a Predictor of Prognosis in Early Stage Ovarian Cancer.
Article in Journal of Korean medical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 20 citations in OpenAlex.
- Prevalence and Prognostic Significance of Sarcopenia in Gynecologic Oncology: A Systematic Review and Meta-Analysis.Journal of cachexia, sarcopenia and muscle · 2025Pooled it
- Low L3 skeletal muscle index associated with the clinicopathological characteristics and prognosis of ovarian cancer: a meta-analysis.Journal of cachexia, sarcopenia and muscle · 2023Pooled it
- Effect of exercise on body composition among women with ovarian cancer.Journal of cancer survivorship : research and practice · 2023Trial
- Evaluation of Psoas Muscle Index for Prognosis Prediction in Patients with Ovarian Cancer: A Retrospective 2-Center Cohort Study.Medical journal of the Islamic Republic of Iran · 2025Article
- A sarcopenia screening test predicts mortality among hospitalized cancer patients.Physiological reports · 2024Article
- Mechanisms of Ovarian Cancer-Associated Cachexia.Endocrinology · 2023Review
- Review
- Association between sarcopenia and survival in patients with gynecologic cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Article
- Progress in Applicability of Scoring Systems Based on Nutritional and Inflammatory Parameters for Ovarian Cancer.Frontiers in nutrition · 2022Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo identify sarcopenia as a predictive prognostic factor of ovarian cancer in terms of survival outcome in patients with early-stage ovarian cancer.
methodsData of Konkuk University Medical Center from March 2002 to December 2017 were reviewed retrospectively. Eighty-two patients who underwent surgery due to early-stage (International Federation of Gynecology and Obstetrics stage I/II) ovarian cancer and had computed tomography (CT) images taken at the initial diagnosis were included. The initial CT scan images were analyzed with SliceOmatic software (TomoVision). A sarcopenia cutoff value was defined as a skeletal muscle index of ≤ 38.7 cm²/m². Overall survival (OS) times were compared according to the existence of sarcopenia, and subgroup analyses were performed.
resultsA Kaplan-Meier analysis showed a significant survival disadvantage for patients with early-stage ovarian cancer when they had sarcopenia (
conclusionThis study demonstrated that sarcopenia was predictive of OS in patients with early-stage ovarian cancer. Further prospective studies with a larger number of patients are warranted to determine the extent to which sarcopenia can be used as a prognostic factor in ovarian cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.