ArticleJournal of oncology2020
Prognostic Factors in Patients with Rhabdomyosarcoma Using Competing-Risks Analysis: A Study of Cases in the SEER Database.
Article in Journal of oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Sarcomas in Adolescents and Young Adults.Current oncology reports · 2026Review
- Ovarian Rhabdomyosarcoma in Children.Cureus · 2025Article
- Analysis of clinicopathological characteristics in rhabdomyosarcoma and identification of risk factors for metastasis to the lung, bone, liver, and brain: a population-based cohort study.Discover oncology · 2025Article
- Impact of prolonged surgical waiting time on cancer-specific mortality in stage I-II pancreatic ductal adenocarcinoma patients who received radical resection.Journal of gastrointestinal oncology · 2024Article
- The Other Site of Rhabdomyosarcoma.Cancer medicine · 2024Article
- Prediction of death probability in adenocarcinoma of the transverse colon: competing-risk nomograms based on 21,469 patients.Journal of cancer research and clinical oncology · 2023Article
- Orbital rhabdomyosarcoma in a 19-year-old male patient: A case report and literature review.Radiology case reports · 2023Article
- Baseline Characteristics, Prognostic Factors, and Treatment Outcomes for Adult Patients With Rhabdomyosarcoma (RMS).Cureus · 2022Article
- A Web-Based Prognostic Model for Pediatric Genitourinary Rhabdomyosarcoma: Analysis of Population-Based Cohort With External Validation.Frontiers in public health · 2022Article
- Methylation profiling reveals novel molecular classes of rhabdomyosarcoma.Scientific reports · 2021Article
- Perianal Rhabdomyosarcoma Mimicking Perianal Abscess: Case Report and Literature Review.Case reports in oncologyArticle
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8 authors.
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Abstract
backgroundRhabdomyosarcoma (RMS) is a rare malignant soft-tissue sarcoma characterized by a poor outcome and unclear prognostic factors. This study applied a competing-risks analysis using data from the Surveillance, Epidemiology, and End Results (SEER) database to RMS patients, with the aim of identifying more accurate prognostic factors.
methodsData of all patients with RMS during 1986-2015 were extracted from the SEER database. We used the competing-risks approach to calculate the cumulative incidence function (CIF) for death due to rhabdomyosarcoma (DTR) and death from other causes (DOC) at each time point. The Fine-Gray subdistribution proportional-hazards model was then applied in univariate and multivariate analyses to determine how the CIF differs between groups and to identify independent prognostic factors. The potential prognostic factors were analyzed using the competing-risks analysis methods in SAS and R statistical software.
resultsThis study included 3399 patients with RMS. The 5-year cumulative incidence rates of DTR and DOC after an RMS diagnosis were 39.9% and 8.7%, respectively. The multivariate analysis indicated that age, year of diagnosis, race, primary site, historic stage, tumor size, histology subtype, and surgery status significantly affected the probability of DTR and were independent prognostic factors in patients with RMS. A nomogram model was constructed based on multivariate models for DTR and DOC. The performances of the two models were validated by calibration and discrimination, with C-index values of 0.758 and 0.670, respectively.
conclusionsA prognostic nomogram model based on the competing-risks model has been established for predicting the probability of death in patients with RMS. This validated prognostic model may be useful when choosing treatment strategies and for predicting survival.
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