|
1000
|
Abstract/Summary
|
-
Background!#!Thymic epithelial tumors are rare neoplasias. There are no internationally accepted standards to treat this complex oncological disease. The studies on which our knowledge is based frequently have methodological weaknesses. If the tumor is resectable, complete surgical excision is currently the first-line therapy. Thymic epithelial tumors respond to radiation. The therapeutic benefit of adjuvant radiotherapy depends on tumor stage. To validate and improve treatment, we share our current experiences with clinical management and surgical intervention.!##!Methods!#!This single-center retrospective study included 40 patients with primarily resectable thymic epithelial tumors who underwent resection with curative intent. The survival data was collected and presented according to Kaplan-Meier. Single- and multiple predictor survival analyses were carried out using the log-rank test and Cox proportional hazards model.!##!Results!#!Single-predictor survival analysis showed survival to be dependent on the Masaoka-Koga classification, WHO histological classification, resection status, surgical technique, and Clavien-Dindo grade for postoperative complications. Multiple predictor analysis confirms that the Masaoka-Koga stage (HR = 4.876, P = 0.032) and Clavien-Dindo grade (HR = 4.904, P = 0.011) are independent prognostic factors for survival.!##!Conclusion!#!In addition to the Masaoka stage, the occurrence of severe postoperative complications represents an independent prognostic factor. Given the tumor's sensitivity to radiation, the use of neoadjuvant radiotherapy can be considered to downstage Masaoka-Koga stages III and higher, thus reducing surgical risks. Further prospective multicenter studies are urgently needed.
|
|
1000
|
Hinweis
|
-
DeepGreen-ID: 279211344f794843a768fe35ab850e4f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
|
