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Article: Development of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study)

TitleDevelopment of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study)
Authors
Keywordsuterine leiomyosarcoma
prediction model
Issue Date2021
PublisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/cancers/
Citation
Cancers, 2021, v. 13 n. 10, p. article no. 2378 How to Cite?
AbstractBackground: The existing staging systems of uterine leiomyosarcoma (uLMS) cannot classify the patients into four non-overlapping prognostic groups. This study aimed to develop a prediction model to predict the three-year survival status of uLMS. Methods: In total, 201 patients with uLMS who had been treated between June 1993 and January 2014, were analyzed. Potential prognostic indicators were identified by univariate models followed by multivariate analyses. Prediction models were constructed by binomial regression with 3-year survival status as a binary outcome, and the final model was validated by internal cross-validation. Results: Nine potential parameters, including age, log tumor diameter, log mitotic count, cervical involvement, parametrial involvement, lymph node metastasis, distant metastasis, tumor circumscription and lymphovascular space invasion were identified. 110 patients had complete data to build the prediction models. Age, log tumor diameter, log mitotic count, distant metastasis, and circumscription were significantly correlated with the 3-year survival status. The final model with the lowest Akaike’s Information Criterion (117.56) was chosen and the cross validation estimated prediction accuracy was 0.745. Conclusion: We developed a prediction model for uLMS based on five readily available clinicopathologic parameters. This might provide a personalized prediction of the 3-year survival status and guide the use of adjuvant therapy, a cancer surveillance program, and future studies.
Persistent Identifierhttp://hdl.handle.net/10722/302126
ISSN
2018 Impact Factor: 6.162
2020 SCImago Journal Rankings: 1.818
PubMed Central ID

 

DC FieldValueLanguage
dc.contributor.authorTse, KY-
dc.contributor.authorWong, RWC-
dc.contributor.authorChao, A-
dc.contributor.authorUeng, SH-
dc.contributor.authorYang, LY-
dc.contributor.authorCummings, M-
dc.contributor.authorSmith, D-
dc.contributor.authorLai, CR-
dc.contributor.authorLau, HY-
dc.contributor.authorYen, MS-
dc.contributor.authorCheung, ANY-
dc.contributor.authorLeung, CKL-
dc.contributor.authorChan, KS-
dc.contributor.authorChan, ANH-
dc.contributor.authorLi, WH-
dc.contributor.authorChoi, CKM-
dc.contributor.authorPong, WM-
dc.contributor.authorHui, HF-
dc.contributor.authorYuk, JYW-
dc.contributor.authorYao, H-
dc.contributor.authorYuen, NWF-
dc.contributor.authorObermair, A-
dc.contributor.authorLai, CH-
dc.contributor.authorIp, PPC-
dc.contributor.authorNgan, HYS-
dc.date.accessioned2021-08-21T03:31:57Z-
dc.date.available2021-08-21T03:31:57Z-
dc.date.issued2021-
dc.identifier.citationCancers, 2021, v. 13 n. 10, p. article no. 2378-
dc.identifier.issn2072-6694-
dc.identifier.urihttp://hdl.handle.net/10722/302126-
dc.description.abstractBackground: The existing staging systems of uterine leiomyosarcoma (uLMS) cannot classify the patients into four non-overlapping prognostic groups. This study aimed to develop a prediction model to predict the three-year survival status of uLMS. Methods: In total, 201 patients with uLMS who had been treated between June 1993 and January 2014, were analyzed. Potential prognostic indicators were identified by univariate models followed by multivariate analyses. Prediction models were constructed by binomial regression with 3-year survival status as a binary outcome, and the final model was validated by internal cross-validation. Results: Nine potential parameters, including age, log tumor diameter, log mitotic count, cervical involvement, parametrial involvement, lymph node metastasis, distant metastasis, tumor circumscription and lymphovascular space invasion were identified. 110 patients had complete data to build the prediction models. Age, log tumor diameter, log mitotic count, distant metastasis, and circumscription were significantly correlated with the 3-year survival status. The final model with the lowest Akaike’s Information Criterion (117.56) was chosen and the cross validation estimated prediction accuracy was 0.745. Conclusion: We developed a prediction model for uLMS based on five readily available clinicopathologic parameters. This might provide a personalized prediction of the 3-year survival status and guide the use of adjuvant therapy, a cancer surveillance program, and future studies.-
dc.languageeng-
dc.publisherMDPI AG. The Journal's web site is located at http://www.mdpi.com/journal/cancers/-
dc.relation.ispartofCancers-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectuterine leiomyosarcoma-
dc.subjectprediction model-
dc.titleDevelopment of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study)-
dc.typeArticle-
dc.identifier.emailTse, KY: tseky@hku.hk-
dc.identifier.emailCheung, ANY: anycheun@hkucc.hku.hk-
dc.identifier.emailChan, KS: drkschan@hku.hk-
dc.identifier.emailIp, PPC: philipip@hku.hk-
dc.identifier.emailNgan, HYS: hysngan@hkucc.hku.hk-
dc.identifier.authorityTse, KY=rp02391-
dc.identifier.authorityCheung, ANY=rp00542-
dc.identifier.authorityIp, PPC=rp01890-
dc.identifier.authorityNgan, HYS=rp00346-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3390/cancers13102378-
dc.identifier.pmid34069227-
dc.identifier.pmcidPMC8155866-
dc.identifier.scopuseid_2-s2.0-85105735317-
dc.identifier.hkuros324208-
dc.identifier.volume13-
dc.identifier.issue10-
dc.identifier.spagearticle no. 2378-
dc.identifier.epagearticle no. 2378-
dc.publisher.placeSwitzerland-

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