Development of a multi-institutional prediction model for three-year survival status in patients with uterine leiomyosarcoma (Agog11-022/qcgc1302 study)

Ka Yu Tse*, Richard Wing Cheuk Wong, Angel Chao, Shir Hwa Ueng, Lan Yan Yang, Margaret Cummings, Deborah Smith, Chiung Ru Lai, Hei Yu Lau, Ming Shyen Yen, Annie Nga Yin Cheung, Charlotte Ka Lun Leung, Kit Sheung Chan, Alice Ngot Htain Chan, Wai Hon Li, Carmen Ka Man Choi, Wai Mei Pong, Hoi Fong Hui, Judy Ying Wah Yuk, Hung YaoNancy Wah Fun Yuen, Andreas Obermair, Chyong Huey Lai, Philip Pun Ching Ip*, Hextan Yuen Sheung Ngan

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

3 Scopus citations

Abstract

Background: 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. Con-clusion: 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.

Original languageEnglish
Article number2378
JournalCancers
Volume13
Issue number10
DOIs
StatePublished - 02 05 2021

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Prediction model
  • Uterine leiomyosarcoma

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