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Tytuł:
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Development of a Multi-Institutional Prediction Model for Three-Year Survival Status in Patients with Uterine Leiomyosarcoma (AGOG11-022/QCGC1302 Study).
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Autorzy:
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Tse KY; Department of Obstetrics and Gynaecology, the University of Hong Kong, Pokfulam, Hong Kong.
Wong RW; Department of Pathology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong.
Chao A; Department of Obstetrics and Gynaecology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.; Linkou Medical Center, Chang Gung University, Taoyuan 33305, Taiwan.
Ueng SH; Department of Pathology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Yang LY; Clinical Trial Center, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Cummings M; Pathology Queensland, the Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia.; Centre for Clinical Research, University of Queensland, Herston, QLD 4029, Australia.
Smith D; Pathology Queensland, the Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia.; Centre for Clinical Research, University of Queensland, Herston, QLD 4029, Australia.
Lai CR; Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Lau HY; Department of Obstetrics and Gynaecology, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Yen MS; Department of Obstetrics and Gynaecology, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Cheung AN; Department of Pathology, the University of Hong Kong, Pokfulam, Hong Kong.
Leung CK; Department of Pathology, North District Hospital, Sheung Shui, Hong Kong.
Chan KS; Department of Obstetrics and Gynaecology, Kwong Wah Hospital, Mong Kok, Hong Kong.
Chan AN; Department of Pathology, Kwong Wah Hospital, Mong Kok, Hong Kong.
Li WH; Department of Obstetrics and Gynaecology, Queen Elizabeth Hospital, Yau Ma Tei, Hong Kong.
Choi CK; Department of Obstetrics and Gynaecology, Tseung Kwan O Hospital, Tseung Kwan O, Hong Kong.
Pong WM; Department of Pathology, Tseung Kwan O Hospital, Tseung Kwan O, Hong Kong.
Hui HF; Department of Obstetrics and Gynaecology, Tuen Mun Hospital, Tuen Mun, Hong Kong.
Yuk JY; Department of Obstetrics and Gynaecology, Princess Margaret Hospital, Lai Chi Kok, Hong Kong.
Yao H; Department of Pathology, Princess Margaret Hospital, Lai Chi Kok, Hong Kong.
Yuen NW; Department of Pathology, Caritas Medical Centre, Sham Shui Po, Hong Kong.
Obermair A; Centre for Clinical Research, University of Queensland, Herston, QLD 4029, Australia.; Queensland Centre for Gynaecological Cancer, Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia.
Lai CH; Department of Obstetrics and Gynaecology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.; Linkou Medical Center, Chang Gung University, Taoyuan 33305, Taiwan.
Ip PP; Department of Pathology, the University of Hong Kong, Pokfulam, Hong Kong.
Ngan HY; Department of Obstetrics and Gynaecology, the University of Hong Kong, Pokfulam, Hong Kong.
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Źródło:
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Cancers [Cancers (Basel)] 2021 May 14; Vol. 13 (10). Date of Electronic Publication: 2021 May 14.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: Basel, Switzerland : MDPI
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Contributed Indexing:
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Keywords: prediction model; uterine leiomyosarcoma
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Entry Date(s):
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Date Created: 20210602 Latest Revision: 20210605
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Update Code:
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20240104
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PubMed Central ID:
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PMC8155866
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DOI:
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10.3390/cancers13102378
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PMID:
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34069227
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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.
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.
