Evidence map›Paper›PMID 34069227›Full record

ArticleCancers2021

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 and 15 more

Abstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

25 authors.

Ka-Yu TseDepartment of Obstetrics and Gynaecology, the University of Hong Kong, Pokfulam, Hong Kong.ORCID 0000-0001-8330-0970
Richard Wing-Cheuk WongDepartment of Pathology, Pamela Youde Nethersole Eastern Hospital, Chai Wan, Hong Kong.
Angel ChaoDepartment of Obstetrics and Gynaecology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Shir-Hwa UengDepartment of Pathology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Lan-Yan YangClinical Trial Center, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Margaret CummingsPathology Queensland, the Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia.
Deborah SmithPathology Queensland, the Royal Brisbane and Women's Hospital, Herston, QLD 4029, Australia.
Chiung-Ru LaiDepartment of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Hei-Yu LauDepartment of Obstetrics and Gynaecology, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Ming-Shyen YenDepartment of Obstetrics and Gynaecology, Taipei Veterans General Hospital, Taipei 11217, Taiwan.
Annie Nga-Yin CheungDepartment of Pathology, the University of Hong Kong, Pokfulam, Hong Kong.
Charlotte Ka-Lun LeungDepartment of Pathology, North District Hospital, Sheung Shui, Hong Kong.
Kit-Sheung ChanDepartment of Obstetrics and Gynaecology, Kwong Wah Hospital, Mong Kok, Hong Kong.
Alice Ngot-Htain ChanDepartment of Pathology, Kwong Wah Hospital, Mong Kok, Hong Kong.
Wai-Hon LiDepartment of Obstetrics and Gynaecology, Queen Elizabeth Hospital, Yau Ma Tei, Hong Kong.
Carmen Ka-Man ChoiDepartment of Obstetrics and Gynaecology, Tseung Kwan O Hospital, Tseung Kwan O, Hong Kong.
Wai-Mei PongDepartment of Pathology, Tseung Kwan O Hospital, Tseung Kwan O, Hong Kong.
Hoi-Fong HuiDepartment of Obstetrics and Gynaecology, Tuen Mun Hospital, Tuen Mun, Hong Kong.
Judy Ying-Wah YukDepartment of Obstetrics and Gynaecology, Princess Margaret Hospital, Lai Chi Kok, Hong Kong.
Hung YaoDepartment of Pathology, Princess Margaret Hospital, Lai Chi Kok, Hong Kong.
Nancy Wah-Fun YuenDepartment of Pathology, Caritas Medical Centre, Sham Shui Po, Hong Kong.
Andreas ObermairCentre for Clinical Research, University of Queensland, Herston, QLD 4029, Australia.ORCID 0000-0003-2199-1117
Chyong-Huey LaiDepartment of Obstetrics and Gynaecology, Chang Gung Memorial Hospital, Taoyuan 33305, Taiwan.
Philip Pun-Ching IpDepartment of Pathology, the University of Hong Kong, Pokfulam, Hong Kong.ORCID 0000-0002-0493-9838
Hextan Yuen-Sheung NganDepartment of Obstetrics and Gynaecology, the University of Hong Kong, Pokfulam, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsIn 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.

resultsNine 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.

conclusionWe 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.

Indexed as

prediction modeluterine leiomyosarcoma

Identifiers

PMID34069227
PMCPMC8155866

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.