Literature DB >> 31796203

Clinical calculator predictive of chemotherapy benefit in stage 1A uterine papillary serous cancers.

D P Mysona1, L K H Tran2, P M H Tran2, P A Gehrig3, L Van Le3, S Ghamande2, B J Rungruang2, J Java4, A K Mann5, J Liao5, D S Kapp6, Bruno Dos Santos7, J X She8, J K Chan9.   

Abstract

OBJECTIVE: Determine the utility of a clinical calculator to predict the benefit of chemotherapy in stage IA uterine papillary serous cancer (UPSC). PATIENTS AND METHODS: Data were collected from NCDB from years 2010-2014. Based on demographic and surgical characteristics, a clinical score was developed using the random survival forest machine learning algorithm.
RESULTS: Of 1,751 patients with stage IA UPSC, 1,012 (58%) received chemotherapy and 739 (42%) did not. Older age (HR 1.06), comorbidities (HR 1.31), larger tumor size (HR 1.27), lymphovascular invasion (HR 1.86), positive peritoneal cytology (HR 2.62), no pelvic lymph node dissection (HR 1.51), and no chemotherapy (HR 2.16) were associated with poorer prognosis. Compared to no chemotherapy, patients who underwent chemotherapy had a 5-year overall survival of 80% vs. 67%. To better delineate those who may derive more benefit from chemotherapy, we designed a clinical calculator capable of dividing patients into low, moderate, and high-risk groups with associated 5-year OS of 86%, 73%, and 53%, respectively. Using the calculator to assess the relative benefit of chemotherapy in each risk group, chemotherapy improved the 5-year OS in the high (42% to 64%; p < 0.001) and moderate risk group (66% to 79%; p < 0.001) but did not benefit the low risk group (84% to 87%; p = 0.29).
CONCLUSION: Our results suggest a clinical calculator is useful for counseling and personalizing chemotherapy for stage IA UPSC. Published by Elsevier Inc.

Entities:  

Keywords:  Chemotherapy; Machine learning; Personalized medicine; Uterine papillary serous

Mesh:

Year:  2019        PMID: 31796203     DOI: 10.1016/j.ygyno.2019.10.017

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  3 in total

1.  Malignant peritoneal cytology and increased mortality risk in stage I non-endometrioid endometrial cancer.

Authors:  Koji Matsuo; David J Nusbaum; Shinya Matsuzaki; Erica J Chang; Lynda D Roman; Jason D Wright; Philipp Harter; Maximilian Klar
Journal:  Gynecol Oncol       Date:  2020-07-18       Impact factor: 5.482

2.  Exploratory study on classification of diabetes mellitus through a combined Random Forest Classifier.

Authors:  Xuchun Wang; Mengmeng Zhai; Zeping Ren; Hao Ren; Meichen Li; Dichen Quan; Limin Chen; Lixia Qiu
Journal:  BMC Med Inform Decis Mak       Date:  2021-03-20       Impact factor: 2.796

3.  Evaluation of a Patient With Non-Myoinvasive Uterine Serous Carcinoma Confined to a Polyp and Positive Peritoneal Washings With Somatic ARHGAP35 and KRAS Mutations.

Authors:  Sierra M Silverwood; Amir Lagstein; John I Risinger; Gregory Gressel
Journal:  Cureus       Date:  2022-07-08
  3 in total

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