Literature DB >> 23295940

Nomogram to predict the probability of relapse in patients diagnosed with borderline ovarian tumors.

Andreas Obermair1, Amy Tang, Srinivas Kondalsamy-Chennakesavan, Hextan Ngan, Petra Zusterzeel, Michael Quinn, Jonathan Carter, Yee Leung, Monika Janda.   

Abstract

OBJECTIVE: This study aimed to develop a nomogram predicting the probability of relapse in individual patients who have surgery for borderline ovarian tumors (BOTs).
METHODS: This retrospective study included 801 patients with BOT diagnosed between 1985 and 2008 at 6 gynecologic cancer centers. We analyzed covariates that were associated with the risk of developing a recurrence by multivariate logistic regression. We identified a parsimonious model by backward stepwise logistic regression. The 5 most significant or clinically important variables associated with an increased risk of recurrence were included in the nomogram. The nomogram was internally validated.
RESULTS: Fifty-one patients developed a recurrence after a median observation period of 57 months. Age at diagnosis, the International Federation of Gynecology and Obstetrics stage, cell type, preoperative serum CA125, and type of surgery (radical vs fertility-sparing) were associated with an increased risk of recurrence and were used in the nomogram. Bootstrap-corrected concordance index was 0.67 and showed good calibration.
CONCLUSIONS: Five factors that are commonly available to clinicians treating patients with BOT were used in the development of a nomogram to predict the risk of recurrence. The nomogram will be useful to counsel patients about risk-reduction strategies to minimize the risk of recurrence or to inform patients about a very low risk of recurrence making intensive follow-up unwarranted.

Entities:  

Mesh:

Year:  2013        PMID: 23295940     DOI: 10.1097/IGC.0b013e31827b8844

Source DB:  PubMed          Journal:  Int J Gynecol Cancer        ISSN: 1048-891X            Impact factor:   3.437


  6 in total

1.  Comment on 'External multicentre validation of a nomogram predicting the risk of relapse in patients with borderline ovarian tumours'.

Authors:  A Obermair
Journal:  Br J Cancer       Date:  2014-01-21       Impact factor: 7.640

2.  Clinicopathological aspects of patients with recurrence of borderline ovarian tumors.

Authors:  Sumin Oh; Ran Kim; Yoo-Kyung Lee; Jae Weon Kim; Noh-Hyun Park; Yong-Sang Song
Journal:  Obstet Gynecol Sci       Date:  2015-03-16

3.  Response to 'Comment on external multicentre validation of a nomogram predicting the risk of relapse in patients with borderline ovarian tumours'.

Authors:  S Bendifallah; E Darai
Journal:  Br J Cancer       Date:  2014-04-22       Impact factor: 7.640

4.  Identification of factors that impact recurrence in patients with borderline ovarian tumors.

Authors:  Xi Chen; Chenyan Fang; Tao Zhu; Ping Zhang; Aijun Yu; Shihua Wang
Journal:  J Ovarian Res       Date:  2017-04-04       Impact factor: 4.234

5.  External multicentre validation of a nomogram predicting the risk of relapse in patients with borderline ovarian tumours.

Authors:  S Bendifallah; C Uzan; R Fauvet; P Morice; E Darai
Journal:  Br J Cancer       Date:  2013-10-29       Impact factor: 7.640

6.  Develop a nomogram to predict overall survival of patients with borderline ovarian tumors.

Authors:  Xiao-Qin Gong; Yan Zhang
Journal:  World J Clin Cases       Date:  2022-03-06       Impact factor: 1.337

  6 in total

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