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.
- Borderline ovarian tumors
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This study was partly funded by the Royal Brisbane and Women’s Hospital Research Foundation, Brisbane, Australia.
The authors declare no conflicts of interest.
Article Category: Cancer therapy
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