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Researchers develop model to predict distant recurrence of cervical cancer
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Researchers have developed a model that they believe may help predict the risk for recurrence in women with locally advanced cervical cancer.
Although strides have been made in recent years in the treatment of cervical cancer, there is still progress to be made in identifying patients who will be at the greatest risk for distant recurrence in locally advanced cancer.
To help clarify this, the Korean Gynecologic Oncology Group undertook a retrospective study to develop a predictive model for distant recurrence. They hypothesized that this model would be useful in the design of clinical trials.
Researchers enrolled women from five institutions between 2001 and 2009. Data from women at three institutions were included in the “model development” cohort (n=434) and data from the other two institutions were included in the validation cohort (n=161).
Using their model, the researchers were able to identify four statistically significant predictors of distant recurrence: positive pelvic and para-aortic nodes detected by PET, a nonsquamous cell histology, and pretreatment serum squamous cell carcinoma antigen.
The researchers were able to validate these predictors in their external validation cohort, which had good discrimination and calibration with a bootstrap-adjusted concordance index of 0.70. Finally, the researchers adapted these data into a Web-based nomogram for external use.
“Our model will allow the selection of a patient population at high risk for distant recurrence and thus will facilitate the design of clinical trials for systemic chemotherapy in locally advanced cervical cancer,” the researchers wrote.
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Kang S. J Clin Oncol. 2012;doi:10.1200/JCO.2011.37.5923.
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