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Gynecol Oncol. 2015 Sep;138(3):554-9. doi: 10.1016/j.ygyno.2015.06.010. Epub 2015 Jun 17.

Incorporation of postoperative CT data into clinical models to predict 5-year overall and recurrence free survival after primary cytoreductive surgery for advanced ovarian cancer.

Author information

1
Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA; Department of Radiology and Nuclear Medicine, University Hospital Zurich, University of Zurich, 8091 Zurich, Switzerland. Electronic address: Irene.burger@usz.ch.
2
Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA.
3
Department of Radiology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA.
4
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA.
5
Department of Gynecology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA.

Abstract

PURPOSE:

The use of multivariable clinical models to assess postoperative prognosis in ovarian cancer increased. All published models incorporate surgical debulking. However, postoperative CT can detect residual disease (CT-RD) in 40% of optimally resected patients. The aim of our study was to investigate the added value of incorporating CT-RD evaluation into clinical models for assessment of overall survival (OS) and progression free survival (PFS) in patients after primary cytoreductive surgery (PCS).

METHODS:

212 women with PCS for advanced ovarian cancer between 01/1997 and 12/2011, and a contrast enhanced abdominal CT 1-7 weeks after surgery were included in this IRB approved retrospective study. Two radiologists blinded to clinical data, evaluated all CT for the presence of CT-RD, and Cohen's kappa assessed agreement. Cox proportional hazards regression with stepwise selection was used to develop OS and PFS models, with CT-RD incorporated afterwards. Model fit was assessed with bootstrapped Concordance Probability Estimates (CPE), accounting for over-fitting bias by correcting the initial estimate after repeated subsampling.

RESULTS:

Readers agreed on the majority of cases (179/212, k=0.68). For OS and PFS, CT-RD was significant after adjusting for clinical factors with a CPE 0.663 (p=0.0264) and 0.649 (p=0.0008). CT-RD was detected in 37% of patients assessed as optimally debulked (RD<1cm) and increased the risk of death (HR: 1.58, 95% CI: 1.06-2.37%).

CONCLUSION:

CT-RD is a significant predictor after adjusting for clinical factors for both OS and PFS. Incorporating CT-RD into the clinical model improved the prediction of OS and PFS in patients after PCS for advanced ovarian cancer.

KEYWORDS:

Debulking; Ovarian carcinoma; Residual disease; Survival

PMID:
26093061
PMCID:
PMC4989241
DOI:
10.1016/j.ygyno.2015.06.010
[Indexed for MEDLINE]
Free PMC Article

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