Ovarian Cancer: An Evidence-Based, Easy-to-Use Prediction Rule to Optimize the Use of Follow-up Chest CT

• Published in: Journal of the American College of Radiology Vol. 14; no. 4; pp. 499 - 508
• Main Authors: Shinagare, Atul B., MD, Suh, Chong Hyun, MD, Kim, Kyung Won, MD, PhD, Somarouthu, Bhanusupriya, MD, Van den Abbeele, Annick D., MD, Ramaiya, Nikhil H., MD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-04-2017
• Subjects: Adult; chest CT; Evidence-Based Medicine; Female; Humans; metastatic spread; Middle Aged; Ovarian cancer; Ovarian Neoplasms - diagnostic imaging; Ovarian Neoplasms - pathology; prediction rule; Predictive Value of Tests; Radiology; Retrospective Studies; Sensitivity and Specificity; thoracic metastases; Thoracic Neoplasms - diagnostic imaging; Thoracic Neoplasms - secondary; Tomography, X-Ray Computed; metastatic spread; thoracic metastases; prediction rule; Ovarian cancer; chest CT
• ISSN: 1546-1440; 1558-349X
• DOI: 10.1016/j.jacr.2016.08.010

Abstract Purpose To create and validate an evidence-based prediction rule to optimize use of follow-up chest CT for ovarian cancer. Methods In this Institutional Review Board–approved retrospective study performed at two academic medical centers, electronic medical records from January through December 2013 at center 1 (USA) and January 2012 through December 2013 at center 2 (South Korea) were searched to identify consecutive chest CTs performed within 5 years of initial cytoreductive surgery in patients with pathologically proven ovarian cancer. Three separate study cohorts were created: cohort 1, 316 CTs (in 150 patients) with high-grade serous ovarian cancer (HGSC) from center 1; cohort 2, 374 CTs (81 patients) with HGSC from center 2; and cohort 3, 87 CTs (56 patients) with non-HGSC histologies from center 1. A radiologist blinded to outcome of CT, using a prediction rule that utilized previously available information, categorized each CT into “high-risk” (stage 4 at presentation and/or preexisting abdominal disease [disease below diaphragmatic dome, visualized on abdominal CT]) or “low-risk” (neither of above). A blinded radiologist then reviewed chest CTs in random order to record thoracic metastases above the diaphragmatic dome, and outcome was compared with prediction rule risk category. Results Among the three cohorts and in the total population, the prediction rule identified 94 of 316 (30%), 170 of 374 (45%), 53 of 87 (61%), and 317 of 777 (41%) CTs as “low-risk,” respectively. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were as follows: cohort 1: 95%, 35%, 24%, 97%, 1.46, 0.14; cohort 2: 88%, 53%, 29%, 95%, 1.87, 0.22; cohort 3: 88%, 66%, 21%, 98%, 2.59, 0.18; total population: 91%, 47%, 26%, 96%, 1.72, 0.19. False-negative rate in the three cohorts and in total population was 3 of 94 (3%), 8 of 170 (5%), 1 of 53 (2%), and 12 of 317 (4%); however, in each of these cases there was concurrent new abdominal disease. Conclusions The easy-to-use prediction rule helps avoid unnecessary chest CTs in patients with ovarian cancer with high sensitivity and negative predictive value, and with minimal risk of missing thoracoabdominal metastases.