A preoperative nomogram incorporating CT to predict the probability of ovarian clear cell carcinoma Journal Article
| Authors: | Horvat, N.; Causa Andrieu, P.; Meier, A.; Ji, X.; Lakhman, Y.; Soslow, R.; Allison, D.; Gangai, N.; Rodriguez, L.; Kattan, M. W.; Chi, D. S.; Hricak, H. |
| Article Title: | A preoperative nomogram incorporating CT to predict the probability of ovarian clear cell carcinoma |
| Abstract: | Objectives: To evaluate clinical, laboratory, and radiological variables from preoperative contrast-enhanced computed tomography (CECT) for their ability to distinguish ovarian clear cell carcinoma (OCCC) from non-OCCC and to develop a nomogram to preoperatively predict the probability of OCCC. Methods: This IRB-approved, retrospective study included consecutive patients who underwent surgery for an ovarian tumor from 1/1/2000 to 12/31/2016 and CECT of the abdomen and pelvis ≤90 days before primary debulking surgery. Using a standardized form, two experienced oncologic radiologists independently analyzed imaging features and provided a subjective 5-point impression of the probability of the histological diagnosis. Nomogram models incorporating clinical, laboratory, and radiological features were created to predict histological diagnosis of OCCC over non-OCCC. Results: The final analysis included 533 patients with surgically confirmed OCCC (n = 61) and non-OCCC (n = 472); history of endometriosis was more often found in patients with OCCC (20% versus 3.6%; p < 0.001), while CA-125 was significantly higher in patients with non-OCCC (351 ng/mL versus 70 ng/mL; p < 0.001). A nomogram model incorporating clinical (age, history of endometriosis and adenomyosis), laboratory (CA-125) and imaging findings (peritoneal implant distribution, morphology, laterality, and diameter of ovarian lesion and of the largest solid component) had an AUC of 0.9 (95% CI: 0.847, 0.949), which was comparable to the AUCs of the experienced radiologists' subjective impressions [0.8 (95% CI: 0.822, 0.891) and 0.9 (95% CI: 0.865, 0.936)]. Conclusions: A presurgical nomogram model incorporating readily accessible clinical, laboratory, and CECT variables was a powerful predictor of OCCC, a subtype often requiring a distinctive treatment approach. © 2023 Elsevier Inc. |
| Keywords: | ovarian neoplasms; nomograms; multidetector computed tomography |
| Journal Title: | Gynecologic Oncology |
| Volume: | 176 |
| ISSN: | 0090-8258 |
| Publisher: | Elsevier Inc. |
| Date Published: | 2023-09-01 |
| Start Page: | 90 |
| End Page: | 97 |
| Language: | English |
| DOI: | 10.1016/j.ygyno.2023.06.579 |
| PROVIDER: | scopus |
| PUBMED: | 37478617 |
| PMCID: | PMC10529038 |
| DOI/URL: | |
| Notes: | The MSK Cancer Center Support Grant (P30 CA008748) is acknowledged in the PDF -- Corresponding author is MSK author: Hedvig Hricak -- Source: Scopus |
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