Investigator

Chae Y. Han

Post Doc · MD Anderson Cancer Center, Experimental Medicine

CYHChae Y. Han
Papers(2)
A Blood-Based Metabol…Normal Risk Ovarian S…
Collaborators(10)
Robert C. BastKaren H. LuEhsan IrajizadEnrique BediaEunice MurageGwen CorriganJames P. LongJennifer B. DennisonJinsong LiuJody Vykoukal
Institutions(2)
The University Of Tex…Unknown Institution

Papers

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

Abstract Purpose: To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Experimental Design: Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed. Results: A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76–0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84–0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84–0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone. Conclusions: A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Normal Risk Ovarian Screening Study: 21-Year Update

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. PURPOSE The Normal Risk Ovarian Screening Study (NROSS) tested a two-stage screening strategy in postmenopausal women at conventional hereditary risk where significantly rising cancer antigen (CA)-125 prompted transvaginal sonography (TVS) and abnormal TVS prompted surgery to detect ovarian cancer. METHODS A total of 7,856 healthy postmenopausal women were screened annually for a total of 50,596 woman-years in a single-arm study (ClinicalTrials.gov identifier: NCT00539162 ). Serum CA125 was analyzed with the Risk of Ovarian Cancer Algorithm (ROCA) each year. If risk was unchanged and <1:2,000, women returned in a year. If risk increased above 1:500, TVS was undertaken immediately, and if risk was intermediate, CA125 was repeated in 3 months with a further increase in risk above 1:500 prompting referral for TVS. An average of 2% of participants were referred to TVS annually. RESULTS Thirty-four patients were referred for operations detecting 15 ovarian cancers and two borderline tumors with 12 in early stage (I-II). In addition, seven endometrial cancers were detected with six in stage I. As four ovarian cancers and two borderline tumors were diagnosed with a normal ROCA, the sensitivity for detecting ovarian and borderline cancer was 74% (17 of 23), and 70% of ROCA-detected cases (12 of 17) were in stage I-II. NROSS screening reduced late-stage (III-IV) disease by 34% compared with UKCTOCS controls and by 30% compared with US SEER values. The positive predictive value (PPV) was 50% (17 of 34) for detecting ovarian cancer and 74% (25 of 34) for any cancer, far exceeding the minimum acceptable study end point of 10% PPV. CONCLUSION While the NROSS trial was not powered to detect reduced mortality, the high specificity, PPV, and marked stage shift support further development of this strategy.

8Works
2Papers
24Collaborators

Positions

2019–

Post Doc

MD Anderson Cancer Center · Experimental Medicine