Serous tubal intraepithelial carcinoma (STIC) outcomes in an average risk population

• Main Authors: Kimberly T. Stewart (Author), Lien Hoang (Author), Janice S. Kwon (Author)
• Format: Book
• Published: Elsevier, 2024-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2352-5789; 10.1016/j.gore.2024.101334
• Keywords: Gynecology and obstetrics; RG1-991; Neoplasms. Tumors. Oncology. Including cancer and carcinogens; RC254-282
• Source: Gynecologic Oncology Reports, Vol 51, Iss , Pp 101334- (2024)

Objective: Serous tubal intraepithelial carcinoma (STIC) are precursors for high grade serous carcinomas (HGSC) of tubo-ovarian origin. It is a rare entity, most commonly described in patients with a BRCA pathogenic variant (PV) undergoing risk-reducing surgery. Little is known about the risk of subsequent HGSC in patients found to have an isolated STIC without a genetic PV. The objective of this study is to report the outcomes of STIC diagnosed in patients with negative genetic testing ("average risk"). Methods: Retrospective population-based cohort study from British Columbia, Canada. Chart review of patients diagnosed with an isolated STIC from January 2012 to May 2022. Average risk patients are defined as individuals with known negative genetic testing results. Treatment and outcomes are described in the "average risk", BRCA PV, and total cohorts. Results: Twenty-nine patients with isolated STIC were identified. Ten patients had a BRCA PV, four had other variants identified (BRIP1, MLH1, BRIP1 VUS, BRCA 2 VUS), nine had no PV identified ("average risk"), and six were unknown (no genetic testing). Of the nine "average risk" patients, eight (89%) underwent surgical staging. Three (33.3%) had subsequent HGSC diagnosed 29, 70 and 86 months after STIC diagnosis. Conclusions: STIC identified in patients with negative genetic testing are at risk of subsequent HGSC. Patients developed primary peritoneal HGSC despite surgical staging. These patients should also be included in future meta-analysis to determine outcomes and optimal treatment.