Outcome-based Validation of Confluent/Expansile Versus Infiltrative Pattern Assessment and Growth-based Grading in Ovarian Mucinous Carcinoma.

Abstract

The growth pattern (confluent/expansile versus infiltrative) in primary ovarian mucinous carcinoma (OMC) is prognostically important, and the International Collaboration on Cancer Reporting (ICCR) currently recommends recording the percentage of infiltrative growth in this tumor type. Histologic grading of OMC is controversial with no single approach widely accepted or currently recognized by the World Health Organization Classification of Tumours. Since ovarian carcinoma grade is often considered in clinical decision-making, previous literature has recommended incorporating clinically relevant tumor parameters such as growth pattern into the OMC grade. We herein validate this approach, termed Growth-Based Grade (GBG), in an independent, well-annotated cohort from 2 institutions. OMCs with available histologic material underwent review and grading by Silverberg, International Federation of Obstetrics and Gynecology (FIGO), and GBG schema. GBG categorizes OMCs as low-grade (GBG-LG, confluent/expansile growth, or ≤10% infiltrative invasion) or high-grade (GBG-HG, infiltrative growth in >10% of tumor). The cohort consisted of 74 OMCs, 53 designated as GBG-LG, and 21 as GBG-HG. Using Silverberg grading, the cohort had 42 (57%) grade 1, 28 (38%) grade 2, and 4 (5%) grade 3 OMCs. Using FIGO grading, 50 (68%) OMCs were grade 1, 23 (31%) grade 2, and 1 (1%) grade 3. Follow-up data was available in 68 patients, of which 15 (22%) had cancer recurrence. GBG-HG tumors were far more likely to recur compared with GBG-LG tumors (57% vs. 6%; χ 2P <0.0001). Silverberg and FIGO grading systems also correlated with progression-free survival in univariate analysis, but multivariate analysis showed only GBG to be significant (hazard ratio: 10.9; Cox proportional regression P =0.0004). Seven patients (10%) died of disease, all of whom had GBG-HG (log-rank P <0.0001). Multivariate analysis showed that the percentage of infiltrative growth was the only factor predictive of disease-specific survival (hazard ratio: 25.5, Cox P =0.02). Adding nuclear atypia to GBG categories did not improve prognostication. Our study validates the prognostic value of the GBG system for both disease-free survival and disease-specific survival in OMC, which outperformed Silverberg and FIGO grades in multivariate analysis. Thus, GBG should be the preferred method for tumor grading.