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

A. Momeni-Boroujeni, H. Song, L. Irshaid, S. Strickland, C. Parra‐Herran, A. Busca
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引用次数: 2

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%; χ2 P<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.
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基于结果的卵巢黏液癌融合/扩张与浸润模式评估和基于生长的分级验证
原发性卵巢粘液癌(OMC)的生长模式(融合性/扩张性与浸润性)对预后具有重要意义,国际癌症报告合作组织(ICCR)目前建议记录这种肿瘤类型浸润性生长的百分比。OMC的组织学分级是有争议的,目前世界卫生组织的肿瘤分类没有被广泛接受或认可的单一方法。由于卵巢癌分级是临床决策中经常考虑的因素,既往文献建议将临床相关肿瘤参数(如生长模式)纳入OMC分级。我们在此验证了这种方法,称为生长分级(GBG),在一个独立的,有充分注释的来自两个机构的队列中。Silverberg、国际妇产科学联合会(FIGO)和GBG模式对具有可用组织学材料的omc进行了审查和分级。GBG将omc分为低级别(GBG- lg,融合性/扩张性生长,或≤10%的浸润性浸润)和高级别(GBG- hg,浸润性生长>10%的肿瘤)。该队列包括74例omc, 53例指定为GBG-LG, 21例指定为GBG-HG。使用Silverberg分级,该队列有42例(57%)1级omc, 28例(38%)2级omc和4例(5%)3级omc。使用FIGO分级,50例(68%)omc为1级,23例(31%)为2级,1例(1%)为3级。68例患者有随访数据,其中15例(22%)有癌症复发。与GBG-LG肿瘤相比,GBG-HG肿瘤的复发率要高得多(57%比6%;χ2 P < 0.0001)。在单因素分析中,Silverberg和FIGO分级系统也与无进展生存相关,但多因素分析显示,只有GBG具有显著性(风险比:10.9;Cox比例回归P=0.0004)。7例(10%)患者死于疾病,均为GBG-HG (log-rank P<0.0001)。多因素分析显示,浸润性生长百分比是预测疾病特异性生存的唯一因素(风险比:25.5,Cox P=0.02)。在GBG分类中加入核非典型性并不能改善预后。我们的研究验证了GBG系统对OMC无病生存和疾病特异性生存的预后价值,在多变量分析中优于Silverberg和FIGO分级。因此,GBG应该是首选的肿瘤分级方法。
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