医学
子宫内膜癌
淋巴结切除术
危险系数
前哨淋巴结
肿瘤科
队列
阶段(地层学)
淋巴结
内科学
比例危险模型
辅助治疗
解剖(医学)
癌症
算法
外科
乳腺癌
置信区间
古生物学
生物
计算机科学
作者
Francesco Multinu,J.A. Ducie,Ane Gerda Zahl Eriksson,Brooke A. Schlappe,William A. Cliby,Gretchen Glaser,Tommaso Grassi,Gary L. Keeney,Amy L. Weaver,Nadeem R. Abu‐Rustum,Mario M. Leitao,Andrea Mariani
标识
DOI:10.1016/j.ygyno.2019.09.011
摘要
To compare survival and progression outcomes between 2 nodal assessment approaches in patients with nonbulky stage IIIC endometrial cancer (EC).Patients with stage IIIC EC treated at 2 institutions were retrospectively identified. At 1 institution, a historical series (2004-2008) was treated with systematic pelvic and para-aortic lymphadenectomy (LND cohort). At the other institution, more contemporary patients (2006-2013) were treated using a sentinel lymph node algorithm (SLN cohort). Outcomes (hazard ratios [HRs]) within the first 5 years after surgery were compared between cohorts using Cox models adjusted for type of adjuvant therapy.The study included 104 patients (48 LND, 56 SLN). The use of chemoradiotherapy was similar in the 2 cohorts (46% LND vs 50% SLN), but the use of chemotherapy alone (19% vs 36%) or radiotherapy alone (15% vs 2%) differed. Although there was evidence of higher risk of cause-specific death (HR, 2.10; 95% CI, 0.79-5.58; P = 0.14) and lower risk of para-aortic progression (HR, 0.27; 95% CI, 0.05-1.42; P = 0.12) for the LND group, the associations did not meet statistical significance. The risk of progression was not significantly different between the groups (HR, 1.27; 95% CI, 0.60-2.67; P =0 .53). In parsimonious multivariable models, high-risk tumor characteristics and nonendometrioid type were independently associated with lower cause-specific survival and progression-free survival.In EC patients with nonbulky positive lymph nodes, use of the SLN algorithm with limited nodal dissection does not compromise survival compared with LND. Aggressive pathologic features of the primary tumor are the strongest determinants of prognosis.
科研通智能强力驱动
Strongly Powered by AbleSci AI