Endometrioid Endometrial RNA Index Predicts Recurrence in Stage I Patients

阶段(地层学) 子宫内膜癌 肿瘤科 医学 索引(排版) 核糖核酸 内科学 妇科 生物 癌症 遗传学 计算机科学 基因 古生物学 万维网
作者
Corrine A. Nief,Phoebe M. Hammer,Aihui Wang,Vivek Charu,Amina Tanweer,Babak Litkouhi,Elizabeth Kidd,Andrew J. Gentles,Brooke E. Howitt
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:30 (13): 2801-2811 被引量:1
标识
DOI:10.1158/1078-0432.ccr-23-3158
摘要

Abstract Purpose: Risk prediction with genomic and transcriptomic data has the potential to improve patient outcomes by enabling clinicians to identify patients requiring adjuvant treatment approaches, while sparing low-risk patients from unnecessary interventions. Endometrioid endometrial carcinoma (EEC) is the most common cancer in women in developed countries, and rates of endometrial cancer are increasing. Experimental Design: We collected a 105-patient case-control cohort of stage I EEC comprising 45 patients who experienced recurrence less than 6 years after excision, and 60 Fédération Internationale de Gynécologie et d'Obstétrique grade-matched controls without recurrence. We first utilized two RNA-based, previously validated machine learning approaches, namely, EcoTyper and Complexity Index in Sarcoma (CINSARC). We developed Endometrioid Endometrial RNA Index (EERI), which uses RNA expression data from 46 genes to generate a personalized risk score for each patient. EERI was trained on our 105-patient cohort and tested on a publicly available cohort of 263 patients with stage I EEC. Results: EERI was able to predict recurrences with 94% accuracy in the training set and 81% accuracy in the test set. In the test set, patients assigned as EERI high-risk were significantly more likely to experience recurrence (30%) than the EERI low-risk group (1%) with a hazard ratio of 9.9 (95% CI, 4.1–23.8; P < 0.001). Conclusions: Tumors with high-risk genetic features may require additional treatment or closer monitoring and are not readily identified using traditional clinicopathologic and molecular features. EERI performs with high sensitivity and modest specificity, which may benefit from further optimization and validation in larger independent cohorts.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
CodeCraft应助出保函费采纳,获得10
1秒前
1秒前
4秒前
Liberal-5完成签到,获得积分10
7秒前
吃吃发布了新的文献求助10
7秒前
爆米花应助123采纳,获得10
8秒前
8秒前
ubiquitin发布了新的文献求助10
10秒前
LLjkh关注了科研通微信公众号
11秒前
11秒前
11秒前
香蕉觅云应助Hshi采纳,获得10
12秒前
荒野小蚂蚁完成签到,获得积分0
13秒前
14秒前
单纯乘风发布了新的文献求助10
15秒前
852应助自由行走的花采纳,获得10
15秒前
15秒前
vn发布了新的文献求助10
17秒前
汉堡包应助suiyi采纳,获得10
17秒前
Jwen关注了科研通微信公众号
18秒前
跳跃如南完成签到,获得积分10
19秒前
深情飞丹完成签到 ,获得积分10
19秒前
kyut完成签到,获得积分10
20秒前
20秒前
isonomia发布了新的文献求助50
21秒前
完美世界应助醒醒采纳,获得10
22秒前
赘婿应助Vincent1990采纳,获得10
22秒前
23秒前
23秒前
hx完成签到 ,获得积分10
25秒前
25秒前
粗心的含莲应助sekidesu采纳,获得30
26秒前
李健的小迷弟应助北洛采纳,获得10
28秒前
28秒前
方赫然应助小四喜采纳,获得10
29秒前
walterick发布了新的文献求助30
30秒前
31秒前
秋子发布了新的文献求助10
32秒前
Elly发布了新的文献求助10
33秒前
34秒前
高分求助中
歯科矯正学 第7版(或第5版) 1004
Semiconductor Process Reliability in Practice 1000
Smart but Scattered: The Revolutionary Executive Skills Approach to Helping Kids Reach Their Potential (第二版) 1000
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 600
GROUP-THEORY AND POLARIZATION ALGEBRA 500
Mesopotamian divination texts : conversing with the gods : sources from the first millennium BCE 500
Days of Transition. The Parsi Death Rituals(2011) 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3234076
求助须知:如何正确求助?哪些是违规求助? 2880478
关于积分的说明 8215669
捐赠科研通 2548044
什么是DOI,文献DOI怎么找? 1377420
科研通“疑难数据库(出版商)”最低求助积分说明 647912
邀请新用户注册赠送积分活动 623263