Machine learning prediction of early recurrence after surgery for gallbladder cancer

医学 胆囊癌 队列 逻辑回归 接收机工作特性 胆囊 癌症 内科学 曲线下面积 比例危险模型 外科 胃肠病学
作者
Giovanni Catalano,Laura Alaimo,Odysseas P. Chatzipanagiotou,Andrea Ruzzenente,Federico Aucejo,Hugo P. Marques,Vincent Lam,Tom Hugh,Nazim Bhimani,Shishir K. Maithel,Minoru Kitago,Itaru Endo,Timothy M. Pawlik
出处
期刊:British Journal of Surgery [Oxford University Press]
卷期号:111 (11)
标识
DOI:10.1093/bjs/znae297
摘要

Abstract Background Gallbladder cancer is often associated with poor prognosis, especially when patients experience early recurrence after surgery. Machine learning may improve prediction accuracy by analysing complex non-linear relationships. The aim of this study was to develop and evaluate a machine learning model to predict early recurrence risk after resection of gallbladder cancer. Methods In this cross-sectional study, patients who underwent resection of gallbladder cancer with curative intent between 2001 and 2022 were identified using an international database. Patients were assigned randomly to a development and an evaluation cohort. Four machine learning models were trained to predict early recurrence (within 12 months) and compared using the area under the receiver operating curve (AUC). Results Among 374 patients, 56 (15.0%) experienced early recurrence; most patients had T1 (51, 13.6%) or T2 (180, 48.1%) disease, and a subset had lymph node metastasis (120, 32.1%). In multivariable Cox analysis, resection margins (HR 2.34, 95% c.i. 1.55 to 3.80; P < 0.001), and greater AJCC T (HR 2.14, 1.41 to 3.25; P < 0.001) and N (HR 1.59, 1.05 to 2.42; P = 0.029) categories were independent predictors of early recurrence. The random forest model demonstrated the highest discrimination in the evaluation cohort (AUC 76.4, 95% c.i. 66.3 to 86.5), compared with XGBoost (AUC 74.4, 53.4 to 85.3), support vector machine (AUC 67.2, 54.4 to 80.0), and logistic regression (AUC 73.1, 60.6 to 85.7), as well as good accuracy after bootstrapping validation (AUC 75.3, 75.0 to 75.6). Patients classified as being at high versus low risk of early recurrence had much worse overall survival (36.1 versus 63.8% respectively; P < 0.001). An easy-to-use calculator was made available (https://catalano-giovanni.shinyapps.io/GallbladderER). Conclusion Machine learning-based prediction of early recurrence after resection of gallbladder cancer may help stratify patients, as well as help inform postoperative adjuvant therapy and surveillance strategies.
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
PDF的下载单位、IP信息已删除 (2025-6-4)

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
suwan完成签到,获得积分10
1秒前
张瀚文完成签到 ,获得积分10
4秒前
不吃香菜完成签到 ,获得积分10
6秒前
何日完成签到,获得积分10
8秒前
明天完成签到,获得积分10
8秒前
rrrick完成签到,获得积分10
8秒前
XF发布了新的文献求助10
9秒前
结实乐曲完成签到,获得积分10
9秒前
9秒前
10秒前
顺利紫山完成签到,获得积分10
11秒前
liaodongjun完成签到,获得积分10
12秒前
13秒前
ma完成签到,获得积分10
13秒前
GOW完成签到,获得积分10
14秒前
淡淡的忆彤完成签到,获得积分10
15秒前
15秒前
15秒前
songvv发布了新的文献求助10
16秒前
六沉完成签到 ,获得积分10
17秒前
爱笑的曼易完成签到,获得积分10
17秒前
爆炒菜头完成签到,获得积分10
17秒前
壮观的谷冬完成签到,获得积分10
17秒前
研友_VZG7GZ应助小王采纳,获得10
17秒前
imuzi完成签到,获得积分10
18秒前
tans0008完成签到,获得积分10
18秒前
霸气果汁完成签到,获得积分10
18秒前
程南完成签到,获得积分10
19秒前
JAMA兜里揣发布了新的文献求助10
19秒前
蓝桉完成签到,获得积分10
19秒前
19秒前
jiajiajai完成签到,获得积分10
19秒前
犹豫曲奇完成签到 ,获得积分10
19秒前
杨佳于发布了新的文献求助10
21秒前
科研通AI5应助Z_yiming采纳,获得10
21秒前
22秒前
Verdant_Official完成签到,获得积分10
22秒前
枕星发布了新的文献求助10
23秒前
沉静的雅柔完成签到 ,获得积分10
24秒前
橘猫完成签到 ,获得积分10
24秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 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 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038303
求助须知:如何正确求助?哪些是违规求助? 3576013
关于积分的说明 11374210
捐赠科研通 3305780
什么是DOI,文献DOI怎么找? 1819322
邀请新用户注册赠送积分活动 892672
科研通“疑难数据库(出版商)”最低求助积分说明 815029