小柯机器人

卵巢癌诊断模型可有效区分附件肿块的良恶性
2020-08-01 23:49

比利时鲁汶大学Dirk Timmerman团队使用卵巢癌诊断模型对手术或保守治疗的患者进行了验证。2020年7月30日,该研究发表在《英国医学杂志》上。

为了评估卵巢恶性肿瘤诊断预测模型在所有手术或保守治疗的卵巢肿块患者中的应用效果,研究组在36个肿瘤科转诊中心或其他类型中心进行了一项多中心队列研究,2012年1月至2015年3月,连续招募了8519例附件出现肿块并通过手术或随访治疗的成年患者。

研究组对卵巢恶性肿瘤6种预测模型进行总体和中心特异性鉴别、校准和临床应用,分别为:恶性肿瘤风险指数(RMI)、逻辑回归模型2(LR2)、简单规则、简单规则风险模型(SRRisk)、有无CA125的附件不同肿瘤的评估(ADNEX)。ADNEX可将恶性肿瘤的风险细分为临界性、I期原发性、II-IV期原发性或继发性转移性恶性肿瘤。

初步分析包括17个合格中心的5717例患者。3441例(70%)患者为良性,978例(20%)为恶性。不确定的结果(486,10%)通常由有限的随访信息来解释。有CA125的ADNEX、无CA125的ADNEX和SRRisk的接受者操作特性曲线下总面积最高,为0.94,RMI最低,为0.89。

所有模型的校准因中心而异,但ADNEX模型和SRRisk的校准效果最好。无论是否将CA125作为预测因子,针对肿瘤亚型估计风险的校准均有利于ADNEX。ADNEX模型和SRRisk的总体临床效用(净收益)最高,而RMI最低。对于至少接受过一次随访扫描的患者(1958例),接受者操作特性曲线下的总面积范围从RMI的0.76至有CA125 ADNEX的0.89不等。

研究结果发现,对于所有出现附件肿块的患者,包括保守治疗者,ADNEX模型和SRRisk是区分良性和恶性肿块的最佳模型。

附:英文原文

Title: Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively: multicentre cohort study

Author: Ben Van Calster, Lil Valentin, Wouter Froyman, Chiara Landolfo, Jolien Ceusters, Antonia C Testa, Laure Wynants, Povilas Sladkevicius, Caroline Van Holsbeke, Ekaterini Domali, Robert Fruscio, Elisabeth Epstein, Dorella Franchi, Marek J Kudla, Valentina Chiappa, Juan L Alcazar, Francesco P G Leone, Francesca Buonomo, Maria Elisabetta Coccia, Stefano Guerriero, Nandita Deo, Ligita Jokubkiene, Luca Savelli, Daniela Fischerová, Artur Czekierdowski, Jeroen Kaijser, An Coosemans, Giovanni Scambia, Ignace Vergote, Tom Bourne, Dirk Timmerman

Issue&Volume: 2020/07/30

Abstract: Objective To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively.

Design Multicentre cohort study.

Setting 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre.

Participants Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up.

Main outcome measures Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain.

Results The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125.

Conclusions Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively.

DOI: 10.1136/bmj.m2614

Source: https://www.bmj.com/content/370/bmj.m2614

BMJ-British Medical Journal:《英国医学杂志》,创刊于1840年。隶属于BMJ出版集团,最新IF:27.604
官方网址:http://www.bmj.com/
投稿链接:https://mc.manuscriptcentral.com/bmj


本期文章:《英国医学杂志》:Online/在线发表

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