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膀胱癌筛查:新的选择与预测模型。

Bladder cancer screening: The new selection and prediction model.

作者信息

Radosavljevic Vladan, Milic Natasa

机构信息

Military Medical Academy, Institute of Epidemiology, Crnotravska 17, 11000 Belgrade, Serbia.

Institute of Medical Statistics and Informatics, Medical Faculty, University of Belgrade, 11000 Belgrade, Serbia.

出版信息

Open Med (Wars). 2023 Jun 16;18(1):20230723. doi: 10.1515/med-2023-0723. eCollection 2023.

Abstract

The objective of this study was to offer new approach for selection of persons with asymptomatic bladder cancer (BC) and highly risky persons for the BC occurrence. Also, it is a part of the BC screening protocol (study is ongoing). Study populations were 100 newly diagnosed (diagnosis maximum 1-year old) males with BC and 100 matched (by sex and age ±5 years) controls (not oncology patients from the same hospital). A hospital based, matched case-control study was done. Statistical analysis comprised of four steps: -test, univariate logistic regression, multivariate logistic regression, and scoring. The fifth step comprised of two changes, deleting one variable and addition of another variable. Six variables were statistically significant: Caucasian men over 45 years age, tobacco smoking over 40 pack-years, occupational and/or environmental exposure to the proved BC carcinogens over 20 years, macrohematuria, difficulty urinating, BC in relatives up to fourth degree of kinships, and they were used for an easy and fast selection of the individuals with high risk for BC occurrence and BC asymptomatic patients (optimal selection at the population level). The final results showed highly significant probability ( < 0.001), with area under ROC curve of 0.913, negative predictive values of 89.7% (95% CI 10.3-100%), and a specificity of 78%. Positive predictive value was 80.5% (95% CI 19.5-100%) and a sensitivity of 91%. It is possible to recruit asymptomatic BC patients (primary prevention) by using this model, as well as persons with high risk for BC occurrence (primordial prevention). This study is the first part of the BC screening protocol and the second part of the BC screening protocol study is ongoing (urine analysis).

摘要

本研究的目的是为无症状膀胱癌(BC)患者的选择以及BC发生的高风险人群提供新方法。此外,它也是BC筛查方案的一部分(研究正在进行中)。研究人群包括100名新诊断(诊断时间最长为1年)的男性BC患者和100名匹配(按性别和年龄±5岁)的对照者(来自同一家医院的非肿瘤患者)。进行了一项基于医院的匹配病例对照研究。统计分析包括四个步骤:-检验、单变量逻辑回归、多变量逻辑回归和评分。第五步包括两个变化,删除一个变量并添加另一个变量。六个变量具有统计学意义:45岁以上的白人男性、吸烟超过40包年、职业和/或环境接触已证实的BC致癌物超过20年、肉眼血尿、排尿困难、四代以内亲属中有BC患者,这些变量用于轻松快速地选择BC发生高风险个体和无症状BC患者(在人群水平上的最佳选择)。最终结果显示概率非常显著(<0.001),ROC曲线下面积为0.913,阴性预测值为89.7%(95%CI 10.3 - 100%),特异性为78%。阳性预测值为80.5%(95%CI 19.5 - 100%),敏感性为91%。使用该模型有可能招募无症状BC患者(一级预防)以及BC发生高风险人群(原级预防)。本研究是BC筛查方案的第一部分,BC筛查方案研究的第二部分正在进行(尿液分析)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c8b/10276611/2610351f61d6/j_med-2023-0723-fig001.jpg

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