Suppr超能文献

预测基底细胞癌复发的组织学特征:多变量分析结果

Histologic features predictive of basal cell carcinoma recurrence: results of a multivariate analysis.

作者信息

Dixon A Y, Lee S H, McGregor D H

机构信息

Department of Pathology and Oncology, University of Kansas Medical Center, Kansas City.

出版信息

J Cutan Pathol. 1993 Apr;20(2):137-42. doi: 10.1111/j.1600-0560.1993.tb00230.x.

Abstract

Previous univariate analysis of 30 recurrent and 74 non-recurrent basal cell carcinomas identified 6 histologic parameters predictive of recurrence: distance to the closest resection margin, growth pattern, shape of cell groups, contour of invading edge, degree of peripheral palisading, and nuclear pleomorphism. Re-analysis of the data by multivariate analysis to select the few most important independent prognostic variables identified two parameters in each of two final models: resection margin distance and growth pattern (Model 1), and resection margin distance and shape of cell groups (Model 2). Based on these variables, a logistic regression equation could be derived for each model to calculate the predicted probability of recurrence or non-recurrence.

摘要

先前对30例复发性和74例非复发性基底细胞癌进行的单变量分析确定了6个预测复发的组织学参数:与最近切除边缘的距离、生长模式、细胞群形状、浸润边缘轮廓、周边栅栏状程度和核多形性。通过多变量分析重新分析数据以选择少数几个最重要的独立预后变量,在两个最终模型中各确定了两个参数:切除边缘距离和生长模式(模型1),以及切除边缘距离和细胞群形状(模型2)。基于这些变量,可以为每个模型推导逻辑回归方程,以计算复发或不复发的预测概率。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验