Covariate clustering: women with breast cancer in southwestern Paraná, Brazil

Author:

Romeiro Neyva M. L.ORCID,Panis CarolinaORCID,dos Santos Mara C.T.ORCID,Rech DanielORCID,Natti Paulo L.ORCID,Cirilo Eliandro R.ORCID

Abstract

ABSTRACTDue to the high incidence and aggressiveness of breast cancer, the understanding of specific factors associated with the profile of the disease is necessary. In this context, the aim of the study was to analyze data from 155 patients with breast cancer, attended at a reference hospital for Oncology of the Unified Health System (SUS), in the period 2015-2020, in the southwest region of Paraná, Brazil. Using multivariate statistical analysis, sample data were divided into three clusters. The heterogeneity between clusters was obtained by Ward’s method. The clinical and pathological variables obtained from the patients’ medical records were: presence of intratumoral emboli, presence of lymph nodes, menopausal status, molecular subtype of breast cancer, histological grade, TNM staging of the disease, tumor size (cm), age at diagnosis (years), weight (kg), height (m2) and body mass index (BMI) (kg/m2). From the data of the total sample, it is observed that 70% of the patients were in menopause at diagnosis, 31.5% had tumors containing emboli, and 41% had positive lymph nodes. The prevalence of Luminal subtype B tumors, intermediate histological grade, and TNM staging II was verified. Furthermore, the prevalence of the disease was higher in women aged over 50 years, representing 66% of cases. The BMI of the patients ranged from 17.63 kg/m2 to 51.26 kg/m2, with 26.45% of the patients with a BMI below 25 kg/m2, 40.65% with a BMI between 25 kg/m2 and 30 kg/m2 and 32.9% with BMI above 30 kg/m2. Cluster analysis, using the spatial distribution of patients, showed that the region of Vale do Iguaçu was the region with the worst averages for clinical-pathological variables, while the region of Vale do Marrecas had the highest number of breast cancer cases.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3