Saruchera Bester, Bodhlyera Oliver, Mwambi Henry, Ndlovu Ntokozo
School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa.
Department of Oncology, Faculty of Medicine and Health Sciences, University of Zimbabwe, P.O.Box MP167. Mt Pleasant, Harare.
Afr Health Sci. 2024 Sep;24(3):156-172. doi: 10.4314/ahs.v24i3.20.
This paper seeks to investigate factors related to time delays for diagnosis and treatment in breast cancer patients at Parirenyatwa Hospital in Zimbabwe and subsequently evaluate the effects of presentation and diagnosis delays on cancer stage.
The study was done for 379 patients with histologically diagnosed invasive breast cancer, from 2015 through to 2019. The study sought to identify factors associated with the time delays ( months)using parametric and non-parametric methods, depending on whether underlying assumptions of such tests are met. A multiple logistic regression model was also used to analyse the association between factors, primary delay, secondary delay variables and cancer stage.
The median of the primary, secondary and treatment delay were found to be 7.6, 1 and 0.4 months respectively. Rural residence, Karnofsky Performance Score below 70%, hypertension comorbidity, tumor size (>5cm) and well differentiated tumors (grade 1) were significant factors for delayed presentation. Longer primary delay times and post-menopausal status were associated with secondary delay. Advanced cancer stage at diagnosis and those on medical aid were more likely to have a delay in treatment onset.
Primary and secondary delay were predictive of advanced disease using logistic regression.
本文旨在调查津巴布韦帕里仁亚瓦医院乳腺癌患者诊断和治疗时间延迟的相关因素，并随后评估就诊延迟和诊断延迟对癌症分期的影响。
该研究针对2015年至2019年期间379例经组织学诊断为浸润性乳腺癌的患者进行。根据此类检验的基本假设是否满足，该研究试图使用参数和非参数方法确定与时间延迟（月）相关的因素。还使用多元逻辑回归模型分析因素、初次延迟、二次延迟变量与癌症分期之间的关联。
发现初次延迟、二次延迟和治疗延迟的中位数分别为7.6个月、1个月和0.4个月。农村居民、卡诺夫斯基体能状态评分低于70%、高血压合并症、肿瘤大小（>5cm）和高分化肿瘤（1级）是就诊延迟的重要因素。较长的初次延迟时间和绝经后状态与二次延迟相关。诊断时癌症分期较晚以及接受医疗救助的患者更有可能出现治疗开始延迟。
使用逻辑回归分析，初次延迟和二次延迟可预测疾病进展。
