Department of Health-Business Administration, Fooyin University, Kaohsiung 83102, Taiwan.
Department of Information Management, National Central University, Taoyuan 32001, Taiwan.
J Healthc Eng. 2021 Aug 21;2021:3831453. doi: 10.1155/2021/3831453. eCollection 2021.
Bladder cancer, the ninth most common cancer worldwide, requires fast diagnosis and treatment to prevent disease progression and improve patient survival. However, patients with bladder cancer often experience considerable delays in diagnosis. One reason for such delays is that hematuria, a major symptom of bladder cancer, has a high probability of also being a warning sign for urinary tract diseases. Another reason is that the sensitivity of the body parts affected by bladder cancer deters patients from undergoing cystoscopy and influences patients' "physician shopping" behavior. In this study, the analytic hierarchy process was used to determine critical variables influencing delayed diagnosis; moreover, the variables were used to construct models for predicting delayed diagnosis in patients with hematuria by using several machine learning techniques. Furthermore, the critical variables associated with delayed diagnosis of bladder cancer in patients with hematuria were evaluated using GainRatio technology. The study sample was selected from a population-based database. The model evaluation results indicated that the prediction model established using decision tree algorithms outperformed the other models. The critical risk factors for delayed diagnosis of bladder cancer were as follows: (1) cystoscopy performed 6 months after hematuria diagnosis and (2) physician shopping.
膀胱癌是全球第九大常见癌症，需要快速诊断和治疗，以防止疾病进展并提高患者生存率。然而，膀胱癌患者常常在诊断上出现相当大的延迟。导致这种延迟的原因之一是膀胱癌的主要症状血尿也很可能是尿路疾病的警告信号。另一个原因是膀胱癌影响的身体部位的敏感性阻止了患者进行膀胱镜检查，并影响了患者的“医生购物”行为。在这项研究中，使用层次分析法确定了影响延迟诊断的关键变量；此外，还使用几种机器学习技术，使用这些变量构建了预测血尿患者延迟诊断的模型。此外，还使用增益比技术评估了血尿患者膀胱癌延迟诊断的相关关键变量。研究样本选自基于人群的数据库。模型评估结果表明，使用决策树算法建立的预测模型优于其他模型。膀胱癌延迟诊断的关键风险因素如下：（1）血尿诊断后 6 个月进行膀胱镜检查，（2）医生选择。
