Department of Hematology, Sichuan University West China Hospital, Chengdu, Sichuan, China.
Sichuan University West China Hospital School of Nursing, Chengdu, Sichuan, China.
BMJ Open. 2023 Aug 18;13(8):e074196. doi: 10.1136/bmjopen-2023-074196.
Perianal infection is a serious complication in patients undergoing chemotherapy for haematological malignancies. Therefore, we aimed to develop a predictive model to help medical staff promptly screen patients at a high risk of perianal infection during chemotherapy.
This was a single-centre prospective observational study.
This study was conducted in a tertiary teaching hospital in Chengdu, China.
The study sample comprised 850 patients with haematological malignancies who underwent chemotherapy at the department of haematology or our hospital between January 2021 and June 2022.
The included patients were randomly divided into training and validation groups in a 7:3 ratio. Based on the discharge diagnosis, patients with perianal infection were selected as the case group and the other patients were selected as the control group.
The main outcome measure was the occurrence of perianal infections.
A predictive model for perianal infections was established. A history of perianal infection, haemorrhoids, constipation and duration of diarrhoea were independent risk factors. The area under the curve of the The area under the receiver operating characteristic (ROC) curve for the training and validation groups were 0.784 (95% CI 0.727 to 0.841) and 0.789 (95% CI 0.818 to 0.885), respectively. Additionally, the model had good calibration in both the training and validation groups with a non-significant Hosmer-Lemeshow test (p=0.999 and 0.482, respectively).
The risk prediction model, including a history of perianal infection, history of haemorrhoids, constipation and duration of diarrhoea ≥3 days of perianal infection in patients with haematological malignancies during chemotherapy, has good prediction reliability and can be helpful in guiding clinical medical staff in screening and early intervention of high-risk groups.
肛门周围感染是血液恶性肿瘤患者接受化疗时的一种严重并发症。因此，我们旨在开发一种预测模型，帮助医务人员在化疗期间及时筛查出肛门周围感染风险较高的患者。
这是一项单中心前瞻性观察研究。
本研究在中国成都的一家三级教学医院进行。
研究样本包括 2021 年 1 月至 2022 年 6 月期间在血液科或我院接受化疗的 850 例血液恶性肿瘤患者。
纳入的患者按 7:3 的比例随机分为训练组和验证组。根据出院诊断，将发生肛门周围感染的患者选为病例组，其他患者选为对照组。
主要结局指标为肛门周围感染的发生情况。
建立了肛门周围感染预测模型。肛门周围感染史、痔疮、便秘和腹泻持续时间是独立的危险因素。训练组和验证组的受试者工作特征曲线（ROC）曲线下面积分别为 0.784（95%可信区间 0.727 至 0.841）和 0.789（95%可信区间 0.818 至 0.885）。此外，该模型在训练组和验证组中均具有良好的校准度，Hosmer-Lemeshow 检验无显著差异（分别为 p=0.999 和 0.482）。
该风险预测模型包括肛门周围感染史、痔疮史、便秘和腹泻持续时间≥3 天的肛门周围感染史，对血液恶性肿瘤患者化疗期间的肛门周围感染具有良好的预测可靠性，有助于指导临床医务人员对高危人群进行筛查和早期干预。
