李丁, 张青, 白长森, 郑珊, 张文芳, 周云丽. 合并真菌血症的恶性肿瘤患者死亡风险预测列线图的构建与评价[J]. 中国肿瘤临床, 2023, 50(11): 575-580. DOI: 10.12354/j.issn.1000-8179.2023.20230076
引用本文: 李丁, 张青, 白长森, 郑珊, 张文芳, 周云丽. 合并真菌血症的恶性肿瘤患者死亡风险预测列线图的构建与评价[J]. 中国肿瘤临床, 2023, 50(11): 575-580. DOI: 10.12354/j.issn.1000-8179.2023.20230076
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Ding Li, Qing Zhang, Changsen Bai, Shan Zheng, Wenfang Zhang, Yunli Zhou. Establishment and evaluation of a predictive nomogram for the mortality of patients with malignant tumor having fungemia[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2023, 50(11): 575-580. DOI: 10.12354/j.issn.1000-8179.2023.20230076
Citation: Ding Li, Qing Zhang, Changsen Bai, Shan Zheng, Wenfang Zhang, Yunli Zhou. Establishment and evaluation of a predictive nomogram for the mortality of patients with malignant tumor having fungemia[J]. CHINESE JOURNAL OF CLINICAL ONCOLOGY, 2023, 50(11): 575-580. DOI: 10.12354/j.issn.1000-8179.2023.20230076
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合并真菌血症的恶性肿瘤患者死亡风险预测列线图的构建与评价

Establishment and evaluation of a predictive nomogram for the mortality of patients with malignant tumor having fungemia

    摘要
  • 摘要:
      目的  分析合并真菌血症的恶性肿瘤患者死亡风险因素，建立基于列线图的评价体系，为临床早期干预，改善预后提供理论依据。
      方法  回顾性分析天津医科大学肿瘤医院2010年1月至2021年12月合并真菌血症的112例恶性肿瘤患者的临床资料，根据第1次从血液中分离出真菌后30天内是否发生死亡，分为死亡组与非死亡组，利用单因素、多因素回归分析及Stepwise算法筛选，明确30天内死亡的独立危险因素，构建预测列线图并进行评价。
      结果  在纳入病例中30天粗病死率为38.4 %，主要感染菌种为白色念珠菌54例（48.2%），其次为光滑念珠菌26例（23.2%）、热带念珠菌13例（11.6%）、近平滑念珠菌12例（10.7%）等非白色念珠菌；肾功能障碍（OR=6.818，95%CI：2.244～23.310）、ICU入住>5天（OR=8.737，95%CI：2.918～28.543），肿瘤远处转移（OR=6.384，95%CI：2.067～21.647）是死亡的独立危险因素，基于此构建的预测列线图，其C指数（C-index）为0.898，受试者工作特征曲线（ROC）下面积为0.898（95%CI：0.839～0.957），当临界值（cutoff value）为28.7分时，其假阳性率为21.7%，敏感度为88.4%。
      结论  本研究构建的预测列线图，能够较好地预测合并真菌血症的恶性肿瘤患者30天内死亡风险，为临床诊治工作提供理论帮助。

     

    Abstract:
      Objective  To evaluate the 30-day mortality from fungemia in patients with malignant tumor and establish a predictive nomogram.
      Methods  A total of 112 patients from Tianjin Medical University Cancer Institute & Hospital were enrolled in the study. Clinical data of the patients with malignant tumor, having fungemia, from January 2010 to December 2021 were retrospectively analyzed. The cases were assigned into survival and non-survival groups based on each patient’s 30-day survival status. Independent risk factors of 30-day mortality from fungemia were identified using multiple Logistic regression and a Stepwise algorithm, and a predictive nomogram was developed.
      Results  The 30-day mortality from fungemia was 38.4%. The most common strains of fungi were Candida albicans (54 cases, 48.2%), Candida glabrata (26 cases, 23.2%), Candida tropicalis (13 cases, 11.6%), and Candida parapsilosis (12 cases, 10.7%). Kidney dysfunction (OR: 6.818, 95% CI: 2.244-23.310), ICU stay >5 days (OR: 8.737, 95%CI: 2.918-28.543), and metastasis (OR: 6.384, 95%CI: 2.067-21.647) were identified as independent risk factors of 30-day mortality from fungemia. The consistency index (C-index) of the model was 0.898, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.898 (95% CI: 0.839-0.957). When the cutoff value was set at 28.7, the false positive rate and sensitivity were 21.7% and 88.4%, respectively.
      Conclusions  The predictive nomogram established in the current study could predict the risk of death in patients with malignant tumor having fungemia, which would benefit the healthcare providers’ decisions regarding individual patient’s treatment and lead to an improved prognosis.

     

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