Institute of Haematology, Department of Haematology and Clinical Oncology "Lorenzo e Ariosto Seràgnoli" S'Orsola-Malpighi Hospital, University of Bologna, Bologna, Italy.
Department of Infectious Diseases, Infection Control and Employee Health, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States.
J Infect. 2019 Jun;78(6):484-490. doi: 10.1016/j.jinf.2019.04.002. Epub 2019 Apr 8.
Our objective was to develop a model that predicts a patient's risk of developing invasive mould disease (IMD) within 60 days of admission for treatment of a haematological malignancy.
We analysed 19 risk factors for IMD in a cohort of 1944 adult patients with haematological malignancies over 4127 admissions at a haematology referral centre in Northern Italy (2007-2016). We used a multivariable logistic regression to estimate the 60-day probability of developing probable or proven IMD. The model was internally validated using a bootstrap resampling procedure.
The prevalence of IMD was 3.3% (90 probable cases, 43 proven cases). Seven risk factors were retained in the final risk model: (1) uncontrolled malignancy, (2) high-risk chemotherapy regimen, (3) high-dose corticosteroids, (4) severe lymphopenia, (5) CMV reactivation or disease, (6) prolonged neutropenia, and (7) a history of previous IMD within 90 days. The model displayed good calibration and discrimination in both the derivation (aROC 0.85, 95% CI 0.84-0.86) and validation (aROC 0.83 95% CI 0.79-0.89) populations.
Our model differentiated with 85% accuracy whether or not patients developed IMD within 60-days of admission. Individualized risk assessment, aided by validated prognostic models, could assist IMD management and improve antifungal stewardship.
我们的目的是开发一种模型,以预测血液病患者在入院治疗恶性血液病后 60 天内发生侵袭性霉菌病(IMD)的风险。
我们分析了意大利北部一家血液学转诊中心 1944 名血液病成年患者的 1944 名患者中的 19 个 IMD 危险因素,共涉及 4127 次住院治疗(2007-2016 年)。我们使用多变量逻辑回归来估计 60 天内发生可能或确诊 IMD 的概率。该模型通过自举重采样程序进行内部验证。
IMD 的患病率为 3.3%(90 例可能病例,43 例确诊病例)。最终风险模型保留了 7 个危险因素:(1)未控制的恶性肿瘤,(2)高危化疗方案,(3)高剂量皮质激素,(4)严重淋巴细胞减少症,(5)CMV 再激活或疾病,(6)中性粒细胞减少症持续时间长,以及(7)90 天内有先前 IMD 病史。该模型在推导(aROC 0.85,95%CI 0.84-0.86)和验证(aROC 0.83,95%CI 0.79-0.89)人群中均显示出良好的校准和区分能力。
我们的模型可以 85%的准确率区分患者是否在入院后 60 天内发生 IMD。个体化风险评估,借助经过验证的预后模型,可辅助 IMD 管理并改善抗真菌药物管理。