1 Medical ICU and.
2 Biostatistics Department, St.-Louis University Hospital, Paris, France.
Am J Respir Crit Care Med. 2018 Dec 15;198(12):1519-1526. doi: 10.1164/rccm.201712-2452OC.
The incidence of Pneumocystis jirovecii pneumonia (PjP) is rising. Longer time to treatment is associated with higher mortality.
To develop a multivariable risk prediction model for PjP diagnosis.
In a prospective multicenter cohort of ICU patients with hematological malignancies and acute respiratory failure, factors associated with documented PjP were identified. The risk prediction model was tested in an independent prospective multicenter cohort. We assessed discrimination (by areas under the receiver operating characteristic curves [AUCs]) and goodness of fit (by Hosmer-Lemeshow statistics). Model performance was assessed using 30 sets of imputed data sets.
Among the 1,330 patients, 134 of 1,092 (12.3%; 95% confidence interval [CI], 10.4-14.4%) had proven PjP in the derivation cohort, as did 15 of 238 (6.3%, 95% CI, 3.6-10.2%) in the validation cohort. The model included age, lymphoproliferative disease, anti-Pneumocystis prophylaxis, the number of days between respiratory symptom onset and ICU admission, shock, chest radiograph pattern, and pleural effusion. The median (interquartile range) score was 3.5 (1.5-5.0) (range, -3.5 to 8.5) in the derivation cohort and 1.0 (0-2.0) (range, -3.5 to 6.0) in the validation cohort. The best threshold was defined on the validation sample as 3, allowing us to reach 86.7% sensitivity and 67.7% specificity for PjP, with a negative predictive value of 97.9% in the case of 10% prevalence. The score had good calibration (goodness of fit, -0.75) and discrimination in the derivation cohort (mean AUC, 0.80; 95% CI, 0.76-0.84) and validation cohort (mean AUC, 0.83; 95% CI, 0.72-0.93).
The PjP score for hematology patients with acute respiratory failure can be computed at admission, based on readily available variables. Potential clinical benefits of using this score deserve assessment.
肺囊虫肺炎（PjP）的发病率正在上升。治疗时间延长与死亡率升高相关。
开发用于诊断 PjP 的多变量风险预测模型。
在一项前瞻性多中心血液恶性肿瘤合并急性呼吸衰竭 ICU 患者队列研究中，确定了与确诊 PjP 相关的因素。该风险预测模型在独立的前瞻性多中心队列中进行了验证。我们评估了区分度（通过接受者操作特征曲线下面积[AUC]）和拟合优度（通过 Hosmer-Lemeshow 统计量）。使用 30 组插补数据集评估模型性能。
在 1330 例患者中，在推导队列中，1092 例中的 134 例（12.3%；95%置信区间[CI]，10.4-14.4%）和验证队列中 238 例中的 15 例（6.3%，95%CI，3.6-10.2%）患有确诊 PjP。模型纳入了年龄、淋巴增生性疾病、抗肺囊虫病预防、从呼吸道症状出现到 ICU 入院的天数、休克、胸部 X 线表现和胸腔积液。推导队列的中位数（四分位间距）评分为 3.5（1.5-5.0）（范围，-3.5 至 8.5），验证队列为 1.0（0-2.0）（范围，-3.5 至 6.0）。最佳阈值在验证样本中定义为 3，使我们能够在 10%患病率的情况下达到 86.7%的敏感性和 67.7%的特异性，阴性预测值为 97.9%。该评分在推导队列中具有良好的校准度（拟合优度，-0.75）和区分度（平均 AUC，0.80；95%CI，0.76-0.84）和验证队列（平均 AUC，0.83；95%CI，0.72-0.93）。
基于易于获得的变量，可在急性呼吸衰竭的血液科患者入院时计算 PjP 评分。使用该评分的潜在临床获益值得评估。
