Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX.
Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX; School of Medicine and Health Sciences, Tecnologico de Monterrey, Monterrey, Mexico.
Chest. 2021 Sep;160(3):1075-1094. doi: 10.1016/j.chest.2021.03.059. Epub 2021 May 11.
Evidence-based guidelines recommend management strategies for malignant pleural effusions (MPEs) based on life expectancy. Existent risk-prediction rules do not provide precise individualized survival estimates.
Can a newly developed continuous risk-prediction survival model for patients with MPE and known metastatic disease provide precise survival estimates?
Single-center retrospective cohort study of patients with proven malignancy, pleural effusion, and known metastatic disease undergoing thoracentesis from 2014 through 2017. The outcome was time from thoracentesis to death. Risk factors were identified using Cox proportional hazards models. Effect-measure modification (EMM) was tested using the Mantel-Cox test and was addressed by using disease-specific models (DSMs) or interaction terms. Three DSMs and a combined model using interactions were generated. Discrimination was evaluated using Harrell's C-statistic. Calibration was assessed by observed-minus-predicted probability graphs at specific time points. Models were validated using patients treated from 2010 through 2013. Using LENT (pleural fluid lactate dehydrogenase, Eastern Cooperative Oncology Group performance score, neutrophil-to-lymphocyte ratio and tumor type) variables, we generated both discrete (LENT-D) and continuous (LENT-C) models, assessing discrete vs continuous predictors' performances.
The development and validation cohort included 562 and 727 patients, respectively. The Mantel-Cox test demonstrated interactions between cancer type and neutrophil to lymphocyte ratio (P < .0001), pleural fluid lactate dehydrogenase (P = .029), and bilateral effusion (P = .002). DSMs for lung, breast, and hematologic malignancies showed C-statistics of 0.72, 0.72, and 0.62, respectively; the combined model's C-statistics was 0.67. LENT-D (C-statistic, 0.60) and LENT-C (C-statistic, 0.65) models underperformed.
EMM is present between cancer type and other predictors; thus, DSMs outperformed the models that failed to account for this. Discrete risk-prediction models lacked enough precision to be useful for individual-level predictions.
基于预期寿命，循证指南为恶性胸腔积液（MPE）推荐了管理策略。现有的风险预测规则无法提供精确的个体化生存估计。
新开发的用于患有 MPE 和已知转移性疾病的患者的连续风险预测生存模型能否提供精确的生存估计？
对 2014 年至 2017 年期间接受胸腔穿刺术的已证实患有恶性肿瘤、胸腔积液和已知转移性疾病的患者进行了单中心回顾性队列研究。结果是从胸腔穿刺术到死亡的时间。使用 Cox 比例风险模型确定了风险因素。使用 Mantel-Cox 检验测试了效应量修正（EMM），并通过使用疾病特异性模型（DSM）或交互项来解决。生成了三个 DSM 和一个使用交互作用的组合模型。使用 Harrell 的 C 统计量评估了区分度。通过在特定时间点观察到的-预测概率图评估了校准。使用 2010 年至 2013 年接受治疗的患者验证了模型。使用 LENT（胸腔积液乳酸脱氢酶、东部合作肿瘤组表现评分、中性粒细胞与淋巴细胞比值和肿瘤类型）变量，我们生成了离散（LENT-D）和连续（LENT-C）模型，评估了离散和连续预测因子的性能。
开发和验证队列分别包括 562 名和 727 名患者。Mantel-Cox 检验表明癌症类型与中性粒细胞与淋巴细胞比值（P <.0001）、胸腔积液乳酸脱氢酶（P =.029）和双侧胸腔积液（P =.002）之间存在交互作用。肺、乳腺和血液恶性肿瘤的 DSM 的 C 统计量分别为 0.72、0.72 和 0.62，组合模型的 C 统计量为 0.67。LENT-D（C 统计量，0.60）和 LENT-C（C 统计量，0.65）模型表现不佳。
癌症类型与其他预测因子之间存在 EMM，因此 DSM 优于未能考虑到这一点的模型。离散风险预测模型缺乏足够的精度，无法用于个体水平的预测。
