Hui David, Hess Kenneth, dos Santos Renata, Chisholm Gary, Bruera Eduardo
Department of Palliative Care and Rehabilitation Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Cancer. 2015 Nov 1;121(21):3914-21. doi: 10.1002/cncr.29602. Epub 2015 Jul 28.
Several highly specific bedside physical signs associated with impending death within 3 days for patients with advanced cancer were recently identified. A diagnostic model for impending death based on these physical signs was developed and assessed.
Sixty-two physical signs were systematically documented every 12 hours from admission to death or discharge for 357 patients with advanced cancer who were admitted to acute palliative care units (APCUs) at 2 tertiary care cancer centers. Recursive partitioning analysis was used to develop a prediction model for impending death within 3 days with admission data. The model was validated with 5 iterations of 10-fold cross-validation, and the model was also applied to APCU days 2 to 6.
For the 322 of 357 patients (90%) with complete data for all signs, the 3-day mortality rate was 24% on admission. The final model was based on 2 variables (Palliative Performance Scale [PPS] and drooping of nasolabial folds) and had 4 terminal leaves: PPS score ≤ 20% and drooping of nasolabial folds present, PPS score ≤ 20% and drooping of nasolabial folds absent, PPS score of 30% to 60%, and PPS score ≥ 70%. The 3-day mortality rates were 94%, 42%, 16%, and 3%, respectively. The diagnostic accuracy was 81% for the original tree, 80% for cross-validation, and 79% to 84% for subsequent APCU days.
Based on 2 objective bedside physical signs, a diagnostic model was developed for impending death within 3 days. This model was applicable to both APCU admission and subsequent days. Upon further external validation, this model may help clinicians to formulate the diagnosis of impending death.
最近发现了几种与晚期癌症患者在3天内即将死亡相关的高度特异性床边体征。基于这些体征开发并评估了一种即将死亡的诊断模型。
对357例入住2家三级癌症中心急性姑息治疗病房(APCU)的晚期癌症患者,从入院到死亡或出院,每12小时系统记录62种体征。采用递归划分分析方法,利用入院数据建立3天内即将死亡的预测模型。该模型经5次10折交叉验证进行验证,并应用于APCU第2至6天。
357例患者中有322例(90%)具备所有体征的完整数据,入院时3天死亡率为24%。最终模型基于2个变量(姑息治疗表现量表[PPS]和鼻唇沟下垂),有4个终末叶:PPS评分≤20%且存在鼻唇沟下垂、PPS评分≤20%且不存在鼻唇沟下垂、PPS评分为30%至60%、PPS评分≥70%。3天死亡率分别为94%、42%、16%和3%。原始树的诊断准确率为81%,交叉验证为80%,后续APCU天数为79%至84%。
基于2种客观的床边体征,开发了一种3天内即将死亡的诊断模型。该模型适用于APCU入院时及随后几天。经过进一步的外部验证,该模型可能有助于临床医生做出即将死亡的诊断。