Royal Marsden NHS Foundation Trust, London, SW3 6JJ, United Kingdom.
Imperial College London, London, United Kingdom.
BMC Palliat Care. 2023 Apr 26;22(1):51. doi: 10.1186/s12904-023-01155-y.
The accuracy of prognostication has important implications for patients, families, and health services since it may be linked to clinical decision-making, patient experience and outcomes and resource allocation. Study aim is to evaluate the accuracy of temporal predictions of survival in patients with cancer, dementia, heart, or respiratory disease.
Accuracy of clinical prediction was evaluated using retrospective, observational cohort study of 98,187 individuals with a Coordinate My Care record, the Electronic Palliative Care Coordination System serving London, 2010-2020. The survival times of patients were summarised using median and interquartile ranges. Kaplan Meier survival curves were created to describe and compare survival across prognostic categories and disease trajectories. The extent of agreement between estimated and actual prognosis was quantified using linear weighted Kappa statistic.
Overall, 3% were predicted to live "days"; 13% "weeks"; 28% "months"; and 56% "year/years". The agreement between estimated and actual prognosis using linear weighted Kappa statistic was highest for patients with dementia/frailty (0.75) and cancer (0.73). Clinicians' estimates were able to discriminate (log-rank p < 0.001) between groups of patients with differing survival prospects. Across all disease groups, the accuracy of survival estimates was high for patients who were likely to live for fewer than 14 days (74% accuracy) or for more than one year (83% accuracy), but less accurate at predicting survival of "weeks" or "months" (32% accuracy).
Clinicians are good at identifying individuals who will die imminently and those who will live for much longer. The accuracy of prognostication for these time frames differs across major disease categories, but remains acceptable even in non-cancer patients, including patients with dementia. Advance Care Planning and timely access to palliative care based on individual patient needs may be beneficial for those where there is significant prognostic uncertainty; those who are neither imminently dying nor expected to live for "years".
预测准确性对患者、家属和医疗服务具有重要意义,因为它可能与临床决策、患者体验和结局以及资源分配有关。本研究旨在评估癌症、痴呆、心脏或呼吸疾病患者生存时间的时间预测准确性。
使用 2010-2020 年伦敦电子姑息治疗协调系统(Coordinate My Care 记录的服务对象)中 98187 名个体的回顾性观察队列研究来评估临床预测的准确性。使用中位数和四分位距总结患者的生存时间。绘制 Kaplan-Meier 生存曲线来描述和比较不同预后类别和疾病轨迹的生存情况。使用线性加权 Kappa 统计量来量化估计和实际预后之间的一致性程度。
总体而言,3%的患者预计“活几天”;13%的患者预计“活几周”;28%的患者预计“活几个月”;56%的患者预计“活一年/几年”。使用线性加权 Kappa 统计量,痴呆/虚弱患者(0.75)和癌症患者(0.73)的估计和实际预后之间的一致性最高。临床医生的估计能够区分具有不同生存前景的患者群体(对数秩检验 p<0.001)。在所有疾病组中,对于预计存活时间少于 14 天(74%的准确性)或超过一年(83%的准确性)的患者,生存估计的准确性较高,但对于预测“几周”或“几个月”的生存情况准确性较低(32%的准确性)。
临床医生善于识别即将死亡的个体和将存活很长时间的个体。这些时间框架的预测准确性在主要疾病类别之间存在差异,但即使在非癌症患者中,包括痴呆患者,也具有可接受的准确性。基于患者个体需求的 Advance Care Planning 和及时获得姑息治疗可能有益于那些存在显著预后不确定性的患者;那些既不会即将死亡,也不会预计存活“数年”的患者。