Nabal Maria, Bescos Mar, Barcons Miquel, Torrubia Pilar, Trujillano Javier, Requena Antonio
1 Palliative Care Supportive Team, Hospital Universitario Arnau de Vilanova , Lleida, Institut Català de la Salut, IRB Lleida, Spain .
J Palliat Med. 2014 Oct;17(10):1158-63. doi: 10.1089/jpm.2013.0630. Epub 2014 Jun 12.
This study sought to develop models to predict survival at 7 and 30 days based on symptoms detected by palliative home care teams (PHCTs).
This prospective analytic study included a 6-month recruitment period with patient monitoring until death or 180 days after recruitment. The inclusion criteria consisted of age greater than 18 years, advanced cancer, and treatment provided by participating PHCTs between April and July 2009. The study variables included death at 7 or 30 days, survival time, age, gender, place of residence, type of tumor and extension, presence of 11 signs and symptoms measured with a 0-3 Likert scale, functional and cognitive status, and use of a subcutaneous butterfly needle. The statistics applied included a descriptive analysis according to the percentage or mean±standard deviation. For symptom comparison between surviving and nonsurviving patients, the χ(2) test was used. Classification and regression tree (CART) methodology was used for model development. An internal validation system (cross-validation with 10 partitions) was used to ensure generalization of the models. The area under the receiver operating characteristics (ROC) curve was calculated (with a 95% confidence interval) to assess the validation of the models.
A total of 698 patients were included. The mean age of the patients was 73.7±12 years, and 60.3% were male. The most frequent type of neoplasm was digestive (37.6%). The mean Karnofsky score was 51.8±14, the patients' cognitive status according to the Pfeiffer test was 2.6±4 errors, and 8.3% of patients required a subcutaneous butterfly needle. Each model provided 8 decision rules with a probability assignment range between 2.2% and 99.1%. The model used to predict the probability of death at 7 days included the presence of anorexia and dysphagia and the level of consciousness, and this model produced areas under the curve (AUCs) of 0.88 (0.86-0.90) and 0.81 (0.79-0.83). The model used to predict the probability of death at 30 days included the presence of asthenia and anorexia and the level of consciousness, and this model produced AUCs of 0.78 (0.77-0.80) and 0.77 (0.75-0.79).
For patients with advanced cancer treated by PHCTs, the use of classification schemes and decision trees based on specific symptoms can help clinicians predict survival at 7 and 30 days.
本研究旨在开发基于姑息家庭护理团队（PHCTs）所检测症状来预测7天和30天生存率的模型。
这项前瞻性分析研究包括为期6个月的招募期，并对患者进行监测直至死亡或招募后180天。纳入标准包括年龄大于18岁、晚期癌症以及2009年4月至7月期间由参与的PHCTs提供治疗。研究变量包括7天或30天内死亡、生存时间、年龄、性别、居住地点、肿瘤类型及分期、用0 - 3李克特量表测量的11种体征和症状的存在情况、功能和认知状态以及皮下蝶形针的使用。所应用的统计方法包括根据百分比或均值±标准差进行描述性分析。对于存活和未存活患者之间的症状比较，使用χ(2)检验。采用分类与回归树（CART）方法进行模型开发。使用内部验证系统（10折交叉验证）来确保模型的通用性。计算受试者操作特征（ROC）曲线下面积（95%置信区间）以评估模型的有效性。
共纳入698例患者。患者的平均年龄为73.7±12岁，60.3%为男性。最常见的肿瘤类型是消化系统肿瘤（37.6%）。卡诺夫斯基评分的平均值为51.8±14，根据 Pfeiffer 测试患者的认知状态为2.6±4个错误，8.3%的患者需要皮下蝶形针。每个模型提供8条决策规则，概率赋值范围在2.2%至99.1%之间。用于预测7天内死亡概率的模型包括厌食、吞咽困难的存在情况以及意识水平，该模型产生的曲线下面积（AUCs）分别为0.88（0.86 - 0.90）和0.81（0.79 - 0.83）。用于预测30天内死亡概率的模型包括乏力、厌食的存在情况以及意识水平，该模型产生的AUCs分别为0.78（0.77 - 0.80）和0.77（0.75 - 0.79）。
对于接受PHCTs治疗的晚期癌症患者，使用基于特定症状的分类方案和决策树可帮助临床医生预测7天和30天的生存率。
