Kikuchi Nobutaka, Ohmori Kaori, Kuriyama Shinichi, Shimada Akira, Nakaho Toshimichi, Yamamuro Makoto, Tsuji Ichiro
Department of Palliative Medicine, Tohoku University Hospital, Miyagi, Japan.
J Pain Symptom Manage. 2007 Dec;34(6):600-6. doi: 10.1016/j.jpainsymman.2007.06.001. Epub 2007 Jul 16.
To determine whether the addition of biological markers to performance status (PS) and physical symptoms would improve survival prediction among patients with advanced cancer, we developed two prediction models with a scoring system based on 294 consecutive patients with advanced cancer (training set), and then tested its validity on another 93 patients (testing set). We assessed the predictive accuracy of the models using receiver-operating characteristic analysis. Albumin (ALB), lactate dehydrogenase (LDH), and lymphocyte percentage (Lymp%) were significantly and independently associated with survival length. For prediction of 60-day survival, the predictive accuracy of Model 2, based on the above biological markers in addition to PS and symptoms, was significantly better than that of Model 1, based on PS and symptoms alone (area under the curve [AUC] for Model 2, 0.80+/-0.03; AUC for Model 1, 0.69+/-0.04; P<0.001). Addition of ALB, LDH, and Lymp% to PS and physical symptoms improved prediction accuracy, especially for longer survival.
为了确定在体能状态（PS）和身体症状基础上增加生物标志物是否能改善晚期癌症患者的生存预测，我们基于294例连续的晚期癌症患者（训练集）开发了两个带有评分系统的预测模型，然后在另外93例患者（测试集）上检验其有效性。我们使用受试者工作特征分析评估模型的预测准确性。白蛋白（ALB）、乳酸脱氢酶（LDH）和淋巴细胞百分比（Lymp%）与生存时长显著且独立相关。对于60天生存的预测，基于上述生物标志物以及PS和症状的模型2的预测准确性显著优于仅基于PS和症状的模型1（模型2的曲线下面积[AUC]为0.80±0.03；模型1的AUC为0.69±0.04；P<0.001）。在PS和身体症状基础上增加ALB、LDH和Lymp%可提高预测准确性，尤其是对于更长生存时间的预测。
