The Royal Marsden National Health Service Foundation Trust, Sutton, United Kingdom.
J Clin Oncol. 2012 Mar 20;30(9):996-1004. doi: 10.1200/JCO.2010.34.5074. Epub 2012 Feb 21.
The appropriate selection of patients for early clinical trials presents a major challenge. Previous analyses focusing on this problem were limited by small size and by interpractice heterogeneity. This study aims to define prognostic factors to guide risk-benefit assessments by using a large patient database from multiple phase I trials.
Data were collected from 2,182 eligible patients treated in phase I trials between 2005 and 2007 in 14 European institutions. We derived and validated independent prognostic factors for 90-day mortality by using multivariate logistic regression analysis.
The 90-day mortality was 16.5% with a drug-related death rate of 0.4%. Trial discontinuation within 3 weeks occurred in 14% of patients primarily because of disease progression. Eight different prognostic variables for 90-day mortality were validated: performance status (PS), albumin, lactate dehydrogenase, alkaline phosphatase, number of metastatic sites, clinical tumor growth rate, lymphocytes, and WBC. Two different models of prognostic scores for 90-day mortality were generated by using these factors, including or excluding PS; both achieved specificities of more than 85% and sensitivities of approximately 50% when using a score cutoff of 5 or higher. These models were not superior to the previously published Royal Marsden Hospital score in their ability to predict 90-day mortality.
Patient selection using any of these prognostic scores will reduce non-drug-related 90-day mortality among patients enrolled in phase I trials by 50%. However, this can be achieved only by an overall reduction in recruitment to phase I studies of 20%, more than half of whom would in fact have survived beyond 90 days.
适当选择适合早期临床试验的患者是一个主要挑战。之前针对该问题的分析受到样本量小和实践间异质性的限制。本研究旨在使用来自多个 I 期试验的大型患者数据库，确定预测因素以指导风险效益评估。
从 2005 年至 2007 年在 14 家欧洲机构中进行的 I 期试验中，共纳入 2182 例符合条件的患者。我们通过多变量逻辑回归分析得出并验证了 90 天死亡率的独立预测因素。
90 天死亡率为 16.5%，药物相关死亡率为 0.4%。由于疾病进展，14%的患者在 3 周内停止试验。有 8 个不同的预后变量与 90 天死亡率相关：体能状态（PS）、白蛋白、乳酸脱氢酶、碱性磷酸酶、转移灶数量、临床肿瘤生长率、淋巴细胞和白细胞。使用这些因素生成了两种不同的 90 天死亡率预后评分模型，包括或不包括 PS；当使用评分截断值为 5 或更高时，两种模型的特异性均超过 85%，敏感性约为 50%。与之前发表的皇家马斯登医院评分相比，这些模型在预测 90 天死亡率方面没有优势。
使用这些预测评分中的任何一种进行患者选择，可使 I 期试验中入组患者的非药物相关 90 天死亡率降低 50%。但是，这只能通过将 I 期研究的总体入组率降低 20%来实现，其中超过一半的患者实际上可以存活 90 天以上。
