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肺小细胞癌:一种预后分期系统的推导

Small-cell carcinoma of the lung: derivation of a prognostic staging system.

作者信息

Sagman U, Maki E, Evans W K, Warr D, Shepherd F A, Sculier J P, Haddad R, Payne D, Pringle J F, Yeoh J L

机构信息

Ontario Cancer Institute, Toronto, Canada.

出版信息

J Clin Oncol. 1991 Sep;9(9):1639-49. doi: 10.1200/JCO.1991.9.9.1639.

Abstract

Retrospective data on 22 pretreatment attributes were evaluated in 614 patients with small-cell carcinoma of the lung (SCCL). The series included 284 patients with limited disease (LD) and 328 patients with extensive disease (ED) managed between 1974 and 1986. Prognostic factors were evaluated by univariate analysis and by the Cox multivariate regression model. Recursive partition and amalgamation algorithm (RECPAM), two clustering methods well suited for obtaining strata and adapted for censoring survival data, were developed and used in the formulation of a new prognostic staging system. In univariate analysis, prognosis was significantly influenced by extent of disease (DE), the number of metastatic sites, and the detection of mediastinal spread in LD. Poor performance status (PS), male sex, and advanced age were negatively correlated with survival, as were increased serum levels of alkaline phosphates (AP), lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), total WBC count (WBCC), and low platelet count and low serum sodium. The Cox model identified plasma LDH and mediastinal spread as the only significant factors in LD; the influence of PS, number of metastatic sites, bone metastasis, brain metastasis, and platelet count were identified as significant in ED. The RECPAM model identified four distinct risk groups defined in a classification tree by the following eight attributes: DE, PS, serum AP, serum LDH, mediastinal spread, sex, WBCC, and liver metastasis. The four groups were distinguished by median survival times of 59, 49, 35, and 24 weeks, respectively (P = .0001). Interactions among prognostic factors are emphasized in the RECPAM classification model as evidenced by reassignment of patients across conventional staging barriers into alternate prognostic groups. The advantages of using RECPAM over the more conventional Cox regression techniques for a new staging system are discussed.

摘要

对614例肺小细胞癌(SCCL)患者的22项预处理属性的回顾性数据进行了评估。该系列包括1974年至1986年间治疗的284例局限性疾病(LD)患者和328例广泛性疾病(ED)患者。通过单因素分析和Cox多变量回归模型评估预后因素。开发了递归划分与合并算法(RECPAM)这两种非常适合获取分层并适用于生存数据删失的聚类方法,并将其用于制定新的预后分期系统。在单因素分析中,疾病范围(DE)、转移部位数量以及LD中纵隔转移的检测对预后有显著影响。较差的体能状态(PS)、男性性别和高龄与生存率呈负相关,血清碱性磷酸酶(AP)、乳酸脱氢酶(LDH)、癌胚抗原(CEA)、白细胞总数(WBCC)升高以及血小板计数低和血清钠低也与生存率呈负相关。Cox模型确定血浆LDH和纵隔转移是LD中唯一的显著因素;PS、转移部位数量、骨转移、脑转移和血小板计数的影响在ED中被确定为显著因素。RECPAM模型通过以下八个属性在分类树中确定了四个不同的风险组:DE、PS、血清AP、血清LDH、纵隔转移、性别、WBCC和肝转移。这四组的中位生存时间分别为59周、49周、35周和24周(P = .0001)。RECPAM分类模型强调了预后因素之间的相互作用,这一点通过将患者跨越传统分期界限重新分配到不同的预后期组得到了证明。文中讨论了在新的分期系统中使用RECPAM优于更传统的Cox回归技术的优势。

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