在肺癌患者中，年龄、种族、性别和吸烟情况可预测不良合并症，而不良合并症又可预测治疗情况和生存率。

In lung cancer patients, age, race-ethnicity, gender and smoking predict adverse comorbidity, which in turn predicts treatment and survival.

作者信息

Tammemagi C Martin, Neslund-Dudas Christine, Simoff Michael, Kvale Paul

机构信息

Josephine Ford Cancer Center, 1 Ford Place, 5C, Detroit, MI 48202-3450, USA.

出版信息

J Clin Epidemiol. 2004 Jun;57(6):597-609. doi: 10.1016/j.jclinepi.2003.11.002.

DOI:10.1016/j.jclinepi.2003.11.002

PMID:15246128

Abstract

OBJECTIVE

This study evaluates the relationship between sociodemographic/exposure factors and comorbidity, and their impact on lung cancer treatment and survival. STUDY AND DESIGN SETTING: Data for 1,155 patients were abstracted from the Josephine Ford Cancer Center Tumor Registry and medical records. Associations were analyzed by linear, logistic, and Cox regression.

RESULTS

Approximately 88% of patients had > or = 1 of 56 comorbidities assessed. In multivariate analysis, comorbidity count was associated with older age, pack-years smoked, heavy alcohol use, lower socioeconomic status (SES), and female gender. Approximately 63% of patients had > or = 1 of 18 adverse prognostic comorbidities (AC), and significant independent predictors of AC were age, pack-years, African-American race/ethnicity, and gender. In multivariate analysis, comorbidity count and AC predicted nonreceipt of surgery in localized disease (OR(> or = 1 vs. 0 AC)=0.38, 95% 0.18, 0.81) and chemotherapy in advanced disease (OR > or = 1 vs. 0 AC)=0.72, 95% 0.51, 1.00). In adjusted analysis, comorbidity predicted survival in localized (hazard ratio (HR)(> or = 2 vs. 0 AC)=2.99, 95% CI 1.75, 5.10) and advanced lung cancer (HR(> or = 2 vs. 0 AC)=1.56, 95% CI 1.25, 1.94).

CONCLUSION

Comorbidity has important deleterious effects on lung cancer outcomes and significant predictors of comorbidity included age, smoking, race/ethnicity, SES, alcohol, and gender.

摘要

目的

本研究评估社会人口统计学/暴露因素与合并症之间的关系，以及它们对肺癌治疗和生存的影响。研究与设计背景：从约瑟芬·福特癌症中心肿瘤登记处和医疗记录中提取了1155例患者的数据。通过线性、逻辑和Cox回归分析关联。

结果

约88%的患者有≥1种所评估的56种合并症。在多变量分析中，合并症数量与年龄较大、吸烟包年数、大量饮酒、社会经济地位较低（SES）和女性性别相关。约63%的患者有≥1种所评估的18种不良预后合并症（AC），AC的显著独立预测因素为年龄、吸烟包年数、非裔美国人种族/族裔和性别。在多变量分析中，合并症数量和AC预测局限性疾病患者不接受手术（比值比（OR）（≥1种AC与0种AC相比）=0.38，95%可信区间0.18，0.81）以及晚期疾病患者不接受化疗（OR≥1种AC与0种AC相比）=0.72，95%可信区间0.51，1.00）。在校正分析中，合并症预测局限性（风险比（HR）（≥2种AC与0种AC相比）=2.99，95%置信区间1.75，5.10）和晚期肺癌患者的生存（HR（≥2种AC与0种AC相比）=1.56，95%置信区间1.25，1.94）。