医学
倾向得分匹配
危险系数
置信区间
内科学
肺癌
比例危险模型
化疗
肿瘤科
性能状态
放射治疗
作者
Tommy Sheu,John V. Heymach,Stephen G. Swisher,Ganesh Rao,Jeffrey S. Weinberg,Reza J. Mehran,Mary Frances McAleer,Zhongxing Liao,Thomas A. Aloia,Daniel R. Gomez
标识
DOI:10.1016/j.ijrobp.2014.07.012
摘要
To retrospectively analyze factors influencing survival in patients with non-small cell lung cancer presenting with ≤3 synchronous metastatic lesions.We identified 90 patients presenting between 1998 and 2012 with non-small cell lung cancer and ≤3 metastatic lesions who had received at least 2 cycles of chemotherapy followed by surgery or radiation therapy before disease progression. The median number of chemotherapy cycles before comprehensive local therapy (CLT) (including concurrent chemoradiation as first-line therapy) was 6. Factors potentially affecting overall (OS) or progression-free survival (PFS) were evaluated with Cox proportional hazards regression. Propensity score matching was used to assess the efficacy of CLT.Median follow-up time was 46.6 months. Benefits in OS (27.1 vs 13.1 months) and PFS (11.3 months vs 8.0 months) were found with CLT, and the differences were statistically significant when propensity score matching was used (P ≤ .01). On adjusted analysis, CLT had a statistically significant benefit in terms of OS (hazard ratio, 0.37; 95% confidence interval, 0.20-0.70; P ≤ .01) but not PFS (P=.10). In an adjusted subgroup analysis of patients receiving CLT, favorable performance status (hazard ratio, 0.43; 95% confidence interval, 0.22-0.84; P=.01) was found to predict improved OS.Comprehensive local therapy was associated with improved OS in an adjusted analysis and seemed to favorably influence OS and PFS when factors such as N status, number of metastatic lesions, and disease sites were controlled for with propensity score-matched analysis. Patients with favorable performance status had improved outcomes with CLT. Ultimately, prospective, randomized trials are needed to provide definitive evidence as to the optimal treatment approach for this patient population.
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