Shahraki Hadi Raeisi, Salehi Alireza, Zare Najaf
Department of Biostatistics, Shiraz University of Medical Sciences, Shiraz, Iran E-mail :
Asian Pac J Cancer Prev. 2015;16(15):6773-7. doi: 10.7314/apjcp.2015.16.15.6773.
We used to LASSO-Cox method for determining prognostic factors of male breast cancer survival and showed the superiority of this method compared to Cox proportional hazard model in low sample size setting. In order to identify and estimate exactly the relative hazard of the most important factors effective for the survival duration of male breast cancer, the LASSO-Cox method has been used. Our data includes the information of male breast cancer patients in Fars province, south of Iran, from 1989 to 2008. Cox proportional hazard and LASSO-Cox models were fitted for 20 classified variables. To reduce the impact of missing data, the multiple imputation method was used 20 times through the Markov chain Mont Carlo method and the results were combined with Rubin's rules. In 50 patients, the age at diagnosis was 59.6 (SD=12.8) years with a minimum of 34 and maximum of 84 years and the mean of survival time was 62 months. Three, 5 and 10 year survival were 92%, 77% and 26%, respectively. Using the LASSO-Cox method led to eliminating 8 low effect variables and also decreased the standard error by 2.5 to 7 times. The relative efficiency of LASSO-Cox method compared with the Cox proportional hazard method was calculated as 22.39. The19 years follow of male breast cancer patients show that the age, having a history of alcohol use, nipple discharge, laterality, histological grade and duration of symptoms were the most important variables that have played an effective role in the patient's survival. In such situations, estimating the coefficients by LASSO-Cox method will be more efficient than the Cox's proportional hazard method.
我们采用LASSO - Cox方法来确定男性乳腺癌生存的预后因素,并显示了在小样本量情况下该方法相对于Cox比例风险模型的优越性。为了准确识别和估计对男性乳腺癌生存持续时间最具影响的重要因素的相对风险,我们使用了LASSO - Cox方法。我们的数据包括1989年至2008年伊朗南部法尔斯省男性乳腺癌患者的信息。针对20个分类变量拟合了Cox比例风险模型和LASSO - Cox模型。为了减少缺失数据的影响,通过马尔可夫链蒙特卡罗方法使用多重插补法20次,并将结果按照鲁宾法则进行合并。50例患者中,诊断时年龄为59.6(标准差 = 12.8)岁,最小34岁,最大84岁,平均生存时间为62个月。3年、5年和10年生存率分别为92%、77%和26%。使用LASSO - Cox方法消除了8个低效应变量,同时将标准误差降低了2.5至7倍。计算得出LASSO - Cox方法相对于Cox比例风险方法的相对效率为22.39。对男性乳腺癌患者长达19年的随访表明,年龄、有饮酒史、乳头溢液、肿瘤侧别、组织学分级和症状持续时间是对患者生存起有效作用的最重要变量。在这种情况下,用LASSO - Cox方法估计系数将比Cox比例风险方法更有效。