Ghavami Vahid, Mahmoudi Mahmood, Rahimi Foroushani Abbas, Baghishani Hossein, Homaei Shandiz Fatemeh, Yaseri Mehdi
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.Email:
Asian Pac J Cancer Prev. 2017 Oct 26;18(10):2825-2832. doi: 10.22034/APJCP.2017.18.10.2825.
Introduction: Survival modeling is a very important tool to detect risk factors and provide a basis for health care planning. However, cancer data may have properties leading to distorted results with routine methods. Therefore, this study aimed to cover specific factors (competing risk, cure fraction and heterogeneity) with a real dataset of Iranian breast cancer patients using a competing risk-cure-frailty model. Materials and methods: For this historical cohort study, information for 550 Iranian breast cancer patients who underwent surgery for tumor removal from 2001 to 2007 and were followed up to March 2017, was analyzed using R 3.2 software. Results: In contrast to T-stage and N-stage, hormone receptor status did not have any significant effect on the cure fraction (long-term disease-free survival). However, T-stage, N-stage and hormone receptor status all had a significant effect on short-term disease-free survival so that the hazard of loco-regional relapse or distant metastasis in cases positive for a hormone receptor was only 0.3 times that for their negative hormone receptor counterparts. The likelihood of locoregional relapse in the first quartile of follow up was nearly twice that of other quartiles. The least cumulative incidence of time to locoregional relapse was for cases with a positive hormone receptor, low N stage and low T stage. The effect of frailty term was significant in this study and a model with frailty appeared more appropriate than a model without, based on the Akaike information criterion (AIC); values for the frailty model and one without the frailty parameter were 1370.39 and 1381.46, respectively. Conclusions: The data from this study indicate ae necessity to consider competing risk, cure fraction and heterogeneity in survival modeling. The competing risk-cure-frailty model can cover complex situations with survival data.
生存建模是检测风险因素并为医疗保健规划提供依据的非常重要的工具。然而，癌症数据可能具有导致常规方法结果失真的特性。因此，本研究旨在使用竞争风险-治愈-脆弱模型，通过伊朗乳腺癌患者的真实数据集来涵盖特定因素（竞争风险、治愈比例和异质性）。
对于这项历史性队列研究，使用R 3.2软件分析了2001年至2007年接受肿瘤切除手术并随访至2017年3月的550名伊朗乳腺癌患者的信息。
与T分期和N分期不同，激素受体状态对治愈比例（长期无病生存）没有任何显著影响。然而，T分期、N分期和激素受体状态对短期无病生存均有显著影响，因此激素受体阳性病例发生局部区域复发或远处转移的风险仅为激素受体阴性对应病例的0.3倍。随访第一四分位数时局部区域复发的可能性几乎是其他四分位数的两倍。激素受体阳性、N分期低和T分期低的病例局部区域复发时间的累积发生率最低。在本研究中，脆弱项的影响显著，基于赤池信息准则（AIC），包含脆弱项的模型似乎比不包含的模型更合适；脆弱模型和不包含脆弱参数的模型的值分别为1370.39和1381.46。
本研究数据表明在生存建模中需要考虑竞争风险、治愈比例和异质性。竞争风险-治愈-脆弱模型可以涵盖生存数据的复杂情况。
