Semi-parametric Adjustment Model Methods for Positioning of Seafloor Control Point

This paper focus on solving the problem of seafloor control point absolute positioning with low vertical accuracy based on the survey ship sailing circle. The method of dealing with the systematic error based on a semi-parametric adjustment model was proposed. Firstly, the influence of sound velocity change on ranging error is analyzed. Secondly, a semi-parametric adjustment model for determining three-dimensional coordinates of seafloor control points was established. And respectively proposed solutions under two different conditions, the observation duration is an integral multiple or non-integer multiple of the long-period term of the ranging error. The simulation experiment shows that this method can obviously improve the accuracy of vertical solution of seafloor control point compared with the difference technique and the least-squares method when internal waves exist and observation duration is less than an integer multiple of the long-period term of the ranging error.

On the Survival Assessment of Asthmatic Patients Using Parametric and Semi-Parametric Survival Models

The goals of asthma management are to prevent or minimize symptoms, avert or reduce risk of asthma attacks and to ensure that asthma does not limit the patient’s activities since it is not curable. Thus in this study, the degrees of success following treatments given to patients over time were assessed based on the patient’s length of stay on admission and factors responsible for patients’ response to treatment were equally examined using survival analysis models of parametric and semi-parametric distributions. The study was conducted on 464 asthmatic patients from four different hospitals in Ogun State. The data were extracted from patients’ records and prognostic factors such as age, sex, smoking, hereditary, obesity, respiratory illness and environmental pollution were considered for survival analysis. It was observed that there was drastic reduction in survival rate from 7 days upward at a cut-off probability value of 0.485, based on Kaplan-Meier (KM) results. Log-normal regression model, a parametric model with the least AIC value (2969.74) and least negative Log likelihood value (1475.87) shows best performance in handling asthma data with prognostic factors of Smoking (HR = 1.32, 95% CI: 0.93 - 1.88), Obesity (HR = 1.25, 95% CI: 0.80 - 1.93), Environmental pollution (HR = 0.79, 95% CI: 0.52 - 1.18) and Respiratory illness (HR = 1.93, 95% CI: 1.33 - 2.79) were found to have significantly affected the length of stay of asthmatic patients in hospital.

糖尿病肾脏疾病预后影响因素的COX比例风险回归模型分析

目的基于COX比例风险回归模型分析糖尿病肾脏疾病(diabetic kidney disease,DKD)预后的影响因素,为临床早期评估和防治DKD提供科学的依据。方法收集多中心(河南中医药大学第一附属医院、河南中医药大学第三附属医院、河南省中医院及郑州市人民医院)2010—2021年就诊治疗的DKD患者资料,包括一般资料、实验室指标、中医辨证分型及中医药治疗,以肾小球滤过率(eGFR)下降≥50%、血肌酐(Scr)翻倍、DKD 5期、死亡为结局指标,随访其发生时间及情况,利用COX比例风险回归模型分析筛选DKD预后影响因素。结果本研究最终纳入1947例患者,随访时间为4.65(4.557~4.746)年,发生复合终点事件305例(15.67%)。单因素COX回归分析结果表明,不同年龄、DKD病程≥4年、饮酒史、吸烟史、高血压、冠心病、脑血管病、糖尿病足、糖尿病眼病、糖化血红蛋白(HbA1c)、血尿酸(SUA)、Scr、24 h尿蛋白定量(24 h-UTP)、eGFR、湿热血瘀证、脾肾气虚兼湿聚血瘀证、脾肾阳虚兼血瘀证、中药熏洗、服用中药患者DKD预后情况比较,差异有统计学意义(P<0.05)。多因素COX回归分析结果表明,年龄[HR(95%CI)=2.52(1.92,3.30)]、DKD病程[HR(95%CI)=1.62(1.09,2.42)]、吸烟史[HR(95%CI)=1.61(1.13,2.29)]、饮酒史[HR(95%CI)=1.41(1.01,1.95)]、脑血管病[HR(95%CI)=1.33(1.01,1.75)]、糖尿病眼病[HR(95%CI)=1.43(1.13,1.82)]、SUA[HR(95%CI)=1.72(1.26,2.33)]、24 h-UTP[HR(95%CI)=1.48(1.14,1.91)]、脾肾气虚兼湿聚血瘀证[HR(95%CI)=2.22(1.44,3.43)]与DKD发生终点事件的风险关系密切(P<0.05),服用中药[HR(95%CI)=2.57(2.00,3.31)]能够减少终点事件的发生(P<0.05)。结论年龄、DKD病程、吸烟史、饮酒史、脑血管病、糖尿病眼病、SUA、24 h-UTP、脾肾气虚兼湿聚血瘀证是影响DKD患者预后的危险因素,而服用中药治疗为其保护因素。

Cox模型中基于Model-X Knockoffs的高维控制变量选择方法

在生物医学、临床试验和流行病学等领域的研究中,由于获得生存数据的试验设计、观测时间的局限,以及观测对象在进入或退出试验时的个体差异等方面的原因,与所关注事件的发生时间相关的数据经常存在右删失。基于右删失生存数据解析协变量和生存时间的关系时,应用最为广泛的统计模型是Cox模型。随着科学技术的进步,数据收集变得越来越容易,导致数据库规模越来越大、复杂性越来越高,数据的维度通常可以达到成百上千维,甚至更高。文章提出一种Cox模型中基于Model-X Knockoffs的高维控制变量选择方法。首先基于Knockoffs框架建立一个Knockoffs变量,并基于原始协变量和其相应的Knockoffs变量构造一个正则化的目标函数,然后通过求解目标函数的最优解构造一个统计量和基于数据的阈值,最后进行变量选择。模拟分析和实证研究结果表明:所提方法可以在变量选择的同时提供可靠的FDR控制,优于传统的LASSO方法。

基于Cox健康行为互动模式的护理措施在宫颈癌患者护理中的应用

目的探讨基于Cox健康行为互动模式的护理措施在宫颈癌患者护理中的应用效果。方法选择2022年3月至2023年3月新乡医学院第一附属医院收治的96例宫颈癌术后患者作为研究对象,按随机数表法将患者分为对照组和观察组各48例。对照组患者术后采用常规护理,观察组患者在对照组护理的基础上给予基于Cox健康行为互动模式的护理措施,两组患者均接受护理至出院,出院后均随访3周。护理结束后出院时,比较两组患者的术后恢复情况(手术切口愈合时间、留置导尿管时间、住院时间)以及护理前、护理后T淋巴细胞亚群中CD3^(+)、CD4^(+)、CD4^(+)/CD8^(+)水平;随访3周回院复查时,比较两组患者的生活质量量表(SF-36)评分;护理结束后出院时,比较两组患者对护理工作的满意度。结果观察组患者的手术切口愈合时间、住院时间、留置导尿管时间分别为(7.60±1.39)d、(1.50±0.24)周、(17.78±2.11)d,明显短于对照组的(10.55±1.51)d、(2.54±0.30)周、(20.10±2.32)d,差异均有统计学意义(P<0.05);观察组患者护理后的CD3^(+)、CD4^(+)及CD4^(+)/CD8^(+)水平分别为(70.64±11.67)%、(39.91±5.23)%、1.50±0.27,明显高于对照组的(66.25±11.32)%、(35.21±5.08)%、1.24±0.18,差异均有统计学意义(P<0.05);随访3周回院复查时,观察组患者的家庭生活、精神活力、社交能力、心理承受评分分别为(36.14±1.58)分、(36.02±1.57)分、(37.10±2.55)分、(36.26±2.31)分,明显高于对照组的(32.31±1.62)分、(30.15±1.63)分、(32.19±2.40)分、(33.11±2.14)分,差异均有统计学意义(P<0.05);观察组患者对护理工作的满意度为95.83%,明显高于对照组的83.33%,差异有统计学意义(P<0.05)。结论基于Cox健康行为互动模式的护理措施在宫颈癌患者术后护理中的应用效果良好,能促进患者术后恢复,提高免疫功能和生活质量。

Clinical Study on the Impact of Long-term Survival Quality in 204 Postoperative Patients with Breast Cancer by Cox Proportional Hazard Models

The aim of study was to evaluate clinical characteristics, social support and the association with the prognosis of breast cancer patients. A total of 204 participants were followed from 2003 until the end of 2008. Information about patients with breast cancer was submitted by investigators. Data were analyzed by Cox’s proportional hazard model. The clinical staging of breast cancer we used was the TNM classification. A 'T' score is based upon the size and/or extent of invasion. The 'N' score indicates the extent of lymph node involvement. Age at diagnose was associated with protective factors (HR=0.972;95%CI (0.834-1.130)), T staging (HR=2.075;95%CI (1.424-3.022)), N staging (HR=1.513;95%CI (1.066-2.148)), were associated with risk factor. Two survival graphs of nodes with negative effects by histology and nodes with positive effects by histology was analyzed by log-rank test, there was statistically significant relationship between two survival graphs (χ2 =136.8467, p <.0001). Age at diagnoses, Clinical stage tumor and node could contribute to the development of breast cancer and disease free survival in Chinese women.

A Cox Proportional Hazard Model Approach to Age at First Sexual Intercourse in Nigeria

Early age at first sexual intercourse comes with many negative sexual outcomes namely: having unprotected sex on first sexual intercourse, condom misuse, high rate of sexually transmitted infections (STIs), teenage pregnancy, increased number of sexual partners, etc. In this paper, we considered some socio-demographic and cultural factors and their relationship with age at first sexual intercourse so as to reduce the numerous negative sexual outcomes of early age at first sexual intercourse using the 2018 Nigerian Demographic and Health Survey data. The analysis was made using the Cox proportional hazard model and the Kaplan-Meier plot. The result shows that some respondents started having their first sexual intercourse at the age of 8 years and about 54.4% of the respondents had their first sexual intercourse before age 17 years. The median age of first sexual intercourse is 16 years which implies that about 50% of the respondents had their first sexual intercourse on or before their 16th birthday. Education, religion, region and residence significantly affects the age of first sexual intercourse while circumcision has no significant effect.

Comparison of Cox proportional hazards model,Cox proportional hazards with time-varying coefficients model,and lognormal accelerated failure time model:Application in time to event analysis of melioidosis patients

Objective:To compare the prognostic factors of mortality among melioidosis patients between lognormal accelerated failure time(AFT),Cox proportional hazards(PH),and Cox PH with time-varying coefficient(TVC)models.Methods:A retrospective study was conducted from 2014 to 2019 among 453 patients who were admitted to Hospital Sultanah Bahiyah,Kedah and Hospital Tuanku Fauziah,Perlis in Northern Malaysia due to confirmed-cultured melioidosis.The prognostic factors of mortality from melioidosis were obtained from AFT survival analysis,and Cox’s models and the findings were compared by using the goodness of fit methods.The analyses were done by using Stata SE version 14.0.Results:A total of 242 patients(53.4%)survived.In this study,the median survival time of melioidosis patients was 30.0 days(95%CI 0.0-60.9).Six significant prognostic factors were identified in the Cox PH model and Cox PH-TVC model.In AFT survival analysis,a total of seven significant prognostic factors were identified.The results were found to be only a slight difference between the identified prognostic factors among the models.AFT survival showed better results compared to Cox's models,with the lowest Akaike information criteria and best fitted Cox-snell residuals.Conclusions:AFT survival analysis provides more reliable results and can be used as an alternative statistical analysis for determining the prognostic factors of mortality in melioidosis patients in certain situations.

The Cox Proportional Hazard Regression Model Vis-à-Vis ITN-Factor Impact on Mortality Due to Malaria

This study has provided a starting point for defining and working with Cox models in respect of multivariate modeling. In medical researches, there may be situations, where several risk factors potentially affect patient prognosis, howbeit, only one or two might predict patient’s predicament. In seeking to find out which of the risk factors contribute the most to the survival times of patients, there was the need for researchers to adjust the covariates to realize their impact on survival times of patients. Aside the multivariate nature of the covariates, some covariates might be categorical while others might be quantitative. Again, there might be cases where researchers need a model that has the capability of extending survival analysis methods to assessing simultaneously the effect of several risk factors on survival times. This study unveiled the Cox model as a robust technique which could accomplish the aforementioned cases. An investigation meant to evaluate the ITN-factor vis-à-vis its contribution towards death due to Malaria was exemplified with the Cox model. Data were taken from hospitals in Ghana. In doing so, we assessed hospital in-patients who reported cases of malaria (origin state) to time until death or censoring (destination stage) as a result of predictive factors (exposure to the malaria parasites) and some socioeconomic variables. We purposefully used Cox models to quantify the effect of the ITN-factor in the presence of other risk factors to obtain some measures of effect that could describe the relationship between the exposure variable and time until death adjusting for other variables. PH assumption holds for all three covariates. Sex of patient was insignificant to deaths due to malaria. Age of patient and user status were both significant. The magnitude of the coefficient (0.384) of ITN user status depicts its high contribution to the variation in the dependent variable.

The Cox-Aalen Models as Framework for Construction of Bivariate Probability Distributions, Universal Representation

Starting with the Aalen （1989） version of Cox （1972） ＇regression model＇ we show the method for construction of ＂any＂ joint survival function given marginal survival functions. Basically, however, we restrict ourselves to model positive stochastic dependences only with the general assumption that the underlying two marginal random variables are centered on the set of nonnegative real values. With only these assumptions we obtain nice general characterization of bivariate probability distributions that may play similar role as the copula methodology. Examples of reliability and biomedical applications are given.

SURVIVAL ANALYSIS OF GASTRIC CANCER PATIENTS BY COX REGRESSION MODEL

Mortality rate of gastric cancer is about 20.93/100000 which is the highest malignancy in China. The scientist of our country are at present interested in studying the postoperative survival model by multivariate analysis method just as stepwise regression model. The proportional hazard model initiated by Cox (1972) is more advanced than other regression method which is unneccessary to suppose the distribution of survival time and easy to analyse censoring data (the latter is difficult). This paper presented the first time application of Cox model in survival analysis of gastric cancer in China. The survival analysis system (SAS-Ⅰ) software complied by the author includes multivariate anlysis by Cox model, PV analysis and estimation of survival function which could provide useful information to surgeon for treatment of cancer patients.

Analysis of Prognostic Factors of Esophageal and Gastric Cardiac Carcinoma Patients after Radical Surgery Using Cox Proportional Hazard Model-A Random Sampling Study from the Fourth Hospital of Hebei Medical University during the Period of 1996-2004

OBJECTIVE To retrospectively analyze clinical data of patientsfrom our hospital who underwent radical surgery for esophagealcarcinoma and for adenocarcinoma of the gastric cardia,as well asto investigate prognostic factors affecting the long-term survival ofthe patients.METHODS Data from the patients eligible for our study,admitted to the 4th Hospital of Hebei Medical University fromJanuary 1996 to December 2004,were randomized,and 12distinctive clinicopathologic factors influencing the survival rateof those who underwent radical surgery for esophageal carcinomaor carcinoma of the gastric cardia were collected.Univariate andmultivariate analysis of these individual variables were performedusing the Cox proportional hazard model.RESULTS It was shown by univariate analysis that age,tumorsize,pathologic type,lymph node status,TNM staging,depthof infiltration and encroachment into local organs,etc.,were thefactors that markedly influenced the prognosis of patients(P<0.01).Multivariate analysis showed that pathologic type,numberof the lymph node metastases,involvement of local organs,andTNM staging were independent prognostic factors(P<0.05).CONCLUSION The independent factors influencing theprognosis of patients with esophageal cancer and carcinoma ofthe gastric cardia include pathologic type,number of lymph nodemetastases,involvement of local organs and TNM staging.Themain prognostic factors affecting the patient's survival are patientage,tumor size and depth of infiltration.In addition,patients withinvolvement of the local organs have a worse prognosis,and theyshould be closely followed up.

Penalized Empirical Likelihood Via Adaptive LASSO for Cox＇s Proportional Hazards Model

Penalized empirical likelihood inferential procedure is proposed for Cox＇s pro- portional hazards model with adaptive LASSO（ALASSO）. Under reasonable conditions, we show that the proposed method has oracle property and the limiting distribution of a penal- ized empirical likelihood ratio via ALASSO is a chi-square distributions. The advantage of penalized empirical likelihood is illustrated in testing hypothesis and constructing confidence sets by simulation studies and a real example.

Analysis of Length of Stay (LOS) Data from the Medical Records of Tertiary Care Hospital in Saudi Arabia for Five Diagnosis Related Groups: Application of Cox Prediction Model

Background: One of the main objectives of hospital managements is to control the length of stay (LOS). Successful control of LOS of inpatients will result in reduction in the cost of care, decrease in nosocomial infections, medication side effects, and better management of the limited number of available patients’ beds. The length of stay (LOS) is an important indicator of the efficiency of hospital management by improving the quality of treatment, and increased hospital profit with more efficient bed management. The purpose of this study was to model the distribution of LOS as a function of patient’s age, and the Diagnosis Related Groups (DRG), based on electronic medical records of a large tertiary care hospital. Materials and Methods: Information related to the research subjects were retrieved from a database of patients admitted to King Faisal Specialist Hospital and Research Center hospital in Riyadh, Saudi Arabia between January 2014 and December 2016. Subjects’ confidential information was masked from the investigators. The data analyses were reported visually, descriptively, and analytically using Cox proportional hazard regression model to predict the risk of long-stay when patients’ age and the DRG are considered as antecedent risk factors. Results: Predicting the risk of long stay depends significantly on the age at admission, and the DRG to which a patient belongs to. We demonstrated the validity of the Cox regression model for the available data as the proportionality assumption is shown to be satisfied. Two examples were presented to demonstrate the utility of the Cox model in this regard.

Sequential Shrinkage Estimate for COX Regression Models with Uncertain Number of Effective Variables

In the applications of COX regression models, we always encounter data sets that contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “noneffective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model based on an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size. Fixed design is considered for numerical simulation. The strong consistency, asymptotic distributions and convergence rates of estimates under the fixed design are obtained. In addition, the sequential procedure is shown to be asymptotically optimal in the sense of Chow and Robbins (1965).

Cox Proportional Hazard Model for Survival Time of Neonatal Mortality in Neonatal Intensive Care Unit of Hospitals in River Nile State-Sudan

Cox Proportional Hazard model is a popular statistical technique for exploring the relationship between the survival time of neonates and several explanatory variables. It provides an estimate of the study variables’ effect on survival after adjustment for other explanatory variables, and allows us to estimate the hazard (or risk) of death of newborn in NICU of hospitals in River Nile State-Sudan for the period (2018-2020). Study Data represented (neonate gender, mode of delivery, birth type, neonate weight, resident type, gestational age, and survival time). Kaplan-Meier method is used to estimate survival and hazard function for survival times of newborns that have not completed their first month. Of 700 neonates in the study area, 25% of them died during 2018-2020. Variables of interest that had a significant effect on neonatal death by Cox Proportional Hazard Model analysis were neonate weight, resident type, and gestational age. In Cox Proportional Hazard Model analysis all the variables of interest had an effect on neonatal death, but the variables with a significant effect included, weight of neonate, resident type and gestational age.

基于Cox健康行为互动模式的护理在乳腺癌化疗患者中的应用

目的:探讨基于Cox健康行为互动模式(IMCHB)的护理对乳腺癌化疗患者健康结局的影响。方法:选取2016年1月1日—2019年1月1日河南省人民医院收治的109例接受化疗的乳腺癌患者,排除随访丢失4例,不遵从医嘱治疗5例,不签署受试者知情同意书8例,共纳入92例作为研究对象。采用随机对照试验设计方案将其分为观察组(n=46)和对照组(n=46)。比较两组患者治疗依从性、护理服务满意度、自我护理能力、焦虑自评量表(SAS)评分、抑郁自评量表(SDS)评分、生活质量、常见化疗不良反应发生情况。结果:观察组患者治疗依从性和护理服务满意度评分高于对照组,差异有统计学意义(t=5.340、8.388,P<0.05)。治疗后,观察组患者自我护理能力评分高于对照组,差异有统计学意义(t=0.067,P<0.05);观察组患者焦虑自评量表SAS、SDS评分低于对照组,差异有统计学意义(t=-2.019、-2.084,P<0.05);观察组患者功能领域评分高于对照组,症状领域评分低于对照组,差异有统计学意义(t=0.006、0.904、0.687、3.278、3.551、1.999、-4.457、-3.089、-2.690、-2.588,P<0.05)。观察组患者不良反应发生率低于对照组,差异有统计学意义(χ^(2)=14.194,P<0.05)。结论:基于IMCHB的护理能提高乳腺癌化疗患者的治疗依从性、护理服务满意度、自我护理能力,降低患者的焦虑和抑郁情绪及化疗不良反应发生率,改善患者的生活质量。

急性硬膜下血肿患者围术期继发颅内高压的Cox比例风险预测模型的建立及评价

目的构建急性硬膜下血肿(ASDH)患者围术期继发颅内高压的Cox比例风险预测模型,并对其效能进行验证。方法回顾性收集78例ASDH患者的临床资料,按围术期继发颅内高压情况将其分为继发组(25例,围术期继发颅内高压)和对照组(53例,围术期未继发颅内高压)。比较2组患者人口统计学指标、合并症、临床生化指标及影像学资料等因素的差异。应用Cox比例风险模型对ASDH患者围术期继发颅内高压的可能影响因素进行多因素分析。建立ASDH患者围术期继发颅内高压的预测模型并测算Harrell′s C指数以评估模型预测的准确度。通过列线图及校准曲线评估该模型预测风险概率与实际风险概率的符合程度。结果全组半年随访率为89.74%(70/78)。继发组年龄、吸烟史、高血压病、糖尿病、术前格拉斯哥昏迷量表(GCS)评分、格拉斯哥预后量表(GOS)评分、复合型血肿、颅内血肿体积、平均动脉压、糖化血红蛋白(HbA1c)、国际标准化比值(INR)、白细胞介素-6(IL-6)、降钙素原(PCT)与对照组比较,差异有统计学意义(P<0.05)。年龄(OR=2.895,95%CI:1.264~6.633,P=0.022)、吸烟史(OR=2.146,95%CI:1.029~4.475,P=0.036)、GOS评分(OR=0.288,95%CI:0.112~0.741,P=0.015)、HbA1c(OR=3.325,95%CI:1.243~8.894,P=0.028)、INR(OR=2.746,95%CI:1.203~6.267,P=0.027)、PCT(OR=3.426,95%CI:1.335~8.795,P=0.019)是ASDH患者围术期继发颅内高压的独立影响因素,Harrell′s C指数为0.812(95%CI:0.789~0.872)。列线图及校准曲线显示实际风险与模型预测风险存在较好的一致性。结论急性硬膜下血肿患者的Cox比例风险模型预测围术期继发颅内高压风险的准确度高,适宜临床推广。

Cox-IMCHB在急性淋巴细胞白血病学龄前儿童口腔黏膜炎干预中的应用研究

目的:探讨Cox健康行为互动模式(Cox-IMCHB)应用于急性淋巴细胞白血病(ALL)学龄前儿童口腔黏膜炎干预中的效果。方法:采用便利抽样法选取2023年1—12月于中国医学科学院血液病医院(中国医学科学院血液学研究所)进行化疗的50例ALL患儿,将其按照入院时间进行分组,2023年1—6月收治的患儿为对照组,2023年7—12月收治的患儿为研究组,各25例。对照组采取常规健康教育模式,研究组采取Cox-IMCHB的护理干预,比较两组口腔黏膜炎的发生率、严重程度、持续时间及患儿口腔治疗依从性和照顾者满意度调查表得分。结果:干预后,研究组患儿口腔黏膜炎发生率低于对照组(χ^(2)=5.433,P<0.05),口腔黏膜炎持续时间中位数为3.00(2.50,3.00)d,短于对照组[5.00(3.75,6.00)d(Z=-3.293,P<0.05)]。干预后,对照组患儿的口腔护理依从性低于研究组(Z=-3.906,P<0.001),对照组照顾者满意度调查表得分低于研究组(t=-15.127,P<0.001)。结论:基于Cox-IMCHB的干预方案可提高ALL学龄前儿童口腔治疗的依从性,降低口腔黏膜炎的发生率,缩短口腔黏膜炎的持续时间,提升照顾者满意度。

老年原发性肝癌微波消融术后复发危险因素的多元COX回归分析

目的按探讨老年原发性肝癌微波消融术后复发多元COX回归模型。方法去选择我院于2018年9月至2021年9月收治的原发性肝癌患者183例,均行微波消融术治疗。所有患者均随访至2023年9月,定期门诊、住院随访,于微波消融术后前3个月内,每月进行1次随访,之后以每3个月进行1次随访,随访终点为患者出现肿瘤复发。以完全消融术后肝内重复出现肝癌或者远处发生转移为复发。采用多元COX回归模型分析影响老年原发性肝癌微波消融术后复发危险因素。结果随访末,微波消融术治疗原发性肝癌患者183例中,复发患者39例,复发率为21.31%。单因素COX回归分析,不同性别、不同年龄、家族史、合并肝硬化、Chlid-Pugh分级、AST、ALT、HBVDNA阳性、腹水、脾大和消融次数复发率比较无明显差异(P>0.05);肿瘤直径>3cm复发率高于肿瘤直径≤3cm,AFP>400ng/ml复发率高于AFP≤400ng/ml(P<0.05)。经多元C0X回归模型分析显示,肿瘤直径>3cm和血清AFP>400ng/ml为影响微波消融术后复发危险因素。结论老年原发性肝癌微波消融术后复发率较高,而肿瘤直径和血清AFP为其危险因素.