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cox proportional hazard model for Survival Time of Neonatal Mortality in Neonatal Intensive Care Unit of Hospitals in River Nile State-Sudan

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Open Journal of Statistics 2022年第5期12卷 634-657页

作者： Abdellateef Khalifa Hamid Ali Amin Ibrahim Adam Mohammed Faculty of Mathematical Science El-Fashir University El-Fashir Sudan Faculty of Economics & Political Sciences Omdurman Islamic University Omdurman 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.

关键词： Neonatal Mortality cox proportional hazard model Survival Function Haz-ard Function Kaplan-Meier Method

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Log-normal censored regression model detecting prognostic factors in gastric cancer:A study of 3018 cases

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World Journal of Gastroenterology 2011年第23期17卷 2867-2872页

作者： A Latengbaolide Department of Breast Surgery General surgerythe First Hospital of China Medical University

AIM:To investigate the efficiency of cox proportional hazard model in detecting prognostic factors for gastric ***:We used the log-normal regression model to evaluate prognostic factors in gastric cancer and compared it with the cox *** thousand and eighteen gastric cancer patients who received a gastrectomy between 1980 and 2004 were retrospectively ***-pathological factors were included in a log-normal model as well as cox *** akaike information criterion (AIC) was employed to compare the efficiency of both *** analysis indicated that age at diagnosis,past history,cancer location,distant metastasis status,surgical curative degree,combined other organ resection,Borrmann type,Lauren's classification,pT stage,total dissected nodes and pN stage were prognostic factors in both log-normal and cox ***:In the final multivariate model,age at diagnosis,past history,surgical curative degree,Borrmann type,Lauren's classification,pT stage,and pN stage were significant prognostic factors in both log-normal and cox ***,cancer location,distant metastasis status,and histology types were found to be significant prognostic factors in log-normal results *** to AIC,the log-normal model performed better than the cox proportional hazard model (AIC value:2534.72 vs 1693.56).CONCLUSION:It is suggested that the log-normal regression model can be a useful statistical model to evaluate prognostic factors instead of the cox proportional hazard model.

关键词： Gastric cancer Log normal regression mod-el cox proportional hazard model Prognostic factors

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High Cycle Fatigue Life Prediction and Reliability Analysis of Aeroengine Blades

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Transactions of Tianjin University 2012年第6期18卷 456-464页

作者：张俊红林杰威张桂昌刘海 State Key Laboratory of Engines Tianjin University

Based on the nonlinear continuum damage model （CDM） developed by Chaboehe, a modified model for high cycle fatigue of TC4 alloy was proposed. Unsymmetrical cycle fatigue tests were conducted on rod specimens at room temperature. Then the material parameters needed in the CDM were obtained by the fatigue tests, and the stress distribution of the specimen was calculated by FE method. Compared with the linear damage model （LDM）, the dam- age results and the life prediction of the CDM show a better agreement with the test and they are more precise than the LDM. By applying the CDM developed in this study to the life prediction of aeroengine blades, it is concluded that the root is the most dangerous region of the whole blade and the shortest life is 58 211 cycles. Finally, the cox propor- tional hazard model of survival analysis was applied to the analysis of the fatigue reliability. The cox model takes the covariates into consideration, which include diameter, weight, mean stress and tensile strength. The result shows that the mean stress is the only factor that accelerates the fracture process.

关键词： life prediction reliability continuum damage model survival analysis cox proportional hazard model aeroengine blade

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Risk prediction model for cutaneous squamous cell carcinoma in adult cardiac allograft recipients

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World Journal of Transplantation 2021年第3期11卷 54-69页

作者： Nandini Nair Zhiyong Hu Dongping Du Enrique Gongora Division of Cardiology Department of Internal MedicineTexas Tech Health Sciences CenterLubbockTX 79430United States Department of Industrial Manufacturing and Systems EngineeringTexas Tech UniversityLubbockTX 79409United States Department of Cardiothoracic Surgery University of Alabama at BirminghamBirminghamAL 35233United States

BACKGROUND Heart transplant recipients are at higher risk of developing skin cancer than the general population due to the long-term immunosuppression *** has been reported as one of the major causes of morbidity and mortality for patients after heart *** different types of skin cancers,cutaneous squamous cell carcinoma(cSCC)is the most common one,which requires timely screening and better *** To identify risk factors and predict the incidence of cSCC for heart transplant *** We retrospectively analyzed adult heart transplant recipients between 2000 and 2015 extracted from the United Network for Organ Sharing *** whole dataset was randomly divided into a derivation set(80%)and a validation set(20%).Uni-and multivariate cox regression were done to identify significant risk factors associated with the development of *** operating characteristics curves were generated and area under the curve(AUC)was calculated to assess the accuracy of the prediction *** on the selected risk factors,a risk scoring system was developed to stratify patients into different risk groups.A cumulative cSCC-free survival curve was generated using the Kaplan-Meier method for each group,and the log-rank test was done to compare the intergroup cSCC *** There were 23736 heart-transplant recipients during the study period,and 1827 of them have been reported with *** predictors of post-transplant cSCC were older age,male sex,white race,recipient and donor human leukocyte antigen(HLA)mismatch level,malignancy at listing,diagnosis with restrictive myopathy or hypertrophic myopathy,heart re-transplant,and induction therapy with OKT3 or *** multivariate model was used to predict the 5-,8-and 10-year incidence of cSCC and respectively provided AUC of 0.79,0.78 and 0.77 in the derivation set and 0.80,0.78 and 0.77 in the validation *** risk scoring system assigned each patient with a

关键词： Cutaneous squamous cell carcinoma Heart transplantation cox proportional hazard model Risk assessment Squamous cell carcinoma Mortality outcomes

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Prognostic analysis of patients with thymoma after resection

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Journal of Medical Colleges of PLA(China) 2004年第1期19卷 31-34页

作者：薛志强王如文蒋耀光 Department of Thoracic Surgery Daping Hospital Third Military Medical University

Objective: To explore the prognostic factors influencing the long term survival rate of thymoma after resection. Methods: Sixty nine patients with thymoma surgically treated in our department from 1973 to 2000 were retrospectively studied. The possible prognostic factors were analyzed by univariate analysis and multivariate analysis with Kaplan Meiter method and cox proportional hazard model respectively. Results: Overall patients survival rates were 83.3%, 67.4%, 48.3% at 5, 10, 15 years. The significant prognostic factors ( P <0 05) demonstrated by univariate analysis included age, Masaoka staging, WHO histological classification, resection method and Rosai/Levine classification. According to multivariate analysis, the independent prognostic factors included Masaoka stage ( P <0 01), resection method ( P <0 05) and age ( P <0 05). Conclusion: Complete surgical resection of thymomas helps increase the long term survival rate.

关键词： thymoma cox proportional hazard model prognosis

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Longitudinal genetic analysis for growth traits in the complete diallel cross of rainbow trout

Longitudinal genetic analysis for growth traits in the compl...

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第六届全国动植物数量遗传学学术研讨会

作者：宋禹昕中国农业科学院北京畜牧兽医研究所

Usually,statistical methods for mapping quantitative trait loci(QTL)require that the phenotypes follow the normal distribution and therefore may not be appropriate to analyze survival traits of skewed *** a result,parametric and semi-parametric models in survival analysis are incorporated into the framework of the interval mapping for survival trait *** formulating the effects of the QTL genotype on the survival time with a cox proportional hazards(PH)model,we construct a general

关键词： Survival time cox proportional hazard model Survival distribution Interval mapping Optimization

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过度需求还是有效需求？

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社会保障制度 2010年第10期

作者：黄枫甘犁

本文利用2002-2005年“中国老年人健康长寿影响因素调查数据”(CLHLS)来估计医疗保险对我国城镇老年人总医疗支出和家庭自付医疗支出，以及老年人死亡风险的影响。利用两部模型和扩展的样本选择模型研究医疗支出发现，在过去一年中享受... 详细信息

本文利用2002-2005年“中国老年人健康长寿影响因素调查数据”(CLHLS)来估计医疗保险对我国城镇老年人总医疗支出和家庭自付医疗支出，以及老年人死亡风险的影响。利用两部模型和扩展的样本选择模型研究医疗支出发现，在过去一年中享受医疗保险的老人，家庭自付医疗支出比无保险的老人低43％(约合1149元)，而总医疗支出则比无保险的老人高28％-37％(约合1072元-1264元)。cox比例风险模型的结果表明，享受医疗保险的老人，死亡风险比无保险的老人低19％；利用扩展的Kaplan-Meier生存函数估计平均生存时间发现，享受医疗保险的老人的平均生存时间比无保险的老人多5年。研究表明，享受医疗保险的老人按生存概率加权的平均总医疗支出为64689元，无医疗保险的老人的医疗支出为42198元，总医疗支出相差22491元，预期寿命相差5年，医疗支出对健康的边际效应较高。我国公共医疗保险制度的选择应侧重于满足老年人的医疗需求，进一步提高老年人的健康和寿命，建立病有所医、老有所养的和谐社会。

关键词：医疗保险医疗支出两部模型样本选择模型 cox比例风险模型 Health Insurance Medical Expenditure Two-part model Sample Selection model cox proportional hazard model

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