scholarly journals Survival Analysis of Duration of exclusive breastfeeding in Ethiopia: Comparison of Proportional Hazard model and Accelerated Failure Time models

2021 ◽  
Author(s):  
Bacha Ewunetu Gemechu ◽  
Tilahun Bedaso Merga
Keyword(s):  
Failure Time ◽  
Mode Of Delivery ◽  
Wealth Index ◽  
Rank Test ◽  
Accelerated Failure Time ◽  
Proportional Hazard ◽  
Aft Model ◽  
Log Rank Test ◽  
Kaplan Meier ◽  
Accelerated Failure

Abstract Introduction Early cessation of EBF has the short and long term effect for the welfare of infants including the life-long impacts of poor school performance, reduced productivity, and impaired intellectual development. Objective of the study: the main objective of this study was to compare the performance of CPH model and AFT models in analyzing EBF data in Ethiopia, 2016 EDHS. Specifically, the study aimed to identify the major predictor variables of the duration of EBF based on 2016 EDHS data.Methodology: The secondary data is obtained from Ethiopian Demographic and Health Survey (EDHS), 2016. The outcome variable of this study was the duration of EBF in month. To achieve the objective of the study, descriptive survival analysis like the median survival time, Kaplan Meier survival estimate and log-rank test were used to compare the estimated survival probability among different levels of predictor variables at 5 percent significant level. The Cox proportional hazard regression and Accelerated failure time model were fitted and their results were compared using model comparison criterion such as AIC, BIC.Results: of 1092 interviewed mothers, 15.3 % of them were discontinued EBF and 84.7% of them were exclusively breastfed (censored). The estimated median duration of EBF was 3 months. Based on estimated Kaplan Meier survival curve and log-rank test, it was found that there was a statistically significant difference in survivor experience of discontinuing EBF over each duration with respect to place of delivery, maternal education, husband education, mode of delivery and employment status. The fitted CPH and AFT model indicated that mode of delivery, wealth index, and employment status was found as significant predictors of EBF duration. Moreover, comparatively Weibull AFT model performed better in analyzing EBF data. According to the fitted model, mothers who were in poor wealth index category and who gave birth by cesarean shortens the duration of EBF by 16% and 29% respectively. On the other hand, employed mothers were improved the duration of EBF by 26%. Conclusion: Weibull AFT model is performed better in analyzing EBF data. A mother who was unemployed, poor wealth index, and gave birth by cesarean shortens the duration of EBF than their counterparts. Therefore, special emphasis should be given for mothers who are unemployed, who are economically poor, and give birth by cesarean to improve the duration of EBF.

The regression analysis of correlated interval-censored data

2009 ◽  
Vol 9 (4) ◽  
pp. 299-319 ◽  
Author(s):  
Arnošt Komárek ◽  
Emmanuel Lesaffre
Keyword(s):  
Failure Time ◽  
Accelerated Failure Time ◽  
Proportional Hazard ◽  
Survival Times ◽  
R Language ◽  
Aft Model ◽  
Practical Usefulness ◽  
Interval Censored ◽  
Accelerated Failure ◽  
Research Questions

The accelerated failure time (AFT) model is a useful alternative to the proportional hazard model for modelling interval-censored survival times. We illustrate the usefulness of a class of flexible AFT models. Flexibility is achieved by assuming that the distributional parts consist of penalized Gaussian mixtures. The AFT models are introduced and exemplified via research questions originating from a longitudinal dental study conducted in Flanders (North of Belgium). Emphasis is put on the analyzes which are performed using routines written in the R-language. They show the practical usefulness of our approach.

Efficient parameter estimation for multivariate accelerated failure time model via the quadratic inference functions method

2019 ◽  
Vol 08 (04) ◽  
pp. 1950013
Author(s):  
Liya Fu ◽  
Zhuoran Yang ◽  
Mingtao Zhao ◽  
Yan Zhou
Keyword(s):  
Correlation Matrix ◽  
Marginal Distribution ◽  
Failure Time ◽  
Correlation Structure ◽  
Accelerated Failure Time Model ◽  
Accelerated Failure Time ◽  
Aft Model ◽  
Accelerated Failure ◽  
Correlation Parameters ◽  
Quadratic Inference Functions

A popular approach, generalized estimating equations (GEE), has been applied to the multivariate accelerated failure time (AFT) model of the clustered and censored data. However, this method needs to estimate the correlation parameters and calculate the inverse of the correlation matrix. Meanwhile, the efficiency of the parameter estimators is low when the correlation structure is misspecified and/or the marginal distribution is heavy-tailed. This paper proposes using the quadratic inference functions (QIF) with a mixture correlation structure to estimate the coefficients in the multivariate AFT model, which can avoid estimating the correlation parameters and computing the inverse matrix of the correlation matrix. Moreover, the estimator derived from the QIF is consistent and asymptotically normal. Simulation studies indicate that the proposed method outperforms the method based on GEE when the marginal distribution has a heavy tail. Finally, the proposed method is used to analyze a real dataset for illustration.

scholarly journals Using the Weibull accelerated failure time regression model to predict time to health events

2018 ◽  
Author(s):  
Enwu Liu ◽  
Karen Lim
Keyword(s):  
Regression Model ◽  
Failure Time ◽  
Prediction Method ◽  
Accelerated Failure Time ◽  
Related Event ◽  
Health Events ◽  
Aft Model ◽  
Worked Example ◽  
Health Related ◽  
Accelerated Failure

AbstractWe describe a statistical method protocol to use a Weibull accelerated failure time (AFT) model to predict time to a health-related event. This prediction method is quite common in engineering reliability research but rarely used for medical predictions such as survival time. A worked example for how to perform the prediction using a published dataset is included.

scholarly journals COMPARISON OF STRATIFIED WEIBULL MODEL AND WEIBULL ACCELERATED FAILURE TIME (AFT) MODEL IN THE ANALYSIS OF CERVICAL CANCER SURVIVAL

2016 ◽  
Vol 78 (6-4) ◽  
Author(s):  
Nurliyana Juhan ◽  
Nuradhiathy Abd Razak ◽  
Yong Zulina Zubairi ◽  
Nyi Nyi Naing ◽  
Che Haziqah Che Hussin ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Survival Time ◽  
Median Survival ◽  
Distant Metastasis ◽  
Median Survival Time ◽  
Failure Time ◽  
Weibull Model ◽  
Accelerated Failure Time ◽  
Aft Model ◽  
Accelerated Failure

Cervical cancer is the fourth most common cancer affecting women worldwide, after breast, colorectal, and lung cancers with 528 000 new cases every year. It is also the fourth most common cause of cancer death with 266 000 deaths in 2012 among women worldwide. In Malaysia it remains to be a great concern among clinicians; yet published works on survival of cervical cancer patients are somewhat limited. In this study, two survival regression models which are parametric Stratified Weibull model and Weibull Accelerated Failure Time (AFT) model are considered as the alternative and improvement of the well-known Cox proportional hazard model to evaluate the prognostic factor that effect on survival of patients with cervical cancer. Comparisons were made to find the best model. Data were taken from Hospital University Science Malaysia (HUSM) over a period of 12 years. From the analyses it was found that the AFT model was the most appropriate. The AFT model has shown that the median survival time for patient at stage III & IV (14 months) is about one third that of those at stages I & II (40 months) for the same distant metastasis group. While, the median survival time for patient with distant metastasis (17 months) is half that of those without distant metastasis (34 months) for the same stage group.

ACCELERATED FAILURE TIME MODELS COMPARISON TO THE PROPORTIONAL HAZARD MODEL FOR TIME-DEPENDENT COVARIATES WITH RECURRING EVENTS

2014 ◽  
Vol 21 (02) ◽  
pp. 1450010 ◽  
Author(s):  
ALEXANDRE C. MENDES ◽  
NASSER FARD
Keyword(s):  
Failure Time ◽  
Hazard Model ◽  
Parametric Model ◽  
Time Dependent ◽  
Accelerated Failure Time ◽  
Proportional Hazard ◽  
Proportional Hazard Model ◽  
Accelerated Failure Time Models ◽  
Accelerated Failure ◽  
Time Dependent Covariates

This paper presents an analysis of parametric survival models and compares their applications to time to event data used to validate the approximation for repeated events applying the Proportional Hazard Model (PHM) proposed in Mendes and Fard [Int. J. Reliab., Qual. Saf. Eng.19(6) (2012) 1240004.1–1240004.18]. The subjects studied do not show degrading failures, allowing the comparison between accelerated failure time models with the PHM. Results showed the applicability of the Weibull model and the versatility of the PHM not only to match the results of the parametric model, but also to allow the implementation of time-dependent covariates, resulting in superior model fit and more insightful interpretation for the covariate hazards. The paper contribution is to present the PHM as a simpler, more robust model to determine the acceleration factor for reliability testing when compared to the formidable task of fitting a parametric model for the distribution of failure. The Kaplan–Meier method may provide misleading guidance for covariate significance when time-dependent covariates are applied; however, relevant graphical screening is supplied. Notwithstanding, the PHM provides additional options to treat the repeated observations applying robust covariance correction for lack of heterogeneity in the fixed effects model or adopting the stratified model that absorbs the error using the stratification concept.

scholarly journals Metformin and Diabetes Prevention in Patients with Prediabetes: Results from Isfahan Diabetes Prevention Study (IDPS)

2021 ◽  
pp. 65-74
Author(s):  
Parisa Khodabandeh Shahraki ◽  
Awat Feizi ◽  
Ashraf Aminorroaya ◽  
Mahboubeh Farmani ◽  
Massoud Amini
Keyword(s):  
Diabetes Prevention ◽  
Rank Test ◽  
Proportional Hazard ◽  
Medical Sciences ◽  
Cox Proportional Hazard ◽  
Log Rank Test ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Adjusted Model

Aim: Although, the effectiveness of metformin in diabetes treatment is well established, its preventive effect in the development of diabetes is still unclear in real world. We aimed to determine the effectiveness of metformin therapy as a single preventive agent in patients with prediabetes in a cohort study (IDPS). Study Design: In this prospective observational study. Place and Duration of Study: Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. Methodology: We included 410 patients with prediabetes (168 metformin user, 242 non-users), who participated in IDPS. To determine the association between metformin use and incidence of type 2 diabetes, Cox proportional hazard method, Kaplan-Meier and log Rank test were used. Results: In fully adjusted model for all confounders, significant hazard ratio (HR) for staying prediabetes rather than returning to normal was detected in male group of metformin non-user (HR: 2·41 [95% CI 1.01-5.79]; P<0·05) and those metformin non-user who had both Impaired Fasting Glucose and Impaired Glucose Tolerance (IFG & IGT) (HR: 2.13 [95% CI 1.05-4.34]; P=0·04).  There was no significant difference in terms of developing diabetes risk between metformin users and non-users. Conclusion: This study evidenced that males and patients with IFG & IGT who had not used metformin are at higher risk to staying prediabetes than returning to normal.

scholarly journals IMPLEMENTASI MODEL ACCELERATED FAILURE TIME (AFT) BERDISTRIBUSI LOG-LOGISTIK PADA PASIEN PENYAKIT JANTUNG BAWAAN

2022 ◽  
Vol 10 (4) ◽  
pp. 518-531
Author(s):  
Dwi Nooriqfina ◽  
Sudarno Sudarno ◽  
Rukun Santoso
Keyword(s):  
Pulmonary Hypertension ◽  
Survival Time ◽  
Failure Time ◽  
Defect Size ◽  
Accelerated Failure Time ◽  
Hypertension Status ◽  
Aft Model ◽  
Pain Status ◽  
Accelerated Failure ◽  
First Recurrence

Log-Logistic Accelerated Failure Time (AFT) model is survival analysis that is used when the survival time follows Log-Logistic distribution. Log-Logistic AFT model can be used to estimate survival time, survival function, and hazard function. Log-Logistic AFT model was formed by regressing covariates linierly against the log of survival time. Regression coefficients are estimated using maximum likelihood method. This study uses data from Atrial Septal Defect (ASD) patients, which is a congenital disease with a hole in the wall that separates the top of two chambers of the heart by using sensor type III. Survival time as the response variable, that is the time from patient was diagnosed with ASD until the first relapse and uses age, gender, treatment status (catheterization/surgery), defect size that is the size of the hole in the heart terrace, pulmonary hypertension status, and pain status as predictor variables. The result showed that variable gender, treatment status, defect size, pulmonary hypertension status, and pain status affect the first recurrence of ASD patients, so it is found that category of female, untreated patient, defect size ≥12mm, having pulmonary hypertension, having chest pain tend to have first recurrence sooner than the other category. 

scholarly journals Alkaline Water and Longevity: A Murine Study

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Massimiliano Magro ◽  
Livio Corain ◽  
Silvia Ferro ◽  
Davide Baratella ◽  
Emanuela Bonaiuto ◽  
...  
Keyword(s):  
Survival Data ◽  
Failure Time ◽  
Control Group ◽  
Accelerated Failure Time ◽  
Survival Functions ◽  
Alkaline Water ◽  
Aft Model ◽  
Accelerated Failure ◽  
Second Year ◽  
Aging Factor

The biological effect of alkaline water consumption is object of controversy. The present paper presents a 3-year survival study on a population of 150 mice, and the data were analyzed with accelerated failure time (AFT) model. Starting from the second year of life, nonparametric survival plots suggest that mice watered with alkaline water showed a better survival than control mice. Interestingly, statistical analysis revealed that alkaline water provides higher longevity in terms of “deceleration aging factor” as it increases the survival functions when compared with control group; namely, animals belonging to the population treated with alkaline water resulted in a longer lifespan. Histological examination of mice kidneys, intestine, heart, liver, and brain revealed that no significant differences emerged among the three groups indicating that no specific pathology resulted correlated with the consumption of alkaline water. These results provide an informative and quantitative summary of survival data as a function of watering with alkaline water of long-lived mouse models.

Absolute T Cell Counts At Diagnosis Predict Absolute Lymphocyte Counts Throughout Therapy For Pediatric Acute Lymphoblastic Leukemia: Evidence For Age-Related Loss Of T Cells and Poor Outcome

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2599-2599
Author(s):  
Catherine H. Boston ◽  
Jimin Wu ◽  
Diane Liu ◽  
Michele Guindani ◽  
Patrick A Zweidler-McKay
Keyword(s):  
T Cells ◽  
T Cell ◽  
Older Patients ◽  
Failure Time ◽  
Lymphoblastic Leukemia ◽  
Accelerated Failure Time ◽  
Time Analysis ◽  
Cell Numbers ◽  
Kaplan Meier ◽  
Accelerated Failure

Abstract Background Absolute lymphocyte count (ALC) during early therapy has been established as an independent prognostic factor in pediatric acute lymphoblastic leukemia (ALL). Importantly, ALC can refine minimal residual disease (MRD)-based risk stratification, particularly for MRD-positive patients. However age-dependent effects on ALC, the lymphocyte subtype (T, NK, B) which underlies this finding, and the role of ALC at relapse are not yet known. Methods Patients with de novo pediatric B-cell ALL had blood samples drawn biweekly during induction chemotherapy and lymphocyte subsets analyzed at different time points by flow cytometry. In addition, ALC was recorded at time points throughout induction and early consolidation chemotherapy, in maintenance therapy, and at time of relapse. Demographic, NCI risk, and treatment characteristics were also collected. Continuous variables were analyzed with Pearson’s coefficient, and categorical variables were analyzed with two-sided Barnard’s test. Survival statistics were measured with Kaplan-Meier curves and accelerated failure time analysis. Results A total of 21 children and young adults with B-cell ALL were identified with a median age of 17 years (range 0.5-35 years). Although not unexpectedly, T cells comprise the majority of lymphocytes that make up the ALC in nearly all cases. Interestingly, absolute CD3+ T cell count at diagnosis (ATC-0) correlates with ALC-15 (p=0.0008) and ALC during maintenance chemotherapy (p=0.01), revealing that T cell numbers at diagnosis predict total lymphocyte count recovery during early treatment as well as 8+ months later. The averages of ATC-0= 828 cells/ul and ALC-maintenance= 940 cells/ul were significant cutoffs as 89% of patients with low ATC-0 had low ALC during maintenance, and 75% of patients with high ATC-0 at diagnosis had high ALC during maintenance (p=0.03). In addition, age was inversely correlated with both ATC-0 and ALC-15 (p=0.035 and 0.006 respectively), linking that older patients have lower ALCs, which correlate to poor outcome. Indeed, 80% of patients with ALC-15 over 500 were < 10 years of age, while 87% of patients with ALC-15 under 500 cells/ul were >/= 10 years at diagnosis (p=0.007). Interestingly, patients with high ATC-0 had 100% 5 year OS while patients with low ATC-0 had 52% 5 year OS (p=0.1), a trend toward significance on Kaplan-Meier curves due to the low number of ATC-0 high patients (n=4) we had in this high risk patient population. However, ALC-15, ALC in maintenance, and age at diagnosis all independently had a significant correlation with RFS in accelerated failure time analysis (p=0.01, 0.0001, and 0.03 respectively). And importantly, ALC at relapse significantly correlated with OS in accelerated failure time analysis (p=0.0001). Discussion In this study, we demonstrate that ALC in ALL patients is inversely correlated with age, reflecting the normal decrease in ALC seen in healthy children, adolescents, and young adults. We also identified T cells as the predominant lymphocyte subtype comprising the ALC, which may reflect an immune reservoir in these patients. Importantly, T cell numbers at diagnosis (ATC-0) predict lymphocyte counts throughout treatment and also inversely correlate with age. This suggests that patients with low T cell numbers at diagnosis continue to have low T cell numbers late into treatment. As ALC and ATC decline with age, this could provide one potential mechanism for why older patients have worse outcomes from ALL. Clinically, ATC at diagnosis may identify patients at risk for relapse and help determine appropriate induction and post-induction therapy. In the future, patients with low ATC/ALC may benefit from immune-modulating therapy, which may overcome a limited immune reservoir. Acknowledgments St. Baldrick’s Foundation Fellow Award Kimberly Patterson Leukemia Research Fellowship Disclosures: No relevant conflicts of interest to declare.

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