Factors affecting enduring participation in a pig farming program in Southern Papua, Indonesia.

In mid-2016, the local government of Papua, Indonesia, launched a subsidised program to improve pig farming in the area, with 250 participants. This study aimed to investigate factors associated with enduring participation in pig farming among the program participants. Two years after the commencement of the program, one hundred of the 250 participants were recruited into the study and divided into two groups: participants who continued to engage in pig farming ("remain") and those who had quit pig farming ("quit"). Data were collected from interviews, including personal data and events on the farms between April 2017 and March 2018. Multiple correspondence analysis, followed by a two-step cluster analysis and multivariate regression, was used to explore factors associated with the durability of pig farmings. Results indicated that associated factors included feed and water security, the use of concrete material for the pig house floor, the avoidance of swill feeding, reduced pig mortality, and continued pig husbandry training. This study highlights that a good feeding regimen and effective control of pig diseases should be priority pig husbandry techniques to be extended through training and assistance to improve traditional pig farming in Papua.

Comparison of risks of cardiovascular events in the elderly using standard survival analysis and multiple-events and recurrent-events methods.

BACKGROUND: Epidemiological studies about cardiovascular diseases often rely on methods based on time-to-first-event for data analysis. Without taking into account multiple event-types and the recurrency of a specific cardiovascular event, this approach may underestimate the overall cardiovascular burden of some risk factors, if that is the goal of the study. METHODS: In this study we compare four different statistical approaches, all based on the Weibull distribution family of survival model, in analyzing cardiovascular risk factors. We use data from the Cardiovascular Health Study as illustration. The four models respectively are time-to-first-event only, recurrent-events only, multiple-event-types only, and joint recurrent and multiple-event-type models. RESULTS: Although the four models produce consistent results regarding the significance of the risk factors, the magnitude of the hazard ratios and their confidence intervals are different. The joint model produces hazard ratios that are substantially higher than the time-to-first-event model especially for the risk factors of smoking and diabetes. CONCLUSION: Our findings suggest that for people with diabetes and are currently smoking, the overall cardiovascular burden of these risk factors would be substantially higher than that estimated using time-to-first-event method.

A multilevel model for hierarchical, repeated, and overdispersed time-to-event outcomes and its estimation strategies.

The aim of this article is to propose a multilevel combined model for repeated, hierarchical, and overdispersed time-to-event outcomes, extending the so-called combined model proposed by Molenberghs et al. (2010), and using three different estimation strategies: full likelihood, pseudo-likelihood, and Bayesian estimation. For the first two estimation methods, we implemented the alternating imputation posterior (AIP) algorithm (Clayton and Rasbash, 1999). It is shown that the multilevel combined model can be fitted nicely using all three estimation methods. In addition, the multilevel combined model has the advantage that it not only can capture the hierarchical structure of the data but also can accommodate overdispersion within the data set. From our simulation results, it follows that the multilevel combined model performs well in terms of point estimation and its precision, fitted with the three different estimation methods. We also observed that pairwise likelihood estimation, a particular form of pseudo-likelihood, is more time-intensive than full likelihood and Bayesian estimation. However, pseudo-likelihood estimation is less sensitive to starting values.

A joint model for longitudinal continuous and time-to-event outcomes with direct marginal interpretation.

Joint modeling of various longitudinal sequences has received quite a bit of attention in recent times. This paper proposes a so-called marginalized joint model for longitudinal continuous and repeated time-to-event outcomes on the one hand and a marginalized joint model for bivariate repeated time-to-event outcomes on the other. The model has several appealing features. It flexibly allows for association among measurements of the same outcome at different occasions as well as among measurements on different outcomes recorded at the same time. The model also accommodates overdispersion. The time-to-event outcomes are allowed to be censored. While the model builds upon the generalized linear mixed model framework, it is such that model parameters enjoy a direct marginal interpretation. All of these features have been considered before, but here we bring them together in a unified, flexible framework. The model framework's properties are scrutinized using a simulation study. The models are applied to data from a chronic heart failure study and to a so-called comet assay, encountered in preclinical research. Almost surprisingly, the models can be fitted relatively easily using standard statistical software.

Relapse-Free Survival as a Surrogate for Overall Survival in the Evaluation of Stage II-III Melanoma Adjuvant Therapy.

Background: We assessed whether relapse-free survival (RFS; time until recurrence/death) is a valid surrogate for overall survival (OS) among resected stage II-III melanoma patients through a meta-analysis of randomized controlled trials. Methods: Individual patient data (IPD) on RFS and OS were collected from 5826 patients enrolled in 11 randomized adjuvant trials comparing interferon (IFN) to observation. In addition, IPD from two studies comparing IFN and vaccination in 989 patients were included. A two-level modeling approach was used for assessing Spearman's patient-level correlation (rho) of RFS and OS and the trial-level coefficient of determination (R²) of the treatment effects on RFS and on OS. The results were validated externally in 13 adjuvant studies without available IPD. We then tested the results on the European Organisation for Research and Treatment of Cancer (EORTC) 18071 double-blind trial comparing ipilimumab 10 mg/kg with placebo, which showed a statistically significant impact of the checkpoint inhibitor on RFS and OS. All statistical tests were two-sided. Results: With a median follow-up of seven years, 12 of 13 trials showed a consistency between the IFN vs No IFN differences regarding RFS (hazard ratio [HR]RFS = 0.88) and OS (HROS = 0.91), but the small trial, Eastern Cooperative Oncology Group 2696, was an outlier (HRRFS = 0.72 vs HROS = 1.11). Therefore, even if rho was high, R² was low and could not reliably be estimated. Based on the 12 trials, rho remained high (0.89), and the hazard ratios for RFS and OS were strongly correlated (R² = 0.91). The surrogate threshold effect for RFS was estimated to be 0.77. For the EORTC 18071 trial, the hazard ratio for RFS was 0.75, predicting an effect of ipilimumab on OS. This was subsequently confirmed (HROS = 0.72, 95.1% confidence interval = 0.58 to 0.88, P = .001). Conclusions: In high-risk stage II-III melanoma, RFS appeared to be a valid surrogate end point for OS for adjuvant randomized studies assessing interferon or a checkpoint inhibitor. In future similar adjuvant studies, a hazard ratio for RFS of 0.77 or less would predict a treatment impact on OS.

A goodness-of-fit test for the random-effects distribution in mixed models.

In this paper, we develop a simple diagnostic test for the random-effects distribution in mixed models. The test is based on the gradient function, a graphical tool proposed by Verbeke and Molenberghs to check the impact of assumptions about the random-effects distribution in mixed models on inferences. Inference is conducted through the bootstrap. The proposed test is easy to implement and applicable in a general class of mixed models. The operating characteristics of the test are evaluated in a simulation study, and the method is further illustrated using two real data analyses.

A combined gamma frailty and normal random-effects model for repeated, overdispersed time-to-event data.

This paper presents, extends, and studies a model for repeated, overdispersed time-to-event outcomes, subject to censoring. Building upon work by Molenberghs, Verbeke, and Demétrio (2007) and Molenberghs et al. (2010), gamma and normal random effects are included in a Weibull model, to account for overdispersion and between-subject effects, respectively. Unlike these authors, censoring is allowed for, and two estimation methods are presented. The partial marginalization approach to full maximum likelihood of Molenberghs et al. (2010) is contrasted with pseudo-likelihood estimation. A limited simulation study is conducted to examine the relative merits of these estimation methods. The modeling framework is employed to analyze data on recurrent asthma attacks in children on the one hand and on survival in cancer patients on the other.

Early alteration of kidney function in nonuremic type 1 diabetic islet transplant recipients under tacrolimus-mycophenolate therapy.

BACKGROUND: Transplant patients on tacrolimus therapy exhibit a reduced glomerular filtration rate (GFR). The type of graft and immune treatment protocol may influence the extent and reversibility of this side effect. METHODS: The present single-center study is conducted in 48 nonuremic type 1 diabetic recipients of an intraportal islet-cell graft under maintenance immunosuppression (IS) with tacrolimus and mycophenolate mofetil. Estimated GFR (eGFR) and albuminuria were followed up to 5 years posttransplantation. RESULTS: Mean eGFR values decreased by 19 mL/min/1.73 m after 1 to 2 weeks of IS (P<0.0001) and then remained stable throughout the complete treatment period. The decrease was related to predose trough tacrolimus concentrations or doses and disappeared upon its discontinuation; it was also associated with the presence of albuminuria at the time of transplantation. Tacrolimus treatment resulted in a reduction of albuminuria; its discontinuation restored albuminuria to the initial levels. CONCLUSIONS: The use of tacrolimus in our islet-cell transplant protocol caused an initial 20% reduction in eGFR, which was reversible following its discontinuation, at least within the 5-year follow-up period. The associated reduction in albuminuria was also reversible, compatible with a tacrolimus-induced preglomerular vasoconstriction. These observations support further use of our tacrolimus regimen in this patient population.