Achmad Efendi

Bio: Achmad Efendi is an academic researcher from University of Brawijaya. The author has contributed to research in topics: Overdispersion & Random effects model. The author has an hindex of 8, co-authored 24 publications receiving 152 citations. Previous affiliations of Achmad Efendi include University of Hasselt & Katholieke Universiteit Leuven.

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

Abstract: 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

Abstract: 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.

Truck Driver Behavior and Travel Time Effectiveness Using Smart GPS

Abstract: The pattern of coal transportation is very dependent on the behaviour of the driver, which influences the effectiveness of travel time. Good driver behaviour will affect the optimization of travel time, and scenarios need to reduce travel time wastage. This study aims to optimize travel time and sensitivity analysis based on the influence of driver behaviour, truck travel movements and the use of travel time on coal haul roads. The research method uses a field survey with a GPS tracker, a smart GPS server 3.3, google earth and statistics. The results showed that the driver's behaviour greatly influenced the pattern of use of travel time and truck travel speed. Coal transportation in the morning can be more optimal than night so that that travel time wastage can reduced by 40%. The proposed optimization scenarios can save 36.7% - 48.61% of the existing travel time and the transport cycle can be increased to four to five times. So that with the addition of the cycle, it will increase the income of the transport company and the driver's income. With smart GPS, companies can improve the performance of transportation services in company management, get coal supplies on time.

A simulation study on Bayesian Ridge regression models for several collinearity levels

Abstract: When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression p...

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

Abstract: 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 Demetrio (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.

Adjuvant Pembrolizumab versus Placebo in Resected Stage III Melanoma

Abstract: Background The programmed death 1 (PD-1) inhibitor pembrolizumab has been found to prolong progression-free and overall survival among patients with advanced melanoma. We conducted a phase 3 double-blind trial to evaluate pembrolizumab as adjuvant therapy in patients with resected, high-risk stage III melanoma. Methods Patients with completely resected stage III melanoma were randomly assigned (with stratification according to cancer stage and geographic region) to receive 200 mg of pembrolizumab (514 patients) or placebo (505 patients) intravenously every 3 weeks for a total of 18 doses (approximately 1 year) or until disease recurrence or unacceptable toxic effects occurred. Recurrence-free survival in the overall intention-to-treat population and in the subgroup of patients with cancer that was positive for the PD-1 ligand (PD-L1) were the primary end points. Safety was also evaluated. Results At a median follow-up of 15 months, pembrolizumab was associated with significantly longer recurrence...

Handbook of Statistical Distributions with Applications

Abstract: The targeted audience for this book is graduate students in engineering and medical statistics courses, and it may be useful for a senior undergraduate statistics course. To get the maximum benefit from this book, one should have a good knowledge and understanding of calculus and sufficient background in elementary probability theory to understand the central limit theorem and the law of large numbers. Some more sophisticated probability terminologies and concepts are defined for a smooth reading of the monograph. This monograph has 10 chapters, including the introduction. Chapter 2 deals with the ageing concept and some usual parametric families of probability distribution are presented in Chapter 3. Parametric and nonparametric statistical inference are nicely treated in Chapters 4 and 5. Chapter 5 also offers tests for exponentiality, which is one of the main feature of the monograph. Chapters 7 and 8 cover two-sample and regression problems, respectively. All of the preceding chapters showcase results for both complete and censored data. One of the interesting contributions is with regard to the analysis of competing risk, which is presented in Chapter 9. Finally, Chapter 10 introduces repairable systems. One of the main strengths of this book is that it introduces the public domain R software and nicely explains how it can be used in computations of methods presented in the book. This book has sufficient material and examples to cover a one semester (13week) course. However, I would be reluctant to adopt this book for one simple reason—there are no exercises. Having said that, the monograph would be useful to some applied researchers in related fields.

Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R

Abstract: Clustered covariances or clustered standard errors are very widely used to account for correlated or clustered data, especially in economics, political sciences, and other social sciences. They are employed to adjust the inference following estimation of a standard least-squares regression or generalized linear model estimated by maximum likelihood. Although many publications just refer to "the" clustered standard errors, there is a surprisingly wide variety of clustered covariances, particularly due to different flavors of bias corrections. Furthermore, while the linear regression model is certainly the most important application case, the same strategies can be employed in more general models (e.g., for zero-inflated, censored, or limited responses). In R, functions for covariances in clustered or panel models have been somewhat scattered or available only for certain modeling functions, notably the (generalized) linear regression model. In contrast, an object-oriented approach to "robust" covariance matrix estimation - applicable beyond lm() and glm() - is available in the sandwich package but has been limited to the case of cross-section or time series data. Starting with sandwich 2.4.0, this shortcoming has been corrected: Based on methods for two generic functions (estfun() and bread()), clustered and panel covariances are provided in vcovCL(), vcovPL(), and vcovPC(). Moreover, clustered bootstrap covariances are provided in vcovBS(), using model update() on bootstrap samples. These are directly applicable to models from packages including MASS, pscl, countreg, and betareg, among many others. Some empirical illustrations are provided as well as an assessment of the methods' performance in a simulation study.

Adjuvant pembrolizumab versus placebo in resected stage III melanoma (EORTC 1325-MG/KEYNOTE-054): distant metastasis-free survival results from a double-blind, randomised, controlled, phase 3 trial

Abstract: Summary Background The European Organisation for Research and Treatment of Cancer (EORTC) 1325/KEYNOTE-054 trial assessed pembrolizumab versus placebo in patients with resected high-risk stage III melanoma. At 15-month median follow-up, pembrolizumab improved recurrence-free survival (hazard ratio [HR] 0·57 [98·4% CI 0·43–0·74], p Methods This double-blind, randomised, controlled, phase 3 trial was done at 123 academic centres and community hospitals across 23 countries. Patients aged 18 years or older with complete resection of cutaneous melanoma metastatic to lymph node, classified as American Joint Committee on Cancer staging system, seventh edition (AJCC-7) stage IIIA (at least one lymph node metastasis >1 mm), IIIB, or IIIC (without in-transit metastasis), and with an Eastern Cooperative Oncology Group performance status of 0 or 1 were eligible. Patients were randomly assigned (1:1) via a central interactive voice response system to receive intravenous pembrolizumab 200 mg or placebo every 3 weeks for up to 18 doses or until disease recurrence or unacceptable toxicity. Randomisation was stratified according to disease stage and region, using a minimisation technique, and clinical investigators, patients, and those collecting or analysing the data were masked to treatment assignment. The two coprimary endpoints were recurrence-free survival in the intention-to-treat (ITT) population and in patients with PD-L1-positive tumours. The secondary endpoint reported here was distant metastasis-free survival in the ITT and PD-L1-positive populations. This study is registered with ClinicalTrials.gov , NCT02362594 , and EudraCT, 2014-004944-37. Findings Between Aug 26, 2015, and Nov 14, 2016, 1019 patients were assigned to receive either pembrolizumab (n=514) or placebo (n=505). At an overall median follow-up of 42·3 months (IQR 40·5–45·9), 3·5-year distant metastasis-free survival was higher in the pembrolizumab group than in the placebo group in the ITT population (65·3% [95% CI 60·9–69·5] in the pembrolizumab group vs 49·4% [44·8–53·8] in the placebo group; HR 0·60 [95% CI 0·49–0·73]; p Interpretation Pembrolizumab adjuvant therapy provided a significant and clinically meaningful improvement in distant metastasis-free survival at a 3·5-year median follow-up, which was consistent with the improvement in recurrence-free survival. Therefore, the results of this trial support the indication to use adjuvant pembrolizumab therapy in patients with resected high risk stage III cutaneous melanoma. Funding Merck Sharp & Dohme.

Longer Follow-Up Confirms Recurrence-Free Survival Benefit of Adjuvant Pembrolizumab in High-Risk Stage III Melanoma: Updated Results From the EORTC 1325-MG/KEYNOTE-054 Trial.

Abstract: PURPOSEWe conducted the phase III double-blind European Organisation for Research and Treatment of Cancer (EORTC) 1325/KEYNOTE-054 trial to evaluate pembrolizumab versus placebo in patients with re...