Journal articles on the topic 'Non-informative censoring'
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Arboretti, Rosa, Roberto Fontana, Fortunato Pesarin, and Luigi Salmaso. "Nonparametric combination tests for comparing two survival curves with informative and non-informative censoring." Statistical Methods in Medical Research 27, no. 12 (June 28, 2017): 3739–69. http://dx.doi.org/10.1177/0962280217710836.
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This paper looks at permutation methods used to deal with hypothesis testing within the survival analysis framework. In the literature, several attempts have been made to deal with the comparison of survival curves and, depending on the survival and hazard functions of two groups, they can be more or less efficient in detecting differences. Furthermore, in some situations, censoring can be informative in that it depends on treatment effect. Our proposal is based on the nonparametric combination approach and has proven to be very effective under different configurations of survival and hazard functions. It allows the practitioner to test jointly on primary and censoring events and, by using multiple testing methods, to assess the significance of the treatment effect separately on the survival and the censoring process.
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Nishikawa, Masako, Toshiro Tango, and Makiko Ogawa. "Non-parametric inference of adverse events under informative censoring." Statistics in Medicine 25, no. 23 (March 8, 2006): 3981–4003. http://dx.doi.org/10.1002/sim.2511.
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López-López, José A., Jonathan A. C. Sterne, and Julian P. T. Higgins. "Selection bias introduced by informative censoring in studies examining effects of vaccination in infancy." International Journal of Epidemiology 48, no. 6 (May 9, 2019): 2001–9. http://dx.doi.org/10.1093/ije/dyz092.
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Abstract Background Many studies have examined ‘non-specific’ vaccine effects on infant mortality: attention has been particularly drawn to diphtheria-tetanus-pertussis (DTP) vaccine, which has been proposed to be associated with an increased mortality risk. Both right and left censoring are common in such studies. Methods We conducted simulation studies examining right censoring (at measles vaccination) and left censoring (by excluding early follow-up) in a variety of scenarios in which confounding was and was not present. We estimated both unadjusted and adjusted hazard ratios (HRs), averaged across simulations. Results We identified scenarios in which right-censoring at measles vaccination was informative and so introduced bias in the direction of a detrimental effect of DTP vaccine. In some, but not all, situations, adjusting for confounding by health status removed the bias caused by censoring. However, such adjustment will not always remove bias due to informative censoring: inverse probability weighting was required in one scenario. Bias due to left censoring arose when both health status and DTP vaccination were associated with mortality during the censored early follow-up and was in the direction of attenuating a beneficial effect of DTP on mortality. Such bias was more severe when the effect of DTP changed over time. Conclusions Estimates of non-specific effects of vaccines may be biased by informative right or left censoring. Authors of studies estimating such effects should consider the potential for such bias and use appropriate statistical approaches to control for it. Such approaches require measurement of prognostic factors that predict censoring.
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Ungolo, Francesco, and Edwin R. van den Heuvel. "Inference on latent factor models for informative censoring." Statistical Methods in Medical Research 31, no. 5 (January 25, 2022): 801–20. http://dx.doi.org/10.1177/09622802211057290.
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This work discusses the problem of informative censoring in survival studies. A joint model for the time to event and the time to censoring is presented. Their hazard functions include a latent factor in order to identify this joint model without sacrificing the flexibility of the parametric specification. Furthermore, a fully Bayesian formulation with a semi-parametric proportional hazard function is provided. Similar latent variable models have been described in literature, but here the emphasis is on the performance of the inferential task of the resulting mixture model with unknown number of components. The posterior distribution of the parameters is estimated using Hamiltonian Monte Carlo methods implemented in Stan. Simulation studies are provided to study its performance and the methodology is implemented for the analysis of the ACTG175 clinical trial dataset yielding a better fit. The results are also compared to the non-informative censoring case to show that ignoring informative censoring may lead to serious biases.
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Yu, Mengzhu, Yanqin Feng, Ran Duan, and Jianguo Sun. "Regression analysis of multivariate interval-censored failure time data with informative censoring." Statistical Methods in Medical Research 31, no. 3 (December 8, 2021): 391–403. http://dx.doi.org/10.1177/09622802211061668.
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Regression analysis of multivariate interval-censored failure time data has been discussed by many authors1–6. For most of the existing methods, however, one limitation is that they only apply to the situation where the censoring is non-informative or the failure time of interest is independent of the censoring mechanism. It is apparent that this may not be true sometimes and as pointed out by some authors, the analysis that does not take the dependent censoring into account could lead to biased or misleading results7,8. In this study, we consider regression analysis of multivariate interval-censored data arising from the additive hazards model and propose an estimating equation-based approach that allows for the informative censoring. The method can be easily implemented and the asymptotic properties of the proposed estimator of regression parameters are established. Also we perform a simulation study for the evaluation of the proposed method and it suggests that the method works well for practical situations. Finally, the proposed approach is applied to a set of real data.
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Bambey Guure, Chris, and Noor Akma Ibrahim. "Generalized Bayesian non-informative prior estimation of Weibull parameter with interval censoring." ScienceAsia 39S, no. 1 (2013): 75. http://dx.doi.org/10.2306/scienceasia1513-1874.2013.39s.075.
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Ejoku, Jonathan, Collins Odhiambo, and Linda Chaba. "Analysis of Recurrent Events with Associated Informative Censoring: Application to HIV Data." International Journal of Statistics in Medical Research 9 (November 16, 2021): 20–27. http://dx.doi.org/10.6000/1929-6029.2020.09.03.
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In this study, we adapt a Cox-based model for recurrent events; the Prentice, Williams and Peterson Total -Time (PWP-TT) that has largely, been used under the assumption of non-informative censoring and evaluate it under an informative censoring setting. Empirical evaluation was undertaken with the aid of the semi-parametric framework for recurrent events suggested by Huang [1] and implemented in R Studio software. For validation we used data from a typical HIV care setting in Kenya. Of the three models under consideration; the standard Cox Model had gender hazard ratio (HR) of 0.66 (p-value=0.165), Andersen-Gill had HR 0.46 (with borderline p-value=0.054) and extended PWP TT had HR 0.22 (p-value=0.006). The PWP-TT model performed better as compared to other models under informative setting. In terms of risk factors under informative setting, LTFU due to stigma; gender [base=Male] had HR 0.544 (p-value =0.002), age [base is < 37] had HR 0.772 (p-value=0.008), ART regimen [base= First line] had HR 0.518 (p-value= 0.233) and differentiated care model (Base=not on DCM) had HR 0.77(p-value=0.036). In conclusion, in spite of the multiple interventions designed to address incidences of LTFU among HIV patients, within-person cases of LTFU are usually common and recurrent in nature, with the present likelihood of a person getting LTFU influenced by previous occurrences and therefore informative censoring should be checked.
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Nagy, M., M. E. Bakr, and Adel Fahad Alrasheedi. "Analysis with Applications of the Generalized Type-II Progressive Hybrid Censoring Sample from Burr Type-XII Model." Mathematical Problems in Engineering 2022 (February 18, 2022): 1–21. http://dx.doi.org/10.1155/2022/1241303.
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In this article, based on the generalized Type-II progressive hybrid censoring sample from the Burr Type-XII distribution, maximum likelihood and Bayesian inference are discussed. Point and interval estimates of unknown parameters, reliability, and hazard functions are developed. We employed several loss functions, such as squared error, LINEX, and general entropy, as symmetric and asymmetric loss functions and various prior distributions as informative and non-informative priors for Bayesian inference of unknown parameters. Under a generalized Type-II progressive hybrid censoring sample, we also propose a Bayesian one-sample prediction for unobserved failures. We conduct simulation study using the MCMC algorithm for the Bayesian approach based on several prior distributions. Finally, we apply the results of the theoretical research to real data.
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Wax, Yohanan, Stuart G. Baker, and Blossom H. Patterson. "A Score Test for Non-Informative Censoring Using Doubly Sampled Grouped Survival Data." Applied Statistics 42, no. 1 (1993): 159. http://dx.doi.org/10.2307/2347418.
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Alotaibi, Refah, Hoda Rezk, Sanku Dey, and Hassan Okasha. "Bayesian estimation for Dagum distribution based on progressive type I interval censoring." PLOS ONE 16, no. 6 (June 2, 2021): e0252556. http://dx.doi.org/10.1371/journal.pone.0252556.
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In this paper, we consider Dagum distribution which is capable of modeling various shapes of failure rates and aging criteria. Based on progressively type-I interval censoring data, we first obtain the maximum likelihood estimators and the approximate confidence intervals of the unknown parameters of the Dagum distribution. Next, we obtain the Bayes estimators of the parameters of Dagum distribution under the squared error loss (SEL) and balanced squared error loss (BSEL) functions using independent informative gamma and non informative uniform priors for both scale and two shape parameters. A Monte Carlo simulation study is performed to assess the performance of the proposed Bayes estimators with the maximum likelihood estimators. We also compute credible intervals and symmetric 100(1 − τ)% two-sided Bayes probability intervals under the respective approaches. Besides, based on observed samples, Bayes predictive estimates and intervals are obtained using one-and two-sample schemes. Simulation results reveal that the Bayes estimates based on SEL and BSEL performs better than maximum likelihood estimates in terms of bias and MSEs. Besides, credible intervals have smaller interval lengths than confidence interval. Further, predictive estimates based on SEL with informative prior performs better than non-informative prior for both one and two sample schemes. Further, the optimal censoring scheme has been suggested using a optimality criteria. Finally, we analyze a data set to illustrate the results derived.
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Tsai, Tzong-Ru, Yuhlong Lio, Jyun-You Chiang, and Yi-Jia Huang. "A New Process Performance Index for the Weibull Distribution with a Type-I Hybrid Censoring Scheme." Mathematics 10, no. 21 (November 2, 2022): 4090. http://dx.doi.org/10.3390/math10214090.
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A new life performance index is proposed for evaluating the quality of lifetime products. The maximum likelihood estimation method and the Bayesian approaches using informative and non-informative prior distributions are utilized to infer the parameters of the Weibull distribution and the proposed new life performance index under a Type-I hybrid censoring scheme. Monte Carlo simulation results show that two Bayesian approaches outperform the maximum likelihood estimation method in terms of the measures of relative bias, relative mean square error, and coverage probability for the point and confidence interval estimators, respectively. The Bayesian approach using a non-informative prior distribution is recommended if the knowledge of setting up the hyper-parameters in the informative prior distribution is not available. Two real data sets are provided for illustration.
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Tahir, Muhammad, and Muhammad Aslam. "Bayesian Analysis of the 3-Component Mixture of Exponential Distribution Assuming the Non-Informative Priors." Revista Colombiana de Estadística 38, no. 2 (July 15, 2015): 431–52. http://dx.doi.org/10.15446/rce.v38n2.51670.
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Bayesian analysis of the 3-component mixture of an Exponential distribution under type-I right censoring scheme is considered in this paper. The Bayes estimators and posterior risks for the unknown parameters are derived under squared error loss function, precautionary loss function and DeGroot loss function assuming the non-informative (uniform and Jeffreys') priors. The Bayes estimators and posterior risks are viewed as a function of the test termination time. A simulation study is given to highlight and compare the properties of the Bayes estimates.
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Alotaibi, Refah, H. Rezk, and Sanku Dey. "MCMC Method for Exponentiated Lomax Distribution based on Accelerated Life Testing with Type I Censoring." WSEAS TRANSACTIONS ON MATHEMATICS 20 (July 5, 2021): 319–34. http://dx.doi.org/10.37394/23206.2021.20.33.
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Accelerated Life Testing (ALT) is an effective technique which has been used in different fields to obtain more failures in a shorter period of time. It is more economical than traditional reliability testing. In this article, we propose Bayesian inference approach for planning optimal constant stress ALT with Type I censoring. The lifetime of a test unit follows an exponentiated Lomax distribution. Bayes point estimates of the model parameters and credible intervals under uniform and log-normal priors are obtained. Besides, optimum test plan based on constant stress ALT under Type I censoring is developed by minimizing the pre-posterior variance of a specified low percentile of the lifetime distribution at use condition. Gibbs sampling method is used to find the optimal stress with changing time. The performance of the estimation methods is demonstrated for both simulated and real data sets. Results indicate that both the priors and the sample size affect the optimal Bayesian plans. Further, informative priors provide better results than non-informative priors.
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Bao, Weihang, Michael Gaffney, Milton L. Pressler, Rana Fayyad, Wayne Wisemandle, Bruce Beckerman, Katherine E. Wolski, and Steven E. Nissen. "Strengthening the interpretability of clinical trial results by assessing the effect of informative censoring on the primary estimand in PRECISION." Clinical Trials 17, no. 5 (July 9, 2020): 535–44. http://dx.doi.org/10.1177/1740774520934747.
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Background: The ICH E9(R1) addendum states that the strategy to account for intercurrent events should be included when defining an estimand, the treatment effect to be estimated based on the study objective. The estimator used to assess the treatment effect needs to be aligned with the estimand that accounted for intercurrent events. Regardless of the strategy, missing data resulting from patient premature withdrawal could undermine the robustness of the study results. Informative censoring due to dropouts in an events-based study is one such example. Sensitivity analyses using imputation methods are useful to examine the uncertainty due to informative censoring and address the robustness and strength of the study results. Methods: We assessed the effect of premature patient withdrawal in the PRECISION study, a randomized non-inferiority clinical trial of patients with chronic arthritic pain that compared the cardiovascular safety of three nonsteroidal anti-inflammatory drugs–based treatment policies or paradigms. The protocol-defined use of concomitant or rescue medications was permitted since changes in pain medications due to insufficient analgesia were expected in patients in this long-term study. Anticipating that premature study discontinuations could potentially lead to informative censoring, a supplementary analysis was pre-specified in which censored outcomes due to the premature study discontinuation were imputed based on adverse events that were clinically associated with the primary endpoint (cardiovascular outcome based on the Antiplatelet Trialists Collaboration composite endpoint). Furthermore, tipping point analyses were conducted to test the robustness of the primary analysis results by assuming data censored not at random. The level of increase at which the primary study conclusion would change was estimated. Results: For the analysis of time to first primary endpoint event through 30 months, 4065 out of the 24,081 enrolled patients were lost to follow-up, withdrew consent, or were no longer willing to participate in the study. These withdrawals occurred gradually and resulted in a cumulative total of 5893 censored patient-years of observation (10.2%). The rate of discontinuation and the baseline characteristics of the discontinued patients were similar across the three treatment groups. The non-inferiority conclusion from the primary analysis was confirmed in the supplementary analysis incorporating relevant adverse events. Furthermore, tipping point analyses demonstrated that in order to lose non-inferiority in the primary analysis, the risk of primary endpoint events during the censored observation time would have to increase by more than 2.7-fold in the celecoxib group while remaining constant in the other nonsteroidal anti-inflammatory drugs groups, demonstrating that the scenarios where the study results are invalid appear not plausible. Conclusions: Supplementary and sensitivity analyses presented to address informative censoring in PRECISION helped to further interpret and strengthen the study results.
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Krishna, Hare, Madhulika Dube, and Renu Garg. "Estimation of Stress Strength Reliability of Inverse Weibull Distribution under Progressive First Failure Censoring." Austrian Journal of Statistics 48, no. 1 (December 17, 2018): 14–37. http://dx.doi.org/10.17713/ajs.v47i4.638.
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In this article, estimation of stress-strength reliability $\delta=P\left(Y<X\right)$ based on progressively first failure censored data from two independent inverse Weibull distributions with different shape and scale parameters is studied. Maximum likelihood estimator and asymptotic confidence interval of $\delta$ are obtained. Bayes estimator of $\delta$ under generalized entropy loss function using non-informative and gamma informative priors is derived. Also, highest posterior density credible interval of $\delta$ is constructed. Markov Chain Monte Carlo (MCMC) technique is used for Bayes computation. The performance of various estimation methods are compared by a Monte Carlo simulation study. Finally, a pair of real life data is analyzed to illustrate the proposed methods of estimation.
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Chen, Qiyue, and Wenhao Gui. "Statistical Inference of the Generalized Inverted Exponential Distribution under Joint Progressively Type-II Censoring." Entropy 24, no. 5 (April 20, 2022): 576. http://dx.doi.org/10.3390/e24050576.
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In this paper, we study the statistical inference of the generalized inverted exponential distribution with the same scale parameter and various shape parameters based on joint progressively type-II censored data. The expectation maximization (EM) algorithm is applied to calculate the maximum likelihood estimates (MLEs) of the parameters. We obtain the observed information matrix based on the missing value principle. Interval estimations are computed by the bootstrap method. We provide Bayesian inference for the informative prior and the non-informative prior. The importance sampling technique is performed to derive the Bayesian estimates and credible intervals under the squared error loss function and the linex loss function, respectively. Eventually, we conduct the Monte Carlo simulation and real data analysis. Moreover, we consider the parameters that have order restrictions and provide the maximum likelihood estimates and Bayesian inference.
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Maringe, Camille, Sara Benitez Majano, Aimilia Exarchakou, Matthew Smith, Bernard Rachet, Aurélien Belot, and Clémence Leyrat. "Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data." International Journal of Epidemiology 49, no. 5 (May 9, 2020): 1719–29. http://dx.doi.org/10.1093/ije/dyaa057.
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Abstract Acquiring real-world evidence is crucial to support health policy, but observational studies are prone to serious biases. An approach was recently proposed to overcome confounding and immortal-time biases within the emulated trial framework. This tutorial provides a step-by-step description of the design and analysis of emulated trials, as well as R and Stata code, to facilitate its use in practice. The steps consist in: (i) specifying the target trial and inclusion criteria; (ii) cloning patients; (iii) defining censoring and survival times; (iv) estimating the weights to account for informative censoring introduced by design; and (v) analysing these data. These steps are illustrated with observational data to assess the benefit of surgery among 70–89-year-old patients diagnosed with early-stage lung cancer. Because of the severe unbalance of the patient characteristics between treatment arms (surgery yes/no), a naïve Kaplan-Meier survival analysis of the initial cohort severely overestimated the benefit of surgery on 1-year survival (22% difference), as did a survival analysis of the cloned dataset when informative censoring was ignored (17% difference). By contrast, the estimated weights adequately removed the covariate imbalance. The weighted analysis still showed evidence of a benefit, though smaller (11% difference), of surgery among older lung cancer patients on 1-year survival. Complementing the CERBOT tool, this tutorial explains how to proceed to conduct emulated trials using observational data in the presence of immortal-time bias. The strength of this approach is its transparency and its principles that are easily understandable by non-specialists.
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Garg, Renu, Madhulika Dube, and Hare Krishna. "Estimation of Parameters and Reliability Characteristics in Lindley Distribution Using Randomly Censored Data." Statistics, Optimization & Information Computing 8, no. 1 (February 17, 2020): 80–97. http://dx.doi.org/10.19139/soic-2310-5070-692.
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This article deals with the estimation of parameters and reliability characteristics of Lindley distribution underrandom censoring. Expected time on test based on randomly censored data is obtained. The maximum likelihood estimators of the unknown parameters and reliability characteristics are derived. The asymptotic, bootstrap p and bootstrap t confidence intervals of the parameters are constructed. The Bayes estimators of the parameters and reliability characteristics under squared error loss function using non-informative and gamma informative priors are obtained. For computing of Bayes estimates, Lindley approximation and MCMC methods are considered. Highest posterior density (HPD) credible intervals of the parameters are obtained using MCMC method. Various estimation procedures are compared using a Monte Carlo simulation study. Finally, a real data set is analyzed for illustration purposes.
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Kim, Soomin, Changhoon Oh, Won Ik Cho, Donghoon Shin, Bongwon Suh, and Joonhwan Lee. "Trkic G00gle: Why and How Users Game Translation Algorithms." Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (October 13, 2021): 1–24. http://dx.doi.org/10.1145/3476085.
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Individuals interact with algorithms in various ways. Users even game and circumvent algorithms so as to achieve favorable outcomes. This study aims to come to an understanding of how various stakeholders interact with each other in tricking algorithms, with a focus towards online review communities. We employed a mixed-method approach in order to explore how and why users write machine non-translatable reviews as well as how those encrypted messages are perceived by those receiving them. We found that users are able to find tactics to trick the algorithms in order to avoid censoring, to mitigate interpersonal burden, to protect privacy, and to provide authentic information for enabling the formation of informative review communities. They apply several linguistic and social strategies in this regard. Furthermore, users perceive encrypted messages as both more trustworthy and authentic. Based on these findings, we discuss implications for online review community and content moderation algorithms.
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Li, Jiaqi, Anil Vachani, Andrew Epstein, and Nandita Mitra. "A doubly robust approach for cost–effectiveness estimation from observational data." Statistical Methods in Medical Research 27, no. 10 (February 27, 2017): 3126–38. http://dx.doi.org/10.1177/0962280217693262.
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Estimation of common cost–effectiveness measures, including the incremental cost–effectiveness ratio and the net monetary benefit, is complicated by the need to account for informative censoring and inherent skewness of the data. In addition, since the two components of these measures, medical costs and survival are often collected from observational claims data, one must account for potential confounders. We propose a novel doubly robust, unbiased estimator for cost–effectiveness based on propensity scores that allow the incorporation of cost history and time-varying covariates. Further, we use an ensemble machine learning approach to obtain improved predictions from parametric and non-parametric cost and propensity score models. Our simulation studies demonstrate that the proposed doubly robust approach performs well even under mis-specification of either the propensity score model or the outcome model. We apply our approach to a cost–effectiveness analysis of two competing lung cancer surveillance procedures, CT vs. chest X-ray, using SEER-Medicare data.
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Bohnsack, Oliver, Annette Maria Schmid, Liddy Chen, and Barbara Chandler. "Challenges with the ODAC-proposed independent audit of site investigator assessments." Journal of Clinical Oncology 31, no. 15_suppl (May 20, 2013): e22161-e22161. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.e22161.
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e22161 Background: The ODAC (Oncologic Drug Advisory Committee) Meeting, July 24th, 2012, on “Evaluation of Radiologic Review of Progression-free Survival in Non-hematologic Malignancies” discussed the merits of implementing an audit process of the investigator assessments in certain oncology trials with PFS endpoint instead of a full Blinded Independent Central Review (BICR) of all cases. The discussion centered around two potential methods (Dodd et al., 2008, 2011 and Amit et al., 2011) – their methods aimed to reduce the risk of informative censoring based on site central discordance, streamline trial conduct and provide cost savings. Both methods provide novel and interesting approaches. However, based on logistical and especially statistical challenges we found that both proposed methods in their current form can not achieve either goal of reducing cost, complexity, time and data censoring challenges inherent in the BICR process. Methods: This paper criticially evaluate the proposed methods and challenge the proposed processes and provide detailed explanations to obstacles inherent logistically, timewise, statistically, operationally. Results: Both of the proposed methods increase the complexity of conducting Oncology trials. As such the study duration will not be shortened but rather extended in certain scenarios. The statistical consequences of a discrepancy rate between Local Evaluations (LE) and BICR are not fully foreseeable and not defined. Operationally, both sponsor and imaging CRO need to implement new and forego well established processes, increasing risk, complexity and the chance for errors. Conclusions: This paper gives examples why the proposed methods are not suitable in their current form to be implemented in Oncology trials and rather put sponsors and study data at risk.
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Mirzaei Salehabadi, Sedigheh, Debasis Sengupta, and Rahul Ghosal. "Estimating menarcheal age distribution from partially recalled data." Biostatistics 21, no. 4 (May 13, 2019): 876–94. http://dx.doi.org/10.1093/biostatistics/kxz013.
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Summary In a cross-sectional study, adolescent and young adult females were asked to recall the time of menarche, if experienced. Some respondents recalled the date exactly, some recalled only the month or the year of the event, and some were unable to recall anything. We consider estimation of the menarcheal age distribution from this interval-censored data. A complicated interplay between age-at-event and calendar time, together with the evident fact of memory fading with time, makes the censoring informative. We propose a model where the probabilities of various types of recall would depend on the time since menarche. For parametric estimation, we model these probabilities using multinomial regression function. Establishing consistency and asymptotic normality of the parametric maximum likelihood estimator requires a bit of tweaking of the standard asymptotic theory, as the data format varies from case to case. We also provide a non-parametric maximum likelihood estimator, propose a computationally simpler approximation, and establish the consistency of both these estimators under mild conditions. We study the small sample performance of the parametric and non-parametric estimators through Monte Carlo simulations. Moreover, we provide a graphical check of the assumption of the multinomial model for the recall probabilities, which appears to hold for the menarcheal data set. Our analysis shows that the use of the partially recalled part of the data indeed leads to smaller confidence intervals of the survival function.
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Wang, Mei-Cheng, and Chin-Tsang Chiang. "Non-parametric methods for recurrent event data with informative and non-informative censorings." Statistics in Medicine 21, no. 3 (2002): 445–56. http://dx.doi.org/10.1002/sim.1029.
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Zheng, Zhiyuan, Ebere Onukwugha, Nader Hanna, Emily S. Reese, Brian S. Seal, and C. Daniel Mullins. "How do first-line treatment and other factors affect the receipt of second-line treatment for elderly metastatic colon cancer patients?" Journal of Clinical Oncology 31, no. 4_suppl (February 1, 2013): 592. http://dx.doi.org/10.1200/jco.2013.31.4_suppl.592.
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592 Background: Metastatic colon cancer (mCC) patients might receive multiple lines of chemotherapy to improve survival or quality of life. However, factors associated with receipt of 1st and 2nd line treatment (TX) haven’t been fully investigated. Methods: Elderly (65+) SEER-Medicare patients diagnosed with mCC in 2003-2007 were followed until death or 12/31/2009 to examine factors for receipt of 1st and 2nd line TX. A Cox regression framework and inverse probability weighting (IPW) method were used to adjust for patients’ informative (death) and non-informative (dropout or end-of-study) censoring histories. Additionally, we controlled for patients’ 1st line TX in the IPW to determine factors for receipt of 2nd line TX. Results: Of 7,951 mCC patients, 3,266 patients received at least 1 line TX, and 1,440 went on to 2nd line TX. For 1st line TX, significant clinical factors were CCI = 2 (HR = 0.86; p = 0.02), oxygen use (HR = 0.74; p = 0.04), walking aid use (HR = 0.58; p = 0.02), and wheel chair use (HR = 0.50; p < 0.01); significant demographic characteristics were age groups 95+ (HR = 0.11; p < 0.01), 85-94 (HR = 0.24; p < 0.01), 75-84 (HR = 0.70; p < 0.01), as compared to 65+-74, female (HR = 1.12; p < 0.01), married (HR = 1.43; p < 0.01), and African American (AA) (HR = 0.80; p < 0.01); significant factors for socio-economics status were state buy-in status (SBI) (HR = 0.97; p < 0.01), and zip code level household median income (HR = 1.03; p < 0.01). For 2nd line TX, significant factors were hospital bed use (HR = 2.82; p = 0.05), oxygen use (HR = 0.68; p = 0.02), age group 85-94 (HR = 0.718; p = 0.02) as compared to 65+-74, and days delayed for 1stline TX (HR = 0.998; p < 0.01). Conclusions: Various factors were associated with receipt of 1st line TX. Conditional on the receipt of 1st line TX, many factors became insignificant for receipt of 2nd line TX, such as age, female, marriage status, AA, SBI, and zip code level household income. Hospital bed use reduced the probability of receipt of 1st line TX, but increased the probability of receipt of 2nd line TX.
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Lafage-Pochitaloff, Marina, Laurence Baranger, Mathilde Hunault, Wendy Cuccuini, Audrey Bidet, Nicole Dastugue, Isabelle Tigaud, et al. "Value of Cytogenetic Abnormalities in Adult Patients with Philadelphia Chromosome (Ph)-Negative Acute Lymphoblastic Leukemia (ALL) Treated in the Pediatric-Inspired Trials from the Group for Research on Adult ALL (GRAALL)." Blood 124, no. 21 (December 6, 2014): 492. http://dx.doi.org/10.1182/blood.v124.21.492.492.
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Abstract Background: Numerous recurrent chromosomal abnormalities have been described in adult Ph-negative ALL, often observed in small patient cohorts. In the largest MRC/ECOG study (Moorman, Blood 2007), t(4;11)(q21;q23), 14q32 involvement, complex karyotype (≥5 abnormalities), and low hypodiploidy/near triploidy (Ho-Tr) were associated with shorter event-free survival (EFS), while patients with high hyperdiploidy or del(9p) had a better outcome. We aimed to confirm these observations in 955 adult patients (15-60y; median, 35y) with Ph-negative ALL treated in the pediatric-inspired GRAALL-2003/2005 trials. Patients and Methods: Overall, a karyotype was performed for 946 (611 BCP-ALL, and 335 T-ALL), successful for 811 (523 BCP-ALL and 288 T-ALL) and abnormal in 590 patients (387 BCP-ALL and 203 T-ALL). FISH and/or PCR screening for relevant abnormalities and DNA index were also performed, finally allowing for the identification of cytogenetic abnormalities in 677/955 patients (71%). All were centrally reviewed. Ultimately, 857/955 patients (90%; 542 BCP-ALL and 315 T-ALL) could be classified in 18 exclusive primary cytogenetic subsets as detailed below. Endpoints were cumulative incidence of failure (CIF, including primary refractoriness and relapse) and EFS. With a median follow-up of 4 years, 5-year CIF and EFS were estimated in these patients at 31% and 51%, respectively. As some abnormalities, including MLL rearrangements, Ho/Tr, t(1;19)(q23;p13)/TCF3 and complex karyotypes were used to stratify allogeneic stem cell transplantation (SCT) in GRAALL trials, some comparisons were repeated after censoring patients transplanted in first CR at SCT time. Results: The 542 informative BCP-ALL patients were classified as: t(4;11)(q21;q23)/MLL-AFF1 (n=72; 13%); other MLL+ 11q23 abnormalities (n=11; 2%); t(1;19)(q23;p13)/TCF3-PBX1 (#28; 5%); Ho/Tr (n=33; 6%); high hyperdiploidy (n=36; 7%); abnormal 14q32/IGH translocation (n=27; 5%); t(12;21)(p13;q22)/ETV6-RUNX1 (n=2; 0.4%); iAMP21 (n=3; 0.6%); other abnormalities (n=210; 39%); and no abnormality (n=120; 22%). The 315 informative T-ALL patients were classified as: t(10;14)(q24;q11)/TLX1 (n=64; 20%); other 14q11 or 7q34/TCR (n=31; 10%); t(5;14)(q35;q32)/TLX3 (n=29; 9%); t(10;11)(p12;q14)/PICALM-MLLT10 (n=14; 4%); deletion 1p32/SIL-TAL (n=18; 6%); MLL+ 11q23 abnormalities (n=6; 2%); other abnormalities (n=93; 30%); and no abnormalities (n=60; 19%). A complex karyotype was observed in 27/527 (5%) BCP-ALL and 21/298 (7%) T-ALL patients and a monosomal karyotype (as per Breems, JCO 2008) in 82/518 (16%) BCP-ALL and 26/286 (9%) T-ALL patients. In BCP-ALL, trends towards higher CIF and shorter EFS were observed in t(4;11) patients, with or without SCT censoring (HRs, 1.34 to 1.64; p values <0.10). Shorter EFS was observed in 3 subsets: 14q32 (HR, 2.10; p=0.002), Ho/Tr (HR, 1.45; p=0.10), and monosomal karyotype (HR, 1.42; p=0.029), but CIF were not different. This might be related to the older age of patients in these subsets (medians, 43y, 53y and 44y; p=0.029, <0.001 and <0.001, respectively) and worse treatment tolerance. For instance, higher incidences of non ALL-related deaths were observed in patients with 14q32 abnormalities or monosomal karyotype (p=0.031 and 0.067, respectively). Patients with high hyperdiploidy only tended to have lower CIF and longer EFS. Complex karyotype did not impact CIF and EFS, even after SCT censoring. Conversely, in T-ALL, complex karyotypes were associated with shorter EFS (HR, 2.20; p=0.004), even if the difference in CIF did not reach significance. A worse outcome was also observed in patients with t(10;11)(p12;q14)/PICALM-MLLT10 (HR, 2.45 and 2.14; p=0.016 and 0.021, for CIF and EFS respectively). A longer EFS was observed in patients with t(10;14)(q24;q11)/TLX1 (HR, 0.55; p=0.014), with a trend for lower CIF (HR, 0.59; p=0.070), while no inferior outcome was observed in t(5;14)(q35;q32)/TLX3 patients. Conclusion: These results show that, in the context of an intensified pediatric-inspired protocol designed for adult Ph-negative ALL patients, few cytogenetic subsets remained reliably predictive of response to therapy. Differences observed in EFS might partly be due to treatment-related mortality. Combining cytogenetics, molecular genetics and minimal residual disease monitoring could allow for better individual risk assessment (Beldjord, Blood 2014). Disclosures No relevant conflicts of interest to declare.
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Zhao, Yuejen, John Condon, Jiqiong You, Steven Guthridge, and Vincent He. "Assessing improvements in survival for stroke patients in the Northern Territory 1992–2013: a marginal structural analysis." Australian Health Review 39, no. 4 (2015): 437. http://dx.doi.org/10.1071/ah14146.
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Objective The aim of the present study was to investigate changes in stroke survival among Indigenous and non-Indigenous patients in the Northern Territory (NT). Methods A longitudinal study was undertaken of stroke patients admitted to NT public hospitals between 1992 and 2013. The Kaplan–Meier method and proportional hazards regression were used for survival analysis. A marginal structural model was applied to adjust for time-dependent confounders and informative censoring. Results There were 4754 stroke in-patients over the period, with 3540 new cases and 837 stroke deaths. Mean age of onset for Indigenous patients (51.7 years) was 12.3 years younger than that for non-Indigenous patients. After adjustments for confounders and loss to follow-up, in-hospital deaths were more likely among Indigenous patients (hazard ratio (HR) = 1.56; P < 0.01) and less likely among males (HR = 0.86; P < 0.05) and patients from remote areas (HR = 0.72; P < 0.01). There was a 3% decrease annually in mortality hazard from 1992 to 2013. Renal disease, cancer and chronic obstructive pulmonary disease had deleterious effects on stroke survival. Conclusions Stroke survival has improved in the NT over the past two decades. The marginal structural models provide a powerful methodological tool that can be applied to hospital administrative data to assess changes in quality of care and the impact of interventions. What is known about the topic? Stroke-related mortality has fallen in the past 30 years in Australia. Indigenous Australians have much worse health outcomes than other Australians, including higher stroke incidence and mortality, but it is not known whether stroke survival has improved for Indigenous stroke patients. What does this paper add? This study measured long-term survival for Indigenous and non-Indigenous patients after hospital admissions for stroke care, using hospital admission data analysed by marginal structural models. The present study demonstrates the usefulness of this approach to the quality assessment of health care interventions. What are the implications for practitioners? Hospital administrative data can, and should, be routinely used for monitoring long-term outcomes of acute care. Although survival has improved for Indigenous stroke patients over the past two decades, their survival remains lower than that of non-Indigenous patients. Coordinated acute and primary care plays a vital role in management of chronic diseases to improve stroke survival.
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Tsimberidou, Apostolia-Maria, Michael J. Keating, Hagop M. Kantarjian, Susan O’Brien, Jorge Cortes, Charles Koller, Francis Giles, et al. "Granulocytic Sarcoma (GS) Is Associated with Event-Free Survival Superior to That of Acute Myeloid Leukemia (AML)." Blood 108, no. 11 (November 1, 2006): 2008. http://dx.doi.org/10.1182/blood.v108.11.2008.2008.
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Abstract Introduction. Granulocytic sarcoma (GS) is an extramedullary tumor composed of immature myeloid cells. Some GS patients develop acute myeloid leukemia (AML), but the outcomes of these two diseases have never been compared. The purpose of this retrospective analysis was to compare the rates of response, survival and event-free survival (EFS) of patients treated for GS and patients treated for AML, after adjusting for presenting characteristics. Patients and Methods. We identified 1720 AML and 24 GS patients who presented at The University of Texas M. D. Anderson Cancer Center from 1990 to 2004. All the AML patients and 17 of the GS patients received ara-C + idarubicin or fludarabine. After comparing outcomes in these patients, we accounted for possible differences in underlying prognosis by matching treated GS and AML patients, using cytogenetics, age +/− 3 years, Zubrod performance status (0–2 vs. >2), and time of treatment +/− 3 years as the criteria for matching. Among 9 GS patients age ≤60 years, cytogenetic abnormalities were found at the sarcoma site or in the bone marrow in 5 patients; 4 of these 5 patients had a +8 abnormality, so we matched GS patients ≤60 years with cytogenetics that were “normal” in bone marrow but not assessed in GS tissue with AML patients with a +8 abnormality, assuming the “normal” karyotype in the GS patients was possibly non-informative and thus falsely negative. Among 15 GS patients <60 years old, cytogenetic abnormalities were inv(16) in 2, +8 in 2, 11q del in 1, −7 in 1, and miscellaneous in 2; 7 patients had normal bone marrow cytogenetics but no assessment in GS tissue. On the basis of the frequency of known cytogenetic abnormalities, we matched each of the 7 non-informative GS patients with better-, intermediate-, or worse-risk AML patients. EFS duration was compared in pair-mates of patients, and the Bayesian posterior probability that GS is associated with longer EFS duration was computed. Results. Among treated patients (GS 17, AML 1720), complete response rates were 71% and 57% in GS and AML, respectively (p=0.28). The respective 2-year EFS rates were 82% and 63% (p=0.049), and 2-year overall survival rates were 94% and 77% (p=0.16). Matches could be found for 14 GS patients, who were matched with 91 AML patients (including 3 matched with 2 different GS patients each). The median number of matches was 4 (range, 3–21). EFS duration was longer in 27 AML pairmates, shorter in 55, and unevaluable owing to censoring in 9. Assuming a beta distribution and a priori that 41 matches would have favored GS and 41 AML if EFS was the same in GS and AML, the posterior probability that EFS duration was longer in GS was 0.99. Eliminating the matches involving 1 GS patient and 21 AML patients led to a 0.92 posterior probability of longer EFS duration in GS. Conclusions. Our results suggest that GS is associated with better prognosis than AML based on the superior EFS of GS patients. Differences in rates of CR and survival did not reach statistical significance, possibly because of the small number of patients with GS.
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Neugebauer, Romain, Malini Chandra, Antonio Paredes, David J. Graham, Carolyn McCloskey, and Alan S. Go. "A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation." Journal of Causal Inference 1, no. 1 (May 29, 2013): 21–50. http://dx.doi.org/10.1515/jci-2012-0003.
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AbstractPurpose: Observational studies designed to investigate the safety of a drug in a postmarketing setting typically aim to examine rare and non-acute adverse effects in a population that is not restricted to particular patient subgroups for which the therapy, typically a drug, was originally approved. Large healthcare databases and, in particular, rich electronic medical record (EMR) databases, are well suited for the conduct of these safety studies since they can provide detailed longitudinal information on drug exposure, confounders, and outcomes for large and representative samples of patients that are considered for treatment in clinical settings. Analytic efforts for drawing valid causal inferences in such studies are faced with three challenges: (1) the formal definition of relevant effect measures addressing the safety question of interest; (2) the development of analytic protocols to estimate such effects based on causal methodologies that can properly address the problems of time-dependent confounding and selection bias due to informative censoring, and (3) the practical implementation of such protocols in a large clinical/medical database setting. In this article, we describe an effort to specifically address these challenges with marginal structural modeling based on inverse probability weighting with data reduction and super learning.Methods: We describe the principles of, motivation for, and implementation of an analytical protocol applied in a safety study investigating possible effects of exposure to oral bisphosphonate therapy on the risk of non-elective hospitalization for atrial fibrillation or atrial flutter among older women based on EMR data from the Kaiser Permanente Northern California integrated health care delivery system. Adhering to guidelines brought forward by Hernan (Epidemiology 2011;22:290-1), we start by framing the safety research question as one that could be directly addressed by a sequence of ideal randomized experiments before describing the estimation approach that we implemented to emulate inference from such trials using observational data.Results: This report underlines the important computation burden involved in the application of the current R implementation of super learning with large data sets. While computing time and memory requirements did not permit aggressive estimator selection with super learning, this analysis demonstrates the applicability of simplified versions of super learning based on select sets of candidate learners to avoid complete reliance on arbitrary selection of parametric models for confounding and selection bias adjustment. Results do not raise concern over the safety of one-year exposure to BP but may suggest residual bias possibly due to unmeasured confounders or insufficient parametric adjustment for observed confounders with the candidate learners selected.Conclusions: Adjustment for time-dependent confounding and selection bias based on the ad hoc inverse probability weighting approach described in this report may provide a feasible alternative to extended Cox modeling or the point treatment analytic approaches (e.g. based on propensity score matching) that are often adopted in safety research with large data sets. Alternate algorithms are needed to permit the routine and more aggressive application of super learning with large data sets.
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Begna, Kebede H., Walid Ali, Naseema Gangat, Michelle A. Elliott, Aref Al-Kali, Mark R. Litzow, C. Christopher Hook, et al. "1,123 Consecutive Adults with Non-APL Acute Myeloid Leukemia: The Mayo Clinic Experience." Blood 132, Supplement 1 (November 29, 2018): 2689. http://dx.doi.org/10.1182/blood-2018-99-110811.
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Abstract Background : Pre-treatment determinants of survival in adult acute myeloid leukemia (AML) include performance status, age, karyotype, the distinction between primary and non-primary AML and FLT3-ITD/NPM1 mutational status. Current literature on AML natural history and risk factors is often based on information derived from stringent protocol studies. In the current series of 1,123 adult patients seen at the Mayo Clinic between 2004 and 2017, we examined long-term survival specified by a number of primarily established risk factors. Methods: Diagnosis of AML and its sub-classification was according to World Health Organization criteria. Study subjects were recruited from the Mayo Clinic AML database. Conventional response criteria were used for CR and CRi assignment; the latter met all criteria for CR with the exception of platelet count <100 x 109/l or absolute neutrophil cunt <1 x 109/l. Standard statistical methods were used for analysis of overall survival, calculated from the initial diagnosis of AML to date of death or last follow-up; analyses were performed both in the absence and in the presence of censoring of survival at time of allogenic stem cell transplant (ASCT). The JMP® Pro 13.0.0 software from SAS Institute, Cary, NC, USA, was used for all calculations. Results: 1,123 adult patients (median age 65 years, range 18-94; 61% males) with non-APL AML were considered; 61% were age >60 years. 351 (31%) patients were seen between 2004 and 2009 and 772 (69%) between 2010 and 2017. AML subcategories were primary (56%), post-myelodysplastic syndromes (post-MDS; 24%), therapy-related (10%), post-myeloproliferative neoplasm (post-MPN; 8%) and post-MDS/MPN (3%). Cytogenetic risk distribution, according to the European LeukemiaNet classification, was favorable in 47 (4%), intermediate in 650 (58%) and adverse risk in 426 (38%) patients. FLT3, NPM1 and CEBPA mutation information was available in 462 (24% mutated), 393 (27% mutated) and 228 (11% mutated) patients, respectively. Treatment included intensive chemotherapy (IC) in 766 (68%) patients, less aggressive chemotherapy, including the use of hypomethylating agents in 144 (13%) and supportive care alone in 213 (19%) patients. ASCT was utilized in 258 (23%) cases, almost all performed after achieving CR/CRi. Complete remission (CR) and CR with incomplete count recovery (CRi) were listed in 333 (30%) and 248 (22%) patients, respectively; the corresponding rates in IC-treated patients were 43% and 32%. Almost all cases of CR/CRi occurred in IC-treated patients; 2 (1.4%) CRs were listed for less aggressive chemotherapy. After a median follow-up of 11 months, 798 (71%) deaths were recorded. Median survival for all 1,123 patients was 14 months with 1-, 3- and 5-year survival rates of 54%, 29% and 23%, respectively; a slight but significant (p=0.01) improvement in survival was apparent in more recent years (Figure 1a). Figures 1b, 1c and 1d depict analysis stratified by AML subcategories, treatment received and response obtained, respectively. Similarly, figures 2a, 2b and 2c depict analysis stratified by karyotype, use of ASCT and age. Multivariable analysis of pre-treatment parameters evaluable in all 1,123 patients identified age >60 years (HR 2.2, 1.9-2.6), adverse karyotype (HR 2.9, 1.9-4.9), intermediate-risk karyotype (HR 1.6, 1.02-2.6), post-MPN AML (HR 1.9, 1.5-2.4) and other secondary AML (HR 1.3 (1.1-1.6), as risk factors for shortened survival; the inclusion in the model of FLT3/NPM1 mutational status in 392 informative cases confirmed the adverse prognostic effect of age >60 years (HR 1.8, 1.4-2.5), adverse karyotype (HR 3.7, 1.4-15.3), post-MPN AML (HR 2.8, 1.6-4.6), other secondary AML (HR 1.4, 1.0-1.9) and FLT3+NPM1- (HR 2.8, 1.6-4.9) and FLT3-NPM1- (HR 1.7, 1.2-2.7) profile. Results were unchanged when survival was censored at time of ASCT. Additional prognostic interaction with treatment strategy and ASCT is further elaborated in an accompanying abstract to be presented. Conclusions: The current study, the largest coming from a single institution, provides practically useful information that should assist with patient consultation on AML prognosis and treatment. The study confirms the primary prognostic importance of age, karyotype and FLT3/NPM1 mutational status, in real-life practice. Novel observations included comparable value of CRi vs CR and the particularly worse prognosis associated with post-MPN AML. Disclosures Al-Kali: Novartis: Research Funding.
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Wan, Fei. "Simulating survival data with predefined censoring rates under a mixture of non-informative right censoring schemes." Communications in Statistics - Simulation and Computation, February 7, 2020, 1–17. http://dx.doi.org/10.1080/03610918.2020.1722838.
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Karamali, Gholamreza, Akram Zardadi, and Hamid Reza Moradi. "Data Censoring with Set-Membership Affine Projection Algorithm." Computer Science 21, no. 1 (January 27, 2020). http://dx.doi.org/10.7494/csci.2020.21.1.3388.
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In this paper, the set-membership affine projection (SM-AP) algorithm is utilized to censor non-informative data in big data applications. To this end, the probability distribution of the additive noise signal and the excess of the mean-squared error (EMSE) in steady-state are employed in order to estimate the threshold parameter of the single threshold SM-AP (ST-SM-AP) algorithm aiming at attaining the desired update rate. Furthermore, by defining an acceptable range for the error signal, the double threshold SM-AP (DT-SM-AP) algorithm is proposed to detect very large errors due to the irrelevant data such as outliers. The DT-SM-AP algorithm can censor non-informative and irrelevant data in big data applications, and it can improve the misalignment and convergence rate of the learning process with high computational efficiency. The simulation and numerical results corroborate the superiority of the proposed algorithms over traditional algorithms.
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Phillips, P. P. J., A. Van Deun, S. Ahmed, R. L. Goodall, S. K. Meredith, F. Conradie, C.-Y. Chiang, I. D. Rusen, and A. J. Nunn. "Investigation of the efficacy of the short regimen for rifampicin-resistant TB from the STREAM trial." BMC Medicine 18, no. 1 (November 4, 2020). http://dx.doi.org/10.1186/s12916-020-01770-z.
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Abstract Background The STREAM trial demonstrated that a 9–11-month “short” regimen had non-inferior efficacy and comparable safety to a 20+ month “long” regimen for the treatment of rifampicin-resistant tuberculosis. Imbalance in the components of the composite primary outcome merited further investigation. Methods Firstly, the STREAM primary outcomes were mapped to alternatives in current use, including WHO programmatic outcome definitions and other recently proposed modifications for programmatic or research purposes. Secondly, the outcomes were re-classified according to the likelihood that it was a Failure or Relapse (FoR) event on a 5-point Likert scale: Definite, Probable, Possible, Unlikely, and Highly Unlikely. Sensitivity analyses were employed to explore the impact of informative censoring. The protocol-defined modified intention-to-treat (MITT) analysis population was used for all analyses. Results Cure on the short regimen ranged from 75.1 to 84.2% across five alternative outcomes. However, between-regimens results did not exceed 1.3% in favor of the long regimen (95% CI upper bound 10.1%), similar to the primary efficacy results from the trial. Considering only Definite or Probable FoR events, there was weak evidence of a higher risk of FoR in the short regimen, HR 2.19 (95%CI 0.90, 5.35), p = 0.076; considering only Definite FoR events, the evidence was stronger, HR 3.53 (95%CI 1.05, 11.87), p = 0.030. Cumulative number of grade 3–4 AEs was the strongest predictor of censoring. Considering a larger effect of informative censoring attenuated treatment differences, although 95% CI were very wide. Conclusion Five alternative outcome definitions gave similar overall results. The risk of failure or relapse (FoR) may be higher in the short regimen than in the long regimen, highlighting the importance of how loss to follow-up and other censoring is accounted for in analyses. The outcome of time to FoR should be considered as a primary outcome for future drug-sensitive and drug-resistant TB treatment trials, provided sensitivity analyses exploring the impact of departures from independent censoring are also included.
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Singh, Umesh, and Anil Kumar. "Bayesian Estimation of the Exponential Parameter under a Multiply Type-II Censoring Scheme." Austrian Journal of Statistics 36, no. 3 (April 3, 2016). http://dx.doi.org/10.17713/ajs.v36i3.334.
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This paper provides the estimation of the scale parameter of the exponential distribution under multiply type-II censoring. Using generalized non-informative prior and natural conjugate prior, Bayes estimator and approximate Bayes estimators of the scale parameter have been obtained under square error loss function. The proposed Bayes estimators and approximate Bayes estimators are compared with the estimators proposed by Singh et al. (2005) and Balasubramanian and Balakrishnan (1992) on the basis of theirsimulated risks under square error loss function of 1000 randomly generated Monte Carlo samples.
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Dutta, Subhankar, and Suchandan Kayal. "Inference of a competing risks model with partially observed failure causes under improved adaptive type-II progressive censoring." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, June 20, 2022, 1748006X2211045. http://dx.doi.org/10.1177/1748006x221104555.
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In this paper, a competing risks model is analyzed based on improved adaptive type-II progressive censored sample (IAT-II PCS). Two independent competing causes of failures are considered. It is assumed that lifetimes of the competing causes of failure follow exponential distributions with different means. Maximum likelihood estimators (MLEs) for the unknown model parameters are obtained. Using asymptotic normality property of MLE, the asymptotic confidence intervals are constructed. Existence and uniqueness properties of the MLEs are studied. Further, bootstrap confidence intervals are computed. The Bayes estimators are obtained under symmetric and asymmetric loss functions with non-informative and informative priors. For informative priors, independent gamma distributions are considered. Highest posterior density (HPD) credible intervals are obtained. A Monte Carlo simulation study is carried out to compare performance of the established estimates. Furthermore, three different optimality criteria are proposed to obtain the optimal censoring plan. Finally, a real-life data set is considered for illustrative purposes.
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Mehdi, Muntazir, Muhammad Aslam, and Navid Feroze. "Bayesian Estimation of Transmuted Lomax Mixture Model with an Application to Type-I Censored Windshield Data." Pakistan Journal of Statistics and Operation Research, December 6, 2022, 1027–48. http://dx.doi.org/10.18187/pjsor.v18i4.4059.
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Transmuted distributions have been centered of focus for researchers recently due to their flexibility and applicability in statistics. However, the only few contributions have considered estimation for mixture of transmuted lifetime models especially under Bayesian methods has been explored more recently. We have considered the Bayesian estimation of transmuted Lomax mixture model (TLMM) for type-I censored samples. The Bayes estimates (BEs) for informative and non-informative priors. The BEs and posterior risks (PRs) are evaluated using four different loss functions (LFs), two symmetric and two asymmetric, namely the squared error loss function (SELF), precautionary loss function (PLF), weighted balance loss function (WBLF), and general entropy loss function (GELF). Simulations are run using Lindley Approximation method to compare the BEs under various sample sizes and censoring rates. The estimates under informative prior and GELF were found superior to their counterparts. The applicability of the proposed estimates has been illustrated using the analysis of a real data regarding type-I censored failure times of windshields airplanes.
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Yousaf, Rahila, Sajid Ali, and Muhammad Aslam. "Bayesian Estimation of Transmuted Weibull Distribution under Different Loss Functions." Journal of Reliability and Statistical Studies, December 30, 2020. http://dx.doi.org/10.13052/jrss0974-8024.13245.
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In this article, we aim to estimate the parameters of the transmuted Weibull distribution (TWD) using Bayesian approach, as the Weibull distribution plays an important role in reliability engineering and life testing problems. Informative and non-informative priors under squared error loss function (SELF), precautionary loss function (PLF) and quadratic loss function (QLF) are assumed to estimate the scale, the shape and the transmuted parameter of the TWD. In addition to this, we also compute the Bayesian credible intervals (BCIs). To estimate parameters, we adopt Markov Chain Monte Carlo (MCMC) technique assuming uncensored and censored environments in terms of different sample sizes and censoring rates. The posterior risks, associated with each estimator are used to compare the performance of different estimators. Two real data sets are analyzed to illustrate the flexibility of the proposed distribution.
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Tran, Tanja, and Samy Suissa. "Comparing New-User Cohort Designs: The Example of Proton Pump Inhibitor Effectiveness in Idiopathic Pulmonary Fibrosis." American Journal of Epidemiology, October 30, 2020. http://dx.doi.org/10.1093/aje/kwaa242.
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Abstract The prevalent new-user cohort design is useful to assess the effectiveness of a drug in the absence of an active comparator. Alternative approaches, particularly in the presence of informative censoring, include a variant of this design based on never-users of the study drug and the marginal structural Cox model approach. These were compared in assessing the effectiveness of proton pump inhibitors (PPI) on mortality in idiopathic pulmonary fibrosis using a cohort of patients with idiopathic pulmonary fibrosis identified from 2003-2016 in the UK’s Clinical Practice Research Datalink. The cohort included 2944 patients, with 1916 initiating PPIs during follow-up and 2136 deaths (rate 25.8 per 100 person-years). The conventional prevalent new-user design found a hazard ratio (HR) of death associated with PPI use compared with non-use of 1.07 (95% confidence interval (CI) 0.94-1.22). The variant to the prevalent new-user design comparing with never-users found a HR of 0.82 (95% CI 0.73-0.91) while the marginal structural Cox model found a HR of 1.08 (95% CI 0.85-1.38). In conclusion, the marginal structural model and the conventional prevalent new-user design, both accounting for informative censoring, produced similar results. However, the prevalent new-user design variant based on never-users introduces selection bias and should be avoided.
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Little, Roderick J. "Missing Data Assumptions." Annual Review of Statistics and Its Application 8, no. 1 (August 21, 2020). http://dx.doi.org/10.1146/annurev-statistics-040720-031104.
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I review assumptions about the missing-data mechanism that underlie methods for the statistical analysis of data with missing values. I describe Rubin's original definition of missing at random, (MAR), its motivation and criticisms, and his sufficient conditions for ignoring the missingness mechanism for likelihood-based, Bayesian, and frequentist inference. Related definitions, including missing completely at random, always MAR, always missing completely at random, and partially MAR are also covered. I present a formal argument for weakening Rubin's sufficient conditions for frequentist maximum likelihood inference with precision based on the observed information. Some simple examples of MAR are described, together with an example where the missingness mechanism can be ignored even though MAR does not hold. Alternative approaches to statistical inference based on the likelihood function are reviewed, along with non-likelihood frequentist approaches, including weighted generalized estimating equations. Connections with the causal inference literature are also discussed. Finally, alternatives to Rubin's MAR definition are discussed, including informative missingness, informative censoring, and coarsening at random. The intent is to provide a relatively nontechnical discussion, although some of the underlying issues are challenging and touch on fundamental questions of statistical inference. Expected final online publication date for the Annual Review of Statistics, Volume 8 is March 7, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Yu, Jonathan W., Dipankar Bandyopadhyay, Shu Yang, Le Kang, and Gaurav Gupta. "Propensity Score Modeling in Electronic Health Records with Time-to-Event Endpoints: Application to Kidney Transplantation." Journal of Data Science, 2022, 1–21. http://dx.doi.org/10.6339/22-jds1046.
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For large observational studies lacking a control group (unlike randomized controlled trials, RCT), propensity scores (PS) are often the method of choice to account for pre-treatment confounding in baseline characteristics, and thereby avoid substantial bias in treatment estimation. A vast majority of PS techniques focus on average treatment effect estimation, without any clear consensus on how to account for confounders, especially in a multiple treatment setting. Furthermore, for time-to event outcomes, the analytical framework is further complicated in presence of high censoring rates (sometimes, due to non-susceptibility of study units to a disease), imbalance between treatment groups, and clustered nature of the data (where, survival outcomes appear in groups). Motivated by a right-censored kidney transplantation dataset derived from the United Network of Organ Sharing (UNOS), we investigate and compare two recent promising PS procedures, (a) the generalized boosted model (GBM), and (b) the covariate-balancing propensity score (CBPS), in an attempt to decouple the causal effects of treatments (here, study subgroups, such as hepatitis C virus (HCV) positive/negative donors, and positive/negative recipients) on time to death of kidney recipients due to kidney failure, post transplantation. For estimation, we employ a 2-step procedure which addresses various complexities observed in the UNOS database within a unified paradigm. First, to adjust for the large number of confounders on the multiple sub-groups, we fit multinomial PS models via procedures (a) and (b). In the next stage, the estimated PS is incorporated into the likelihood of a semi-parametric cure rate Cox proportional hazard frailty model via inverse probability of treatment weighting, adjusted for multi-center clustering and excess censoring, Our data analysis reveals a more informative and superior performance of the full model in terms of treatment effect estimation, over sub-models that relaxes the various features of the event time dataset.
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Silverberg, Michael J., Wendy Leyden, Raúl U. Hernández-Ramírez, Li Qin, Haiqun Lin, Amy C. Justice, Nancy A. Hessol, et al. "Timing of Antiretroviral Therapy Initiation and Risk of Cancer Among Persons Living With Human Immunodeficiency Virus." Clinical Infectious Diseases, August 12, 2020. http://dx.doi.org/10.1093/cid/ciaa1046.
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Abstract Background Persons living with human immunodeficiency virus (HIV; PLWH) experience a high burden of cancer. It remains unknown which cancer types are reduced in PLWH with earlier initiation of antiretroviral therapy (ART). Methods We evaluated AIDS-free, ART-naive PLWH during 1996–2014 from 22 cohorts participating in the North American AIDS Cohort Collaboration on Research and Design. PLWH were followed from first observed CD4 of 350–500 cells/µL (baseline) until incident cancer, death, lost-to-follow-up, or December 2014. Outcomes included 6 cancer groups and 5 individual cancers that were confirmed by chart review or cancer registry linkage. We evaluated the effect of earlier (in the first 6 months after baseline) versus deferred ART initiation on cancer risk. Marginal structural models were used with inverse probability weighting to account for time-dependent confounding and informative right-censoring, with weights informed by subject’s age, sex, cohort, baseline year, race/ethnicity, HIV transmission risk, smoking, viral hepatitis, CD4, and AIDS diagnoses. Results Protective results for earlier ART were found for any cancer (adjusted hazard ratio [HR] 0.57; 95% confidence interval [CI], .37–.86), AIDS-defining cancers (HR 0.23; 95% CI, .11–.49), any virus-related cancer (HR 0.30; 95% CI, .16–.54), Kaposi sarcoma (HR 0.25; 95% CI, .10–.61), and non-Hodgkin lymphoma (HR 0.22; 95% CI, .06–.73). By 15 years, there was also an observed reduced risk with earlier ART for virus-related NADCs (0.6% vs 2.3%; adjusted risk difference −1.6; 95% CI, −2.8, −.5). Conclusions Earlier ART initiation has potential to reduce the burden of virus-related cancers in PLWH but not non-AIDS-defining cancers (NADCs) without known or suspected viral etiology.
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Lambert, Paul C., Elisavet Syriopoulou, and Mark R. Rutherford. "Direct modelling of age standardized marginal relative survival through incorporation of time-dependent weights." BMC Medical Research Methodology 21, no. 1 (April 24, 2021). http://dx.doi.org/10.1186/s12874-021-01266-1.
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Abstract Background When quantifying the probability of survival in cancer patients using cancer registration data, it is common to estimate marginal relative survival, which under assumptions can be interpreted as marginal net survival. Net survival is a hypothetical construct giving the probability of being alive if it was only possible to die of the cancer under study, enabling comparisons between populations with differential mortality rates due to causes other the cancer under study. Marginal relative survival can be estimated non-parametrically (Pohar Perme estimator) or in a modeling framework. In a modeling framework, even when just interested in marginal relative survival it is necessary to model covariates that affect the expected mortality rates (e.g. age, sex and calendar year). The marginal relative survival function is then obtained through regression standardization. Given that these covariates will generally have non-proportional effects, the model can become complex before other exposure variables are even considered. Methods We propose a flexible parametric model incorporating restricted cubic splines that directly estimates marginal relative survival and thus removes the need to model covariates that affect the expected mortality rates. In order to do this the likelihood needs to incorporate the marginal expected mortality rates at each event time taking account of informative censoring. In addition time-dependent weights are incorporated into the likelihood. An approximation is proposed through splitting the time scale into intervals, which enables the marginal relative survival model to be fitted using standard software. Additional weights can be incorporated when standardizing to an external reference population. Results The methods are illustrated using national cancer registry data. In addition, a simulation study is performed to compare different estimators; a non-parametric approach, regression-standardization and the new marginal relative model. The simulations study shows the new approach is unbiased and has good relative precision compared to the non-parametric estimator. Conclusion The approach enables estimation of standardized marginal relative survival without the need to model covariates that affect expected mortality rates and thus reduces the chance of model misspecification.
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Dormuth, Ina, Tiantian Liu, Jin Xu, Menggang Yu, Markus Pauly, and Marc Ditzhaus. "Which test for crossing survival curves? A user’s guideline." BMC Medical Research Methodology 22, no. 1 (January 30, 2022). http://dx.doi.org/10.1186/s12874-022-01520-0.
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Abstract Background The exchange of knowledge between statisticians developing new methodology and clinicians, reviewers or authors applying them is fundamental. This is specifically true for clinical trials with time-to-event endpoints. Thereby, one of the most commonly arising questions is that of equal survival distributions in two-armed trial. The log-rank test is still the gold-standard to infer this question. However, in case of non-proportional hazards, its power can become poor and multiple extensions have been developed to overcome this issue. We aim to facilitate the choice of a test for the detection of survival differences in the case of crossing hazards. Methods We restricted the review to the most recent two-armed clinical oncology trials with crossing survival curves. Each data set was reconstructed using a state-of-the-art reconstruction algorithm. To ensure reproduction quality, only publications with published number at risk at multiple time points, sufficient printing quality and a non-informative censoring pattern were included. This article depicts the p-values of the log-rank and Peto-Peto test as references and compares them with nine different tests developed for detection of survival differences in the presence of non-proportional or crossing hazards. Results We reviewed 1400 recent phase III clinical oncology trials and selected fifteen studies that met our eligibility criteria for data reconstruction. After including further three individual patient data sets, for nine out of eighteen studies significant differences in survival were found using the investigated tests. An important point that reviewers should pay attention to is that 28% of the studies with published survival curves did not report the number at risk. This makes reconstruction and plausibility checks almost impossible. Conclusions The evaluation shows that inference methods constructed to detect differences in survival in presence of non-proportional hazards are beneficial and help to provide guidance in choosing a sensible alternative to the standard log-rank test.
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Hernandez Meneses, BG, G. Padilla-Rodriguez, J. Carmona-Carmona, R. Hidalgo-Urbano, M. Almendro-Delia, and JC Garcia-Rubira. "Prognosis impact of ticagrelor vs clopidogrel based DAPT discontinuation after acute coronary syndrome. Insights from the multicenter CREA ARIAM Andalucia registry." European Heart Journal. Acute Cardiovascular Care 11, Supplement_1 (May 1, 2022). http://dx.doi.org/10.1093/ehjacc/zuac041.067.
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Abstract Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): The study project was financially supported by a non-conditional grant by Astrazeneca. Background/Introduction Premature cessation of dual antiplatelet therapy (DAPT) after acute coronary syndrome (ACS) has been associated with increased risk of major adverse cardiovascular events (MACE) Purpose To assess the relationship between premature DAPT discontinuation versus therapy continuation and outcomes in ACS patients discharged on ticagrelor or clopidogrel. Methods Prospective, observational, multicentre all-comers registry of ACS patients who were intended to receive 12-month DAPT with ticagrelor or clopidogrel. Adherence was defined by the medication possession ratio metric (MPA, proportion of days of medication supply within a time interval). Categories for DAPT cessation included: physician-recommended discontinuation, brief interruption (invasive procedures), or disruption due to non-compliance or because of bleeding. Fully-adjusted Cox models with time-varying covariates to account for informative censoring, were used to examine the effect of DAPT cessation on MACE (a composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, definite stent thrombosis, or target-lesion revascularization). Moderation analysis was also performed to assess for potential exposure-adherence interaction. Results Among 2070 patients included (mean age 63 years, 73% men), 150 (7.3%) prematurely discontinued DAPT, median (IQR) 214 (101-236) days. Significantly more clopidogrel than ticagrelor users discontinued medication (9.5% vs 5%, respectively; P = .001), though timing of cessation was similar in both groups. At 1 year, MPR was slightly higher, but not significantly different, in the clopidogrel group than in the ticagrelor group (70±30 vs 64±29; P = .06). Overall, physician-guided discontinuation and bleeding were the main reasons for DAPT cessation. These were observed with a similar rate in both groups, while non-compliant disruption was more common among ticagrelor- than clopidogrel-treated patients (8% vs 2%, respectively; P for trend .04). After adjustments, DAPT cessation was associated with significantly increased risk of MACE (adjusted HR 2.94; 95% CI 1.82 – 4.74; P < .0001), regardless of the P2Y12 inhibitor (P interaction = 0.665). Non-compliance related cessation resulted in higher risk of MACE (HR 6.04, 95%CI 2.15 – 16.95; P = .001). Conclusion(s) Overall, approximately 7% of patients discontinued DAPT. Early cessation of either ticagrelor- or clopidogrel-based DAPT portended to a near 3-fold increased risk of MACE. Disruption due to non-compliance resulted in higher risk for ischemic events. These data warrant efforts to focus on patient education in subgroups at high risk of non-compliance.
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Chesnaye, Nicholas, Yvette Meuleman, Esther De Rooij, Friedo W. Dekker, Marie Evans, Fergus Caskey, Claudia Torino, et al. "FC 068QUALITY OF LIFE OVER TIME IN OLDER MEN AND WOMEN WITH ADVANCED CKD - RESULTS FROM THE EQUAL STUDY." Nephrology Dialysis Transplantation 36, Supplement_1 (May 1, 2021). http://dx.doi.org/10.1093/ndt/gfab122.002.
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Abstract Background and Aims Differences between the sexes are apparent in the epidemiology of CKD. Cross-sectional studies show that women consistently report a poorer health-related quality of life (QoL) than men, however, longitudinal studies are lacking. Here we investigate the sex-specific evolution of QoL over time in advanced CKD. As a secondary aim, we explore the sex-specific determinants of QoL. Method EQUAL is an observational prospective cohort study in stages 4 and 5 CKD patients ≥65 years not on dialysis with an incident estimated glomerular filtration rate (eGFR) < 20 ml/min/1.73m². Data on QoL (measured using the RAND-36), clinical and demographic patient characteristics were collected between April 2012 and September 2020. QoL trajectories were modelled by sex using linear mixed models, and joint models were applied to deal with informative censoring. We followed patients until death or dialysis initiation. Results We included 5151 QoL measurements in 1416 patients over a total of 1986 person years of follow-up. Overall, the physical component summary (PCS) declined with 2.0 (95% CI 1.4-2.6) points and the mental component summary (MCS) by 2.4 (95% CI 1.8-3.0) points per year. Although women had overall lower QoL scores, figure 1 demonstrates that PCS and MCS declined more than twice as fast in men (PCS: 2.4 per year, 95% CI 1.7 – 3.1, MCS: 2.9 per year, 95% CI 2.2 – 3.6) compared with women (PCS: 1.1 per year, 95% CI -0.2 – 2.0, MCS: 1.5 per year, 95% CI 0.5 – 2.4). We identified a non-linear interaction effect between sex and eGFR levels on QoL, demonstrating a stronger negative effect of decreased eGFR on both PCS (p=0.02) and MCS (p=0.04) in men compared with women. Subsequent adjustment for renal decline attenuated the difference in rate of QoL decline between men and women (difference after adjustment; PCS: 1.1, 95% CI -0.1 – 2.2, MCS: 1.2, 95% 0.0 – 2.3). In univariable analyses, higher serum haemoglobin was more beneficial to QoL in men compared to women (p-value for interaction; PCS: p=0.03, MCS: p=0.01). Higher serum phosphate had a strong harmful effect on both PCS and MCS in men, but not in women (PCS & MCS: p<0.001). The presence of pre-existing diabetes had a negative effect on PCS and MCS in men, but to a lesser extent in women (PCS: p=0.02, MCS: p=0.01). Conclusion Despite the higher overall QoL reported by men, both their physical and mental QoL declined approximately twice as fast compared with women. The faster decline in men was mediated in part by their lower levels of renal function, which had a stronger impact on their QoL as compared with women. Furthermore, in exploratory analyses we identified that high levels of phosphate, low levels of haemoglobin, and pre-existing diabetes were more detrimental to QoL in men than in women.