Improvement of survival after hematopoietic stem cell transplantation and trends at a pediatric transplantation center; a three-decade journey.

BACKGROUND: Advances in stem cell transplantation have resulted in improved outcomes. METHODS: This is a retrospective study aimed to analyze changes in patient profile, transplantation, graft characteristics, and outcome among 241 pediatric patients who received stem cell transplantation in a single center between 1993 and 2019. RESULTS: In the 2010-2019, compared with the 1993-2009 period, a significantly higher 5-year overall survival (60% vs. 44%, p = .022) and an event-free survival (53% vs. 34%, p = .025) were observed. Cumulative incidence of deaths due to relapse or progression between the 1993-2009 and 2010-2019 periods were 33% and 26% respectively (p = .66). Cumulative incidence of non-relapse mortality was significantly higher during the 1993-2009 period compared with the 2010-2019 period for malignant diseases (57.7% vs. 28.3%, p = .007). The overall survival from acute graft-versus-host disease between 1993 and 2009 was 11% versus 46% between 2010 and 2019 (p = .0001). The overall survival from infection in both eras did not show any difference (p = .41). CONCLUSIONS: Development in transplantation technology has led to a decrease in non-relapse mortality and better control of graft-versus-host disease. However, relapse and infection remained as major causes of death. Studies evaluating institutional trends in patients undergoing HSCT and analyzing their mortality profile, can improve the management of patients, leading to a reduction in transplant-related problems.

Joint modeling the frequency and duration of accelerometer-measured physical activity from a lifestyle intervention trial.

Physical activity (PA) guidelines recommend that PA be accumulated in bouts of 10 minutes or more in duration. Recently, researchers have sought to better understand how participants in PA interventions increase their activity. Participants can increase their daily PA by increasing the number of PA bouts per day while keeping the duration of the bouts constant; they can keep the number of bouts constant but increase the duration of each bout; or participants can increase both the number of bouts and their duration. We propose a novel joint modeling framework for modeling PA bouts and their duration over time. Our joint model is comprised of two sub-models: a mixed-effects Poisson hurdle sub-model for the number of bouts per day and a mixed-effects location scale gamma regression sub-model to characterize the duration of the bouts and their variance. The model allows us to estimate how daily PA bouts and their duration vary together over the course of an intervention and by treatment condition and is specifically designed to capture the unique distributional features of bouted PA as measured by accelerometer: frequent measurements, zero-inflated bouts, and skewed bout durations. We apply our methods to the Make Better Choices study, a longitudinal lifestyle intervention trial to increase PA. We perform a simulation study to evaluate how well our model is able to estimate relationships between outcomes.

Total nucleated cell dose in graft is a better prognostic factor for survival in pediatric patients transplanted with bone marrow compared to CD34+, CD3+, or total mononuclear cell count.

BACKGROUND: Most studies investigating the impact of graft composition on transplant-related outcomes have focused on the effect of CD34+ cell dose and reported equivocal results. The aim of this study is to investigate the impact of doses of total nucleated cells (TNCs), total mononuclear cells (TMCs), CD3+, and CD34+ cells on the outcome of children receiving allogeneic hematopoietic stem cell transplantation (HSCT). METHODS: Children and adolescents who underwent allogeneic HSCT for malignant hemato-oncological diseases or nonmalignant diseases in Cukurova University Faculty of Medicine, Pediatric Bone Marrow Transplantation Center between 2010 and 2020 were enrolled in the study. RESULTS: A total of 212 patients receiving allogeneic HSCT (154 bone marrow transplantation; 58 peripheral blood stem cell transplantation) from matched related or unrelated donors were included in the study. Higher TNC doses associated with a superior 5-year event-free survival (EFS; 67.7% vs 44.7%) in the whole group (log-rank P = .027). Overall survival (OS) and EFS of bone marrow-transplanted patients differed significantly according to TNC doses (log-rank P = .041 and .027, respectively). Multivariant analysis for OS revealed a P value of .038 for TNC, Exp(B) = 1.939 (95% CI: [1.038, 3.621]). That for EFS revealed a P value of .025 for TNC, Exp(B) = 1.992 (95% CI: [1.088, 3.647]). There was no relationship between doses of CD34+ cells, CD3+ cells, TMC, TNC, and neutrophil or platelet engraftment. CONCLUSION: Our data suggest that TNC dose is a better prognostic factor for pediatric allogeneic HSCT outcomes than doses of CD34+ cells, CD3+ cells, or TMC in patients transplanted with bone marrow. Future studies analyzing cell subsets and other components in TNC could elaborate the factor(s) accompanying this observed survival advantage.

A population-averaged approach to diagnostic test meta-analysis.

The meta-analysis of diagnostic accuracy studies is often of interest in screening programs for many diseases. The typical summary statistics for studies chosen for a diagnostic accuracy meta-analysis are often two dimensional: sensitivities and specificities. The common statistical analysis approach for the meta-analysis of diagnostic studies is based on the bivariate generalized linear-mixed model (BGLMM), which has study-specific interpretations. In this article, we present a population-averaged (PA) model using generalized estimating equations (GEE) for making inference on mean specificity and sensitivity of a diagnostic test in the population represented by the meta-analytic studies. We also derive the marginalized counterparts of the regression parameters from the BGLMM. We illustrate the proposed PA approach through two dataset examples and compare performance of estimators of the marginal regression parameters from the PA model with those of the marginalized regression parameters from the BGLMM through Monte Carlo simulation studies. Overall, both marginalized BGLMM and GEE with sandwich standard errors maintained nominal 95% confidence interval coverage levels for mean specificity and mean sensitivity in meta-analysis of 25 of more studies even under misspecification of the covariance structure of the bivariate positive test counts for diseased and nondiseased subjects.

One-inflation and unobserved heterogeneity in population size estimation by Ryan T. Godwin.

In this study, we would like to show that the one-inflated zero-truncated negative binomial (OIZTNB) regression model can be easily implemented in R via built-in functions when we use mean-parameterization feature of negative binomial distribution to build OIZTNB regression model. From the practitioners' point of view, we believe that this approach presents a computationally convenient way for implementation of the OIZTNB regression model.

Power analysis of C-TDT for small sample size genome-wide association studies by the joint use of case-parent trios and pairs.

In family-based genetic association studies, it is possible to encounter missing genotype information for one of the parents. This leads to a study consisting of both case-parent trios and case-parent pairs. One of the approaches to this problem is permutation-based combined transmission disequilibrium test statistic. However, it is still unknown how powerful this test statistic is with small sample sizes. In this paper, a simulation study is carried out to estimate the power and false positive rate of this test across different sample sizes for a family-based genome-wide association study. It is observed that a statistical power of over 80% and a reasonable false positive rate estimate can be achieved even with a combination of 50 trios and 30 pairs when 2% of the SNPs are assumed to be associated. Moreover, even smaller samples provide high power when smaller percentages of SNPs are associated with the disease.

Application of Dempster-Schafer method in family-based association studies.

In experiments designed for family-based association studies, methods such as transmission disequilibrium test require large number of trios to identify single-nucleotide polymorphisms associated with the disease. However, unavailability of a large number of trios is the Achilles' heel of many complex diseases, especially for late-onset diseases. In this paper, we propose a novel approach to this problem by means of the Dempster-Shafer method. The simulation studies show that the Dempster-Shafer method has a promising overall performance, in identifying single-nucleotide polymorphisms in the correct association class, as it has 90 percent accuracy even with 60 trios.