Bayesian approach to the assessment of the population-specific risk of inhibitors in hemophilia A patients: a case study

Survival Rate and Prognostic Factors Among Patients Undergoing Hematopoietic Stem Cell Transplantation: Using the Joint Model

Background: Hematopoietic stem cell transplantation (HSCT) is the most effective of all hematologic malignancies treatments, resulting in a significant improvement in survival rate. Objectives: This study aimed at determining the survival rate and factors affecting the survival in patients undergoing hematopoietic stem cell transplantation, using the joint model. Methods: This study was a retrospective cohort study, used for collecting data from patients with hematopoietic malignancies who underwent hematopoietic stem cell transplantation in Taleghani Hospital (Shahid Beheshti University of Medical Sciences), Tehran, Iran during the years 2007 and 2015 and were followed up till 2017. A Bayesian joint model of longitudinal and survival was chosen, using Win Bugs software. Results: A total of 395 patients were enrolled. The median overall survival was 6.3 years (95% CI (5.86, 6.76)). Eighty-one patients had died. The obtained results from this study manifested that age (HR: 1.02, 95% CI: (1.002, 1.04)) and pre-transplantation relapse (HR = 1.64, 95% CI: (1.09, 2.4)) have incremental impact on death after transplantation, while malignancy type (NHL (HR: 0.33, 95%CI: (0.152, 0.73)) and AML (HR: 0.62, 95% CI: (0.29, 0.7)) are also effective in reducing death after transplantation. Similarly, the correlation index between longitudinal and survival models proved to be significant (HR: 0.6, 95% CI: (0.0802, 0.37)). Conclusions: This study showed that age, per-transplantation relapse, and malignancy type are the effective factors in the survival rate. Moreover, the link parameter between longitudinal response (WBC) and the survival indicated that an increase in WBC count leads to a decrease in the death risk.

Effective Factors on the Recurrence of Bipolar Mood Disorder I in an Iranian Population Sample Using the Frailty Model with Bayesian Approach

Objective: Bipolar I disorder is one of the most frequent mental disorders characterized by manic or mixed +/- depressive episodes. Drug treatment has been proved to diminish next episodes, but many other factors are important for exacerbating the conditions. This study aimed to investigate the effective factors on the time and number of episodes in these patients by applying the shared frailty model.

Method: In this retrospective longitudinal study, the information of 606 patients with bipolar I disorder, admitted for the first time in Ibn-e-Sina psychiatric hospital in Mashhad from the beginning of 2007 until the end of 2009 were used. These patients were followed up until the end of 2018 for readmission. The Cox model with gamma frailty and Bayesian approach were used to determine the effective factors of frequent recurrences.

Results: History of head trauma, substance abuse, and legal conflict had a positive impact on recurrences, while age had a negative effect on recurrences and the risk of recurrence was higher in younger people (P < 0.05). The variance estimation of frailty effect was 0.97 that indicates a correlation between the recurrence intervals of bipolar I patients, owing to a heterogeneity among patients.

Conclusion: Based on the results, a higher risk of recurrence of bipolar I disorder was found in younger patients and those with a history of head trauma, substance abuse, and legal conflicts. Further investigations are required to account for the genetic factor and psychosocial exposure during critical periods applying this model.

The design of a Bayesian platform trial to prevent and eradicate inhibitors in patients with hemophilia

Among individuals with the rare congenital bleeding disorder hemophilia A, the major challenge is inhibitor formation, which is associated with significant morbidity and cost. Yet, as the optimal approach to prevent and eradicate inhibitors is not known, we are at equipoise. Because classic trial design is not practical in a rare disease setting, we designed 2 48-week randomized trials comparing ELOCTATE and emicizumab to prevent and eradicate inhibitors. To achieve statistical efficiency, we incorporated historic data (Bayesian priors) on inhibitor formation to allow preferential randomization to emicizumab, piecewise exponential survival models to determine mean and 95% confidence interval for inhibitor formation in each arm, and simulations to determine the best model design to optimize power. To achieve administrative efficiency, the trials will be performed with the same sites, staff, visit frequency, blood sampling, laboratories, and laboratory assays, with streamlined enrollment so patients developing inhibitors in the first trial may be enrolled on the second trial. The primary end point is the probability of inhibitor formation or inhibitor eradication, respectively. The design indicates early stopping rules for overwhelming evidence of superiority of the emicizumab arms. Simulations indicate that, with 66 subjects, the Prevention Trial will have 84% power to detect noninferiority of emicizumab to ELOCTATE with a margin of 10% if emicizumab is truly 10% superior to ELOCTATE; with 90 subjects, the Eradication Trial will have 80% power to detect 15% superiority of ELOCTATE immune tolerance induction with vs without emicizumab. Thus, a platform design provides statistical and administrative efficiency to conduct INHIBIT trials.

The national blueprint for future factor VIII inhibitor clinical trials: NHLBI State of the Science (SOS) Workshop on factor VIII inhibitors

INTRODUCTION

Inhibitor formation is a major complication of haemophilia for which clinical trials are planned. Despite emerging novel haemostatic agents, challenges of rare disease trials are limited subjects and lack of an organized research organization with strategic resources and partnerships.

AIM

The charge to Working Group 1 was to establish scientific priorities and innovative implementation strategies to conduct inhibitor prevention and eradication trials. To determine feasibility of trial design and strategic resources and partnerships to be leveraged, two clinical trial concepts were considered.

RESULTS

For the Inhibitor Prevention Trial, we considered adaptive design with early stopping rules, dynamic randomization and Master Protocol models to reduce sample size; and registries to provide concurrent controls and natural history data. For the Inhibitor Eradication Trial using gene therapy, an adaptive design was considered in a small number of subjects, and, if safe and meeting regulatory requirements, enrolment would be expanded. A Haemophilia Clinical Trials Group (HCTG) infrastructure was envisioned, with uniform procedures and standardized outcomes, data collection and assays, within which trial concepts would be developed, vetted and prioritized by a Steering Committee, and submitted to NIH and other research sponsors for review and funding. Mechanistic studies would be embedded within the trials, early stage investigators trained and mentored, and the research infrastructure established within the haemophilia centre (HTC) network and supported by partnerships with foundations, community, federal partners and industry.

CONCLUSION

The success of inhibitor trials will depend on innovative trial design and an organized HCTG research infrastructure, leveraged through community partnerships.