Multicomponent Strategy Improves Human Papillomavirus Vaccination Rates Among Adolescents with Sickle Cell Disease.

OBJECTIVE: To evaluate the effectiveness of a vaccine strategy bundle to increase human papillomavirus (HPV) vaccine initiation and completion in a specialty clinic setting. STUDY DESIGN: Our Hematology clinic utilized an implementation framework from October 1, 2018, to December 31, 2019, involving nurses, nursing coordinators, and clinicians in administering the HPV vaccination series to our adolescent sickle cell sample of nearly 500 patients. The bundle included education for staff on the need for HPV vaccine administration, provider incentives, vaccines offered to patients in SCD clinics, and verification of patients' charts of vaccine completion. RESULTS: Following the implementation of the bundle, the cumulative incidence of HPV vaccination initiation and completion improved from 28% to 46% and 7% to 49%, respectively. Both rates remained higher postimplementation as well. HPV vaccination series completion was associated with a decreased distance to the health care facility, lower state deprivation rank, and increased hospitalizations. CONCLUSION: Our clinic's implementation strategy successfully improved vaccine completion rates among adolescents with sickle cell disease (SCD) while continuing to educate staff, patients, and families on the importance of cancer prevention among people living with SCD.

GMEPS: a fast and efficient likelihood approach for genome-wide mediation analysis under extreme phenotype sequencing.

Due to many advantages such as higher statistical power of detecting the association of genetic variants in human disorders and cost saving, extreme phenotype sequencing (EPS) is a rapidly emerging study design in epidemiological and clinical studies investigating how genetic variations associate with complex phenotypes. However, the investigation of the mediation effect of genetic variants on phenotypes is strictly restrictive under the EPS design because existing methods cannot well accommodate the non-random extreme tails sampling process incurred by the EPS design. In this paper, we propose a likelihood approach for testing the mediation effect of genetic variants through continuous and binary mediators on a continuous phenotype under the EPS design (GMEPS). Besides implementing in EPS design, it can also be utilized as a general mediation analysis procedure. Extensive simulations and two real data applications of a genome-wide association study of benign ethnic neutropenia under EPS design and a candidate-gene study of neurocognitive performance in patients with sickle cell disease under random sampling design demonstrate the superiority of GMEPS under the EPS design over widely used mediation analysis procedures, while demonstrating compatible capabilities under the general random sampling framework.

Threshold selection for covariance estimation.

Thresholding is a regularization method commonly used for covariance estimation, which provides consistent estimators if the population covariance satisfies certain sparsity condition (Bickel and Levina, 2008a; Cai and Liu, 2011). However, the performance of the thresholding estimators heavily depends on the threshold level. By minimizing the Frobenius risk of the adaptive thresholding estimator for covariances, we conduct a theoretical study for the optimal threshold level, and obtain its analytical expression. A consistent estimator based on this expression is proposed for the optimal threshold level, which is easy to implement in practice and efficient in computation. Numerical simulations and a case study on gene expression data are conducted to illustrate the proposed method.