Fractures following hematopoietic stem cell transplantation: Risk prediction and evaluation of prevention and treatment stratergies
In the last couple of decades, the number of survivors following a hematopoietic stem cell transplantation (HSCT) has been steadily increasing. Bone loss and its clinical manifestations of osteopenia, osteoporosis and fragility fractures are rapidly occurring, long-lasting and common complications following HSCT. Bone remodeling in the context of HSCT is multifactorial and pre-, peri- and post- transplantation factors are involved in the dysregulation of bone homeostasis. Little research has been conducted to identify patients at high risk of bone complications following HSCT. The overall objectives of this study are to identify patients at high risk of bone complications that can potentially benefit from pharmacological intervention in a large cohort of patients that received a HSCT and to evaluate the most effective methods to prevent and treat bone loss and fractures following HSCT. ^ This project was divide into three papers with the following aims: 1) To evaluate the predictive ability of the World Health Organization Fracture Risk Assessment model - FRAX in identifying osteoporotic fractures in patients following a HSCT; 2) To compare and contrast the rates of osteoporotic fractures and evaluate a comprehensive set of demographic and clinical characteristics in osteoporotic fracture risk prediction following HSCT in patients with and without multiple myeloma; 3) To evaluate the evidence and analyze the treatments currently available to treat or prevent bone loss following HSCT in a systematic review and meta-analysis. The first two aims utilize data from a 10-year cohort of adult patients that underwent a HSCT at The University of Texas MD Anderson Cancer Center. All patients were retrospectively followed for a minimum of 3 years for assessment of osteoporotic fractures. (Abstract shortened by ProQuest.) ^
Pundole, Xerxes N, "Fractures following hematopoietic stem cell transplantation: Risk prediction and evaluation of prevention and treatment stratergies" (2016). Texas Medical Center Dissertations (via ProQuest). AAI10249550.