Gonadal failure is a health and quality-of-life concern in hematopoietic cell transplant (HCT) survivors. While ovarian dysfunction is nearly universal following myeloablative (MA) conditioning, the risk is unclear after reduced-intensity conditioning (RIC). Gonadotropin-releasing hormone agonists decrease ovarian failure rates following conventional chemotherapy, but little is known about its effectiveness with HCT. We investigated the impact of leuprolide on ovarian function after MA conditioning and monitored ovarian function after RIC in this descriptive pilot study. Post-menarchal females <50 years undergoing HCT with adequate baseline ovarian function (follicle-stimulating hormone (FSH) level <40 mIU/mL and normal menstruation) were eligible. Prior to MA conditioning, leuprolide was administered. Those undergoing RIC were observed. FSH was measured at various time points. Seventeen women aged 12-45 years were evaluated (7 in the intervention group and 10 in the observation group). Compared to the historical high rate of ovarian failure after MA conditioning, 3 of 7 evaluable Lupron recipients had ovarian failure at a median of 703 days post transplant. Ovarian failure occurred in 1 of 10 recipients of RIC at a median follow-up of 901 days. In conclusion, leuprolide may protect ovarian function after MA conditioning. Additionally, RIC with cyclophosphamide, fludarabine and low-dose TBI has a low risk of ovarian failure.
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http://dx.doi.org/10.1038/bmt.2016.150 | DOI Listing |
Biometrics
January 2025
Department of Biostatistics, University of Michigan at Ann Arbor, Ann Arbor, MI 48109, United States.
Graphical models are powerful tools to investigate complex dependency structures in high-throughput datasets. However, most existing graphical models make one of two canonical assumptions: (i) a homogeneous graph with a common network for all subjects or (ii) an assumption of normality, especially in the context of Gaussian graphical models. Both assumptions are restrictive and can fail to hold in certain applications such as proteomic networks in cancer.
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Division of Reproductive Sciences, Department of Obstetrics and Gynecology, Duke University School of Medicine, 701 West Main Street, Suite 510, Duke, P.O. Box 90534, Durham, NC 27701, USA.
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Department of Physiological Sciences, Interinstitutional Post-Graduate Program of Physiological Sciences, Federal University of São Carlos (UFSCar), São Carlos 13.566-490, SP, Brazil.
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