Engraftment Syndrome after Nonmyeloablative Allogeneic Hematopoietic Stem Cell Transplantation: Incidence and Effects on Survival

AbstractEngraftment syndrome (ES) encompasses a constellation of symptoms that occur during neutrophil recovery after both autologous and allogeneic hematopoietic stem cell transplantation (HCT). Although it is well characterized after conventional myeloablative procedures, limited data exist on this complication after nonmyeloablative allogeneic HCT. The clinical manifestations, incidence, and risk factors associated with ES were investigated in a consecutive series of patients undergoing cyclophosphamide/fludarabine-based nonmyeloablative allogeneic HCT from a related HLA-compatible donor. Fifteen (10%) of 149 patients (median age, 53 years; range, 27–66 years) developed ES; the onset of symptoms occurred at a median of 10 days (range, 3–14 days), and they consisted of fever (100%), cough (53%), diffuse pulmonary infiltrates (100%), rash (13%), and room air hypoxia (87%). ES was more likely to develop in patients who received empiric amphotericin formulations after transplant conditioning (Fisher exact test; P = .007). In a multivariate analysis, older patient age, female sex, and treatment with amphotericin were predictors for the development of ES. Intravenous methylprednisolone led to the rapid resolution of ES; however, transplant-related mortality was significantly higher (cumulative incidence, 49% versus 16%; P = .0005), and median survival was significantly shorter (168 versus 418 days; P = .005) in patients with ES compared with non-ES patients. In conclusion, ES occurs commonly after cyclophosphamide/fludarabine-based nonmyeloablative transplantation and responds rapidly to corticosteroid treatment, but it is associated with a higher risk of nonrelapse mortality and with shorter overall survival

Understanding the Impact of Belzutifan on Treatment Strategies for Patients with VHL

Belzutifan was recently approved for the management of Von Hippel–Lindau disease (VHL). Given the morbidity of recurrent treatment, systemic therapy to reduce or eliminate the need for surgery has been long-awaited. Herein, we sought to gain insight about future utilization by surveying VHL  experts in the United States. A survey developed by members of the VHL Alliance (VHLA) Clinical Advisory Council was distributed to kidney cancer providers at VHLA and National Comprehensive Cancer Network (NCCN) centers. Surveys were administered on a secure web-based platform. A total of 60 respondents from 29 institutions participated. Urologists (50%) and medical oncologists (43%) represented the majority of participants. The majority (98%) of respondents anticipated that belzutifan’s approval would signifi-cantly change the current treatment landscape. Most reported that therapy should be continuous (76%). There was a difference in willingness to prescribe belzutifan by specialty (38% of urologists vs 91% of medical oncologists (P = 0.02). In individuals with renal tumors <3 cm, 36% would still recommend surveillance, while 36% would initiate belzutifan to prevent growth. In those with multifocal renal lesions and growth of a solitary tumor on belzutifan, 50% would proceed with only treatment of that site. In conclusion, VHL kidney cancer specialists anticipate a paradigm shift with the approval of belzutifan. Provider roles may change with movement away from surgical management. Opinions on treatment indications, such as when to initiate therapy and how to best salvage, vary widely and collaborative efforts among experts may assist in the development of clinical guidelines

Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%). The correct classification by subtype was 19/20 (95%) for clear cell, 14/14 (100%) for papillary, 17/19 (89%) for chromophobe, 18/19 (95%) for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors