How Sarah Cannon Blood Cancer Network (SCBCN) Uses Historical Data to Benchmark Survival, Transplant Related Mortality, Engraftment and GVHD for Performance Improvement

Biology of Blood and Marrow Transplantation - Netherlands
doi 10.1016/j.bbmt.2018.12.629
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Elsevier BV

Related search

Dendritic Cells Recovery After Umbilical Cord Blood Transplant Is Superior to Related Donor Transplant and Predicts Better Survival

Biology of Blood and Marrow Transplantation
TransplantationHematology
2016English

Screening, Survival and Mortality for Cervical Cancer

2012English

Comparison of GVHD Biomarker Algorithms for Predicting Lethal GVHD and Non-Relapse Mortality

Biology of Blood and Marrow Transplantation
TransplantationHematology
2019English

Interpretable Deep Neural Network for Cancer Survival Analysis by Integrating Genomic and Clinical Data

BMC Medical Genomics
Genetics
2019English

Lower Risk of One-Year Non-Relapse Mortality, Rapid Engraftment and Better NK Cell Recovery With GvHD Prophylaxis Based in Post-Transplant Cyclophosphamide/Bendamustine in Pediatric Hematopoietic Stem Cell Transplantation

Biology of Blood and Marrow Transplantation
TransplantationHematology
2019English

Monocyte-Predominant Engraftment, Cytokine Levels and Early Transplant-Related Complications in Pediatric Hematopoietic Stem Cell Recipients

Cancer Medicine
Cancer ResearchNuclear MedicineRadiologyImagingOncology
2019English

GVHD After Unrelated Cord Blood Transplant in Children: Characteristics, Severity, Risk Factors and Influence on Outcome

Bone Marrow Transplantation
TransplantationHematology
2010English

How Is Students’ Motivation Related to Their Performance and Anxiety?

PISA in Focus
2019English

A Performance Benchmark for NetFlow Data Analysis on Distributed Stream Processing Systems

2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy