Objective: Information about the long-term survival impact of hematopoietic stem cell transplant (HSCT) in adults with relapsed/refractory B-cell acute lymphoblastic leukaemia is limited. The objective was to conduct a systematic review identifying studies reporting survival in HSCT-receiving patients and apply parametric analyses to predict long-term survival.
Materials And Methods: Twenty-five relevant studies were identified. Analyses were conducted in 10 studies (n=503; "global" analysis) reporting overall survival (OS) data as Kaplan-Meier curves or at patient level. Four studies (n=217; "subgroup" analysis) measured OS from the point of HSCT. Patient-level data were recreated from Kaplan-Meier curves and pooled, with six models tested for longer-term extrapolation. Additionally, a sensitivity analysis was undertaken involving removal of data from the oldest study cohort (recruited between 1981-1997) to determine if the year which patients received HSCT impacted survival compared to post-2009 data.
Results: Median OS and five-year survival probability were 11.4 months and 24.4% (95% CI, 20.5-28.5%) in the global analysis, and 12.0 months and 28.4% (95% CI, 22.1-34.9%) in the subgroup analysis. The generalised gamma and Gompertz models fit longer-term extrapolation criteria. The generalised gamma model predicted survival at 10.4% vs. 14.8% (15 years), 8.3% vs. 12.8% (20 years), and 6.9% vs. 11.4% (25 years) for the global and subgroup analysis, respectively. The Gompertz model predicted survival to plateau at 23% vs. 25.6% just before 10 years. The sensitivity analysis excluding older data found median survival increased two-fold (25.3 vs. 12 months).
Conclusions: Results synthesize long-term evidence of outcomes for HSCT-receiving patients, providing a basis for treatment comparison. Risk of death is low beyond four years and newer data appears correlated with improved outcomes.
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http://dx.doi.org/10.26355/eurrev_202202_28007 | DOI Listing |
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.
View Article and Find Full Text PDFPlant Physiol Biochem
January 2025
Laboratory of Plant Stress Biology and Biotechnology, Department of Plant Genetics and Crop Breeding, Czech Agrifood Research Center, Drnovská 507, 161 06, Prague 6, Ruzyně, Czech Republic.
Cold acclimation and vernalization represent the major evolutionary adaptive responses to ensure winter survival of temperate plants. Due to climate change, mild winters can paradoxically worsen plant winter survival due to cold deacclimation induced by warm periods during winter. It seems that the ability of cold reacclimation in overwintering Triticeae cereals is limited, especially in vernalized plants.
View Article and Find Full Text PDFPlant Physiol Biochem
January 2025
College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, 310058, China. Electronic address:
Competition is ubiquitous and an important driver of tree mortality. Non-structural carbohydrates (NSCs, including soluble sugars and starch) and C-N-P stoichiometries are affected by the competitive status of trees and, in turn, physiologically determine tree growth and survival in competition. However, the physiological mechanisms behind tree mortality caused by intraspecific competition remain unclear.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Department of Cardiology, Royal North Shore Hospital, Sydney, NSW, Australia.
Objective: We aimed to develop a highly interpretable and effective, machine-learning based risk prediction algorithm to predict in-hospital mortality, intubation and adverse cardiovascular events in patients hospitalised with COVID-19 in Australia (AUS-COVID Score).
Materials And Methods: This prospective study across 21 hospitals included 1714 consecutive patients aged ≥ 18 in their index hospitalization with COVID-19. The dataset was separated into training (80%) and test sets (20%).
West Afr J Med
September 2024
Medical Microbiology & Parasitology Department, University of Ilorin, Ilorin, Nigeria. Email:
Background: Neonatal sepsis (NNS) is a known cause of morbidity and mortality especially in developing countries. The global resistance scourge may worsen the management outcomes of NNS. This study aims to determine the current profile of bacteriological agents of NNS, their resistance status and associated mortality in our setting.
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