ReviewHistopathology2025
Global view of haematolymphoid tumor classifications and their application in low- and middle-income countries.
Review in Histopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Diagnostic and health system constraints in pediatric hematologic malignancies in East Africa and implications for WHO classification reconsidering in limited resource settings.Discover oncology · 2026Review
- The Diagnostic Evolution of Haematological Neoplasms: A Narrative Review of the Road to Two Genetically Focused Classification Systems Through a Resource-Limited Perspective.Diagnostics (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The accurate diagnosis of haematolymphoid malignancies is crucial for effective cancer care, but major obstacles to diagnosis exist in low- and middle-income countries (LMICs). This article explores the global applicability of current haematolymphoid classification systems, which are predominantly derived from data generated in high-income countries (HICs). Although disproportionately burdened with poor cancer outcomes, LMICs are generally faced with limited diagnostic resources, suboptimal access to therapeutics, and inadequate healthcare infrastructure. The article highlights the challenges faced by LMICs, including inconsistent access to high-quality pathology services, limited availability of advanced diagnostic techniques, and a lack of population-based cancer registry data. It also discusses the progress made in narrowing the gap between LMICs and HICs, such as the introduction of resource-adapted classifications, improved guidance on essential diagnostic tools, and strengthening of in-country professional pathology networks. Innovative diagnostic approaches, including gene expression profiling and machine learning, represent potential solutions for improving the diagnostic accuracy in LMICs, but addressable gaps remain. Recommendations are suggested for sustainable investments in diagnostic infrastructure, capacity-building, and population-based cancer registries to enhance the global applicability of haematolymphoid classification systems and improve outcomes for patients in LMICs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.