Evidence map›Paper›PMID 42527452›Full record

Articlenpj health systems2025

Network analysis of cross-income-level collaboration on multiple myeloma in sub-Saharan Africa.

Kaiyi Yang, Sam Benkwitz-Bedford, Jean-Baptiste Cazier, Fabian Spill

Abstract read
In one paragraph

Article in npj health systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kaiyi YangSchool of Mathematics, University of Birmingham, Birmingham, UK.
Sam Benkwitz-BedfordCentre for Computational Biology, University of Birmingham, Birmingham, UK.
Jean-Baptiste CazierFrancis Crick Institute, London, UK. jean-baptiste.cazier@crick.ac.uk.
Fabian SpillSchool of Mathematics, University of Birmingham, Birmingham, UK. f.spill@bham.ac.uk.

Funding

UKRI MR/T043571/1
6 · The paper itself

Abstract

Cross-income-level collaboration (CILC) is crucial for developing global health approaches that benefit low- and middle-income countries (LMICs). Multiple myeloma (MM) is a representative example of a complex, understudied disease in sub-Saharan Africa (SSA). Based on publications, we developed a network analysis tool to assess scientific collaborations. Here, we present findings from a systematic analysis of publications retrieved from PubMed between January 2002 and June 2022. We evaluated individual institutional contributions and collaboration patterns using undirected weighted networks. Our findings reveal that intra-income-level collaborations dominate MM research in SSA, with high-income countries (HICs) primarily engaging with a few local institutions, mainly in South Africa and Nigeria. Increasing CILC is essential to advance research in this area. Our analysis tool provides insights into the collaboration strength, highlights gaps in the field and identifies leading institutions, ultimately aiming to support the development of more effective international collaboration and research strategies.

Identifiers

PMID42527452
PMCPMC13354229

What OpenQuestion holds

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Registered trials

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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.