Evidence map›Paper›PMID 42536644›Full record

SynthesisPloS one2026

Diagnostic accuracy of automated hematology analyzer abnormal flags for detecting hematological malignancies: A systematic review and meta-analysis.

Zewudu Mulatie, Bruktawit Eshetu, Afewerk Habtamu, Sisay Desale, Saleamlak Sebsibe, Yonas Erkihun, Yeshimebet Kassa, Tesfaye Gessese, Mihreteab Alebachew, Mikiyas Shimeles and 2 more

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in PloS one, 2026. 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

12 authors.

Zewudu MulatieDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.ORCID https://orcid.org/0009-0006-9702-6689
Bruktawit EshetuDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Afewerk HabtamuDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.ORCID https://orcid.org/0009-0005-5238-9884
Sisay DesaleDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Saleamlak SebsibeDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Yonas ErkihunDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Yeshimebet KassaDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Tesfaye GesseseDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Mihreteab AlebachewDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Mikiyas ShimelesDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Mahider Shimelis FeyisaSchool of Medical Laboratory Sciences, Asrat Weldeyes Health Science Campus, Debre Berhan University, Debre Berhan, Ethiopia.
Dereje Mengesha BertaDepartment Hematology and immunohematology, School of Biomedical and Laboratory Science, College of Medicine and Health Science, University of Gondar, Gondar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHematological malignancies including leukemia, lymphoma, and myelodysplastic syndromes, are characterized by clonal proliferation of abnormal blood or bone marrow cells. Early and accurate detection is essential for improving treatment outcomes and survival. Automated hematology analyzers generate abnormal flags that may indicate underlying hematologic malignancies; however, their overall diagnostic accuracy has not been comprehensively evaluated. This systematic review and meta-analysis aimed to assess the diagnostic performance of abnormal flags for detecting hematological malignancies.

methodsA systematic search of PubMed, PubMed Central, Scopus, ScienceDirect, and Google Scholar was conducted to identify relevant diagnostic accuracy studies. Methodological quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2(QUADAS-2) tool. Pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using a bivariate random-effects model in Stata version 17.0. Heterogeneity was assessed using the I2 statistic, and subgroup and meta-regression analyses were performed to explore potential sources of variability.

resultsTwenty-eight studies met the inclusion criteria. The pooled sensitivity and specificity of abnormal hematology analyzer flags for detecting hematological malignancies were 91% (95% CI: 87%-94%) and 89% (95% CI: 84%-92%), respectively, indicating good diagnostic accuracy. Significant heterogeneity was observed across studies (I2 > 50%). Meta-regression analysis identified the type of abnormal flag as a significant source of heterogeneity in sensitivity (p < 0.001), whereas both the type of abnormal flag and the analyzer platform significantly influenced specificity.

conclusionAutomated hematology analyzer abnormal flags showed promising diagnostic performance. However, substantial heterogeneity and differences in analyzer platforms, flag types, and reference standards reduce the certainty and generalizability of pooled estimates. Nevertheless, these findings support the use of abnormal hematology analyzer flags as an effective initial screening tool in routine laboratory practice, particularly in resource-limited settings where rapid and cost-effective diagnostic support is essential. Systematic review registration PROSPERO (CRD42024601908).

Indexed as

Hematologic NeoplasmsHematologyHumansSensitivity and Specificity

Identifiers

PMID42536644
PMCPMC13426980

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.