Evidence map›Paper›PMID 42638353›Full record

ArticleJournal of clinical laboratory analysis2026

Development and Validation of a Nomogram Based on Red Blood Cell and Reticulocyte Parameters for Differentiating Thalassemia Trait From Iron Deficiency Anemia.

Yong Chen, Yazhen Mao, Jie Liu, Yice Lin, Dandan Chen

Abstract readValidation Study
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Article in Journal of clinical laboratory analysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Yong ChenDepartment of Laboratory Medicine, Fuzhou First General Hospital Affiliated With Fujian Medical University, Fuzhou, Fujian, China.ORCID https://orcid.org/0009-0005-6921-5573
Yazhen MaoDepartment of Laboratory Medicine, Fuzhou First General Hospital Affiliated With Fujian Medical University, Fuzhou, Fujian, China.ORCID https://orcid.org/0000-0002-7877-8870
Jie LiuDepartment of Laboratory Medicine, Fuzhou First General Hospital Affiliated With Fujian Medical University, Fuzhou, Fujian, China.
Yice LinDepartment of Laboratory Medicine, Fuzhou First General Hospital Affiliated With Fujian Medical University, Fuzhou, Fujian, China.
Dandan ChenDepartment of Laboratory Medicine, Mindong Hospital Affiliated to Fujian Medical University, Ningde, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThalassemia trait (TT) and iron deficiency anemia (IDA) are the most common causes of microcytic hypochromic anemia with overlapping hematological features, complicating differential diagnosis. This study developed and internally validated a nomogram incorporating red blood cell (RBC) and reticulocyte parameters to preliminarily distinguish TT from IDA.

methodsA retrospective cohort of 517 patients (320 IDA, 197 TT) was randomly divided into training (n = 361) and validation (n = 156) cohorts at a 7:3 ratio using stratified random sampling according to diagnostic group. RBC parameters (RBC count, MCV, MCH) and reticulocyte indices (RET%, IRF, LFR, MFR, HFR) were collected. LASSO regression identified key variables, followed by multivariate logistic regression. Model performance was evaluated using ROC curves, calibration plots, and decision curve analysis (DCA).

resultsLASSO regression selected four predictors: RBC count, MCV, RET%, and HFR. Multivariate analysis showed elevated MCV (p < 0.001), RET% (p < 0.001), and HFR (p < 0.001) were associated with IDA, while elevated RBC count (p < 0.001) predicted TT. The nomogram achieved excellent discrimination with AUC of 0.900 in training and 0.904 in validation cohorts. Calibration plots showed good agreement and DCA suggested potential clinical net benefit across threshold probabilities of 7%-96% (training) and 5%-97% (validation).

conclusionsThis nomogram integrating RBC count, MCV, RET%, and HFR showed promising performance for the preliminary differentiation of TT from IDA and may serve as a practical, noninvasive screening aid for risk stratification and prioritization of confirmatory testing. It should not be used as a substitute for hemoglobin electrophoresis, thalassemia genetic testing, or iron studies.

Indexed as

Anemia, Iron-DeficiencyErythrocytesNomogramsReticulocytesThalassemiaAdolescentAdultDiagnosis, DifferentialErythrocyte CountErythrocyte IndicesFemaleHumansMaleMiddle AgedRetrospective StudiesROC Curve

Identifiers

PMID42638353
PMCPMC13504082

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