Logistic-Nomogram model based on red blood cell parameters to differentiate thalassemia trait and iron deficiency anemia in southern region of Fujian Province, China

Meihong Xu; Guojin Lin; Zhigao Dong; Qingqing Wang; Lili Ma; Junnan Su

doi:10.1002/jcla.24940

Logistic-Nomogram model based on red blood cell parameters to differentiate thalassemia trait and iron deficiency anemia in southern region of Fujian Province, China

J Clin Lab Anal. 2023 Jun;37(11-12):e24940. doi: 10.1002/jcla.24940. Epub 2023 Jun 30.

Authors

Meihong Xu¹, Guojin Lin¹, Zhigao Dong², Qingqing Wang², Lili Ma², Junnan Su²

Affiliations

¹ Department of Physical Examination, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China.
² Department of Blood Rheumatism Immunology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China.

Abstract

Background: Differentiation between thalassemia trait (TT) and iron deficiency anemia (IDA) is challenging and costly. This study aimed to construct and evaluate a model based on red blood cell (RBC) parameters to differentiate TT and IDA in the southern region of Fujian Province, China.

Methods: RBC parameters of 364 TT patients and 316 IDA patients were reviewed. RBC parameter-based Logistic-Nomogram model to differentiate between TT and IDA was constructed by multivariate logistic regression analysis plus nomogram, and then compared with 22 previously reported differential indices.

Results: The patients were randomly selected to a training cohort (n_TT = 248, n_IDA = 223) and a validation cohort (n_TT = 116, n_IDA = 93). In the training cohort, multivariate logistic regression analysis identified RBC count, mean corpuscular hemoglobin (MCH), and MCH concentration (MCHC) as independent parameters associated with TT susceptibility. A nomogram was plotted based on these parameters, and then the RBC parameter-based Logistic-Nomogram model g (μ_y ) = 1.92 × RBC count-0.51 × MCH + 0.14 × MCHC-39.2 was devised. The area under the curve (AUC) (95% CI) was 0.95 (0.93-0.97); sensitivity and specificity at the best cutoff score (120.24) were 0.93 and 0.89, respectively; the accuracy was 0.91. In the validation cohort, the RBC parameter-based Logistic-Nomogram model had AUC (95% CI) of 0.95 (0.91-0.98); sensitivity and specificity were 0.92 and 0.87, respectively; accuracy was 0.90. Moreover, compared with 22 reported differential indices, the RBC parameter-based Logistic-Nomogram model showed numerically higher AUC, net reclassification index, and integrated discrimination index (all p < 0.001).

Conclusion: The RBC parameter-based Logistic-Nomogram model shows high performance in differentiating patients with TT and IDA from the southern region of Fujian Province.

Keywords: differentiation; iron deficiency anemia; nomogram; red blood cell parameters; thalassemia trait.

MeSH terms

Anemia, Iron-Deficiency* / diagnosis
Anemia, Iron-Deficiency* / epidemiology
China / epidemiology
Diagnosis, Differential
Erythrocyte Indices
Erythrocytes
Humans
Logistic Models
Nomograms
beta-Thalassemia* / diagnosis