Evidence map›Paper›PMID 41998030›Full record

ArticleScientific reports2026

Hematological parameters as predictive indicators of disease stage in patients with cervical cancer.

Muluken Walle, Zewudu Mulatie, Negesse Cherie, Abdirizak Mahdi Ibrahim, Dereje Mengesha Berta

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Article in Scientific reports, 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 authors.

Muluken WalleDepartment of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, P.O. Box: 196, Gondar, Ethiopia. muluken.walle23@gmail.com.
Zewudu MulatieDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia.
Negesse CherieDepartment of Quality Assurance and Laboratory Management, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Abdirizak Mahdi IbrahimShiekh Hassan Yabare Comprehensive Specialized Hospital, Jigjiga University, Jigjiga, Ethiopia.
Dereje Mengesha BertaDepartment of Hematology and Immunohematology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, P.O. Box: 196, Gondar, Ethiopia.

Funding

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6 · The paper itself

Abstract

backgroundHematological abnormalities are highly common in cervical cancer and may serve as key indicators of disease progression. This study evaluates the predictive value of routine hematological parameters in identifying the stage of cervical cancer. This comparative cross-sectional study enrolled 200 women with cervical cancer, categorized into early and advanced clinical stages groups (100 per group). A consecutive sampling technique was employed to select the study participants. Three milliliters of venous blood were collected from each participant for hematological analysis. Data analysis was performed using Stata version 17 software. The Mann-Whitney U test was employed to compare hematological profiles between the two groups. Spearman's rank correlation was used to assess the relationship between hematological parameters and the stage of cervical cancer. Furthermore, ROC curve analysis was used to determine the predictive values and optimal cut-off points of hematological parameters in identifying disease stage. A p value < 0.05 was considered statistically significant. Hematological parameters, including hemoglobin (Hb) levels, hematocrit, and red blood cell (RBC) indices, were significantly lower in patients with advanced-stage cervical cancer compared to those in the early stage (p < 0.05). Conversely, white blood cell (WBC) count, platelet count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) were significantly higher in the advanced-stage group. ROC curve analysis revealed that NLR had the highest discriminative power (AUC = 0.9049), followed by neutrophil count (AUC = 0.8500), WBC count (AUC = 0.8248), PLR (AUC = 0.7776), MLR (AUC = 0.7466), and platelet count (AUC = 0.7335). Disease progression in cervical cancer is associated with a significant decline in RBC parameters and a concurrent elevation in inflammatory markers. WBC, neutrophil, and platelet counts, as well as NLR, PLR, and MLR, demonstrated desirable predictive performance in discriminating advanced-stage from early-stage cervical cancer. These hematological parameters may serve as potential indicators of disease stage; however, further prospective, multicenter studies are required to confirm these findings and validate their clinical applicability.

Indexed as

Uterine Cervical NeoplasmsAdultCross-Sectional StudiesFemaleHematocritHemoglobinsHumansLeukocyte CountMiddle AgedNeoplasm StagingNeutrophilsPlatelet CountROC CurveHemoglobinsCervical cancerHematological parametersPrognosisStages

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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.