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. 2023 Aug 16:10:1208022.
doi: 10.3389/fmed.2023.1208022. eCollection 2023.

Pattern recognition of hematological profiles of tumors of the digestive tract: an exploratory study

Miguel A Santos-Silva  1   2 , Nuno Sousa  1   2   3   4 , Marina Majar  5 , Miguel Machado  5 , Joana Reis  1   2   3 , Joao C Sousa  1   2
Affiliations

Pattern recognition of hematological profiles of tumors of the digestive tract: an exploratory study

Miguel A Santos-Silva et al. Front Med (Lausanne). .

Abstract

Aims: In this study, we aimed to apply laboratory blood analysis to identify the hematological (based on hemoglobin concentration, erythrocytes, hematocrit, and RDW count) profiles associated with the most prevalent forms of digestive tract malignancies. Furthermore, we aimed to evaluate how these profiles contributed to distinguishing these tumors at diagnosis.

Methods: We collected data from the date of ICD-10 diagnostic coding for C15 esophagus, C16 stomach, C18 colon, and C19 rectum tumors of 184 individuals. The statistical analysis and data visualization approaches, notably the heat map and principal component analysis (PCA), allowed for creating a summary hematological profile and identifying the most associated parameters for each pathologic state. Univariate and multivariate data modeling and ROC analysis were performed in both SPSS and Python.

Results: Our data reveal unique patterns based on tumor development anatomical location, clustering the C18 colon and C19 rectum from the C15 esophagus and C16 stomach. We found a significant difference between C16 stomach carcinoma and the other tumors, which substantially correlated with raised RDW in conjunction with low hemoglobin concentration, erythrocytes, and hematocrit counts. In contrast, C18 colon carcinoma had the higher red blood cell count, allowing for the best classification metrics in the test set of the binary logistic regression (LR) model, accounting for an AUC of 0.77 with 94% sensitivity and 52% specificity.

Conclusion: This study emphasizes the significance of adding hematological patterns in diagnosing these malignancies, which could path further investigations regarding profiling and monitoring at the point of care.

Keywords: anatomical location; cancer; digestive tract tumor; hematological profile; pattern recognition.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Correlation heat map between each blood parameter and the tumors of the digestive tract.
Figure 2
Figure 2
Scores plot of the PCA showing a relationship between digestive tract tumors, based on the four hematologic parameters.
Figure 3
Figure 3
ROC curves and performance metrics of the LR prediction models for the classification of each digestive tract tumor.
See this image and copyright information in PMC

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