Evidence map›Paper›PMID 37663664›Full record

ArticleFrontiers in medicine2023

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

Miguel A Santos-Silva, Nuno Sousa, Marina Majar, Miguel Machado, Joana Reis, Joao C Sousa

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2023. 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
0.5field-weighted citation impact, top 26% of its field
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, 2 citations in OpenAlex.

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

6 authors at 3 institutions in 1 country.

Miguel A Santos-SilvaLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus de Gualtar, Braga, Portugal.
Nuno SousaLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus de Gualtar, Braga, Portugal.
Marina MajarClinical Pathology Department, Hospital de Braga, Braga, Portugal.
Miguel MachadoClinical Pathology Department, Hospital de Braga, Braga, Portugal.
Joana ReisLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus de Gualtar, Braga, Portugal.
Joao C SousaLife and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus de Gualtar, Braga, Portugal.
University of Minho · PTHospital Braga · PTClinical Academic Center of Braga · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

anatomical locationcancerdigestive tract tumorhematological profilepattern recognition

Identifiers

PMID37663664
PMCPMC10469010
OpenAlexW4385950205

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.