Evidence map›Paper›PMID 41466945›Full record

ArticleCureus2025

Diagnostic Concordance Between Clinical and Histopathologic Diagnoses of Oral Mucosal Lesions: A Retrospective Study.

Patricia Hernandez-Rivera, Masoud Mirimoghaddam, Hollis Lai, Pallavi Parashar

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Patricia Hernandez-RiveraFaculty of Medicine and Dentistry, University of Alberta, Edmonton, CAN.
Masoud MirimoghaddamFaculty of Medicine and Dentistry, University of Alberta, Edmonton, CAN.
Hollis LaiFaculty of Medicine and Dentistry, University of Alberta, Edmonton, CAN.
Pallavi ParasharFaculty of Medicine and Dentistry, University of Alberta, Edmonton, CAN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Accurate diagnosis is essential for effective treatment and for determining the outcome of any pathologic condition. This study aimed to evaluate the concordance between the clinical and histopathologic diagnoses of biopsied soft-tissue specimens submitted to the Oral Pathology Biopsy Service at the University of Alberta over a 23-year period. Methods The clinical and histopathological diagnoses were coded using the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT). Subsequently, all the diagnoses were classified according to their pathogenesis. The outcome measurement was the percentage of absolute concordance, relative concordance, and discordance. Diagnostic agreement was evaluated using Cohen's kappa; sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) were calculated. Additionally, the relationship between gender, age, and pathogenic-cluster concordance was tested using the Chi-square test or the Sample t-test. Results The anonymized database comprised 18,935 oral soft-tissue biopsies. The absolute concordance by SNOMED-CT codes was 47.8%, and by synonyms, 52.1%. The relative concordance was 76.2%, and the discordance was 23.8%. The accuracy of the clinical diagnosis in detecting oral potentially malignant disorders (OPMDs) was evaluated, yielding a sensitivity of 79.3%, a specificity of 97.9%, a PPV of 88.4%, and an NPV of 95.9%. Moreover, for malignant lesions, the clinical diagnosis demonstrated a sensitivity of 67.8%, a specificity of 98.5%, a PPV of 47.0%, and an NPV of 99.4%. Conclusions The results indicated that cluster concordance demonstrated substantial agreement. While clinical examination effectively identifies patients without malignancy or OPMD, it is not sufficiently sensitive to diagnose them. Therefore, histopathologic evaluation of biopsy specimens remains critical for achieving an accurate and definitive diagnosis.

Indexed as

clinical diagnosisconcordancedescriptive analysishistopathologyoral lesions

Identifiers

PMID41466945
PMCPMC12744888

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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.