Comparison of the concordance between clinical and histopathologic diagnosis of oral mucosal lesions in an Oral Medicine graduate program and the Oral Pathology biopsy service.
Notice bibliographique
Résumé
Background: The concordance between clinical and histopathologic diagnosis is vital to managing pathologic conditions. Comparing factors related to discrepancies between the clinical judgment and histopathologic study, which is the gold standard, will help identify weaknesses that should be improved so clinicians can provide better disease management to improve the quality of life of our patients. Objectives: To evaluate the concordance between the clinical and histopathological diagnosis of biopsied soft tissue specimens and analyze incidence variations and demographic information from two databases: 1. the Oral Medicine graduate program at the University of Alberta between August 2020 and August 2021, and 2. the Oral Pathology Biopsy Service database at the University of Alberta between 1985 and 2008. Methods: This retrospective study was approved by the Health Research Ethics Board, University of Alberta (Pro00116378). The anonymized databases contained biographic data and clinical and histopathologic information. The inclusion criteria included reports with complete clinical and histopathologic diagnoses of oral soft tissue biopsies. “Absolute Concordance” was determined if clinical and histopathological diagnostic SNOMED-CT codes were identical and, as a second analysis, if the clinical and histopathological diagnoses were identical at a synonyms level. “Relative Concordance” if diagnoses shared an etiopathologic cluster; and “Discordance” if they belonged to different clusters. The outcome measurement was the percentage of absolute concordance, relative concordance and discordance. The diagnostic accuracy according to prognosis was analyzed using Cohen’s kappa to determine the agreement between the diagnoses; also, sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) were calculated. Additionally, the relationship between gender and age and cluster concordance was tested using the Chi-square and Analyses of variance. Results: The University of Alberta database spanning from 1985 to 2008 constituted 19,259 analyzed cases; gender distribution was 10,095 (52.42%) females, 8,838 (45.89%) males and 326 (1.69%) unknowns. Age distribution included <14 years, 1,128 (5.85%); 15-24 years, 1,320 (6.85%); 25-64 years, 12,489 (64.85%); >65 years, 3,609 (18.74%); and unknown, 713 (3.71%). The absolute concordance comparing the SNOMED-CT codes was 47.17%, and by diagnostic synonyms, 50.22%. The relative concordance was 74.61%, and the discordance was 25.39%. The accuracy of the clinical diagnosis to detect OPMD showed a sensitivity of 76.9%, specificity of 97.6%, PPV of 87.3%, and NPV of 95.1%. Moreover, for malignancy identification, the sensitivity was 67.5%, specificity was 98.4%, PPV was 46.3%, and NPV was 99.3%. The Oral Medicine 2020-21 database comprised 122 cases, 67 (54.92%) females and 55 (45.08%) males. The age distribution was < 14 years, 1 (0.82%); 15-24 years, 3 (2.46%); 25-64 years, 75 (61.48%); and > 65 years, 43 (35.25%). The absolute concordance comparing the SNOMED-CT codes and synonyms was 36.89%. The relative concordance was 72.95%, and the discordance was 27.05%. The accuracy of the clinical diagnosis to detect OPMD showed a sensitivity of 84.4%, specificity of 89.0%, PPV of 87.5%, and NPV of 86.3%. Moreover, for malignancy identification, the sensitivity was 100%, specificity was 99%, PPV was 50%, and NPV was 100%. Conclusions: In the case of the Oral Medicine program, the concordance by etiopathologic clusters demonstrated moderate agreement, and the sensitivity to diagnose benign and OPMD was high. However, despite this high sensitivity, 12.7% and 15.6% of cases, respectively, were still misdiagnosed. Regarding the University of Alberta 1985-2008 database, the results indicated that concordance by clusters demonstrated a substantial agreement. While clinical examination effectively identifies patients without malignancy or OPMD, it is not sufficiently sensitive for diagnosing malignancy or OPMD. Therefore, the histopathological examination is essential to provide a definitive diagnosis, especially in those cases where cellular behavior dictates future management decisions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».