Concordancia diagnóstica entre diagnósticos clínicos e histopatológicos de lesiones de la mucosa oral: un estudio...

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.