Prospective Analysis of Squamous Cell Carcinoma Antigen-1 and -2 for Diagnosing Sinonasal Inverted Papilloma.
Hitoshi HirakawaTaro IkegamiMasatomo ToyamaYurika OoshiroTomoyo HigaHidetoshi KinjyoShunsuke KondoNorimoto KiseYukashi YamashitaMikio SuzukiPublished in: Journal of clinical medicine (2024)
Background : The goal of this research was to confirm whether preoperative serum squamous cell carcinoma antigen (SCCA)-1 and -2 levels are useful diagnostic markers for sinonasal inverted papilloma (IP) in a prospective study. Methods : Participants were 102 patients who underwent consecutive endoscopic sinus surgery: 18 with IP, two with other types of papilloma, 77 with chronic rhinosinusitis, four with sinonasal cancer, and one with hemangioma. SCCA-1 and SCCA-2 were measured preoperatively by an automatic chemiluminescence immunoassay and an enzyme-linked immunosorbent assay, respectively. Results : SCCA-1 and SCCA-2 values were significantly correlated (r = 0.603, p < 0.001). Receiver operating characteristic analysis for differentiating papilloma (IP and other types of papilloma) from other diseases yielded an area under the curve of 0.860, with a Youden index of 1.75. Combined with SCCA-2 analysis, the detection system had a sensitivity and specificity of 0.65 and 0.98, respectively. While our study did not find a strong link between SCCA levels and skin or lung diseases, smoking status may influence SCCA levels in IP patients ( p = 0.035). We recommend a cutoff value of 1.8 ng/mL for SCCA-1 in IP diagnosis. Conclusions : SCCA-1 and SCCA-2 when combined with imaging and pathology hold promise for enhancing the preoperative detection of IP, which would be a valuable contribution to clinical practice.
Keyphrases
- squamous cell carcinoma
- end stage renal disease
- chronic rhinosinusitis
- ejection fraction
- newly diagnosed
- peritoneal dialysis
- patients undergoing
- magnetic resonance imaging
- high throughput
- magnetic resonance
- deep learning
- lymph node metastasis
- label free
- photodynamic therapy
- sensitive detection
- papillary thyroid
- artificial intelligence
- single cell
- squamous cell
- molecularly imprinted