BREAST CANCER DIAGNOSIS: A COMPARATIVE STUDY OF METHODS BASED ON SENSITIVITY AND SPECIFICITY

Аннотация

This study compares different methods for diagnosing breast cancer, focusing on their sensitivity, specificity, and clinical usefulness. Using the PICO framework, we reviewed key studies published from 2002 to 2024, sourced from databases like PubMed, Scopus, and Google Scholar. In total, we analysed 8 studies, covering a range of diagnostic techniques. These methods include traditional approaches like Core Needle Biopsy (CNB) and Fine Needle Aspiration (FNA), as well as more advanced methods such as Abbreviated MRI(ABB-MRI), image segmentation algorithms, Raman and infrared spectroscopy, blood- based proteomics, and cytometric testing. The findings showed that CNB had the highest diagnostic performance overall. However, ABB-MRI and some molecular techniques offered strong non-invasive alternatives. Computational tools, while promising, still need more validation for widespread use. In conclusion, no single diagnostic method stood out as the best for all cases. Instead, a combination of different approaches, tailored to each patient’s specific situation, seems to be the most accurate and efficient strategy for detecting breast cancer. Keywords: Breast cancer, diagnosis, sensitivity, specificity, core needle biopsy, MRI, spectroscopy, proteomics, image segmentation, SCM test. INTORDUCTION In breast cancer diagnosis, the clinical relevance of sensitivity and specificity cannot be overstated, as these metrics directly impact patient outcomes by guiding therapeutic decisions and minimizing diagnostic errors. Sensitivity ensures that malignant cases are correctly identified, crucial for initiating timely treatment and preventing disease progression. Specificity, on the other hand, reduces false positives, sparing patients from unnecessary anxiety, biopsies, and interventions. The ideal diagnostic method balances both, adapting to clinical needs whether in screening asymptomatic populations or confirming malignancy in symptomatic patients. With evolving technologies—from imaging modalities like MRI to molecular and computational diagnostics—emphasis on sensitivity and specificity helps clinicians choose the most effective approach for each scenario. As breast cancer presentations and patient risk profiles vary, the nuanced application of these performance metrics ensures more accurate, patient-centred care and supports the broader goals ofearly detection and personalized oncology. 98,7:ROTCAFTCAPMI.SECNEICSLACIDEM ,5202 ,lirpA,5emuloV gro.srehsilbupcimedaca.www