Ultrasonographically-guided fine-needle aspiration of axillary lymph nodes: role in breast cancer management
2003

Ultrasound-guided Fine-Needle Aspiration for Breast Cancer

Sample size: 298 publication Evidence: high

Author Information

Author(s): Sapino A, Cassoni P, Zanon E, Fraire F, Croce S, Coluccia C, Donadio M, Bussolati G

Primary Institution: University of Turin

Hypothesis

Can ultrasonographic examination of axillary lymph nodes combined with fine-needle aspiration improve preoperative staging in breast cancer patients?

Conclusion

Ultrasound-guided fine-needle aspiration can reliably predict the presence of metastases in axillary lymph nodes, potentially allowing for more appropriate surgical treatment.

Supporting Evidence

  • Ultrasound-guided FNAC showed high sensitivity and absolute specificity in diagnosing lymph node metastases.
  • 49 out of 88 metastatic lymph nodes were correctly identified by FNAC.
  • The combination of ultrasound and FNAC improved diagnostic accuracy compared to ultrasound alone.
  • Only 16% of cytological diagnoses were false negatives, indicating high reliability of the method.
  • Immunocytochemistry increased the sensitivity of routine cytological diagnosis.

Takeaway

Doctors can use a special ultrasound and needle technique to check if breast cancer has spread to nearby lymph nodes, which helps them decide the best treatment.

Methodology

The study involved 298 breast cancer patients who underwent ultrasound examination and fine-needle aspiration of axillary lymph nodes before surgery.

Potential Biases

There may be risks of bias related to the selection of patients and the interpretation of cytological results.

Limitations

The study may have limitations related to the skill of the operators performing the procedures and the potential for false negatives.

Participant Demographics

The study included 298 patients with breast carcinomas, with a majority being invasive carcinomas.

Statistical Information

P-Value

p<0.05

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1038/sj.bjc.6600744

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