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716 Advancing tailored treatments: a predictive nomogram based on ultrasound and laboratory data to assess nodal involvement in endometrial cancer patients
  1. Ida Pino1,
  2. Elisa Gozzini2,
  3. Davide Radice3,
  4. Sara Boveri4,
  5. Anna Daniela Iacobone1,
  6. Ailyn Mariela vidal Urbinati1,5,
  7. Francesco Multinu6 and
  8. Dorella Franchi1
  1. 1Preventive Gynecology Unit, European Institute of Oncology IRCCS, Milan, Italy
  2. 2Department of Clinical and Experimental Sciences, University of Brescia,, Brescia, Italy
  3. 3Division of Epidemiology and Biostatistics, IEO European Institute of Oncology IRCCS, Milan, Italy
  4. 4Laboratory of Biostatistics and Data Management, Scientific Directorate, IRCCS Policlinico San Donato, Milan, Italy
  5. 5Department of Biomedical Sciences, University of Sassari, Sassari, Italy
  6. 6Department of Gynecologic Surgery, IRCCS European Institute of Oncology, Milan, Italy


Introduction/Background Assessing lymph node metastasis is crucial in determining the optimal therapeutic approach for endometrial cancer (EC). Considering the impact of lymphadenectomy, there is an urgent need for a cost-effective and easily applicable method to evaluate the risk of lymph-node metastasis in case of sentinel lymph node (SLN) biopsy failure.

Methodology This retrospective monocentric study enrolled EC patients who underwent surgical staging with nodal assessment. Data concerning demographic, clinicopathological, ultrasound, and surgical characteristics were collected from medical records. Ultrasound examinations were conducted in accordance with the IETA statement.

Results We identified 425 patients, and after applying exclusion criteria, the analysis included 313 women. Parameters incorporated into the nomogram were selected via univariate and multivariable analyses, including platelet count, myometrial infiltration, minimal tumor-free margin, and CA125. The nomogram exhibited good accuracy in predicting lymph node involvement with an AUC of 0.88. Using a cutoff of 10% likelihood of nodal involvement, the nomogram displayed a low false-negative rate of 0.04 (95% CI 0.00–0.19) in the training set.

Conclusion The adaptability of this straightforward model renders it suitable for implementation across diverse clinical settings, aiding gynecologic oncologists in preoperative patient evaluations and facilitating the design of personalized treatments. However, external validation is mandatory to confirm diagnostic accuracy.

Disclosures All authors declare no conflicts of interest.

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