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September 5, 2025Open Access

Machine Learning Uncovers Novel Predictors of PRRT Eligibility in Neuroendocrine Neoplasms

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Authors

GSGábor SipkaIFI. FarkasABAnnamária Bakos

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Overview

Retrospective analysis uncovers key factors influencing somatostatin receptor expression and PRRT prospects in metastatic neuroendocrine neoplasms.

Key Points

  • Mathematical models estimated somatostatin receptor expression accurately in 70-83% of cases, highlighting their effectiveness in predicting eligibility for therapy.
  • Key factors influencing treatment suitability included tumor origin, immunohistochemical markers, and clinical parameters such as age and disease extent.
  • SPECT/CT imaging showed strong potential in evaluating somatostatin receptor expression across 392 lesions, with notable correlations in metastatic sites.
  • Certain laboratory parameters could enhance individualised treatment strategies, indicating the potential for improved patient outcomes in neuroendocrine neoplasms.

Cite This Study

Sipka et al. (2025) studied this question.

synapsesocial.com/papers/68bb4def6d6d5674bcd01eb0https://doi.org/10.20944/preprints202509.0048.v1
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