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Poster session 17

1158P - A novel nomogram for predicting overall survival of small intestinal neuroendocrine tumors treated with PRRT

Date

14 Sep 2024

Session

Poster session 17

Topics

Tumour Site

Neuroendocrine Neoplasms

Presenters

Dimitrios Papantoniou

Citation

Annals of Oncology (2024) 35 (suppl_2): S749-S761. 10.1016/annonc/annonc1598

Authors

D. Papantoniou1, B.E. Ziolkowska2, M. Grönberg3, E. Tiensuu Janson4

Author affiliations

  • 1 Department Of Medical Sciences, Uppsala University, 751 85 - Uppsala/SE
  • 2 Radiotherapy And Chemotherapy 2nd Department, Maria Sklodowska-Curie National Research Institute of Oncology, 02-781 - Warsaw/PL
  • 3 Department Of Medical Sciences, Uppsala University, 751 05 - Uppsala/SE
  • 4 5th Floor, University Hospital Uppsala Akademiska Sjukhuset, 751 85 - Uppsala/SE

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Abstract 1158P

Background

There is no generally accepted model to predict overall survival (OS) of patients treated with peptide receptor radionuclide therapy (PRRT) for small intestinal neuroendocrine tumors (siNET).

Methods

We searched literature for non-experimental clinical and biochemical predictors of OS after treatment with PRRT. Among 13 potential markers related to patient baseline status, function of organs affected by PRRT toxicity, inflammation, tumor burden and tumor proliferation, seven candidate variables were selected based on previous publication results, and analyzed in a retrospective cohort of 326 patients treated with PRRT between 2005 and 2019 in a tertiary referral center. An accelerated failure-time model was used and a nomogram was constructed. The model was internally validated with bootstrapping, and its discrimination and calibration evaluated with Harrell’s c-index and calibration plots.

Results

During a median follow-up of 40 months, there were 230 deaths. All selected variables were significantly associated with OS in unadjusted analysis. A prognostic nomogram was created using age (0-68) and performance status (PS, 0-44), tumor markers chromogranin A (CgA, log, 0-100) and 5-hydroxyindoloacetaic acid (5HIAA, 0-57), albumin (0-15), alkaline phosphatase (ALP, log, 0-20) and hemoglobin (Hb, 0-32). The full model had good discriminatory ability (optimism-corrected c-index 0.74) and calibration. A backward selection algorithm was used to approximate the full model. The final model contained age, PS, CgA, 5HIAA and Hb.

Conclusions

We suggest a novel nomogram, based on a small number of readily available clinical and biochemical parameters, to predict OS after treatment with PRRT for siNET. Our nomogram may assist clinicians in more accurate clinical decision-making and patient counseling.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Swedish Cancer Society, Futurum – the Academy for Health and Care, Region Jönköping County.

Disclosure

All authors have declared no conflicts of interest.

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