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Poster Display

88P - Can we improve the FIGO risk score? Developing the inFIGO score for patients with gestational trophoblastic neoplasia

Date

20 Jun 2024

Session

Poster Display

Presenters

Katia Mercedes Roque Perez

Citation

Annals of Oncology (2024) 9 (suppl_5): 1-4. 10.1016/annonc/esmoop103500

Authors

K.M. Roque Perez1, R.E. Ruiz2, M.A. Galvez Nino2, M. Castro-Mollo2, Y. Ferreyra3, O. Coanqui Gonzales2, M. Olivera2, N.I. Valdiviezo Lama2, R.A.B. De Mello4, L. Mas2

Author affiliations

  • 1 Instituto Nacional de Enfermedades Neoplasicas, Surquillo/PE
  • 2 INEN - Instituto Nacional de Enfermedades Neoplasicas, Lima/PE
  • 3 Universidad de Ingeniería y Tecnología, Lima/PE
  • 4 Nine of July University (UNINOVE), Sao Paulo/BR

Resources

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Abstract 88P

Background

Gestational trophoblastic neoplasia (GTN) is a rare tumor with excellent prognosis. Besides the FIGO risk score, factors related to immune nutritional status have not been studied. We proposed the immune nutritional FIGO (inFIGO) risk score based on the association of pretreatment body mass index (BMI), hemoglobin (Hb), prognostic nutritional index (PNI), and neutrophil-to-lymphocyte ratio (NLR) with response to chemotherapy (rCT) and overall survival (OS).

Methods

This is a retrospective analysis of women newly diagnosed with GTN between 2005 and 2019 who received CT. Wilcoxon test, univariate and multivariate analysis were performed to evaluate the association with rCT. Cox proportional hazards regression models were used to identify independent significantly influencing OS. ROC curve was used to determine the cutoff point of variables significantly predicting rCT and OS. The inFIGO risk score was calculated based on the FIGO score and variables with significant association; and was compared with the original FIGO score.

Results

A total of 160 GTN patients were included. There was a positive association between rCT, PNI (p <0.0001) and NLR (p <0.001). In multivariate analysis, only PNI had significant association (p= 0.001), with an optimal cutoff of 35.005 (sensitivity 66.3% and specificity 72.7%) and AUC=0.722. A significant association was found between higher PNI (HR 0.95-IC 0.91-0.99, p= 0.019) and OS. The optimal cutoff was 30.005 (sensitivity 57.7% and specificity 78.8%) and AUC=0.704. The inFIGO score was obtained by summing the logarithm of the FIGO HR plus the PNI HR, and was calculated for all patients. For rCT, the inFIGO score had higher sensitivity (71.6 vs. 61.5%), specificity (74.3 vs. 62.9%), and AUC (0.719 vs. 0.633) than the original FIGO score. For OS, the inFIGO score demonstrated higher sensitivity (96.6% vs. 72.4%) but lower specificity (45.0% vs. 61.8%) and AUC (0.691 vs. 0.710).

Conclusions

PNI impacts in rCT and OS. Patients with low PNI may require additional interventions to improve outcomes. The inFIGO score demonstrated improved sensitivity and specificity in predicting rCT compared to the original FIGO score. Further research is warranted to assess its applicability in clinical practice.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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