en
Scientific article
Open access
English

Enhancing precision: A predictive model for 177 Lu-DOTATATE treatment response in neuroendocrine tumors using quantitative 68 Ga-DOTATATE PET and clinicopathological biomarkers

Published inTheranostics, vol. 14, no. 9, p. 3708-3718
Publication date2024
Abstract

Purpose: This study aims to elucidate the role of quantitative SSTR-PET metrics and clinicopathological biomarkers in the progression-free survival (PFS) and overall survival (OS) of neuroendocrine tumors (NETs) treated with peptide receptor radionuclide therapy (PRRT).

Methods: A retrospective analysis including 91 NET patients (M47/F44; age 66 years, range 34-90 years) who completed four cycles of standard 177Lu-DOTATATE was conducted. SSTR-avid tumors were segmented from pretherapy SSTR-PET images using a semiautomatic workflow with the tumors labeled based on the anatomical regions. Multiple image-based features including total and organ-specific tumor volume and SSTR density along with clinicopathological biomarkers including Ki-67, chromogranin A (CgA) and alkaline phosphatase (ALP) were analyzed with respect to the PRRT response.

Results: The median OS was 39.4 months (95% CI: 33.1-NA months), while the median PFS was 23.9 months (95% CI: 19.3-32.4 months). Total SSTR-avid tumor volume (HR = 3.6; P = 0.07) and bone tumor volume (HR = 1.5; P = 0.003) were associated with shorter OS. Also, total tumor volume (HR = 4.3; P = 0.01), liver tumor volume (HR = 1.8; P = 0.05) and bone tumor volume (HR = 1.4; P = 0.01) were associated with shorter PFS. Furthermore, the presence of large lesion volume with low SSTR uptake was correlated with worse OS (HR = 1.4; P = 0.03) and PFS (HR = 1.5; P = 0.003). Among the biomarkers, elevated baseline CgA and ALP showed a negative association with both OS (CgA: HR = 4.9; P = 0.003, ALP: HR = 52.6; P = 0.004) and PFS (CgA: HR = 4.2; P = 0.002, ALP: HR = 9.4; P = 0.06). Similarly, number of prior systemic treatments was associated with shorter OS (HR = 1.4; P = 0.003) and PFS (HR = 1.2; P = 0.05). Additionally, tumors originating from the midgut primary site demonstrated longer PFS, compared to the pancreas (HR = 1.6; P = 0.16), and those categorized as unknown primary (HR = 3.0; P = 0.002).

Conclusion: Image-based features such as SSTR-avid tumor volume, bone tumor involvement, and the presence of large tumors with low SSTR expression demonstrated significant predictive value for PFS, suggesting potential clinical utility in NETs management. Moreover, elevated CgA and ALP, along with an increased number of prior systemic treatments, emerged as significant factors associated with worse PRRT outcomes.

eng
Keywords
  • SSTR-PET
  • Images-based features
  • NET
  • PRRT
  • Outcome prediction
Funding
Citation (ISO format)
AKHAVANALLAF, Azadeh et al. Enhancing precision: A predictive model for 177 Lu-DOTATATE treatment response in neuroendocrine tumors using quantitative 68 Ga-DOTATATE PET and clinicopathological biomarkers. In: Theranostics, 2024, vol. 14, n° 9, p. 3708–3718. doi: 10.7150/thno.98053
Main files (1)
Article (Published version)
Identifiers
ISSN of the journal1838-7640
17views
34downloads

Technical informations

Creation06/21/2024 8:52:34 PM
First validation06/24/2024 3:22:53 PM
Update time06/24/2024 3:22:53 PM
Status update06/24/2024 3:22:53 PM
Last indexation06/24/2024 3:23:14 PM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack