Radionuclide Theranostics in Neuroendocrine Neoplasms: An Update

Di Franco, Martina; Zanoni, Lucia; Fortunati, Emilia; Fanti, Stefano; Ambrosini, Valentina

doi:10.1007/s11912-024-01526-5

Cited by 3 publications

(1 citation statement)

References 111 publications

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“…For example, any information about somatostatin receptor analogs, PRRT, and targeted therapy, which are currently available therapies, is not recorded in the database. Thus, we cannot justify those factors during model development [55]. Other unavailable information includes patient performance, margin status, surgery indication, chemotherapy agent, radiotherapy detail, venous invasion, and volume of the healthcare organization.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Novel Machine Learning Model to Predict the Survival of Patients with Gastrointestinal Neuroendocrine Neoplasms

Liu,

Chen,

Dai

et al. 2024

Neuroendocrinology

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Introduction: Well-calibrated models for personalized prognostication of patients with gastrointestinal neuroendocrine neoplasms (GINENs) are limited. This study aimed to develop and validate a machine-learning model to predict the survival of patients with GINENs. Methods: oblique random survival forest (ORSF) model, Cox proportional hazard risk model, Cox model with least absolute shrinkage and selection operator penalization, CoxBoost, Survival Gradient Boosting Machine, Extreme Gradient Boosting survival regression, DeepHit, DeepSurv, DNNSurv, Logistic-Hazard model, and PC-Hazard model were compared. We further tuned hyperparameters and selected variables for the best-performing ORSF. Then, the final ORSF model was validated. Results: 43444 patients with GINENs were included. The median (interquartile range) survival time was 53 (19-102) months. The ORSF model performed best, in which age, histology, M stage, tumor size, primary tumor site, sex, tumor number, surgery, lymph nodes removed, N stage, race, and grade were ranked as important variables. However, chemotherapy and radiotherapy were not necessary for the ORSF model. The ORSF model had an overall C-index of 0.86 (95% confidence interval, 0.85-0.87). The area under the receiver operation curves at 1-, 3-, 5-, and 10-year were 0.91, 0.89, 0.87, and 0.80, respectively. The decision curve analysis showed superior clinical usefulness of the ORSF model than the American Joint Committee on Cancer Stage. A nomogram and an online tool were given. Conclusion: The machine-learning ORSF model could precisely predict the survival of patients with GINENs, with the ability to identify patients at high risk for death and probably guide clinical practice.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Novel Machine Learning Model to Predict the Survival of Patients with Gastrointestinal Neuroendocrine Neoplasms

Liu,

Chen,

Dai

et al. 2024

Neuroendocrinology

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First Successful In-Human Application of 225Ac-DOTA-LM3 Mono-PRRT for the Treatment of an Otherwise Therapy-Resistant Neuroendocrine Tumor (NET G3)

Speicher,

Burgard,

Bastian

et al. 2025

Clin Nucl Med

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We present a case of a 60-year-old woman diagnosed with metastasized small bowl NET G3 with high hepatic tumor burden and highly glucometabolic (FDG-avid) disease. In the postchemotherapy setting with progressive disease, the patient underwent PRRT with 177Lu-DOTA-octreotate and 225Ac-DOTA-octreotate initially resulting in stable disease. In a novel approach, 225Ac-DOTA-LM3 (somatostatin receptor antagonist) was administered, leading to a favorable treatment response in the 18F-FDG PET/CT scan. This interesting image illustrates the promising antitumor potential of alpha-sst2 antagonist PRRT with 225Ac-DOTA-LM3, and to the best of our knowledge, it is the first documented evidence of superiority over standard alpha-PRRT from intraindividual comparison.

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Challenges in developing response evaluation criteria for peptide receptor radionuclide therapy: A consensus report from the European Neuroendocrine Tumor Society Advisory Board Meeting 2022 and the ENETS Theranostics Task Force

Prasad,

Koumarianou,

Denecke

et al. 2024

J Neuroendocrinology

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Assessing the response to systemic therapy in neuroendocrine tumors (NET) is challenging since morphological imaging response is often delayed and not necessarily reflective of clinical benefit. Peptide receptor radionuclide therapy (PRRT) has a complex mechanism of action, further complicating response assessment. In response to these challenges, the European Neuroendocrine Tumor Society (ENETS) Theranostics Task Force conducted a statement‐based survey among experts to identify the current landscape and unmet needs in PRRT response assessment. The survey, presented at the 2022 ENETS Advisory Board (AB) meeting in Vienna, was completed by 70% of AB members, most of whom (81%) were from ENETS Centers of Excellence (CoE). It comprised a set of 13 questions with two substatements in three questions. Six (46%) of the statements achieved more than 75% agreement, while five (39%) additional statements reached over 60% consensus. Key points from the survey include: AB members agreed that lesions deemed equivocal on computed tomography (CT) or magnetic resonance imaging (MRI) should be characterized by somatostatin receptor (SST) positron emission tomography (PET)/CT before being designated as target lesions. It was agreed that interim response assessments should occur after the second or third PRRT cycle. Over half (54%) preferred using both conventional cross‐sectional imaging (CT and/or MRI) and hybrid imaging (SST PET/CT) for this purpose. Almost all AB members supported further response assessment 3 months after the final PRRT cycle. A majority (62%) preferred using a combination of conventional cross‐sectional imaging and SST PET/CT. For cases showing equivocal progression (ambiguous lesions or nontarget lesions) on CT and/or MRI, further confirmation using SST PET/CT was recommended. A significant majority (74%) preferred assessing pseudo‐progression and delayed response by combining SST PET with diagnostic CT and/ or MRI. Though just below the 75% consensus threshold, there was substantial agreement on selecting target lesions based on SST PET/CT uptake intensity and homogeneity. Sixty‐nine percent noted the importance of documenting and closely following heterogeneity in lesions in liver, lymph nodes, primary tumors, or other organs. As to the statement on parameters for new response criteria, AB members recommended exploring maximum standard unit value, tumor‐to‐background ratio, Hounsfield Unit (Choi Criteria), total tumor burden, and novel serum or molecular markers for future response evaluation criteria. Sixty‐five percent supported the use of a single SST PET/CT for response assessment of NET lesions treated with PRRT. These findings highlight the importance of integrating advanced imaging techniques and recognizing the need for more nuanced criteria in assessing the efficacy of PRRT in NET patients. This approach aims to enhance the accuracy of treatment monitoring and improve patient outcomes.

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Radionuclide Theranostics in Neuroendocrine Neoplasms: An Update

Cited by 3 publications

References 111 publications

Development and Validation of a Novel Machine Learning Model to Predict the Survival of Patients with Gastrointestinal Neuroendocrine Neoplasms

Development and Validation of a Novel Machine Learning Model to Predict the Survival of Patients with Gastrointestinal Neuroendocrine Neoplasms

First Successful In-Human Application of 225Ac-DOTA-LM3 Mono-PRRT for the Treatment of an Otherwise Therapy-Resistant Neuroendocrine Tumor (NET G3)

Challenges in developing response evaluation criteria for peptide receptor radionuclide therapy: A consensus report from the European Neuroendocrine Tumor Society Advisory Board Meeting 2022 and the ENETS Theranostics Task Force

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