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Record W4388845145 · doi:10.1007/s12325-023-02714-8

Optimising Radioligand Therapy for Patients with Gastro-Entero-Pancreatic Neuroendocrine Tumours: Expert Opinion from an Italian Multidisciplinary Group

2023· review· en· W4388845145 on OpenAlexaff
Nicola Fazio, Massimo Falconi, Emanuela Foglia, Mirco Bartolomei, Alfredo Berruti, Mirko D’Onofrio, Diego Ferone, Alessandro Giordano, Franco Grimaldi, Massimo Milione, Francesco Panzuto, Monica Santimaria, Orazio Schillaci, Ettore Seregni, M. Stasi, Marco Volante, Secondo Lastoria

Bibliographic record

VenueAdvances in Therapy · 2023
Typereview
Languageen
FieldMedicine
TopicNeuroendocrine Tumor Research Advances
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineNeuroendocrine tumorsReimbursementPsychosocialMultidisciplinary approachProtocol (science)Intensive care medicineInternal medicineHealth careAlternative medicinePathology

Abstract

fetched live from OpenAlex

Lu) oxodotreotide is an approved therapy in combination with somatostatin analogues (SSAs) for patients with advanced, well-differentiated G1-G2, gastro-entero-pancreatic neuroendocrine tumours (GEP-NETs) that progress on SSAs. We conducted a series of round table meetings throughout Italy to identify issues related to RLT delivery to patients with GEP-NETs. Four key issues were identified: (1) the proper definition of tumour progression prior to RLT initiation; (2) the impact of RLT in patients with bone metastases and/or high hepatic tumour burden; (3) the optimal follow-up protocol after RLT; and (4) organisational issues related to RLT use and managerial implications. This article reviews the literature relating to the aforementioned issues and makes recommendations based on available evidence and Italian NET experts' opinions. In particular, the group recommends the development of a diagnostic-therapeutic care pathway (DTCP) for patients undergoing RLT which provides systematic guidance but can still be individualised for each patient's clinical and psychosocial needs. A DTCP may clarify the diagnostic, therapeutic and post-treatment monitoring process, and improve communication and the coordination of care between hub and spoke centres. The DTCP may also contribute to changes in the care process related to the 2013/59/EURATOM Directive and to the definition of costs when planning for future or updated reimbursement of RLT in Italy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.414
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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