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Record W3003230805 · doi:10.2967/jnumed.119.237990

Efficacy of Peptide Receptor Radionuclide Therapy for Esthesioneuroblastoma

2020· article· en· W3003230805 on OpenAlexaff
Olfat Kamel Hasan, Aravind S. Ravi Kumar, Grace Kong, Kira Oleinikov, Simona Ben‐Haim, Simona Grozinsky‐Glasberg, Rodney J. Hicks

Bibliographic record

VenueJournal of Nuclear Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Surgical Oncology
Canadian institutionsMcMaster UniversityHamilton Health SciencesWestern University
Fundersnot available
KeywordsEsthesioneuroblastomaRadionuclide therapyMedicineInternal medicineOncologyProgression-free survivalPeptide receptorRadioimmunotherapyCohortNuclear medicineRadiation therapyOverall survivalReceptorImmunology

Abstract

fetched live from OpenAlex

Esthesioneuroblastoma is rare, with limited therapeutic options when unresectable or metastatic; however, expression of somatostatin receptors qualifies it for peptide receptor radionuclide therapy (PRRT). We report outcomes of PRRT in esthesioneuroblastoma from 2 referral centers. Methods: Using PRRT databases at 2 European Neuroendocrine Tumor Society Centers of Excellence, cases were sought between 2004 and 2018 of patients who had PRRT with recurrent or metastatic esthesioneuroblastoma deemed unsuitable for further conventional therapies. Evaluations of survival and of response using a composite reference standard were performed. Results: Of 7 patients, 4 had partial response, 2 had disease stabilization, and one had early progression. Possible side effects include worsening cerebrospinal fluid leaks. Median progression-free survival was 17 mo (range, 0-30 mo), and median overall survival was 32 mo (range, 4-53 mo). Conclusion: PRRT shows promising efficacy and moderate survival duration in unresectable locally advanced or metastatic esthesioneuroblastoma warranting larger cohort studies incorporating measures of quality of life.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.608
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.323
Teacher spread0.270 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations36
Published2020
Admission routes1
Has abstractyes

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