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Record W4406844367 · doi:10.3390/ph18020165

Urinary Dopamine Levels Can Predict the Avidity of Post-Therapy [131I]MIBG Scintigraphy in Unresectable or Metastatic Pheochromocytomas and Paragangliomas: A Preliminary Clinical Study

2025· article· en· W4406844367 on OpenAlexaboutno aff
Junki Takenaka, Shirô Watanabe, Takashige Abe, Satoshi Takeuchi, Kenji Hirata, Rina Kimura, Hiroshi Ishii, N. Wakabayashi, Mungunkhuyag Majigsuren, Kohsuke Kudo

Bibliographic record

VenuePharmaceuticals · 2025
Typearticle
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsMedicineUnivariate analysisOdds ratioUrinary systemParagangliomaUrologyPheochromocytomaScintigraphyInternal medicineNeuroendocrine tumorsAvidityGastroenterologyRadiologyMultivariate analysis

Abstract

fetched live from OpenAlex

Background/Objectives: Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors that produce catecholamines. Unresectable or metastatic PPGLs are treated with [131I]metaiodobenzylguanidine (MIBG), but MIBG avidity is often heterogeneous. Identifying predictive factors for non-avid lesions on scintigraphy is clinically important. The primary objective of this study was to investigate the relationship between MIBG avidity and catecholamine secretion patterns in patients with unresectable or metastatic PPGLs. Methods: This retrospective study included 27 patients treated with [131I]MIBG for unresectable/metastatic PPGLs between 2001 and 2024. Patients received a single intravenous dose of [131I]MIBG (5.5–7.4 GBq), with post-therapy scintigraphy performed 3–7 days later. Non-avid lesions were assessed by imaging and confirmed using CT, MRI, and FDG-PET. Clinical factors, including age, sex, prior treatments, metastasis sites, and urine catecholamines, were evaluated using univariate logistic analysis. Predictive factors were assessed via receiver operating characteristic curves. Results: Non-avid lesions were found in nine patients (33.3%). These patients were younger (median age 38 vs. 62.5 years) and had higher urine dopamine levels (median 1510 vs. 779 μg/day) than those without non-avid lesions. Younger age (odds ratio: 0.892, p < 0.01) and higher urinary dopamine levels (odds ratio: 1.003, p < 0.01) were significantly associated with non-avid lesions. All patients > 45 years with urinary dopamine < 1190 μg/day had no non-avid lesions, whereas patients < 45 years with urinary dopamine > 1190 μg/day had non-avid lesions. Conclusions: Age and urinary dopamine levels may predict non-avid lesions in unresectable/metastatic PPGLs, aiding treatment decisions for [131I]MIBG therapy. This article is a revised and expanded version of a paper entitled “Urine dopamine level and age can predict non-avid lesion on scintigraphy after I-131 MIBG treatment for unresectable/metastatic PPGL”, which was presented at SNMMI 2024, Toronto, from 8 June to 11 June 2024.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.132
GPT teacher head0.450
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2025
Admission routes1
Has abstractyes

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