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Record W4411541911 · doi:10.1158/1078-0432.ccr-24-4354

Update on Tumor Surveillance for Children with Hereditary Pheochromocytoma/Paraganglioma Syndromes

2025· review· en· W4411541911 on OpenAlexaff
Surya P. Rednam, Junne Kamihara, Kerri Becktell, Garrett M. Brodeur, Lisa J. States, Stephan D. Voss, Anita Villani, Kristin Zelley, David Malkin, Yoshiko Nakano, Andréa S. Doria, Elysa Widjaja, Kristian W. Pajtler, Kami Wolfe Schneider, Maria Isabel Achatz, Lisa Diller, Bailey Gallinger, Chieko Tamura, Jonathan D. Wasserman

Bibliographic record

VenueClinical Cancer Research · 2025
Typereview
Languageen
FieldMedicine
TopicAdrenal and Paraganglionic Tumors
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersSt. Baldrick's Foundation
KeywordsPheochromocytomaParagangliomaMedicinePathologyPediatrics

Abstract

fetched live from OpenAlex

Hereditary pheochromocytoma/paraganglioma syndromes (HPPS) are a collection of conditions caused by variants in genes producing subunits of the succinate dehydrogenase (SDH) complex or related proteins. These conditions are characterized by substantial lifetime risks for developing pheochromocytomas, paragangliomas, and other tumors. Affected individuals who develop these tumors may experience severe, acute, and chronic problems. Indeed, aggressive, malignant, and/or disseminated tumors may result in death. Tumor surveillance enables early intervention, which, in turn, should lead to improved clinical outcomes. However, the desire for intensive surveillance strategies must be balanced against medical and psychosocial risks. In 2017, consensus HPPS surveillance recommendations addressing germline predisposition to SDHA-, SDHAF2-, SDHB-, SDHC-, SDHD-, MAX-, and TMEM127 (collectively, SDHx+)-related tumors were published after the inaugural American Association for Cancer Research Childhood Cancer Predisposition Workshop. Based on the limited available clinical data at that time, these recommendations advocated a uniform approach to tumor surveillance in HPPS. Since then, several other groups have proposed alternative consensus surveillance guidelines. Although these surveillance approaches share some common elements, including recommendations tailored to emerging differences in tumor phenotype based on underlying specific SDHx+ genes, these approaches also vary significantly among each other. As clinical data continue to accrue, it is critical that surveillance strategies continue to be refined to address emerging genotype-phenotype differences. In this review, we provide a brief up-to-date clinical overview of HPPS and describe recently proposed tumor surveillance regimens. We then detail our updated consensus pediatric-focused tumor surveillance recommendations from the 2023 American Association for Cancer Research Childhood Cancer Predisposition Workshop.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.831
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.229
GPT teacher head0.544
Teacher spread0.316 · 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
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

Citations4
Published2025
Admission routes1
Has abstractyes

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