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Record W4393040844 · doi:10.3390/curroncol31030123

Paraneoplastic Syndromes in Neuroendocrine Prostate Cancer: A Systematic Review

2024· review· en· W4393040844 on OpenAlexvenueno aff
Mohammad Abufaraj, Raghad Ramadan, Amro Alkhatib

Bibliographic record

VenueCurrent Oncology · 2024
Typereview
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineProstate cancerCancerAndrogen deprivation therapyNeuroendocrine tumorsProstateHormone therapyInternal medicineOncologyPathologyDermatologyBreast cancer

Abstract

fetched live from OpenAlex

Neuroendocrine prostate cancer (NEPC) is a rare subtype of prostate cancer (PCa) that usually results in poor clinical outcomes and may be accompanied by paraneoplastic syndromes (PNS). NEPC is becoming more frequent. It can initially manifest as PNS, complicating diagnosis. Therefore, we reviewed the literature on the different PNS associated with NEPC. We systematically reviewed English-language articles from January 2017 to September 2023, identifying 17 studies meeting PRISMA guidelines for NEPC and associated PNS. A total of 17 articles were included in the review. Among these, Cushing's Syndrome (CS) due to ectopic Adrenocorticotropic hormone (ACTH) secretion was the most commonly reported PNS. Other PNS included syndrome of inappropriate Anti-Diuretic Hormone secretion (SIADH), Anti-Hu-mediated chronic intestinal pseudo-obstruction (CIPO), limbic encephalitis, Evans Syndrome, hypercalcemia, dermatomyositis, and polycythemia. Many patients had a history of prostate adenocarcinoma treated with androgen deprivation therapy (ADT) before neuroendocrine features developed. The mean age was 65.5 years, with a maximum survival of 9 months post-diagnosis. NEPC is becoming an increasingly more common subtype of PCa that can result in various PNS. This makes the diagnosis and treatment of NEPC challenging. Further research is crucial to understanding these syndromes and developing standardized, targeted treatments to improve patient survival.

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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.176
GPT teacher head0.502
Teacher spread0.325 · 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 designSystematic review
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
Published2024
Admission routes1
Has abstractyes

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