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Record W2804787305 · doi:10.1159/000489408

Clinical Stage IIA-IIC Seminoma: Radiation Therapy versus Systemic Chemotherapy versus Retroperitoneal Lymph Node Dissection

2018· review· en· W2804787305 on OpenAlexaff
Gunhild von Amsberg, Robert J. Hamilton, Alexandros Papachristofilou

Bibliographic record

VenueOncology Research and Treatment · 2018
Typereview
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineSeminomaLymph nodeRadiation therapyChemotherapyStage (stratigraphy)LymphEtoposideRetroperitoneal lymph node dissectionBleomycinDissection (medical)LymphadenectomyRadiologySurgeryUrologyInternal medicineTesticular cancerPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical stage II (CSII) seminoma is defined by the presence of pure seminoma accompanied by retroperitoneal lymph node metastases. In patients with bulky disease (lymph nodes > 5 cm in diameter), platinum-based chemotherapy is the widely accepted standard of care. However, the optimal choice of treatment for CSIIA and IIB is more controversial. METHODS: We performed a PubMed search using the key words stage II seminoma, BEP (cisplatin, etoposide, and bleomycin), hockey-stick radiotherapy, dog-leg radiotherapy and retroperitoneal lymph node dissection. Most relevant publications were summarized for this review. RESULTS: To date, no randomized trials have prospectively compared radiotherapy (RT), chemotherapy (CT) and retroperitoneal lymph node dissection (RLND) for CSII seminoma. Because of the predominantly retrospective analyses and only few prospective trials data interpretation is complex. In CSIIA with lymph nodes of < 2 cm, RT and CT seem to be equally effective, while in CSIIB, a decreased number of relapses were observed in CT-treated patients. In addition, RT seems to be associated with a higher incidence of long-term sequelae when compared with CT. CONCLUSION: Prospective clinical trials are needed to systematically compare the different treatment modalities. De-escalation of treatment intensity without loss of efficacy is required to improve long-term outcome for this young patient population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.277
GPT teacher head0.534
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations10
Published2018
Admission routes1
Has abstractyes

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