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Stage I seminoma: What should a practicing uro‐oncologist do in 2009?

2009· review· en· W1572415194 on OpenAlexaff
Julia Skliarenko, Danny Vesprini, Padraig Warde

Bibliographic record

VenueInternational Journal of Urology · 2009
Typereview
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineSeminomaRadiation oncologistGynecologyInternal medicineMedical physicsRadiation therapyChemotherapy

Abstract

fetched live from OpenAlex

Testicular tumors are uncommon, but they continue to represent an important group of malignancies in young men. It is the most common solid malignancy in males between the ages of 20 and 35, and primary germ cell tumors are the most common histological type. In the United States in 2008, approximately 4800 cases of seminoma, approximately 4100 of which were stage I disease were projected after the completion of staging investigations. Remarkable progress has been made in the treatment of testicular seminoma over the past 25 years. Management options of stage I seminoma include radiotherapy, surveillance, or adjuvant chemotherapy. Standard management until recent years has been adjuvant retroperitoneal radiotherapy. Although providing excellent long term results, this approach has been associated with increased risk of gonadal toxicity, development of secondary malignancies and an increased risk of cardiovascular disease. The use of surveillance in management of patients with stage I seminoma is therefore becoming more frequent as it minimizes the burden of treatment and maintains the cure rate at virtually 100%. Adjuvant chemotherapy using Carboplatin has been investigated as an alternative management approach. However, the long term outcomes of patients managed with Carboplatin are not yet clear and this strategy should only be used in a study setting. It has been suggested that more patients with stage I seminoma will die of their treatment than of their cancer; therefore, the thrust of modern management should be to maintain 100% cure while minimizing the burden of treatment.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.090
GPT teacher head0.447
Teacher spread0.357 · 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 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

Citations7
Published2009
Admission routes1
Has abstractyes

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