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Record W2094965147 · doi:10.1159/000292358

Patterns of Relapse after Chemotherapy in Patients with High-Risk Non-Seminomatous Germ Cell Tumor

2010· article· en· W2094965147 on OpenAlexaff
Karin Oechsle, Anja Lorch, Friedemann Honecker, Christian Kollmannsberger, Jörg T. Hartmann, I. Boehlke, Carsten Bokemeyer

Bibliographic record

VenueOncology · 2010
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsChemotherapyMedicineGerm cell tumorsOncologyInternal medicineTumor markerMetastasisTesticular Germ Cell TumorRadiologyCancerTesticular cancer

Abstract

fetched live from OpenAlex

OBJECTIVES: We investigated the pattern of relapse after chemotherapy in patients with high-risk germ cell tumor (GCT) to critically review common follow-up procedures including close monitoring of serum tumor markers and radiologic procedures. METHODS: 645 patients received first-line (434 patients) or salvage platinum-based (211 patients) high-dose chemotherapy in three multicenter trials. Retrospective analysis comprised 77 patients after first-line and 61 after salvage chemotherapy, who had achieved at least a partial remission but progressed afterwards. RESULTS: At relapse, 24% of the patients presented with an isolated elevation in serum tumor markers, 26% with pathologic radiologic confirmation with negative tumor markers, and 42% with elevated tumor markers and radiologically confirmed progression. Relapse was detected by clinical symptoms in 8%. 46% relapsed within 3 months and 97% within 2 years. Relapse pattern did not correlate with tumor marker status or metastasis location prior to chemotherapy, line of chemotherapy, response status after chemotherapy or time point of relapse. CONCLUSION: In high-risk GCT patients, relapse after chemotherapy is detected either by tumor marker elevation alone, radiologic imaging alone or both, in one third each. Close monitoring including serum tumor markers, radiologic imaging and clinical examination appears warranted within the first 2 years.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.002
GPT teacher head0.219
Teacher spread0.217 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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