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Record W2063648710 · doi:10.1038/bjc.2012.367

Association between treatment effects on disease progression end points and overall survival in clinical studies of patients with metastatic renal cell carcinoma

2012· article· en· W2063648710 on OpenAlexaff
Thomas E. Delea, A. Khuu, Daniel YC Heng, T Haas, Denis Soulières

Bibliographic record

VenueBritish Journal of Cancer · 2012
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity of Calgary
FundersNovartis Pharmaceuticals Corporation
KeywordsRenal cell carcinomaHazard ratioMedicineInternal medicineConfidence intervalOncologyProgression-free survivalProportional hazards modelChemotherapy

Abstract

fetched live from OpenAlex

BACKGROUND: The relationship between progression-free survival and time to progression (PFS/TTP) and overall survival (OS) has been demonstrated in a variety of solid tumours but not in metastatic renal cell carcinoma (mRCC). METHODS: A systematic literature search was conducted to identify controlled trials of cytokine or targeted therapies for mRCC reporting information on treatment effects on PFS/TTP and OS for one or more comparison. The associations between treatment effects on PFS/TTP and OS were analysed using linear regression. RESULTS: Thirty-one studies representing 10943 patients, 75 treatment groups, and 41 comparisons were identified. The correlation coefficient between the negative log of the hazard ratio (HR) for PFS/TTP (-ln HR(PFS/TTP)) vs the negative log of the HR for OS (-ln HR(OS)) was 0.80 (P<0.0001). In linear regression, the coefficient on -ln HR(PFS/TTP) vs -ln HR(OS) was 0.64 (95% confidence interval (CI): 0.470.81; R(2)=0.63), suggesting each 10% relative risk reduction (RRR) for PFS/TTP was associated with a 6% RRR for OS. A 1-month gain in median PFS/TTP was associated with a 1.17-month gain in median OS (95% CI: 0.59,1.76; R(2)=0.28). CONCLUSION: In trials of treatments for mRCC, treatment effects on PFS/TTP are strongly associated with treatment effects on OS.

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)0.001
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 score0.062
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.036
GPT teacher head0.345
Teacher spread0.309 · 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

Citations37
Published2012
Admission routes1
Has abstractyes

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