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Baseline lactate dehydrogenase (LDH) and overall survival (OS) in metastatic renal cell carcinoma (mRCC) patients (pts) treated with everolimus (EVE) versus sunitinib (SUN): Predictive biomarker analysis from the RECORD-3 trial.

2016· article· en· W2890030948 on OpenAlexaff
Martin H. Voss, David Chen, Mahtab Marker, Jennifer J. Knox, James J. Hsieh, Maurizio Voi, Robert J. Motzer

Bibliographic record

VenueJournal of Clinical Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineLactate dehydrogenaseSunitinibInternal medicineTemsirolimusRenal cell carcinomaEverolimusProgression-free survivalProportional hazards modelGastroenterologyHazard ratioUrologyOncologyDiscovery and development of mTOR inhibitorsOverall survivalPI3K/AKT/mTOR pathwayConfidence intervalApoptosis

Abstract

fetched live from OpenAlex

e16118 Background: Data from a randomized mRCC trial of temsirolimus vs interferon reported elevated baseline LDH to be a favorable predictive marker for OS with mTOR inhibitors (Armstrong, JCO 2012). As a product of anaerobic glycolysis, LDH was hypothesized to reflect mTOR activation in tumor cells. We explored this association in the RECORD-3 trial, which randomly assigned untreated pts to the mTOR inhibitor EVE vs the VEGFR TKI SUN without difference in OS (Knox, ASCO 2015). Methods: Pts were grouped by baseline LDH (low, ≤1×ULN; high, > 1×ULN). Treatment arms were stratified by MSKCC risk group. Cox proportional hazards and log-rank tests were used to test the association of LDH category with OS and progression-free survival (PFS). Correlation between LDH category and genomically defined subgroups (somatic mutations in BAP1 or PBRM1, both commonly altered in RCC with reported effects on OS for EVE-treated pts) was tested using Fisher exact test. Results: Among 468 randomly assigned pts, 13% were LDH high and 87% LDH low, with a median of 0.73×ULN (range, 0.15-10.54×ULN). High baseline LDH adversely affected OS for pts receiving EVE (HR 2.96; P< .0001) but showed no association for those receiving SUN (HR 1.18; P= .09). When comparing outcomes with first-line EVE vs SUN, OS was shorter for EVE in LDH-high pts but was not different in LDH-low pts. Associations between LDH and PFS were seen for EVE (HR 2.3; P< .0001) but not for SUN (HR 1.04; P.33). No statistically significant association was seen between LDH category and mutation status of BAP1 (P= .54) or PBRM1 (P= .47). Conclusions: Elevated baseline LDH correlated adversely with PFS and OS for first-line EVE but not SUN. Notably, this predictive effect for EVE is opposite that previously reported in the randomized trial for the mTOR inhibitor temsirolimus vs interferon. Clinical trial information: NCT00903175.Comparison Within HR for OS 95% CI for HR Log-Rank P LDH high vs low EVE arm 2.96 1.83 4.77 < .0001 LDH high vs low SUN arm 1.18 0.71 1.95 .0932 EVE vs SUN LDH low 0.96 0.75 1.24 .4036 EVE vs SUN LDH high 2.42 1.32 4.43 .0024

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.109
GPT teacher head0.374
Teacher spread0.264 · 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 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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