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Ability of C‐reactive protein to complement multiple prognostic classifiers in men with metastatic castration resistant prostate cancer receiving docetaxel‐based chemotherapy

2012· article· en· W1541532008 on OpenAlexaff
Gregory R. Pond, Andrew J. Armstrong, Brian Wood, Lance Leopold, Matthew D. Galsky, Guru Sonpavde

Bibliographic record

VenueBritish Journal of Urology · 2012
Typearticle
Languageen
FieldMedicine
TopicInflammatory Biomarkers in Disease Prognosis
Canadian institutionsMcMaster UniversityOntario Clinical Oncology Group
FundersSanofi
KeywordsDocetaxelProstate cancerMedicineOncologyChemotherapyInternal medicineComplement (music)CastrationCancerBiologyHormone

Abstract

fetched live from OpenAlex

UNLABELLED: What's known on the subject? and What does the study add? Serum C-reactive protein (C-reactive protein) is emerging as a potential novel prognostic factor in metastatic castration-resistant prostate cancer (mCRPC). In the present study, a prospective trial was investigated retrospectively and a significant prognostic impact for C-reactive protein that was independent of multiple published prognostic models was identified in men receiving docetaxel-based chemotherapy for mCRPC. Prospective validation is warranted. OBJECTIVE: • Given the recent emergence of C-reactive protein levels as a novel prognostic factor in men with metastatic castration-resistant prostate cancer (mCRPC), we sought to evaluate the independent prognostic ability of C-reactive protein in the context of published prognostic nomograms, risk grouping and disease state models in men receiving docetaxel-based chemotherapy for mCRPC. PATIENTS AND METHODS: • A large randomized phase II trial (CS-205) of mCRPC patients who received docetaxel-prednisone + AT-101 (Bcl-2 inhibitor) or docetaxel-prednisone + placebo was analyzed retrospectively (n= 220). • Overall survival (OS), progression-free survival (PFS) and measures of discriminatory ability were assessed in a hypothesis-generating analysis using Cox regression and concordance probabilities. • Patients from both treatment groups were combined for this analysis because no significant differences in outcomes were observed. • Because some factors used in nomograms were not collected or defined differently, risk was estimated based on slightly modified versions of nomograms. RESULTS: • C-reactive protein was independently prognostic for OS and PFS (P ≤ 0.002) after adjusting for all modeled risk estimates and classifiers. • C-reactive protein showed a concordance probability of 0.65 for both OS and PFS. • A 10-factor modified prognostic model based on the TAX327 trial had the greatest observed discrimination ability for OS and PFS (concordance probability = 0.623 and 0.603, respectively) among the modified nomograms or classifiers. • Adding the TAX327 model risk estimates to C-reactive protein did not substantially increase discrimination ability over C-reactive protein alone. CONCLUSIONS: • Current prognostic classifications provide modest discrimination of outcomes in mCRPC receiving docetaxel-based chemotherapy, highlighting the need for improved risk-based models. • Baseline C-reactive protein appears to be an useful, independent prognostic factor and prospective external validation is warranted.

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 score0.104
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.290
Teacher spread0.268 · 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

Citations36
Published2012
Admission routes1
Has abstractyes

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