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Record W4301035879

Progression-free survival/time to progression as a potential surrogate for overall survival in HR+, HER2– metastatic breast cancer

2018· article· en· W4301035879 on OpenAlexaboutno aff
Allie Forsythe, D Chandiwana, J Barth, M Thabane, J Baeck, G Tremblay

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsMetastatic breast cancerBreast cancerOncologyInternal medicineMedicineSurrogate endpointCancerProgression-free survivalCancer survivalOverall survival
DOInot available

Abstract

fetched live from OpenAlex

Anna Forsythe,1 David Chandiwana,2 Janina Barth,3 Marroon Thabane,4 Johan Baeck,2 Gabriel Tremblay1 1Purple Squirrel Economics, New York, NY, 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA; 3Novartis Pharma GmbH, Nuremberg, Germany; 4Novartis Pharmaceuticals Incorporated, Dorval, QC, Canada Background: Several recent randomized controlled trials (RCTs) in hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2–) metastatic breast cancer (MBC) have demonstrated significant improvements in progression-free survival (PFS); however, few have reported improvement in overall survival (OS). The surrogacy of PFS or time to progression (TTP) for OS has not been formally investigated in HR+, HER2– MBC.Methods: A systematic literature review of RCTs in HR+, HER2– MBC was conducted to identify studies that reported both median PFS/TTP and OS. The correlation between PFS/TTP and OS was evaluated using Pearson’s product–moment correlation and Spearman’s rank correlation. Subgroup analyses were performed to explore possible reasons for heterogeneity. Errors-in-variables weighted least squares regression (LSR) was used to model incremental OS months as a function of incremental PFS/TTP months. An exploratory analysis investigated the impact of three covariates (chemotherapy vs hormonal/targeted therapy, PFS vs TTP, and first-line therapy vs second-line therapy or greater) on OS prediction. The lower 95% prediction band was used to determine the minimum incremental PFS/TTP months required to predict OS benefit (surrogate threshold effect [STE]).Results: Forty studies were identified. There was a statistically significant correlation between median PFS/TTP and OS (Pearson =0.741, P=0.000; Spearman =0.650, P=0.000). These results proved consistent for chemotherapy and hormonal/targeted therapy. Univariate LSR analysis yielded an R2 of 0.354 with 1 incremental PFS/TTP month corresponding to 1.13 incremental OS months. Controlling the type of treatment (chemotherapy vs hormonal/targeted therapy), line of therapy (first vs subsequent), and progression measure (PFS vs TTP) led to an improved R2 of 0.569 with 1 PFS/TTP month corresponding to 0.78 OS months. The STE for OS benefit was 5–6 months of incremental PFS/TTP.Conclusion: We demonstrated a significant association between PFS/TTP and OS, which may justify the use of PFS/TTP as a surrogate for OS benefit in HR+, HER2– MBC. Keywords: breast cancer, overall survival, progression-free survival, time to progression, correlation analysis, surrogate endpoint

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.000

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 head0.138
GPT teacher head0.560
Teacher spread0.423 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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