Abstract P3-13-03: A phase III, open-label, randomized study of eribulin versus capecitabine in patients (pts) with metastatic breast cancer (MBC): Effect of post-progression anti-cancer treatments (PPT) and metastatic progression events on overall survival
Bibliographic record
Abstract
Abstract Background A Phase III trial (Study 301; NCT00337103) in MBC comparing eribulin (E) with capecitabine (C) showed a trend for improved overall survival (OS) (hazard ratio [HR] 0.88; 95% CI 0.77, 1.00; P = 0.056) but not progression-free survival (PFS) (HR 1.08; 95% CI 0.93, 1.25; P = 0.30) with E. In order to investigate this apparent discordance, post-hoc analyses assessed the effect of PPT and events defining disease progression on OS. Methods Pts with locally advanced or MBC who had received an anthracycline and a taxane (≤2 prior chemotherapy regimens for advanced disease), were randomized to E (554) or C (548). Co-primary endpoints were OS and PFS. The impact of PPT on OS was assessed by analysis of exploratory PPT subgroups. Analyses of OS sensitivity censoring at time of PPT, and OS adjusted by PPT as a time-dependent covariate in a Cox regression model, were performed. The relationship between OS and progression events (appearance of a “new” lesion or metastasis [NM]; increase in size of pre-existing lesions [IPEL]; or other [death, clinical progression, or censored]) was investigated using Cox regression. Results PPT was received by 70% and 62% of E and C pts, respectively. For E pts, there were no significant OS differences by PPT (Table 1). Excluding 56 pts (22 E, 34 C) who received anti-HER2 therapy as PPT from the intent-to-treat OS analysis, OS was longer with E (HR 0.86; 95% CI 0.76, 0.99; nominal P = 0.03). OS sensitivity analysis censoring at time of PPT was consistent with the overall study results (HR 0.82; 95% CI 0.65, 1.03). Assessment of the overall effect of PPT, adjusting by PPT as a time-dependent covariate in a Cox regression model, showed that OS was longer with E (HR 0.85; 95% CI 0.75, 0.97; nominal P = 0.02). Progression due to NM or IPEL occurred in 271 and 147 of E pts, and 285 and 129 of C pts, respectively. Median OS was similar between arms in pts with IPEL and longer with E vs C in pts with NM (Table 2). Pts who progressed due to NM were at higher risk of death (HR 2.12; 95% CI 1.84, 2.43; nominal P<0.01). Conclusions Treatment with C or any other PPT after progression on E did not account for the trend in OS benefit with E observed in the primary analysis. Pts who progressed with NM had a worse prognosis than those with IPEL. The appearance of NM was highly correlated with OS, and the apparent discordance between PFS and OS seems to be related to these different progression events. Tab 1: OS by PPT after EPPTAll ptsC as 1stOther than C as 1stC at any timeOther than C at any timeNoneN554221169275115164Median OS, months (95% CI)15.9 (15.2, 17.6)18.3 (15.8, 20.9)19.9 (17.6, 24.0)19.6 (17.6, 21.5)18.0 (15.4, 22.7)7.4 (6.2, 9.1) Tab 2: OS by progression event Progression event NMIPELOther ECECECN271285147129136134Median OS, months (95% CI)15.5 (14.2, 17.5)12.9 (11.3, 14.5)17.4 (14.4, 19.7)17.4 (15.3, 20.9)16.7 (14.8, 24.2)15.5 (11.7, 18.3)HR (95% CI)0.81 (0.68, 0.97)1.13 (0.87, 1.46)0.78 (0.59, 1.03)Nominal P -value0.020.350.08Time to NM or death, months (95% CI)5.8 (5.2, 6.5)5.2 (4.3, 5.9)NANAHR (95% CI)0.90 (0.77, 1.05)NANANominal P-value0.17NANA Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P3-13-03.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".