Progression-free survival as a potential surrogate for overall survival in metastatic breast cancer
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Progression-free survival (PFS) and time to progression (TTP) are frequently used to establish the clinical efficacy of anti-cancer drugs. However, the surrogacy of PFS/TTP for overall survival (OS) remains a matter of uncertainty in metastatic breast cancer (mBC). This study assessed the relationship between PFS/TTP and OS in mBC using a trial-based approach. METHODS: WE CONDUCTED A SYSTEMATIC LITERATURE REVIEW ACCORDING TO THE PICO METHOD: 'Population' consisted of women with mBC; 'Interventions' and 'Comparators' were standard treatments for mBC or best supportive care; 'Outcomes' of interest were median PFS/TTP and OS. We first performed a correlation analysis between median PFS/TTP and OS, and then conducted subgroup analyses to explore possible reasons for heterogeneity. Then, we assessed the relationship between the treatment effect on PFS/TTP and OS. The treatment effect on PFS/TTP and OS was quantified by the absolute difference of median values. We also conducted linear regression analysis to predict the effects of a new anti-cancer drug on OS on the basis of its effects on PFS/TTP. RESULTS: A total of 5,041 studies were identified, and 144 fulfilled the eligibility criteria. There was a statistically significant relationship between median PFS/TTP and OS across included trials (r=0.428; P<0.01). Correlation coefficient for the treatment effect on PFS/TTP and OS was estimated at 0.427 (P<0.01). The obtained linear regression equation was ΔOS =-0.088 (95% confidence interval [CI] -1.347-1.172) + 1.753 (95% CI 1.307-2.198) × ΔPFS (R(2)=0.86). CONCLUSION: Results of this study indicate a significant association between PFS/TTP and OS in mBC, which may justify the use of PFS/TTP in the approval for commercialization and reimbursement of new anti-cancer drugs in this cancer setting.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it