Validity of event-free survival as a surrogate endpoint in haematological malignancy: Review of the literature and health technology assessments
Bibliographic record
Abstract
OBJECTIVE: Event-free survival (EFS) is increasingly used as a primary endpoint in trials of haematological malignancies (HMs). A key consideration is whether EFS can reliably predict survival. METHODS: We conducted a review of the scientific literature and health technology assessments to evaluate evidence for EFS-OS surrogacy in HMs and acceptability of EFS by payers. RESULTS: Evidence of surrogacy varies by indication and line of therapy. In first-line AML, EFS is highly correlated with OS at the trial-level supporting its use as an early endpoint for traditional approval of treatments with curative intent. Surrogacy was also demonstrated in first-line DLBCL but remains unexplored in relapsed/refractory setting where post-transplant EFS24 was not prognostic of survival. In first-line FL, PTCL, T-LBL, and MCL, EFS24 is prognostic of survival but trial-level surrogacy has not yet been evaluated. CONCLUSION: Strong EFS-OS correlation required for surrogacy may only be achievable in HMs with treatments characterised by high rates of durable remissions. Nevertheless, EFS24 is associated with favourable outcomes and remains a clinically meaningful endpoint in HMs.
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 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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".