Association Between Disease-Free Survival and Overall Survival When Survival Is Prolonged After Recurrence in Patients Receiving Cytotoxic Adjuvant Therapy for Colon Cancer: Simulations Based on the 20,800 Patient ACCENT Data Set
Bibliographic record
Abstract
PURPOSE: We previously validated disease-free survival (DFS) as a surrogate for overall survival (OS) in fluorouracil-based adjuvant colon cancer clinical trials. New therapies have extended survival after recurrence from 1 to approximately 2 years. We examined the possible impact of this improvement on the DFS/OS association. METHODS: The Adjuvant Colon Cancer Endpoints (ACCENT) data set of 20,898 patients was analyzed. In an exploratory fashion, time from recurrence to death in patients experiencing recurrence was extended using several algorithms, and the association of DFS after 3 years of median follow-up and OS after varying lengths of follow-up (median of 5, 6, and 7 years) was assessed. RESULTS: Seven thousand four hundred two patients (35%) experienced recurrence. Median time from recurrence to death was 24 months in the hypothetical data sets. When times from recurrence to death were doubled, the association between treatment effects on DFS and 5-year OS was modest (R(2) = 0.51 for both 2- and 3-year DFS) but remained strong for DFS and 6-year OS (R(2) = 0.67 for both 2- and 3-year DFS) and 7-year OS (R(2) = 0.70 for both 2- and 3-year DFS). The reduced DFS/OS association with extended survival after recurrence was greater in stage II than stage III patients. Multiple simulations provided consistent findings. CONCLUSION: Extended survival after recurrence reduces the association between treatment effects on 3-year DFS and 5-year OS, particularly in stage II patients; longer follow-up strengthens the association. In modern adjuvant trials, 6 or 7 years may be required to demonstrate OS improvements, further supporting DFS as the preferred primary end point for future adjuvant colon cancer clinical trials.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".