Randomized controlled trials (RCTs) examining continuous (CS) versus intermittent strategies (IS) of delivering systemic treatment (Tx) for untreated metastatic colorectal cancer (mCRC): A meta-analysis from the Cancer Care Ontario program in evidence-based care.
Bibliographic record
Abstract
3534 Background: Given the varying impact on efficacy demonstrated in individual RCTs of CS vs IS of delivering systemic Tx for mCRC, a meta-analysis of the available RCTs was performed. Methods: RCTs that compared a CS versus IS of delivering systemic Tx were identified by a systematic search (MEDLINE, EMBASE and ASCO and ESMO proceedings) and review. The results of identified trials were clinically homogeneous (Table) so the data was pooled using Review Manager software (RevMan 5.2). Overall survival (OS) hazard ratios were extracted directly from the most recently reported trial results. A random effects model was used for all pooling. Results: 10 RCTs were identified (n= 4,296). After an induction period, the maintenance Tx patients received during the IS was: none (5 trials, n=2,562), fluoropyrimidine (F) (2 trials, n=759), biologic (B) (2 trials, n=852), F+B (1 trial, n=123). Results of the meta-analysis are summarized in the Table (HR>1 favors CS). Sensitivity analyses performed demonstrate results are robust independent of the induction or maintenance Tx used. QOL (data from 2 trials) was either the same in both arms (single Tx induction trial with no maintenance Tx, n=354) or improved in the IS arm (combination tx induction trial with no maintenance Tx, n=1,630). Conclusions: IS of delivering systemic Tx for mCRC do not result in a statistically significant reduction in OS compared to a CS of delivery whether or not maintenance therapy is included. QOL is the same or better with an IS. [Table: see text]
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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 | 0.035 | 0.068 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.044 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".