Effect of age on the effectiveness of the first-line standard of care treatment in patients with metastatic colorectal cancer: systematic review of observational studies
Bibliographic record
Abstract
PURPOSE: Most metastatic colorectal cancer (mCRC) patients are elderly. This systematic review identifies and describes observational studies evaluating the influence of age on first-line treatment effectiveness in real-world practice. METHODS: Medline and EMBASE were searched up to May 2016. The included studies were those that investigated first-line treatment of mCRC and reported age groups and overall survival (OS), progression-free survival (PFS) or overall response rate (ORR) were included. Studies published before 2008 were excluded. Study quality was assessed using the Newcastle-Ottawa Scale. Data were evaluated by age group (< 70 vs. ≥ 70 years; 65-75 vs. ≥ 75 years) and outcome. A pooled survival median was calculated for patients (cutoff = 70 years). RESULTS: In total, 11 articles with 11,063 patients were included. Four studies using a cutoff of 70 years of age reported OS and PFS, and two studies reported ORRs. In terms of OS, all studies showed a higher OS for those < 70 years of age than for those ≥ 70 years of age. PFS did not find differences by age. For ORRs, one study favoured the younger group, while the second study did not differ by age. Based on three studies, the pooled medians for < 70 years of age and ≥ 70 years of age were the same for PFS (10.2) and were 27.0 and 22.9 for OS, respectively. All included studies were of high or acceptable quality. CONCLUSIONS: The results suggest that age has no effect on PFS. For ORR, the results were inconsistent between studies. Younger patients in general had better OS, which might be partly explained by more aggressive treatment. This treatment seemed not to be guided by performance status or number of metastatic sites.
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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 | 0.014 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".