Time to diagnosis and treatment in younger adults with colorectal cancer: A systematic review
Bibliographic record
Abstract
BACKGROUND: The incidence of colorectal cancer is rising in adults <50 years of age. As a primarily unscreened population, they may have clinically important delays to diagnosis and treatment. This study aimed to review the literature on delay intervals in patients <50 years with colorectal cancer (CRC), and explore associations between longer intervals and outcomes. METHODS: MEDLINE, Embase, and LILACS were searched until December 2, 2021. We included studies published after 1990 reporting any delay interval in adults <50 with CRC. Interval measures and associations with stage at presentation or survival were synthesized and described in a narrative fashion. Risk of bias was assessed using the Newcastle-Ottawa Scale, Institute of Health Economics Case Series Quality Appraisal Checklist, and the Aarhus Checklist for cancer delay studies. RESULTS: 55 studies representing 188,530 younger CRC patients were included. Most studies used primary data collection (64%), and 47% reported a single center. Sixteen unique intervals were measured. The most common interval was symptom onset to diagnosis (21 studies; N = 2,107). By sample size, diagnosis to treatment start was the most reported interval (12 studies; N = 170,463). Four studies examined symptoms onset to treatment start (total interval). The shortest was a mean of 99.5 days and the longest was a median of 217 days. There was substantial heterogeneity in the measurement of intervals, and quality of reporting. Higher-quality studies were more likely to use cancer registries, and be population-based. In four studies reporting the relationship between intervals and cancer stage or survival, there were no clear associations between longer intervals and adverse outcomes. DISCUSSION: Adults <50 with CRC may have intervals between symptom onset to treatment start greater than 6 months. Studies reporting intervals among younger patients are limited by inconsistent results and heterogeneous reporting. There is insufficient evidence to determine if longer intervals are associated with advanced stage or worse survival. OTHER: This study's protocol was registered with the Prospective Register of Systematic Reviews (PROSPERO; registration number CRD42020179707).
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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 | 0.006 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.007 | 0.009 |
| 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) | 0.003 | 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".