Role of surveillance imaging and endoscopy in colorectal cancer follow-up: Quality over quantity?
Bibliographic record
Abstract
Colorectal cancer (CRC) is a prevalent disease and represents a major cause of morbidity and mortality in the developed world. Intensive post-treatment surveillance is routinely recommended by major expert groups for early stage (II and III) CRC survivors because previous meta-analyses showed a modest, but significant survival benefit. This practice has been recently challenged based on data emerging from several large phase III randomized trials that demonstrated a lack of survival benefit from intensive surveillance strategies. In addition, findings from cost-effectiveness analyses of such an approach are inconsistent. Data on real-world practice, specifically adherence to these follow-up guidelines, are also limited. The debate is especially controversial in resected stage IV patients where there are currently no clear guidelines for follow-up. In an era of personalized medicine, there may be a shift towards a more risk-adapted approach to better define the optimal follow-up strategy. In this article, we review the evidence and highlight the role of surveillance in CRC survivors.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".