A systematic review of treatment guidelines for metastatic colorectal cancer
Bibliographic record
Abstract
AIM: A systematic review of treatment guidelines for metastatic colorectal cancer (mCRC) was performed to assess recommendations for monoclonal antibody therapy in these guidelines. METHOD: Relevant papers were identified through electronic searches of MEDLINE, MEDLINE In Process, EMBASE and the Cochrane Library; through manual searches of reference lists; and by searching the Internet. RESULTS: A total of 57 relevant guidelines were identified, 32 through electronic database searches and 25 through the website searches. The majority of guidelines were published between 2004 and 2010. The country publishing the most guidelines was the USA (12), followed by the UK (10), Canada (eight), France (eight), Germany (three), Australia (two), Spain (two) and Italy (one). In addition, eight European and three international guidelines were identified. As monoclonal antibody therapy for mCRC was not introduced until 2004, no firm recommendations for monoclonal antibody therapy were made in guidelines published between 2004 and 2006. Recommendations for monoclonal antibody therapy first appeared in 2007 and evolved as more data became available. The most recent international, European and US guidelines recommend combination chemotherapy with the addition of a monoclonal antibody for the first-line treatment of mCRC. Second-line treatment depends on the first-line regimen used. For chemoresistant mCRC, cetuximab or panitumumab are recommended as monotherapy in patients with wild-type KRAS tumours. CONCLUSION: The study indicates that recent treatment guidelines have recognized the role of monoclonal antibodies in the management of mCRC, and that treatment guidelines should be updated in a timely manner to reflect the most recently available data.
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 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 | 0.021 | 0.108 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".