The Screening and COnsensus Based on Practices and Evidence (SCOPE) Program–Results of a Survey on Daily Practice Patterns for Patients with mCRC
Bibliographic record
Abstract
The SCOPE project aimed to better understand practice patterns, identify drivers for treatment goals, and determine third- and fourth-line treatment choices for patients with metastatic colorectal cancer (mCRC). The survey was developed by an expert panel of gastrointestinal oncologists. Questions concerned general practice patterns, and treatment decisions for three hypothetical patient case scenarios. Participants had to routinely manage patients with mCRC. We present results from 629 participants who provided input on patient treatment scenarios (data cutoff: 17/01/2020). Prolonging overall survival (OS; 51%) was the main aim in first line. In third line, quality of life (QOL) was the primary goal (34%). Forty-three percent also cited efficacy-focused goals; 18% and 13% noted prolonging OS and improving progression-free survival as main aims, respectively. For fit and active patients, 89% of respondents considered trifluridine-tipiracil an appropriate third-line treatment; regorafenib (31%) or clinical trial enrollment (29%) were the fourth-line options. For patients with comorbidities and limited caregiver support, trifluridine-tipiracil was the preferred third-line treatment (70%). For KRAS-mutated patients with comorbidities and adverse events who received prior oxaliplatin, 90% considered oxaliplatin rechallenge an unsuitable third-line treatment, mainly due to the risk of cumulative toxicity (75%). In the third/fourth-line settings, trifluridine-tipiracil followed by regorafenib was the most common option (54%); 17% chose regorafenib followed by trifluridine-tipiracil. Efficacy coupled with QOL are important goals in third-line treatment. Daily practice patterns reflect the guideline recommendations in third- and fourth-line settings, with a trend toward using trifluridine-tipiracil versus regorafenib in KRAS-wildtype and KRAS-mutant tumors.
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 | 0.018 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".