Eligibility of real-world patients with stage II/III colorectal cancer (CRC) in adjuvant chemotherapy (AC) trials.
Bibliographic record
Abstract
50 Background: The results of AC trials in stage II/III CRC are often generalized to real-world patients. However, clinical trials have stringent inclusion and exclusion criteria, which can potentially lead to poor generalizability of results and slow accrual. This study was conducted to determine the proportion of real-world patients with stage II/ III CRC who would be eligible for AC trials based on common eligibility criteria and to compare the outcomes in eligible and ineligible patients. Methods: We identified all patients diagnosed with stage II/III CRC in 2004-2015 from the Alberta Cancer Registry. Patients meeting any one of the following criteria were considered ineligible: age >75 years, anemia, comorbid conditions (heart disease, uncontrolled diabetes, kidney disease, liver disease) and history of a prior malignancy or immunosuppression. Logistic regression was used to describe the likelihood of receiving AC and Cox regression models were constructed to determine overall survival (OS). Results: A total of 7841 patients with stage II/III CRC were identified, of whom 52% were men and median age at diagnosis was 71 years (IQR: 61-79 years). Approximately 59% patients were deemed trial-ineligible and the most common reasons for ineligibility were advanced age (36%), renal dysfunction (27%), and cardiac disease (17%), respectively. In the real-world, 54% of eligible patients received AC as compared to 23% of ineligible patients [odds ratio 3.89, 95% confidence interval (CI) 3.53-4.28, P< 0.0001]. The 5-year OS of trial-ineligible patients who received AC was significantly better than those treated with surgery alone (table). Conclusions: Majority of real-world patients with stage II/ III CRC are unable to participate in AC trials due to strict exclusion criteria, but a fair proportion of these patients still derive some benefit from AC. The eligibility criteria of AC trials in CRC should be broadened to be more representative of real-world patients. [Table: see text]
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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 | 0.039 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".