Etiology of Delays in the Initiation of Adjuvant Chemotherapy and Their Impact on Outcomes for Stage II and III Rectal Cancer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: This study was designed to evaluate the role of access to care and postsurgical recovery on delays in adjuvant chemotherapy for rectal cancer. METHODS: Using data from the linked Surveillance, Epidemiology, and End Results-Medicare database, we analyzed patients with Stage II or III rectal cancer who received adjuvant chemotherapy after curative rectal cancer surgery between 1991 and 2002. Logistic and Cox regressions were performed to assess determinants of adjuvant chemotherapy delays and outcomes in two cohorts: patients with access to medical oncology care because of prior neoadjuvant chemotherapy (Group A) and patients without such access (Group B). Length of postoperative hospital stay served as the main proxy for postsurgical recovery. RESULTS: A total of 442 and 5,617 patients were included in Groups A and B, respectively. The median interval between surgery and adjuvant chemotherapy was 46 days in Group A and 42 days in Group B. Although 17 percent and 11 percent of patients in Groups A and B, respectively, waited three or more months for adjuvant chemotherapy, median overall survival was worse in this subset than in those who waited less than 3 months (54 vs. 76 months, P < 0.01). Postoperative hospital stay independently predicted for adjuvant chemotherapy delay in both groups. Disparities in delays were seen only in Group B, such that patients who were older or black had greater odds of an adjuvant chemotherapy delay (for both, P < 0.05). CONCLUSION: Advanced age and black race contribute to adjuvant chemotherapy delays and inferior outcomes, but postoperative recovery is the more important driver.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 it