Characteristics, Treatment and Outcomes of Stage I to III Colorectal Cancer in Patients Aged over 80 Years Old
Bibliographic record
Abstract
Background: Colorectal cancer primarily affects older adults and poses treatment challenges due to age-related comorbidities and frailty, which hinder surgical and chemotherapy options for many elderly patients. This study aims to analyze treatment and disease patterns in elderly colorectal cancer patients, aged over 80 years old, to inform personalized therapies that accommodate their unique clinical needs and improve their outcomes. Patients and Methods: The medical records of all patients aged 80 years old and above, and those aged 65 to 75 years old, who were diagnosed with colorectal cancer at a cancer center in Canada over a seven year period, were retrospectively reviewed. Results: No significant differences in the initial presentation, location, grade or stage at colorectal cancer diagnosis were observed between age groups. Patients aged 80 years old and above were less likely to receive neoadjuvant and adjuvant chemotherapy treatments for stage II disease (19.2% versus. 58.6%, p = 0.002; 7.9% versus. 40.0%, p = 0.002). There were also differences in the intensity of chemotherapy received and the frequency of dose reductions (76.0% vs. 10.0%, p = 0.0001), neoadjuvant and adjuvant radiation therapy (34.6% vs. 65.5%, p = 0.02) and surgical management (83.7% vs. 95.3%, p = 0.006). Despite these differences in treatments, recurrence rates were not statistically significant between the two groups. However, overall survival was reduced in the older age group. Conclusions: Treatment plans for patients aged 80 years old and above should be tailored to the patient’s colorectal cancer presentation, comorbidity status and life expectancy, weighing the impact of cancer treatments on the patient’s short- and long-term outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".