Systemic therapy (ST) in cancer patients ≥ 80 years of age: A Manitoba population-based assessment
Bibliographic record
Abstract
6090 Background: Little is known about the cancer characteristics, treatment options and outcomes in the oldest subset of the elderly, those ≥ 80, who develop cancer. Methods: We employed a population-based, cross-sectional design utilizing the provincial cancer registry and administrative data augmented by clinic-specific retrospective chart review to study the demographics, treatment and outcomes of patients ≥ 80 diagnosed with cancer in the years 2002–2003 in Manitoba, Canada. We assessed treatment patterns for various subgroups (analyzed using chi-square and Fisher’s exact tests to determine association, as appropriate) and associated survival. Results: Our cohort included 2,194 patients. This represented 20.8% of all incident cases. The median age was 84 (range: 80–102), with a slight preponderance of females (53%). As expected, prostate, lung, and colorectal cancers were most common for males with breast, lung, and colorectal cancer being most common for females. Only 241 (10.9%) of the cohort were referred to the central cancer centre for consideration of ST which was less than the overall referral rate of 33%. Of those referred, 57% did not receive ST, 20% received palliative ST, and 23% received adjuvant/curative ST. The two year survival rates were statistically significant by treatment categories (not referred = 39%, referred but who did not receive ST = 39%, palliative ST = 27%, and adjuvant/curative ST = 76%,) (p<0.0001). The Charlson score for those patients referred who received ST was lower than those who did not receive ST (p<0.0001) Conclusions: Our data indicate that in patients ≥ 80 years of age with cancer, few are referred to the central cancer clinic for ST. Of those referred, patients who receive adjuvant/curative intent ST live longer then those not receiving ST. Lower Charlson scores (indicative of fewer comorbidities and better general health) were found more often in patients receiving ST. No significant financial relationships to disclose.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".