Palliative chemotherapy in advanced colorectal cancer patients age 80 or older.
Bibliographic record
Abstract
e14598 Background: Colorectal cancer (CRC) is the second most common cancer worldwide, with a median age at diagnosis of 71 years. While there has been significant progress in chemotherapy (CT) options for metastatic CRC (mCRC) patients (pts) over the past decade, there is very little data on outcomes or toxicity from CT in mCRC pts aged ≥80 years. We investigated palliative CT in the 80+ mCRC population, hypothesizing that high rates of hospitalization and toxicity may be observed. Methods: With ethics approval, a retrospective chart review was conducted of pts ≥80 years with mCRC who initiated a CT course between June 2005 and November 2009 at our institution. Baseline data on pt demographics were collected, in addition to CT data. The endpoints included: rates of hospitalization, CT discontinuation due to toxicity, and overall survival (OS). Results: CT was initiated on 88 occasions during the study period. The median age was 83 (range 80-92) and 52% of pts were male. Where data were available, 60% of pts had a good performance status (PS) of ECOG 0-1, 20% PS 2 and 9% PS 3 (10% unknown). 63 pts (72%) lived with family and 23% lived alone. 76% had a Charlson Comorbidity Index (CCI) ≥7 and 31% were taking ≥6 baseline prescription medications. At baseline, 33% of pts were anemic (Hgb <100), 36% had leukocytosis (WBC>11) and 48% had renal impairment (eGFR <60). Palliation was the intent for 95% of cases and 47 pts (53%) were receiving first line CT. The initial CT dose was adjusted from standard of care in 67% of cases. The most common CT was capecitabine monotherapy (45%). In total 19 pts (22%) were hospitalized during or within 30 days of CT; 26 pts (30%) discontinued CT due to toxicity, and 48 pts (55%) required at least 1 dose reduction, delay or omission. The median OS was 14.6 months (95% CI 11.7-18.6). No baseline factors (age, sex, PS, CCI, line of CT, baseline dose adjustment, baseline blood work) were associated with hospitalization, CT discontinuation due to toxicity, or OS. Conclusions: Palliative CT for mCRC in the ≥80 population is feasible, but most pts will require dose adjustments, and a significant minority will be hospitalized or stop CT due to toxicity. Prospective research incorporating geriatric assessment tools is required.
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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 | 0.000 | 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) | 0.004 | 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".