Managing comorbidities in oncology: A multisite randomized controlled trial of continuing versus discontinuing statins in the setting of life-limiting illness.
Bibliographic record
Abstract
LBA9514 Background: For patients with life-threatening illness such as advanced cancer, optimal management of longstanding medications prescribed for comorbid illness is uncertain. Risks may outweigh benefits; e.g., benefits from HMG Co-A reductase inhibitors (“statins”) may take years to accrue and may not be relevant for a person with limited prognosis. Is it safe to discontinue statins for the patient with less than a year to live? Methods: This was a multicenter, unblinded pragmatic trial. At enrollment, participants were randomized (1:1) to discontinue or continue their statin medication. Eligible patients were adults with advanced life-limiting illness on a statin for ≥3 months for primary or secondary prevention, a life expectancy of greater than one month, and evidence of recent deterioration in performance status. Outcomes measured at baseline and at least monthly included survival, cardiovascular-related events, quality of life (QOL), symptoms, and polypharmacy. Rate of death within 60 days of randomization was the primary outcome. Results: 381 patients were enrolled (189 discontinue statins; 192 continue statins). Mean age was 74 years (SD 12); 22% were cognitively impaired; 49% had cancer as the primary diagnosis; and, 69% had used statins for >5 years. Rate of death within 60 days was not statistically different between groups (discontinue vs. continue, 23.8% vs. 20.3%, 90% CI -3.5% to 10.5%, p=0.36). The group discontinuing statins had longer median time-to-death (229 days [90% CI 186–332] vs. 190 days [90% CI 170-257]; p=0.60). Total QOL was significantly better among the group discontinuing statins (McGill QOL: 7.11 vs. 6.85, p=0.037) and there were fewer symptoms in this group (Edmonton Symptom Assessment Scale: 25.2 vs. 27.4, p=0.128). People in the discontinue statins group took significantly fewer medications (10.1 vs. 10.8, p = 0.034). Few participants in either group experienced cardiovascular events (13 vs. 11). Conclusions: In the setting of life-limiting illness such as advanced cancer, it is unlikely that harm will accrue when statins being used for primary or secondary prevention are discontinued; these patients may even benefit. Clinical trial information: NCT01415934.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".