A257 PANCREATIC CANCER TREATMENT AND END OF LIFE OUTCOMES: A POPULATION BASED COHORT STUDY
Bibliographic record
Abstract
Abstract Background Patients with pancreatic cancer face challenging decisions regarding treatment choices following their diagnosis and often lack data on end-of-life (EOL) outcomes. Without the available information, older patients may be undertreated, dying earlier than they would have with treatment, while others may be overtreated and exposed to aggressive measures with harmful side effects. Aims To describe survival and EOL outcomes among pancreatic cancer patients based on index cancer treatment, disease stage, and patient characteristics. Methods We conducted a population based cohort study in Ontario, Canada of patients who died from April 2010 to December 2017 and were diagnosed with pancreatic cancer prior to death. We used administrative databases to collect data on demographics, baseline health status, treatments, and outcomes. The primary exposure was index cancer treatment (no treatment, radiation, chemotherapy alone, surgery alone, and surgery with chemotherapy). The primary outcomes were mortality, health care encounters per 30 days in the last six months of life, and palliative care visits per 30 days within the last six months of life. Secondary outcomes were location of death (institution vs. community), hospitalization within the last 30 days of life, and receipt of chemotherapy within the last 30 days of life. We estimated the association between the exposure and outcomes using multivariable models, adjusting for demographics, comorbidities, and cancer stage. Hazard ratios, adjusted mean differences, and odds ratios were reported with 95% confidence intervals. Results Our cohort included 9950 adults with a median age at diagnosis of 78. 56% received no index treatment, 5% underwent radiation, 27% underwent chemotherapy alone, 7% underwent surgery alone, and 6% underwent surgery and chemotherapy. In the multivariable regression (Table and Figure), radiation, chemotherapy alone, surgery alone, and surgery with chemotherapy were all associated with decreased mortality and fewer healthcare encounters. All groups except radiation were associated with fewer palliative care visits. All treatment groups were associated with lower odds of institutional death and hospitalization within the last 30 days of life, and higher odds of chemotherapy within the last 30 days of life. Conclusions Our data, the first to provide EOL outcome estimates based on index cancer treatment, can help patients make initial treatment decisions after a diagnosis of pancreatic cancer. Multivariable regression analyses predicting primary and secondary outcomes Association between index cancer treatment and primary outcomes. Funding Agencies CIHR
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".