Predictive impact of quality of life measurements in chemotherapy treated advanced pancreatic cancer patients at a single Canadian cancer institution.
Bibliographic record
Abstract
e21650 Background: Despite advancements in the treatment of advanced pancreatic cancer (APC), prognosis remains poor. With short survival despite aggressive chemotherapy regimens, maintaining quality of life (QOL) is paramount. Evidence suggests QOL may be a prognostic and predictive marker for clinical outcomes in poor prognosis cancers; we hypothesize this is the case in APC. Methods: Patients (pts) > 18 years of age with APC diagnosed between January 1, 2005 and December 31, 2010 and treated at a single Canadian institution were identified using the provincial cancer registry. QOL was assessed using a composite endpoint of clinical benefit, defined as an improvement in patient-reported pain, opioid consumption, ECOG performance status and/or weight. Best radiologic response, progression free survival (PFS) and overall survival (OS) were recorded. Results: Of 387 pts identified by the provincial cancer registry, 103 were seen in consultation and received chemotherapy. Median age was 64 (range 38-84); 58% were male and 66% had metastatic disease. At baseline, the majority of pts reported pain (80%), opioid use (61%) or weight loss (71%). Thirty five (34%) pts experienced a clinical benefit with chemotherapy, but only 6 (17%) of these pts had a radiologic response. The median PFS and OS were improved in pts who experienced a clinical benefit (6.6 months versus 4.6 months, p= 0.03 and 11.7 months versus 6.1 months, p< 0.0001, respectively). Conclusions: In pts with APC treated with chemotherapy, improvement in QOL as indexed by clinical benefit from chemotherapy, predicted for improved PFS and OS. However, it did not appear to be associated with radiologic response to chemotherapy. As such, we have undertaken a prospective study, using validated QOL assessment tools, to further investigate the prognostic and predictive significance of baseline and subsequent QOL scores in patients with APC receiving palliative chemotherapy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".