Impact of surveillance among patients with resected pancreatic cancer following adjuvant chemotherapy.
Bibliographic record
Abstract
e16795 Background: Pancreatic adenocarcinoma carries a poor prognosis and high risk of recurrence even after surgery and adjuvant chemotherapy (AC). Guidelines recommend against routine surveillance imaging due to lack of evidence supporting a survival benefit. With current first-line chemotherapy options, it is unclear whether surveillance scans allow for early detection of asymptomatic disease and therefore an opportunity to offer fit patients chemotherapy. We describe the patterns of surveillance in patients followed at a Canadian provincial cancer agency and determine whether routine imaging after AC is associated with receipt of palliative chemotherapy (PC). Methods: A retrospective review was completed to identify patients treated at British Columbia (BC) Cancer centres between January 1, 2010 and December 31, 2016 who had undergone curative intent resection and received at least one cycle of AC. Baseline characteristics, number of scans done after completing AC to recurrence, and PC were collected. Logistic regression analysis was performed. Results: A total of 151 patients followed at BC Cancer were identified. Patients who recurred within 28 days after AC were excluded, leaving 142 patients, of which 115 patients had recurrence (81%). We defined 2 cohorts based on number of scans done between completion of AC and recurrence: those with 0-1 scans were “symptomatic” recurrences (22 patients, median age 68y, 64% female, and 91% node-positive) and those with > 1 scan were “surveillance” recurrences (93 patients, median age 64y, 43% female, and 81% node-positive). Patients who underwent surveillance scans were more likely to receive PC at time of recurrence, though statistical significance was not reached (OR 2.11, 95% CI 0.75-6.58, p = 0.17). Conclusions: Despite guidelines, the majority of patients treated in BC underwent surveillance imaging. Within the limits of our sample size, we demonstrated a trend towards increased likelihood of receiving PC in patients who receive surveillance scans following AC. With efficacious PC options available, studies to determine whether receipt of PC in asymptomatic recurrences detected on imaging translates into improved survival and/or quality of life are warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".