Patient Reported Pain Burden after Diagnosis of Gastrointestinal Cancer: Identifying Factors Associated with Symptom Screening and Moderate-to-Severe Pain Outcomes
Bibliographic record
Abstract
Gastrointestinal (GI) cancers impose a significant burden on patients. Pain, as one of the most common and distressing symptoms, remains inadequately managed despite advances in cancer care. Patient reported outcome measures have emerged as powerful tools in eliciting patient’s experiences and managing symptom burden. A retrospective analysis of patients diagnosed with GI cancers between 2011-2019 and registered at an Ontario Regional Cancer Center was conducted to 1) identify factors associated with receiving symptom screening at diagnosis (T0) and in follow-up (T1) and 2) examine factors associated with reporting moderate-to-severe pain in follow up. Among 84,867 patients, only 8.6% received symptom screening at both diagnosis and follow-up and baseline pain scores at diagnosis was the most significant factor associated with the odds of experiencing moderate-to-severe pain in follow-up. This thesis identifies key areas for improvement in current symptom screening practices, while advocating for the importance of timely assessment and proactive symptom management.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".