Daily symptom monitoring commonly leads to treatment modification in older adults receiving treatment for metastatic prostate cancer (mPC).
Bibliographic record
Abstract
82 Background: Treatment options for older adults with mPC expanded significantly in recent years but commonly include chemotherapy with Docetaxel (Chemo), androgen receptor-axis-targeted therapies (ARAT), and Radium-223 (Ra-223). Symptom burden associated with Chemo, ARAT, and Ra-223 is frequently observed and often leads to treatment modification, especially in older men. The objective of this study is to explore how often, and which moderate to severe symptoms during treatment for mPC and triggered follow-up, lead to treatment delay and/or dose reduction. Methods: Men aged 65+ with mPC starting standard dose (n=24) or reduced dose (n=1) Chemo, standard dose (n=41) or reduced dose (n=1) ARATs, or Ra223 (n=12) from two tertiary cancer centres in Toronto, Canada, were enrolled in a prospective cohort study. Participants self-reported symptoms daily using the Edmonton Symptom Assessment Scale (ESAS) for 3-4 weeks either through a web-based interface or phone calls. ESAS scores of >4 were followed by ‘triggered’ detailed questionnaires. The oncology care team was informed of reportable events based on scores of triggered questionnaires and patients were advised to call their care team. Clinical and treatment data were abstracted from electronic patient records and descriptive analysis was used. Results: 52/79 participants (66%) reported 345 moderate to severe symptoms that merited triggered questionnaires (table) with an adherence of 83%. Tiredness (n=74), appetite (n=49), insomnia (n=49), and pain (n=48) were the most frequently reported symptoms. 28 patients reported high scores on triggered questionnaires that led to informing the oncology care team and 79% of these patients were contacted by the care team, or an appointment with the Most Responsible Physician was scheduled. Moderate to severe symptom reporting resulted in treatment modification for 9 patients, Chemo (n=5), ARAT (n=3), and Ra-223 (n=1). Conclusions: Daily monitoring identified clinically relevant symptoms and actionable concerns. Informing care teams of reportable adverse events resulted in contacting patients and ultimately in treatment modification in a considerable number of patients. [Table: see text]
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".