Which Symptoms Come First? Exploration of Temporal Relationships Between Cancer-Related Symptoms over an 18-Month Period
Bibliographic record
Abstract
BACKGROUND: Anxiety, depression, insomnia, fatigue, and pain are frequently reported by cancer patients. These symptoms are highly interrelated. However, few prospective studies have documented the sequence with which symptoms occur during cancer care. PURPOSE: This longitudinal study explored the temporal relationships between anxiety, depression, insomnia, fatigue, and pain over an 18-month period in a large population-based sample of nonmetastatic cancer patients (N = 828), using structural equation modeling. METHODS: The patients completed a battery of self-report scales at baseline and 2, 6, 10, 14, and 18 months later. RESULTS: The relationships between the same symptom at two consecutive assessments showed the highest coefficients (β = 0.29 to 0.78; all ps ≤ 0.05). Cross-loading parameters (β = 0.06 to 0.19; ps ≤ 0.05) revealed that fatigue frequently predicted subsequent depression, insomnia, and pain, whereas anxiety predicted insomnia. CONCLUSIONS: Fatigue and anxiety appear to constitute important risk factors of other cancer-related symptoms and should be managed appropriately early during the cancer care trajectory.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".