Longitudinal Study of Depressive Symptoms in Patients With Metastatic Gastrointestinal and Lung Cancer
Bibliographic record
Abstract
PURPOSE: Although early intervention is increasingly advocated to prevent and relieve distress in patients with metastatic cancer, the risk factors for such symptoms and their trajectory are not well established. We therefore conducted a longitudinal study to determine the course and predictors of depressive symptoms. PATIENTS AND METHODS: Patients (N = 365) with metastatic gastrointestinal or lung cancer completed measures of physical distress, self-esteem, attachment security, spiritual well-being, social support, hopelessness, and depression at baseline; physical distress, social support, hopelessness, and depression were subsequently assessed at 2-month intervals. RESULTS: Of the sample, 35% reported at least mild depressive symptoms, with 16% reporting moderate to severe depressive symptoms that persisted in at least one third of such individuals. Moderate to severe depressive symptoms were almost three times more common in the final 3 months of life than > or = 1 year before death. Predictors of depressive symptoms included younger age, antidepressant use at baseline, lower self-esteem and spiritual well-being, and greater attachment anxiety, hopelessness, physical burden of illness, and proximity to death. The combination of greater physical suffering and psychosocial vulnerability put individuals at greatest risk for depression. CONCLUSION: Depressive symptoms in advanced cancer patients are relatively common and may arise as a final common pathway of distress in response to psychosocial vulnerabilities, physical suffering, and proximity to death. These findings support the need for an integrated approach to address emotional and physical distress in this population and to determine whether early intervention may prevent depression at the end of life.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".