Agreement for depression diagnosis between DSM-IV-TR criteria, three validated scales, oncologist assessment, and psychiatric clinical interview in elderly patients with advanced ovarian cancer
Bibliographic record
Abstract
BACKGROUND: Depression, a major outcome in cancer patients, is often evaluated by physicians relying on their clinical impressions rather than patient self-report. Our aim was to assess agreement between patient self-reported depression, oncologist assessment (OA), and psychiatric clinical interview (PCI) in elderly patients with advanced ovarian cancer (AOC). METHODS: This analysis was a secondary endpoint of the Elderly Women AOC Trial 3 (EWOT3), designed to assess the impact of geriatric covariates, notably depression, on survival in patients older than 70 years of age. Depression was assessed using the Geriatric Depression Scale-30 (GDS), the Hospital Anxiety Depression Scale, the distress thermometer, the mood thermometer, and OA. The interview guide for PCI was constructed from three validated scales: the GDS, the Hamilton Depression Rating Scale, and the Montgomery Asberg Depression Rating Scale (MADRS). The Diagnostic and Statistical Manual of Mental Disorders, fourth edition, revised (DSM) criteria for depression were used as a gold standard. RESULTS: Out of 109 patients enrolled at 21 centers, 99 (91%) completed all the assessments. Patient characteristics were: mean age 78, performance status ≥2: 47 (47%). Thirty six patients (36%) were identified as depressed by the PCI versus 15 (15%) identified by DSM. We found moderate agreement for depression identification between DSM and GDS (κ=0.508) and PCI (κ=0.431) and high agreement with MADRS (κ=0.663). We found low or no agreement between DSM with the other assessment strategies, including OA (κ=-0.043). Identification according to OA (yes/no) resulted in a false-negative rate of 87%. As a screening tool, GDS had the best sensitivity and specificity (94% and 80%, respectively). CONCLUSION: The use of validated tools, such as GDS, and collaboration between psychologists and oncologists are warranted to better identify emotional disorders in elderly women with AOC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".