A screening algorithm for early detection of major depressive disorder in head and neck cancer patients post‐treatment: Longitudinal study
Bibliographic record
Abstract
OBJECTIVE: The primary purpose of this study was to identify predictors of Major Depressive Disorder in head and neck cancer (HNC) patients in the immediate post-treatment period (ie, at 3 months post-diagnosis), with a focus on previously unexamined historical and contextual factors. METHODS: Prospective longitudinal study of 223 consecutive adults (72% participation) newly diagnosed with a first occurrence of primary HNC, including validated psychometric measures, Structured Clinical Interviews for DSM Disorders, and medical chart reviews. RESULTS: The 3-month period prevalence of Major Depressive Disorder was 20.4%; with point prevalences of 6.8% upon HNC diagnosis, 14.2% at 3 months, and 22.6% lifetime. Patients most susceptible to developing Major Depressive Disorder in the immediate post-treatment period: were diagnosed with advanced-stage cancer rather than early-stage cancer (O.R. = 4.94, P = 0.04), received surgery only (O.R. = 8.73, P = 0.04), presented a lifetime history of Anxiety Disorder on SCID-I (O.R. = 6.62; P = 0.01), and indicated higher pre-treatment levels of anxiety on the HADS (O.R. = 0.45, P = 0.05). CONCLUSIONS: Our results outline the predominant role of anxiety upon diagnosis as a precursor to post-treatment Major Depressive Disorder, suggesting the need for identification and prophylactic treatment of anxiety upon diagnosis in head and neck cancer patients. Further investigation into pathways by which pre-treatment anxiety predisposes to post-treatment Major Depressive Disorder in this population is warranted.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| 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 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".