Depression and Survival in Patients With Head and Neck Cancer
Bibliographic record
Abstract
IMPORTANCE: The incidence of depression in patients with head and neck cancer (HNC) is estimated to be as high as 40%. Previous studies have demonstrated an effect of depression on rehabilitation and survival in the posttreatment period. OBJECTIVE: To systematically review the relationship between depression and survival in patients with HNC undergoing curative treatment. EVIDENCE REVIEW: A search of electronic databases as well as gray literature was undertaken from January 1, 1974, to August 20, 2014, including MEDLINE (via Ovid), EMBASE (via Ovid), CINAHL, EBSCO, PsycINFO (via Ovid), Elsevier Scopus, and Institute for Scientific Information Web of Science Core Collection, using controlled vocabulary and medical subject headings representing HNC, depression, and survival. Articles in these databases were reviewed for inclusion by 2 independent reviewers according to predetermined eligibility criteria and were adjudicated by a third reviewer. The articles were then quantitatively scored using the GRACE (Good Research for Comparative Effectiveness) tool, a validated instrument for assessing the quality of observational studies. Qualitative assessment of each article was then undertaken. FINDINGS: A total of 654 references were retrieved across all databases. A review of the abstracts and full texts identified 3 articles, each describing a distinct, single study, including a total of 431 patients, that were eligible for analysis. Scores for the articles as assessed with the GRACE tool ranged from 9 to 11. In each of the 3 studies used in the analysis, the comparison groups were depressed and nondepressed patients as established by a standardized psychiatric assessment tool. Two of the 3 studies demonstrated a statistically significant difference in survival for patients with HNC and depression; however, a sensitivity analysis was not possible due to the incompatible statistical analyses performed in each study. CONCLUSIONS AND RELEVANCE: An association between depression and survival in patients with HNC is apparent; however, the strength and etiology of this association is not yet clear. Further directed and multi-institutional study is required to investigate this association and determine appropriate screening and management strategies.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".