PTSD in Patients Who Undergo Head and Neck Cancer Treatment: A Systematic Review
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Post-traumatic stress disorder (PTSD) can develop after exposure to real or perceived threats to life and is characterized by symptoms including intrusive thoughts, hyperarousal, and emotional numbness. While PTSD is well-studied in populations affected by disasters and combat, the impact of serious medical conditions like cancer and its treatments remain under-researched. Due to the aggressive nature of the disease, fear of recurrence, and disfiguring nature of treatments, patients with head and neck cancer (HNC) may experience a real or perceived risk of death. This systematic review synthesizes current knowledge on PTSD in patients with HNC. METHODS: A systematic review was conducted per PRISMA guidelines. Five databases (PubMed, EMBASE, SCOPUS, CINAHL, and COCHRANE) were searched for studies describing PTSD in patients with and survivors of HNC. Studies with PTSD diagnosis and/or symptom data specific to patients with HNC were included. RESULTS: Of 80 studies, 14 met the inclusion criteria. The most commonly used scale was the PTSD Checklist-Civilian Version. The prevalence of PTSD ranged from 8% to 41% across the studies. No significant differences were found with regards to PTSD prevalence by HNC tumor site, disease stage, or treatment modality. Two studies identified significant associations between PTSD after treatment and depression at the time of diagnosis. Patients with PTSD who received cognitive behavioral therapy showed improvement in their PTSD symptoms compared to those who did not. CONCLUSIONS: PTSD is common in individuals with HNC; however, the lack of a standardized approach to diagnosing PTSD in patients with and survivors of HNC creates challenges in identifying patients who may benefit from treatment. Given that HNC is the seventh most common cancer worldwide, with increasing incidence, there is a need to better understand the relationship between HNC and PTSD to allow for better PTSD screening, identification, and treatment to improve patients' health-related quality of life and provide optimal patient care.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".