Depression as a predictor of postoperative functional performance status (PFPS) and treatment adherence in head and neck cancer patients: A prospective study
Bibliographic record
Abstract
BACKGROUND: Head and neck cancer (HNC) is a debilitating disease due in part to its effects on function, including speech, swallowing, and cosmesis. Previous studies regarding depression in HNC have focused on demographic predictors, incidence, and quality of life studies. There is, however, a paucity of studies that objectively address depressive symptoms in HNC patients and the resultant effects on post-treatment functional performance status. The aim of this study was to assess the relationship between preoperative depressive symptoms (PDS) and postoperative functional performance status (PFPS), in addition to other predictors of rehabilitation and survival. METHODS: A prospective cohort study was undertaken at the University of Alberta, including all new adult HNC patients undergoing surgery as primary therapy for HNC from May 2013 to January 2014. Baseline depressive symptoms were measured on the Quick Inventory of Depressive Symptoms (QIDS) questionnaire 2 weeks preoperatively and PFPS was assessed 12 months postoperatively on the Functional Assessment of Cancer Therapy-Head & Neck (FACT-HN) scale. Secondary outcomes included completion of adjuvant therapy, narcotic dependence, return to detrimental habits, loss of follow-up, and length of hospital stay (LOHS). Differences between the Normal-Mild and Moderate-Severe QIDS groups were assessed using Mann-Whitney and Fischer Exact statistical analyses. RESULTS: Seventy-one patients were included in the study. Mild and Moderate-Severe PDS were 35.2 % and 18.3 %, respectively. Significantly lower FACT-HN scores were noted in the Moderate-Severe group at 12 months (p = 0.03). The risk ratio (RR) for FACT-HN score < 50 % at 12 months in the Moderate-Severe group was 5.66. In addition, significantly lower completion of adjuvant treatment (p = 0.03), significantly higher incidence of narcotic dependence (p = 0.004), and significantly higher LOHS (24 days vs. 18 days; p = 0.02) was observed in the Moderate-Severe group. There was no significant difference in loss of follow-up between the 2 groups (p = 0.64). CONCLUSIONS: The incidence and severity of PDS in HNC patients treated with surgery is high (53.5 %). Patients with Moderate-Severe PDS have significantly decreased PFPS, increased narcotic use, decreased completion of adjuvant therapy, and a longer LOHS. HNC patients should be monitored closely for depressive symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".