Socioeconomic Status, Length of Stay, and Postoperative Complications in Oral Cavity Squamous Cell Carcinoma
Bibliographic record
Abstract
Background: Despite universal healthcare in Canada, low socioeconomic status (SES) has been associated with worse survival in oral cavity squamous cell carcinoma (OCSCC) patients. However, the relationship between SES and outcomes during the acute postoperative period is poorly defined. Hamilton, Ontario, presents a unique population with widely varying SES within the same geography. The objective of this study was to examine the relationship between SES, length of hospital stay (LOHS), and postoperative complications in OCSCC. Methods: Newly diagnosed OCSCC patients receiving primary surgical treatment from 2010 to 2014 were identified within a prospectively collected database. Inclusion criteria included age >18 years old, pathological diagnosis of oral cavity cancer, and primary surgical treatment with curative intent. Patients were excluded if they were undergoing palliative treatment or had previous head and neck surgery/radiotherapy. Postal codes were used to identify neighborhood-level socioeconomic variables via 2011 Canada Census data. Income quartiles were defined from groups of neighboring municipalities based on Canada Census definitions. Demographic, social, pathological, staging, and treatment data were collected through chart review. Results: One hundred and seventy-four patients were included in the final analysis. OCSCC patients with lower SES were more likely to be younger ( P = .041), male ( P = .040), have significant tobacco and alcohol use ( P = .001), higher Charlson Comorbidity Index (CCI; P = .014), lower levels of education ( P = .001), and have lower employment levels ( P = .001). Lower SES patients had higher clinical tumor ( P = .006) and clinical nodal ( P = .004) staging and were more likely to receive adjuvant therapy ( P = .001) and G-tubes ( P = .001). Multivariable regression analysis showed that low SES was a statistically significant predictor of postoperative complications [β 2.50 (95% confidence interval (CI) 0.200, 3.17); P = .014] and LOHS [β 2.03 (95% CI 1.06, 2.99); P = .0001]. Tobacco and alcohol use, clinical tumor, and nodal stage, CCI, and planned adjuvant therapy were also statistically significant predictors of postoperative complications and LOHS ( P < .05). Conclusion: Patients with lower SES have more advanced OCSCC disease with increased comorbidities that owes itself to more acute postoperative complications and LOHS within this study population. Patients with low SES should be identified as patients that require more support during their cancer treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".