Multiple Primary Tumours in Oral Cancer: Patient Characteristics and Survival Patterns.
Bibliographic record
Abstract
BACKGROUND: The development of multiple primary tumours (MPTs) is an important consequence of oral cancer and one of the leading causes of mortality among these patients. This study aimed to identify some of the risk factors for MPT development in oral cancer patients and to examine its impact on survival rates. METHODS: In this retrospective, population-based cohort study, we retrieved administrative data from the Alberta Cancer Registry database for 3549 patients diagnosed with primary oral cancer (POC) between 2005 and 2020. RESULTS: Among these patients, 513 developed MPTs for an overall incidence of 14.5%. The average time interval for development of the first MPT was 4.04 ± 3.67 years. The proportion of patients with any comorbid conditions was significantly higher in MPT patients compared with non-MPT patients. Advanced age, average income, comorbidities including chronic obstructive pulmonary disease, diabetes and cardiovascular disease, and increased time from diagnosis to treatment were found to be potential risk factors for MPT development. Analysis revealed a sharp decrease in survival rate of oral cancer patients after developing MPTs. Furthermore, age >45 years, body mass index <18.5, synchronous tumours, stage III and IV POC, >2 comorbid conditions and MPT developing in the digestive system were associated with poor disease-specific survival. CONCLUSION: The development of MPTs significantly affects the survival of oral cancer patients. Advanced age, comorbidities and delayed initiation of treatment were identified as key risk factors for MPTs. The poor survival outcomes, particularly in patients with synchronous tumours, advanced-stage primary cancers and specific comorbid conditions, highlight the need for early detection and proactive management strategies to mitigate these risks and improve long-term survival in this population.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".