Cause of Death in Patients with Oropharyngeal Carcinoma by Human Papillomavirus Status: Comparative Data Analysis
Bibliographic record
Abstract
BACKGROUND: The incidence of oropharyngeal squamous cell carcinomas (OPSCC) has increased in recent decades, and human papillomavirus (HPV) infection is the main cause of OPSCC. The data regarding causes of death (CODs) are vitally important in informing follow-up strategies and revising treatment strategies to deal with any possible preventable treatment-related COD. However, limited studies have assessed the competing COD by HPV status in patients with OPSCC. OBJECTIVE: We aimed to analyze the distribution of the competing COD according to HPV status in OPSCC. METHODS: We retrospectively included stage I-IVB patients with OPSCC from the Surveillance, Epidemiology, and End Results database between 2010 and 2015. The association between HPV status and head and neck cancer-specific mortality (HNCSM), second primary cancer mortality (SPCM), and noncancer-caused mortality (NCCM) were analyzed. The chi-square test, Kaplan-Meier analysis, and Fine and Gray model were used for statistical analysis. RESULTS: We included 5852 patients in this study and 73.2% (n=4283) of them had HPV-related tumors. A total of 1537 (26.3%) patients died, including 789 (51.3%), 333 (21.7%), and 415 (27%) patients who died from head and neck cancer, second cancer, and noncancer causes, respectively. The 5-year HNCSM, SPCM, NCCM, and overall mortality were 14.7%, 6.5%, 7.7%, and 26.4%, respectively. Those with HPV-positive disease had a lower cumulative incidence of HNCSM (subdistribution hazard ratio [sHR] 0.362, 95% CI 0.315-0.417; P<.001), SPCM (sHR 0.400, 95% CI 0.321-0.496; P<.001), and NCCM (sHR 0.460, 95% CI 0.378-0.560; P<.001) than those with HPV-negative disease. The 5-year risk of HNCSM was 26.9% and 10.7% in those with HPV-negative and HPV-positive disease, respectively (P<.001). The 5-year risk of SPCM was 12.4% and 4.6% in those with HPV-negative and HPV-positive disease, respectively (P<.001). The 5-year risk of NCCM of death was 13.7% and 5.8% in those with HPV-negative and HPV-positive disease, respectively (P<.001). Using the Fine and Gray competing-risks model, our results show that those with HPV-negative tumors had a significantly higher risk of HNCSM (P<.001), SPCM (P<.001), and NCCM (P<.001) than those with HPV-negative tumors. CONCLUSIONS: HPV-positive OPSCC has a lower NCSM, SPCM, and NCCM as compared to those with HPV-negative OPSCC. HPV positivity is a favorable prognostic factor in the context of overcoming cancer as well as in terms of reducing the risk of other CODs in OPSCC. Our finding supports the need to tailor patient follow-up based on the HPV status of patients with OPSCC.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".