Trans‐Oral Brush Biopsies and Quantitative PCR for EBV DNA Detection and Screening of Nasopharyngeal Carcinoma
Bibliographic record
Abstract
OBJECTIVES: To evaluate a newly developed noninvasive ambulatory, quantitative polymerase chain reaction (Q-PCR) Epstein-Barr virus (EBV) DNA detection and screening system (NP Screen™) for nasopharyngeal carcinoma (NPC). STUDY DESIGN: Correlation of the nasopharyngeal epithelial EBV-DNA levels and clinical findings by nasopharyngoscopy and final pathologic diagnosis of NPC with biopsy. SETTING: Multicenter ENT/Oncology clinics in Hong Kong (Radiation Oncology Clinic at the Queen Elizabeth Hospital and Radiation Oncology Clinic and Head and Neck Clinic, Queen Mary Hospital, University of Hong Kong) and in Toronto, Canada (the Otolaryngology-Head and Neck Clinic at the Rouge Valley Health System and 2 large ENT practices in Toronto). METHODS: A single-use trans-oral brush was used for rapid, nontraumatic nasopharyngeal (NP) epithelial cells DNA harvest in 600 Chinese patients, combined with a preservation and shipping kit for remote, real-time Q-PCR EBV DNA determinations. RESULTS: All 600 patients had NP brushings using NP Screen in an ambulatory environment, and no adverse events or complications were recorded. A final 578 patients were included with sufficient amount of DNA for completion of the Q-PCR assay. Of these 578 patients, 94 were confirmed positive for NPC histologically. The study yielded a sensitivity of 98.9%, specificity of 99.3%, positive predictive value (PPV) of 96.9%, and negative predictive value (NPP) of 99.7% for NP Screen in detecting NPC. Endoscopy had a sensitivity of 94%, specificity 97.1%, PPV 85%, and NPP 98.9%. CONCLUSIONS: The trans-oral brushing system fulfills the characteristics of a noninvasive, sensitive, specific detection method suitable for routine, large-scale ambulatory NPC risk assessment for high-risk NPC populations.
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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 | 0.000 | 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) | 0.001 | 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".