Case Report: Prolonged remission of metastatic cisplatin-refractory nasopharyngeal carcinoma with Pembrolizumab
Bibliographic record
Abstract
Background: Epstein-Barr virus (EBV)-related nasopharyngeal cancer (NPC) is a common type of cancer in certain areas of the world such as southeast Asia, but is uncommon in Canada. There is currently no reliably effective standard treatment for incurable metastatic EBV-related NPC that progresses after first-line therapy with gemcitabine/cisplatin. Methods: With his consent, the health records of a patient with relapsed metastatic EBV-related NPC treated with pembrolizumab immunotherapy were retrospectively reviewed and reported. Case report: A male patient presented at age 15 with stage IVA EBV-related NPC. Despite response to initial chemoradiation and adjuvant chemotherapy, the patient experienced metastatic cancer relapse in lymph nodes and bone. There was initial response to gemcitabine/cisplatin chemotherapy, but the cancer progressed after 7 cycles. The patient was then switched to pembrolizumab and had a near complete clinical response after 14 cycles. Serum EBV titers have normalized and CT imaging shows only some healed bone metastasis. Retrospective assessment of tumor CPS PD-L1 was >20. Hypothyroidism developed, possibly due to radiation treatment, but otherwise he did not experience any other immune-mediated toxicities on or following treatment, which lasted in total 2 years with 41 cycles. To date, the patient has been observed off pembrolizumab for over one year and is highly functional without evidence of disease progression. Conclusion: This case illustrates the potential benefit of immunotherapy for improving survival and quality of life in selected patients with metastatic EBV-positive cisplatin-refractory NPC.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".