Durvalumab for Extensive-Stage of Small-Cell Lung Cancer With Lambert-Eaton Myasthenic Syndrome
Bibliographic record
Abstract
Durvalumab is an immune checkpoint inhibitor (ICI) of anti-programmed cell death protein 1 ligand antibody. ICI-combined chemotherapy has recently become a standard regimen for extensive-stage of small-cell lung cancer (ES-SCLC). SCLC is well known to be the most likely tumor associated with Lambert-Eaton myasthenic syndrome (LEMS), a rare autoimmune disease of a neuromuscular junction disorder. Although LEMS has been reported to be induced by ICI as immune-mediated adverse events, it remains unknown whether ICI can deteriorate preexisting paraneoplastic syndrome (PNS) of LEMS. Our rare case was successfully treated by durvalumab plus chemotherapy without exacerbation of preexisting PNS of LEMS. We report a 62-year-old female with ES-SCLC and preexisting PNS of LEMS. She started carboplatin-etoposide in combination with durvalumab. This immunotherapy achieved nearly complete response. However, multiple brain metastases were found after two courses of maintenance durvalumab. Her symptoms and physical examinations of LEMS improved despite of no significant change in compound muscle action potential amplitude in the nerve conduction study. The titer of anti-P/Q-type voltage-gated calcium channel (VGCC) antibody decreased from 1,419.2 to 263.5 pmol/L during the immunotherapy. In conclusion, ICI in combination with platinum doublet chemotherapy is still challenging but may be a treatment option for ES-SCLC patients complicated with PNS of LEMS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".