Perspectives from the community setting: A retrospective chart review of nivolumab for previously treated non-small cell lung cancer.
Bibliographic record
Abstract
86 Background: Lung cancer is among the most commonly diagnosed cancers in Canada and is the leading cause of cancer deaths. Non-small cell lung cancer (NSCLC) is one of the most common types representing 85-90% of cases. Compared to other cancers, the five-year survival rate for lung cancer in Canada is among the lowest at 17%. Nivolumab has been in use in the setting of progression of previously treated NSCLC at the Windsor Regional Cancer Center since June 2015. This retrospective chart review abstracts data from 26 patients at WRCC with NSCLC who were treated with nivolumab. Methods: A retrospective chart review of 26 patients treated with nivolumab in the setting of progressive NSCLC. Results: 26 patients were reviewed (1 stage 2a, 2 stage 3a, 3 stage 3b, 20 stage 4 with 12 M1b and 8 M1a). Grade 1-2 side effects were documented in 4 patients treated with monitoring and no discontinuation or dose modification of nivolumab. A grade 3 side effect was documented in 1 patient leading to discontinuation of treatment. 3 living patients discontinued treatment due to progression. 6 patients died while on treatment secondary to disease progression. The remaining patients are on nivolumab with no side effects documented. Conclusions: As the use of immuno-oncology agents use expand in community clinics, opportunities arise from community data to further learn which patients benefit from these treatments, what side effects can occur and how to manage them, and how response to treatment may look. Out of the 26 patients receiving nivolumab, 5 patients had documented side effects resulting in discontinuation of treatment in 1 patient. Overall nivolumab has been well tolerated in patients with NSCLC in this community setting.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".