Second-line drug regimens in metastatic melanoma patients based on BRAF mutation status: A Canadian real-world retrospective study.
Bibliographic record
Abstract
e21054 Background: Overall survival for metastatic melanoma patients has improved with targeted- and immuno-therapies. This study describes the second-line drug regimens in these patients based on their BRAF mutation status. Methods: This retrospective observational study utilized IMS Health Real-World Oncology Data, an anonymised patient database which includes patient and treatment metrics. This database is populated via an electronic questionnaire completed by physicians who treat metastatic melanoma patients. Second-line regimens, BRAF mutation status, co-morbidities and sites of metastasis were identified in a subset (N=383) of stage IV patients treated in Canada between October 2014 and September 2015. The second-line drug regimens were classified as immuno-, targeted-, combined immuno- and targeted- and chemo-therapies. The proportions of patients receiving each treatment modality were compared across the BRAF mutation status populations, with statistical testing of the differences at a 5% level of significance. Results: Of the 383 study patients receiving second-line treatment, 204 (53%) were BRAF+, 126 (33%) were BRAF- and 53 (14%) had unknown BRAF status. A statistically higher proportion of patients diagnosed as BRAF+ received targeted therapy compared to patients diagnosed as BRAF- (p=<0.05). Whereas, a statistically higher proportion of the patients diagnosed as BRAF- were treated with immunotherapy compared to BRAF+ patients (p=<0.05). Within our data, a subset of patients (N=28) received combined immuno- and targeted-therapies, predominantly in the BRAF+ patient group. Conclusions: The second-line landscape in metastatic melanoma is now dominated by immuno- and targeted-therapies in Canada. The synergistic effects of combining these two modalities are currently an area of research and this practice has been captured in our dataset. This study provides real-world evidence of the use of immuno- and targeted-therapies in patients with metastatic melanoma. Therapeutic Base BRAF+ (%) BRAF- (%) Unknown BRAF Status (%) Immunotherapies 21% 70% 36% Targeted Therapies 45% 7% 21% Combined Immuno- and Targeted- therapies 13% 1% 0% Chemotherapies 22% 22% 43%
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".