Clinical Activity of Mitogen-Activated Protein Kinase–Targeted Therapies in Patients With Non–V600 BRAF-Mutant Tumors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Non-V600 mutations comprise approximately 35% of all BRAF mutations in cancer. Many of these mutations have been identified as oncogenic drivers and can be classified into three classes according to molecular characteristics. Consensus treatment strategies for class 2 and 3 BRAF mutations have not yet been established. METHODS: We performed a systematic review and meta-analysis with published reports of individual patients with cancer harboring class 2 or 3 BRAF mutations from 2010 to 2021, to assess treatment outcomes with US Food and Drug Administration-approved mitogen-activated protein kinase (MAPK) pathway targeted therapy (MAPK TT) according to BRAF class, cancer type, and MAPK TT type. Coprimary outcomes were response rate and progression-free survival. RESULTS: A total of 18,167 studies were screened, identifying 80 studies with 238 patients who met inclusion criteria. This included 167 patients with class 2 and 71 patients with class 3 BRAF mutations. Overall, 77 patients achieved a treatment response. In both univariate and multivariable analyses, response rate and progression-free survival were higher among patients with class 2 compared with class 3 mutations, findings that remain when analyses are restricted to patients with melanoma or lung primary cancers. MEK ± BRAF inhibitors demonstrated greater clinical activity in class 2 compared with class 3 BRAF-mutant tumors than BRAF or EGFR inhibitors. CONCLUSION: This meta-analysis suggests that MAPK TTs have clinical activity in some class 2 and 3 BRAF-mutant cancers. BRAF class may dictate responsiveness to current and emerging treatment strategies, particularly in melanoma and lung cancers. Together, this analysis provides clinical validation of predictions made on the basis of a mutation classification system established in the preclinical literature. Further evaluation with prospective clinical trials is needed for this population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it