Outcomes of larotrectinib compared with real-world data from non-TRK inhibitor therapies in patients with TRK fusion cancer: VICTORIA study.
Bibliographic record
Abstract
3105 Background: NTRK gene fusions are oncogenic drivers identified in <1% of solid tumors. Larotrectinib (laro) is a highly selective TRK inhibitor (i) that was approved in patients (pts) with TRK fusion cancers based on data from single-arm trials. Here we report results from VICTORIA (NCT05192642), a protocol-driven, exact-matching study comparing the outcomes of pts with TRK fusion cancer treated with laro in clinical trials (NCT02122913, NCT02576431, NCT02637687) to pts treated with non-TRKi therapies in the real-world (RW) setting. Methods: Adult (≥18 years old) pts with non-small cell lung cancer, colorectal cancer, soft-tissue sarcoma, thyroid cancer, or salivary gland carcinoma were included. Deduplicated data from RW pts were from US and ex-US databases: American Association for Cancer Research GENIE, Cardinal, Flatiron, and ORIEN, as well as a global chart review. Pts in the laro cohort were exactly matched to RW pts based on tumor type and line of therapy to define index line and date for RW pts. A propensity score (weighting) model was used to balance key pt characteristics between cohorts. Pts were followed from index date to last activity, end of study period, or death, whichever occurred first. RW pts were censored at the start of any TRKi therapy or investigational agent, or censored at their last known alive date. Overall survival (OS) was the primary outcome. Results: In total,164 pts with TRK fusion cancer were matched (82 in each cohort). Balance in the baseline covariates was achieved after weighting. Matched RW pts received standard index treatments for their disease, which comprised chemotherapy (49%), non-TRKi small molecule targeted therapy (27%), chemotherapy + non-TRKi non-small-molecule targeted therapy (11%), or immune checkpoint inhibitor therapy (10%). Laro-treated pts had longer OS compared to RW pts (median not reached [NR] vs 37.2 months; hazard ratio [HR]: 0.44 [95% confidence interval {CI}: 0.23-0.83]) after weighting. In the weighted analysis, laro-treated pts had longer time to next therapy (TTNT; median NR vs 10.6 months; HR: 0.22 [95% CI: 0.13-0.38]), duration of therapy (DoT; median 30.8 vs 3.4 months; HR: 0.23 [95% CI: 0.15-0.33]), and progression-free survival (PFS; median 36.8 vs 5.2 months; HR: 0.29 [95% CI: 0.18-0.46] compared to RW pts. Conclusions: In adult pts with TRK fusion cancer, treatment with laro was associated with longer OS and all measured time-to-event endpoints (TTNT, DoT, and PFS), compared to exactly matched pts treated with standard non-TRKi therapies in the RW. These results furnish additional evidence illustrating the benefit of laro treatment in pts with TRK fusion cancer and support the data generated in the single-arm registrational trials. Clinical trial information: NCT05192642 .
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".