Abstract 105P
Background
Neurotrophic tyrosine receptor kinase (NTRK) gene fusions involving either NTRK1, 2, or 3 are oncogenic drivers of various adult and pediatric tumor types. The corresponding tropomyosin receptor kinase (TRK) proteins are targets for precision medicines. Patients (pts) with NTRK fusion-positive (NTRK+) cancers can be treated with TRK inhibitors, for which single-arm studies have shown high response rates. However, the assessment of comparative effectiveness is challenging. Using historical data is complicated by insufficient information about the prognostic value of NTRK gene fusions, creating uncertainty about the appropriate control group. Our study contributes to filling this gap.
Methods
This is a retrospective analysis on the Hartwig Medical Foundation database with metastatic cancer pts from 44 hospitals in the Netherlands, who received genomic profiling between 2012 and 2020 (CPCT-02 study). Pts were categorized into NTRK+ and NTRK-. Within each tumor type, pts were matched using the optimal matching method with a 1:4 ratio (NTRK+: NTRK-) on demographic and clinical characteristics, including age, gender and number of previous lines of therapy. Descriptive and time-to-event analyses were conducted. Overall survival (OS) was evaluated using the Kaplan-Meier method and Cox regression, with the date of the first post-biopsy treatment as the index date.
Results
Out of 3,661 pts with known tumor location, 30 pts across 10 tumor locations had an NTRK fusion. NTRK1 was involved in 8 (26.7%), NTRK2 in 6 (20.0%), and NTRK3 in 16 (53.3%) of the observed fusion events. Co-occurrence with ALK and/or ROS1 gene fusions was 6.7%. The dataset used for matching consisted of 23 NTRK+ and 92 NTRK- pts. Demographic and clinical characteristics were similar between the matched cohorts. The hazard ratio for pts with NTRK+ vs. NTRK- cancer was 1.37 (95% CI 0.78-2.42).
Conclusions
Although not statistically significant, there was a trend to shorter OS for NTRK+ pts. Given the small sample size, insufficient data for other relevant covariates (e.g. performance status), and other limitations, residual confounding cannot be ruled out.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
European Union’s Horizon 2020 Research and Innovation programme.
Disclosure
All authors have declared no conflicts of interest.