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Estimating Long-Term Survival Outcomes for Tumor-Agnostic Therapies: Larotrectinib Case Study
Andrew Briggs1, Noman Paracha2, Katherine Rosettie3
1London School of Hygiene and Tropical Medicine, London, United Kingdom.
Background:
Larotrectinib is a precision oncology treatment for solid tumors with neurotrophic tyrosine receptor kinase (NTRK) gene fusions. Larotrectinib efficacy has been evaluated in single-arm basket trials with limited follow-up and sample sizes at the initial regulatory approval due to the rarity of solid tumors with NTRK gene fusion.
Objectives:
We aim to demonstrate that trends in progression-free survival (PFS) and overall survival (OS) in survival data with longer follow-up may be predicted from long-term survival estimates from survival data with shorter follow-up, including predictions for median survival when it is not observed in the trial.
Methods:
Patient-level data were pooled from 3 clinical trials (NCT02122913, NCT02576431, and NCT02637687) using the 2018 and 2020 data cuts for the same subset of pediatric and adult patients. The Weibull distribution was selected for survival models. Survival predictions using 2018 data were compared to 2020 Kaplan-Meier (KM) curves.
Results:
A total of 102 patients representing 15 tumor types were included in the analysis, with a mean age of 37 years. When comparing PFS from the 2018 survival prediction to observed 2020 KM data, the 12-month PFS rate was identical (66.6%). The 36-month PFS rate was lower for the 2018 prediction (35.3%) compared to 2020 KM data (44.4%). The median OS had not yet been reached in either data cut but was predicted to be 90 months using the 2018 data. When comparing OS from the 2018 survival prediction to the observed 2020 KM data, the 12-month OS rate was 89.0% and 86.6% and the 48-month OS rate was 67.2% and 63.0%, respectively.
Conclusion:
Long-term PFS predictions deviated from observed PFS rates due to response differences across tumor types and heavy censoring towards the end of the survival curve. However, for OS, the 48-month survival prediction was consistent with the observed 2020 KM estimate.
Insights
Predicting long-term survival trends for larotrectinib (NTRK inhibitor) is possible using earlier data. While progression-free survival (PFS) predictions showed some deviation, overall survival (OS) predictions remained consistent with longer follow-up.
Area of Science:
- Oncology
- Precision Medicine
- Biostatistics
Background:
- Larotrectinib is a targeted therapy for NTRK gene fusion-positive solid tumors.
- Limited follow-up and sample size in early trials necessitate methods for long-term survival estimation.
- Rarity of NTRK fusion-positive tumors presents challenges for traditional clinical trial designs.
Discussion:
- Survival models using Weibull distribution were employed to predict long-term outcomes.
- Comparison of predictions from 2018 data against 2020 Kaplan-Meier (KM) curves assessed accuracy.
- Analysis included pooled patient-level data from three clinical trials.
Key Insights:
- Progression-free survival (PFS) predictions showed divergence from observed data, particularly at 36 months, due to tumor type variability and censoring.
- Overall survival (OS) predictions demonstrated consistency, with the 48-month OS rate aligning well with observed 2020 KM estimates.
- Median OS was not reached but was predicted to be 90 months based on earlier data.
Outlook:
- The study validates the utility of predictive survival modeling for rare cancer indications.
- Longer follow-up data can refine predictions and inform clinical decision-making.
- Further research can explore advanced modeling techniques to improve accuracy for PFS predictions.
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