Andrew Briggs1, Noman Paracha2, Katherine Rosettie3, Alexander Upton4, Carsten Bokemeyer5, Ulrik Lassen6, Sean D Sullivan7. 1. London School of Hygiene and Tropical Medicine, London, United Kingdom. 2. Bayer Pharmaceuticals, Basel, Switzerland. 3. IQVIA, 3110 Fairview Park Dr #400, Falls Church, Virginia, USA, katherine.rosettie@iqvia.com. 4. Bayer Pharmaceuticals, Whippany, New Jersey, USA. 5. University Hospital Hamburg-Eppendorf, Hamburg, Germany. 6. Department of Oncology, Rigshospitalet, Copenhagen, Denmark. 7. The CHOICE Institute, University of Washington School of Pharmacy, Seattle, Washington, USA.
Abstract
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.
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.
Authors: Alexander Drilon; Theodore W Laetsch; Shivaani Kummar; Steven G DuBois; Ulrik N Lassen; George D Demetri; Michael Nathenson; Robert C Doebele; Anna F Farago; Alberto S Pappo; Brian Turpin; Afshin Dowlati; Marcia S Brose; Leo Mascarenhas; Noah Federman; Jordan Berlin; Wafik S El-Deiry; Christina Baik; John Deeken; Valentina Boni; Ramamoorthy Nagasubramanian; Matthew Taylor; Erin R Rudzinski; Funda Meric-Bernstam; Davendra P S Sohal; Patrick C Ma; Luis E Raez; Jaclyn F Hechtman; Ryma Benayed; Marc Ladanyi; Brian B Tuch; Kevin Ebata; Scott Cruickshank; Nora C Ku; Michael C Cox; Douglas S Hawkins; David S Hong; David M Hyman Journal: N Engl J Med Date: 2018-02-22 Impact factor: 91.245
Authors: Theodore W Laetsch; Steven G DuBois; Leo Mascarenhas; Brian Turpin; Noah Federman; Catherine M Albert; Ramamoorthy Nagasubramanian; Jessica L Davis; Erin Rudzinski; Angela M Feraco; Brian B Tuch; Kevin T Ebata; Mark Reynolds; Steven Smith; Scott Cruickshank; Michael C Cox; Alberto S Pappo; Douglas S Hawkins Journal: Lancet Oncol Date: 2018-03-29 Impact factor: 41.316
Authors: D S Hong; T M Bauer; J J Lee; A Dowlati; M S Brose; A F Farago; M Taylor; A T Shaw; S Montez; F Meric-Bernstam; S Smith; B B Tuch; K Ebata; S Cruickshank; M C Cox; H A Burris; R C Doebele Journal: Ann Oncol Date: 2019-02-01 Impact factor: 32.976
Authors: Ash Bullement; Anna Willis; Amerah Amin; Michael Schlichting; Anthony James Hatswell; Murtuza Bharmal Journal: BMC Med Res Methodol Date: 2020-05-06 Impact factor: 4.615