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X. Zhou
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P3.01 - Advanced NSCLC (ID 621)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Advanced NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P3.01-087 - Impact Factor Analysis for Efficacy and Prognosis of Anlotinib in NSCLC as Third-Line Treatment: Data from Trial ALTER 0303 (ID 9129)
09:30 - 09:30 | Author(s): X. Zhou
- Abstract
Background:
Anlotinib hydrochloride is a novel TKI targeting the VEGFR, FGFR, PDGFR and c-Kit. With the capability of inhibiting the tumor angiogenesis and tumor cell itself, anlotinib had showed significantly improvement in OS (9.63 vs. 6.30 months, HR=0.68, 95%CI 0.54-0.87, p=0.0018) and PFS (5.37 vs. 1.40 months, HR=0.26, 95%CI 0.21-0.33, p<0.0001) in ALTER 0303 study for refractory cancer, a randomized, double-blind, placebo-controlled Phase Ⅲ trial in China. Here, we report the main impact factors affecting the efficacy and prognosis of anlotinib based on the data from ALTER0303 to elucidate the most benefit population.
Method:
Analyzed data were collected from 294 patients that were enrolled in ALTER0303 trial and received anlotinib treatment between 4[th] March 2015 and 15[th] August 2016. The statistical analysis was conducted using SPSS19.0 software, in which the measuring and enumeration materials were described with Mean±SD and frequency/percentage respectively, Kaplan-Meier method was used for survival curves in survival analysis. Independent impact factors of OS and PFS were identified by univariate and multivariate analysis in Cox proportional hazards regression model (Significant level, α=0.05).
Result:
Several factors were discovered to be associated with the efficacy of Anlotinib treatment. The impact factors were presented in Tab1.Tab1. Impact factors for PFS and OS analyzed by Cox proportional hazards regression model Independent risk factor Independent protective factor PFS Ratio of granulocytes to lymphocytes at PD (HR=1.07, 95%CI 1.041-1.100, p<0.0001) Elevated ALP level (HR=1.553, 95%CI 1.142-2.112, p=0.005) Baseline sum of longest diameters of target lesions (HR=1.004, 95%CI 1.001-1.006, p=0.007) Elevated TSH level (HR= 0.555, 95%CI 0.422-0.730, p<0.0001) Hypercholesteremia (HR=0.720, 95%CI 0.534-0.971, p=0.031) Hypertension (HR=0.482, 95%CI 0.370-0.628, p<0.0001) Hand-foot skin reaction (HR=0.489, 95%CI 0.373- 0.643, p<0.0001) Elevated LDL level (HR=0.630, 95%CI 0.437-0.909, p=0.014) Age (HR=0.987, 95%CI 0.975-0.999, p=0.039) OS Ratio of granulocytes to lymphocytes at PD (HR=1.116, 95%CI 1.081-1.151, p<0.0001) Baseline sum of longest diameters of target lesions (HR=1.006, 95%CI 1.003-1.008, p<0.0001) ECOG PS≥2 at PD (HR=2.245, 95%CI 1.704- 3.508, p<0.0001) Elevated TSH level (HR=0.725, 95%CI 0.524- 1.005, p=0.053) Hypertriglyceridemia (HR=0.601, 95%CI 0.440-0.821, p<0.0001) Rash (HR=0.581, 95%CI 0.369-0.916, p=0.019) Female (HR=0.713, 95%CI 0.533-0.953, p=0.022)
Conclusion:
This analysis explored the possible impact factors of PFS and OS in Anlotinib treatment. Moreover, we provide real data for the prediction of Anlotinib efficacy and most benefit population through the baseline characteristics and variety of clinical index. However, further analysis in the larger scale study is still looking forward.
