Author of

• 11745

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  P2.11 - Poster Session 2 - NSCLC Novel Therapies (ID 209)

  • Event: WCLC 2013
  • Type: Poster Session
  • Track: Medical Oncology
  • Presentations: 2
  • Moderators:
  • Coordinates: 10/29/2013, 09:30 - 16:30, Exhibit Hall, Ground Level

  • 11759

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    P2.11-014 - Biomarkers reduce clinical trial risk and the cost of drug development in non-small cell lung cancer (NSCLC) (ID 1525)

    09:30 - 09:30  |  Author(s): G. Lopes
    • Abstract

    Background
    We evaluated the risk of clinical trial failure and the cost of drug development for patients with NSCLC between 1998 and 2012

    Methods
    For assessment of drug development we used trial disclosures from publically available resources, such as clinicaltrials.gov and others. Compounds were excluded from the analysis if they began phase I clinical testing before 1998 and if they did not use clinically significant, treatment-relevant endpoints, such as response rate, progression-free and overall survival. Analysis was conducted in regards to treatment indication, compound classification and mechanism of action. A compound that had completed a phase I clinical trial was classified as successful if there was an ongoing, completed, or currently recruiting phase II clinical trial found. A compound that had completed a phase II clinical trial was similarly classified as successful if there was an ongoing, completed or currently recruiting phase III found. A compound that had completed a phase III clinical trial was classified as successful if there was an official FDA approved indication in our study population. In addition, a phase I/II trial was classified as a phase II trial and a phase II/III trial was classified as a phase III trial for analysis purposes. Follow up was completed until January 1, 2012. Costs of clinical drug development for advanced NSCLC were calculated using industry data and assumptions, a 9% yearly discount rate and assuming a clinical trial length of 2.5 years for phase I trials, 4 years for phase II trials, 5 years for phase III trials and an average of 5 phase I trials, 7 phase II trials, and 4 phase III trials per approved drug. All funding costs are in US dollars (USD).

    Results
    2,407 clinical trials met search criteria. 676 trials and 199 unique compounds met our inclusion criteria. The likelihood, or cumulative clinical trial success rate, that a new drug would pass all phases of clinical testing and be approved was found to be 11% (less than the expected industry aggregate rates of 16.5%). The biggest obstacle for approval was the success of phase III trials: success rate was only 28%. Biomarker-guided targeted therapies (with a success rate of 62%) and receptor targeted therapies (with a success rate of 31%) were found to have the highest likelihood of success in clinical trials. The risk-adjusted cost for NSCLC clinical drug development with biomarkers was US$1.4 billion, a 26% reduction when compared to overall lung cancer drug development costs of US$1.89 billion, which is within industry expectations. Potential savings may be even higher if fewer clinical trials are required for successful development.

    Conclusion
    Physicians that enroll patients in NSCLC trials should prioritize their participation in programs that involve either a biomarker or receptor targeted therapy, which appear to carry the best chances for a successful treatment response. Given the high adjusted cost of clinical testing alone in NSCLC, efforts to mitigate the risk of trial failure need to explore these factors more fully.

  • 11760

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    P2.11-015 - Comparative effectiveness of gefitinib, erlotinib, afatinib and chemotherapy in the first line treatment of patients with advanced non small cell lung cancer (NSCLC) and epidermal growth factor receptor (EGFR) mutations (ID 1533)

    09:30 - 09:30  |  Author(s): G. Lopes
    • Abstract

    Background
    EGFR tyrosine kinase inhibitors (TKI) have revolutionized the treatment of patients with advanced NSCLC who harbor activating EGFR mutations. No large prospective trial has compared gefitinib, erlotinib and afatinib face-to-face. We did a network analysis comparing the three drugs against chemotherapy and among themselves.

    Methods
    We searched PUBMED, EMBASE, google scholar databases and abstracts from ASCO, ESMO and WCLC abstracts between 2000 and 2013 using relevant search terms. Prospective, randomized clinical trials comparing erlotinib, gefitinib, or afatinib to chemotherapy or one another as first-line therapy in patients with non-small-cell lung cancer were selected. Studies were included if they included only patients with EGFR activating mutations or if they reported relative efficacy within the EGFR positive subgroup. Endpoints of interest were progression-free survival (PFS), overall survival (OS), and overall response rate (ORR). Direct and indirect meta-estimates were generated in the context of linear mixed effects models, similar to the model of DerSimonian and Laird, with fixed effects for each relative comparison and random effects for each study. Heterogeneity across studies was tested using chi-squared and I[2] statistics in the manner of Higgins and Thompson. Confidence (CI) and Predictive intervals (PIs) were calculated using the study-to-study variance estimates from each linear mixed-effects model. Results were considered statistically significant if the CI and PI did not cross unity.

    Results
    Eight studies fulfilled search and inclusion criteria: OPTIMAL, EURTAC, LUX-Lung 3, LUX-Lung 6, IPASS, West Japan, North-east Japan, and First-SIGNAL. The pooled hazard ratio (HR) meta-estimate for PFS were as follows: erlotinib vs. chemotherapy - 0.25 (95% CI 0.14-0.43; 95% PI 0.11-0.58), afatinib vs. chemotherapy - 0.44 (95% CI 0.25-0.77; 0.19-1.03), gefitinib vs. chemotherapy - 0.43 (95% CI 0.29-0.63; 95% PI 0.21-0.90), erlotinib vs. afatinib - 0.57 (95% CI 0.26-1.23; 95% PI 0.21-1.55), erlotinib vs. gefitinib - 0.58 (95% CI 0.30-1.13; 95% PI 0.23-1.46), and afatinib vs. gefitinib - 1.02 (95% CI 0.52-2.00; 95% PI 0.41-2.58). The test of heterogeneity (for PFS) indicated moderately high study-to-study variability with Q = 17.7 on 5 degrees of freedom (p = 0.003) and I[2] of 72%. For ORR, The pooled odds ratio (OR) meta-estimate for erlotinib vs. chemotherapy was 8.2 (95% CI 4.5-15.1; 95% PI 3.9-17.5), afatinib vs. chemotherapy was 5.5 (95% CI 3.4-8.8; 95% PI 2.9-10.5), gefitinib vs. chemotherapy was 4.1 (95% CI 2.7-6.3; 95% PI 2.3-7.6), erlotinib vs. afatinib was 1.5 (95% CI 0.7-3.3; 95% PI 0.6-3.7), erlotinib vs. gefitinib was 2.0 (95% CI 0.9-4.1; 95% PI 0.8-4.7), and afatinib vs. gefitinib was 1.3 (95% CI 0.7-2.5; 95% PI 0.6-2.8). The test of heterogeneity indicated moderate study-to-study variability with Q = 7.32 on 5 degrees of freedom (p = 0.198) and I[2] of 32% (For ORR). There were no statistically significant differences for overall survival.

    Conclusion
    Erlotinib, gefitinib and afatinib improved clinical outcomes when compared with chemotherapy. There were no statistically significant differences in the comparison among erlotinib, afatinib, and gefitinib.