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G. Blumenthal



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    MINI 29 - Meta Analyses and Trial Conduct (ID 156)

    • Event: WCLC 2015
    • Type: Mini Oral
    • Track: Treatment of Advanced Diseases - NSCLC
    • Presentations: 1
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      MINI29.09 - Recommendations for Standardized Efficacy Data Specifications in Lung Cancer (ID 1599)

      G. Blumenthal

      • Abstract
      • Presentation
      • Slides

      Background:
      There are general standards for common clinical trial data elements submitted to US Food and Drug Administration (FDA) in a new drug application (NDA) or biologic license agreement (BLA). There is, however, considerable heterogeneity in the structure of data elements that are unique to a particular therapeutic area. As part of an effort organized by Coalition for Accelerating Standards and Therapies (CFAST), we developed specifications for efficacy data standardization in lung cancer.

      Methods:
      Using FDA guidance documents, NDA and BLA reviews, sample case report forms, and clinical trial datasets, we identified data elements in lung cancer clinical trials that are essential in evaluating the efficacy of new drugs and biologics. We constructed a concept map outlining the data elements and specifying their relational structure.

      Results:
      Data elements were captured under two main categories: efficacy endpoints (Figure 1) and covariates (Figure 2). Efficacy endpoints consist of overall survival, progression-free survival, objective response rate, duration of response, and disease-free survival. All lesions are assigned an organ-specific code. Data on tumor kinetics are captured as continuous variables supporting precise estimation of response while capturing all the requirements of Response Evaluation Criteria in Solid Tumors, version 1.1. Covariates were divided into disease and patient characteristics. Disease characteristics include specifications on molecular, immunohistochemical, and histological classification of tumors and detailed staging variables. Molecular definitions follow established nomenclature and include information on mutation subtypes as indicated. Patient characteristics include information on prior therapy, race and ethnicity. Figure 1 Figure 2





      Conclusion:
      The data elements we have identified (Figures 1 and 2) include concepts not adequately captured in current data standards and highlight important regulatory needs for the efficacy evaluation of new drugs and biologics in lung cancer. These specifications will be integrated with CFAST’s efforts to promote the development of lung cancer-specific data standards.

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    MTE 01 - Endpoints in Clinical Trials in Advanced NSCLC (Ticketed Session) (ID 53)

    • Event: WCLC 2015
    • Type: Meet the Expert (Ticketed Session)
    • Track: Treatment of Advanced Diseases - NSCLC
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/07/2015, 07:00 AM - 08:00 AM, 103
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      MTE01.02 - Endpoints in Clinical Trials in Advanced NSCLC (ID 1978)

      G. Blumenthal

      • Abstract
      • Presentation
      • Slides

      Abstract not provided

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    ORAL 31 - PD1 Axis Inhibition (ID 143)

    • Event: WCLC 2015
    • Type: Oral Session
    • Track: Treatment of Advanced Diseases - NSCLC
    • Presentations: 1
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      ORAL31.06 - An Exploratory Responder Analysis of Best RECIST Response and Survival in Patients with Metastatic Squamous NSCLC Treated with Nivolumab (ID 1701)

      G. Blumenthal

      • Abstract
      • Presentation
      • Slides

      Background:
      New therapeutic modalities in metastatic squamous non-small cell lung cancer (SQ NSCLC) focus on targeting pathways (programmed cell death 1 [PD-1]) involved in inhibiting anti-tumor T cell responses leading to tumor evasion. Nivolumab, an anti-PD-1 monoclonal antibody, blocks T cell inhibitory signal pathways by preventing engagement of PD-1. On March 4, 2015, FDA approved nivolumab for the treatment of patients with metastatic SQ NSCLC with progression on or after platinum-based doublet chemotherapy. The approval was based on a randomized study (CA209017) demonstrating a large magnitude of improvement in overall survival (OS) and was supported by single arm study (CA209063) demonstrating a 15% objective response rate (ORR), which appeared to be durable. We conducted a retrospective exploratory responder analysis to evaluate the association between response and OS in study CA209063. Figure 1



      Methods:
      CA209063 was a multicenter, multinational, single-arm, open-label study in patients with SQ NSCLC who previously received at least two lines of systemic therapies. Patients (n=117) received nivolumab 3 mg/kg as an intravenous (IV) infusion every 2 weeks until progressive disease (PD) or toxicity; treatment past PD was allowed if certain “clinical benefit” criteria were met. Response was defined as a partial response (PR) or complete response (CR) as determined by a blinded independent review committee (IRC) utilizing the Response Evaluation Criteria In Solid Tumors (RECIST) criteria (98 of 117 were evaluable). Responders were categorized into the following groups: A CR or PR, stable disease (SD), PD with continuation of treatment, and PD with discontinuation of treatment. A sensitivity landmark-based analysis was performed to exclude timing of response evaluation bias (Anderson et al, 1983).

      Results:
      The exploratory responder analysis showed that patients who achieved a best response of CR or PR had the longest survival with anti-PD1 therapy, followed by patients who either achieved a best response of SD or PD with continuation of treatment beyond RECIST progression. Patients whose best response was PD and no treatment beyond progression had poor survival (figure 1). The Landmark time-based sensitivity analysis at 3.5 months (median time to response) also suggested that responders had longer survival than non-responders.

      Conclusion:
      Our analysis suggests that patients with NSCLC who respond are likely to derive the most clinical benefit from anti-PD1 therapy. However, given the exploratory retrospective nature of this analysis, results should be interpreted cautiously. Further development of predictive biomarkers to identify patients most likely to respond is necessary.

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