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H. Barraclough



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    MO06 - NSCLC - Chemotherapy I (ID 108)

    • Event: WCLC 2013
    • Type: Mini Oral Abstract Session
    • Track: Medical Oncology
    • Presentations: 1
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      MO06.04 - A Randomized Phase 3 Study Comparing First-line Pemetrexed plus Cisplatin Followed by Gefitinib as Maintenance with Gefitinib Monotherapy in East Asian Patients with Locally Advanced or Metastatic Nonsquamous Non-Small Cell Lung Cancer (nSqNSCLC) (ID 1943)

      16:30 - 16:35  |  Author(s): H. Barraclough

      • Abstract
      • Presentation
      • Slides

      Background
      The IPASS study reported that in a clinically selected lung cancer patient population (East Asian, light ex-/nonsmokers with adenocarcinoma) gefitinib (G) provided superior progression-free survival (PFS) than chemotherapy with carboplatin/paclitaxel; however, the benefit was restricted to patients with epidermal growth factor receptor gene (EGFR)-mutant tumors whereas patients with wild-type (WT) tumors had inferior outcomes. Pemetrexed, in combination with cisplatin, (PC) has demonstrated improved efficacy in first-line treatment of nSqNSCLC and is a preferred chemotherapy choice. The primary objective was to compare PC induction therapy followed by G as maintenance therapy to G monotherapy, in terms of PFS, as first-line treatment in a similar “IPASS” patient population.

      Methods
      Patients with unknown EGFR mutation status (N=236) were randomized 1:1 to PCG treatment for 6 cycles or G. Patients on Arm A without progressive disease after 6 cycles received G maintenance therapy. Stage IIIB/IV nSQ NSCLC, light ex-smokers or never-smokers, and ECOG PS 0-1 patients with no prior systemic therapy were eligible. Primary endpoint analysis was conducted using a Wilcoxon test after 169 PFS events. This assessment provided 80% power if the true hazard ratio (HR) was 0.65. Tissue samples from consenting patients were analyzed for EGFR mutation status.

      Results
      Baseline characteristics were balanced across treatment arms. One-hundred-forty-one patients provided tissue for EGFR mutation analysis (59.7%). Mutation status was determined for 74 samples (52.5%);50/74 samples (67.6%) had mutations (mutation type: EX19_DEL, n=25; L858R, n=23; other, n=2). The primary analysis of PFS showed no significant difference between treatment arms (Wilcoxon p=0.217). The unadjusted HR was 0.85 (95% CI: 0.63, 1.13). During most of the study period, the KM curve for PC remained above the G curve. In a prespecified subgroup analysis, EGFR-by-treatment interaction was statistically significant (p=0.008), showing treatment effect significantly differed by EGFR mutation status. The HR for PFS favored PC in both EGFR-mutated and EGFR-WT patients, but the magnitude of benefit was greater in EGFR-WT patients [EGFR-mutated patients HR=0.83 ([95% CI: 0.42, 1.62], p=0.585); EGFR-WT HR 0.18 ([95% CI: 0.06, 0.51], p=0.001)]. HRs for ITT and EGFR-mutated patients should be interpreted with caution as they were not constant. Arm A had more patients with ≥1 possibly drug-related CTCAE grade 3/4 TEAEs but similar rates of all-grade TEAEs during induction. Selected grade 3/4 or all-grade TEAEs which occurred significantly more included anemia, neutropenia, emesis, and neuropathy in Arm A and AST/ALT elevations, diarrhea, pruritus, and skin rash in Arm B. The toxicity profile was similar in both arms during the G maintenance period.

      Conclusion
      In the ITT population, the PFS difference was not statistically significant. In the biomarker assessable population, results are consistent with the existing consensus that patients with WT EGFR do not benefit with front-line EGFR TKI treatment. Overall, the results show that identification of the EGFR mutational status is key in the management of advanced NSCLC. Even in the presence of clinically favorable predictors of EGFR mutation positivity (>60% in our population), “empirical” choice of EGFR TKIs as front-line therapy may be detrimental to NSCLC patients without EGFR mutations.

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    P3.11 - Poster Session 3 - NSCLC Novel Therapies (ID 211)

    • Event: WCLC 2013
    • Type: Poster Session
    • Track: Medical Oncology
    • Presentations: 1
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      P3.11-016 - Using Statistical Models to Improve Phase II Study Designs (ID 1580)

      09:30 - 09:30  |  Author(s): H. Barraclough

      • Abstract

      Background
      Single arm phase II studies have traditionally been conducted in oncology, but they rely completely on historical information to assess treatment benefits and are associated with high bias and false-positive error rates. This has contributed unsustainably high phase III clinical trial failure rates in oncology. On the other hand, conventional randomized controlled trials (RCT) involve more patients, higher cost and longer timelines. Thus, innovative statistical methods have been developed to try to address this challenge. An area of focus has been the use of statistical models to improve the design of phase II studies to better mimic what is intended for the phase III design, and therefore to predict its outcomes with greater precision.

      Methods
      Two statistical innovations have been applied to our phase II portfolio. Firstly, the Bayesian Augmented Control (BAC) design has been implemented to gain the benefits of using historical information (“borrowing”) as well as using randomization to a concurrent control arm. The BAC design utilizes models to summarize existing knowledge on the standard of care (SOC) in a defined patient population. For example, patients can be “borrowed” from a previous well-designed phase III RCT which established the SOC. The extent of “borrowing” depends on the similarity between the response in the new control patients and the historical patients, which is evaluated by pre-specified models. Secondly, Change in Tumour Size (CTS) from baseline to the end of Cycle 2 has been incorporated as an endpoint in our studies because this endpoint correlates strongly with progression-free survival (PFS) and overall survival (OS) in certain tumor types such as Non-Small Cell Lung Cancer (NSCLC). The approach consists in using tumor size measurements as a continuous variable, rather than a categorical endpoint based on Response Evaluation Criteria In Solid Tumors (RECIST), for assessing anti-tumor activity.

      Results
      The BAC design enables randomized controlled trials with smaller sample sizes, yet maintains statistical power. It also allows disproportionate enrollment to the experimental arm, which is often attractive to investigators and patients seeking access to novel therapies.

      Conclusion
      We believe that our phase II data package is now more informative whilst still meeting the logistical needs. It is hoped that this will facilitate a better Phase III prediction, which will increase our Phase III success rate. To date, insufficient phase III trials which were designed based on these improved phase II trials have yet been completed to be able to evaluate whether our phase III success rate has ultimately improved.