Randomised phase II study of axitinib or bevacizumab combined with paclitaxel/carboplatin as first-line therapy for patients with advanced non-small-cell lung cancer.

BACKGROUND: Efficacy and safety of first-line axitinib/paclitaxel/carboplatin versus bevacizumab/paclitaxel/carboplatin in advanced non-squamous non-small-cell lung cancer (NSCLC) was evaluated. PATIENTS AND METHODS: Patients with stage IIIB/IV disease stratified by adjuvant therapy and gender were randomised 1 : 1 to axitinib (5 mg twice daily) or bevacizumab [15 mg/kg every 3 weeks (Q3W)], both with paclitaxel (200 mg/m(2) Q3W)/carboplatin (AUC 6 mg min/ml Q3W). RESULTS: The trial was discontinued after preliminary analysis. Median progression-free survival (primary end point) for axitinib (N = 58) and bevacizumab (N = 60), respectively, was 5.7 and 6.1 months [hazard ratio (HR) 1.09, 95% confidence interval (CI) 0.68-1.76; one-sided stratified P = 0.64]; median overall survival was 10.6 and 13.3 months (HR 1.12, 95% CI 0.74-1.69; one-sided stratified P = 0.70). Objective response rates (95% CI) were 29.3% (18.1-42.7) and 43.3% (30.6-56.8), respectively; risk ratio 0.676 (95% CI 0.41-1.11; one-sided stratified P = 0.94). The most common grade 3/4 adverse events included neutropenia (28% versus 20%), fatigue (14% versus 7%), and hypertension (14% versus 5%). Patient-reported outcomes based on the EORTC QLQ-C30 were similar between arms. CONCLUSIONS: In patients with advanced non-squamous NSCLC, axitinib/paclitaxel/carboplatin did not improve efficacy versus bevacizumab/paclitaxel/carboplatin, and was less well tolerated.

Ignorance is not bliss: Statistical power is not probability of trial success.

The purpose of this commentary is to place probability of trial success, or assurance, in the context of decision making in drug development, and to illustrate its properties in an intuitive manner for the readers of Clinical Pharmacology and Therapeutics. The hope is that this will stimulate a dialog on how assurance should be incorporated into a quantitative decision approach for clinical development and trial design that uses all available information.

The prognostic value of PSA levels in radiation therapy of patients with carcinoma of the prostate: the UCLA experience 1988-1992.

BACKGROUND AND OBJECTIVES: Pretreatment prostate-specific antigen (PSA) levels may be of prognostic significance for patients with prostate cancer. Posttreatment PSA data are more limited. This study was undertaken to examine the prognostic role of pretreatment and posttreatment PSA levels in the radiation treatment of patients with carcinoma of the prostate. METHODS: One hundred one patients who received primary radiation therapy at UCLA between 1988 and 1992 for clinical stage A to D1 prostate cancer were analyzed. Included were 4 patients with stage A, 77 with stage B, 16 with stage C, and 4 with stage D. All patients had pretherapy and posttherapy PSA values. Patients received definitive radiation therapy with photons (81), neutrons (13), or interstitial implant (7). Correlations were made with other prognostic factors and treatment outcome. RESULTS: Median follow-up was 28 months. At last follow-up, 64% were without evidence of disease, 17% had rising PSA profiles or failure of PSA to normalize (chemical failure), and 19% had local recurrence and/or distant metastases. The 4-year overall survival was 85%, whereas actuarial survival free of chemical or clinical failure was only 32%. Pretreatment PSA levels and posttreatment PSA level normalization at 6 months correlated significantly with disease-free survival. On univariate analysis, pretreatment PSA levels correlated significantly with stage, high versus low Gleason score, and outcome. Posttreatment PSA level normalization at 6 and 12 months correlated with stage, pretreatment PSA level, and outcome, but not with Gleason score. Only PSA level normalization at 6 months and age were independent variables using multivariate analysis. PSA nadir values differed significantly between patients free of disease and those who failed. CONCLUSIONS: In our analysis, posttreatment PSA levels were independently predictive of outcome, whereas pretreatment PSA levels, while correlating with other prognostic factors, were not independently predictive. Given the prognostic value of posttreatment PSA levels, it is appropriate that chemical failures be included in outcome analyses, although this will lower disease-free survival.

A Phase II trial of axitinib in patients with various histologic subtypes of advanced thyroid cancer: long-term outcomes and pharmacokinetic/pharmacodynamic analyses.

PURPOSE: Axitinib, a potent and selective second-generation inhibitor of vascular endothelial growth factor receptors, has shown activity in advanced thyroid cancer in a Phase II study. We report updated overall survival and pharmacokinetic/pharmacodynamic (PK/PD) analyses from the study. METHODS: Patients (N = 60) with advanced thyroid cancer of any histology for whom iodine-131 ((131)I) failed to control the disease or (131)I was not appropriate therapy were administered axitinib 5 mg twice daily. Objective response rate (primary endpoint), duration of response, progression-free survival, overall survival, safety, and PK/PD relationships were assessed. RESULTS: Objective response rate was 38 % [23 partial responses; 95 % confidence interval (CI) 26-52], and 18 (30 %) patients had stable disease lasting ≥16 weeks. Responses occurred in all histologic subtypes. With median follow-up of 34 months (95 % CI 32-37), median overall survival was 35 months (95 % CI 19-not estimable), median progression-free survival was 15 months (95 % CI 10-20), and median duration of response was 21 months (95 % CI 13-46). Most common Grade 3/4 treatment-related adverse events included hypertension (13 %), proteinuria (8 %), diarrhea (7 %), weight decrease (7 %), and fatigue (5 %). PK/PD analyses revealed trends toward greater tumor size reduction and response probability with higher axitinib plasma exposures. CONCLUSIONS: Axitinib appears active and well tolerated in patients with various histologic subtypes of advanced thyroid cancer, demonstrating durable responses and long overall survival. Axitinib may be useful for the treatment of advanced thyroid cancer.

A comparison of smoothing techniques for CD4 data measured with error in a time-dependent Cox proportional hazards model.

The use of CD4+ T-lymphocyte counts as a covariate presents some unique challenges in survivorship analyses due to the variability of this marker. If one does not account for the measurement error component of this variability in some manner, the estimate of the relative risk parameter in a time-dependent Cox model is biased towards zero, and coverage levels of confidence intervals may be seriously incorrect. We use a two-stage approach to reduce the variability in the observed CD4 counts in order to obtain a more accurate estimate of the relative risk parameter and more valid summary statistics. In the first stage, population based smoothing methods derived from a random-effects model plus a stochastic process or individual based smoothing methods are used to replace the observed longitudinal CD4 counts with less variable imputes at each failure time. In the second stage, we use the imputes in a time-dependent Cox model to estimate the risk parameter and its associated summary statistics. We compare the smoothing methods in simulation studies and find that the use of these smoothing methods results in a substantial reduction in bias for the true risk parameter estimate, better efficiency, and more accurate coverage rates in confidence intervals. We apply our two-stage smoothing methods to the marker CD4 in the ACTG-019 clinical trial part B.

An evaluation of a measure of the proportion of the treatment effect explained by a surrogate marker.

Time-dependent markers, such as CD4 and viral load, are potential surrogate markers in AIDS clinical trials. A critical issue with surrogate markers is whether changes in these markers explain the beneficial effect of treatment on the real end point of the clinical trial. A statistic to measure the proportion of the treatment effect explained by the surrogate is p(FGS) = 1 - gamma/alpha, where alpha is the treatment effect coefficient in a Cox model and gamma is the treatment effect coefficient from a time-dependent Cox model adjusted for the marker. In this article we evaluate the statistical properties of p(FGS). Using a Monte Carlo study we show that the statistic is not well calibrated, because it can fall outside the range zero to one, even in very large samples. In the simulation study we consider situations where the time-dependent marker is measured with error at a fixed number of times. We show that a method of fitting a time-dependent Cox model involving smoothing the marker reduces the bias in the estimate of p(FGS) compared with the standard method of using the current or last observed marker value. We also show that the estimate of p(FGS) has considerable variability and can have wide confidence intervals. We conclude that p(FGS) is only likely to be useful in large trials with a strong treatment effect. The methods are illustrated using CD4 counts from an AIDS clinical trial of zidovidine versus placebo.