Success stories

The following success stories demonstrate how IDDI innovative Biostatistics and eClinical solutions are key in the successful conduct and outcome of your clinical trials.

Meta-Analysis To Assess Efficacy in Colorectal Cancer

Success stories

Meta-AnalysisIn this meta-analysis, tumor responses and survival were analyzed combining the data from the different trials using patient individual data. The statistical methodology was based on the classical notion of stratification, consisting of estimating a treatment effect within each trial, and then overall. A statistic for heterogeneity between the trials was calculated. A test of overall treatment effect was calculated. The following quantities were used in the calculation: O, which is the number of untoward events observed in the treatment group, E, which is the number of events that would be expected in the treatment group if there were no differences between treatment and control; and V, the variance of the number of events. Those data were shown graphically in a forest plot.

Applying Likelihood Method For Data Safety Monitoring

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Data Safety Monitoring

Data safety monitoringFormal data safety monitoring, often performed by independent committees of physicians, biostatisticians and ethicists, has become common in modern clinical trials. Safety monitoring often includes reading of many pages of tabulated adverse events classified by body system, type and severity. Monitors look for within treatment incidence and between treatment differences in incidence that may be of concern. Frequentist statistical methodology is not appropriate for this type of surveillance due to multiplicity issues and the inappropriateness of the background repeated sampling assumption. A safety monitoring committee in an international ophthalmology clinical trial used the principle of support and support intervals based on the log likelihood function for incidence parameter conditional on the data at hand. Rates were calculated as poisson random variables and support methods were used for both incidence and treatment differences.

Validation of a Genetic Signature For Women With Node-Negative Breast Cancer

Success stories

genetic signatureA 70-genetic signature was shown in a single institution to have prognostic value in patients with node-negative breast cancer. The purpose of this study was to validate this signature in independent patient samples. Hazard ratios were estimated by IDDI’s methodology group of experts, to compare rates in high versus low risk groups for the time related endpoints. The models were or not stratified by a clinicpathological risk group to verify if the gene signature adds independent prognostic information to clinic-pathological risk factor.

Validating Adverse Events On A Large Scale

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Adverse Events coded by IDDI Medical Coding System

Adverse eventsTwo pivotal trials were conducted (one in the US, one in Europe) to seek approval of a new treatment for a chronic condition in elderly patients. The safety of the new drug was of particular concern. Adverse events and medications were coded by IDDI using proprietary coding system ID-code, based on the standard MedDRA and WHO-drug dictionaries. More importantly, the large volume of over 36,000 coded terms could easily be validated by the Sponsor using real-time, web-based technology. This cut the time required by several months, and the budget by almost half a million dollars.

Jumping Ahead to Phase III trial

Success stories

FDA ApprovalA new ophthalmic drug was going to enter a phase II dose-ranging trial in order to determine the dose to use in phase III trials. IDDI proposed to jump ahead and test a dose-effect hypothesis in two pivotal phase III trials, using appropriate statistical methodology to adjust for multiple testing (simulations showed a step-up procedure to be slightly preferable to a closed-test procedure). Although the two trials were far larger than if a single dose had been used, this bold approach resulted in a gain of at least one year of clinical development. The drug has received FDA approval (Food and Drug Administration).

Analyzing a Biomarker As A Proof Of Concept

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Biomarker Analysis with the Mixed Modelling Methodology

BiomarkerTwo doses of a therapeutic vaccine were tested simultaneously in a randomized phase II trial. While the trial’s primary endpoint was not sensitive enough to show efficacy of either dose or any difference between the two, using the advanced statistical methodology of mixed modelling on repeated measures, it was found that the high dose had a highly significant effect on a relevant biomarker, while the low dose had no such effect. This proof of concept allowed the sponsor to raise additional funding to support further trials.

Meta-Analysis of Clinical Trials to Support New Drug Approval

Success stories

Meta-Analysis performed with IDDI’s Methodology Skills

Meta-analysesIDDI has been involved in numerous meta-analyses to directly or indirectly support new drug applications. The purpose of these meta-analysis was to combine evidence from several trials in order to confirm efficacy and/or safety of a new drug; to explore different endpoints; to validate earlier endpoints as surrogates for later endpoints; and to look at meaningful subsets reliably (Buyse M. Contributions of meta-analyses based on individual patient data to therapeutic progress in colorectal cancer. Int J Clin Oncol 14: 95-101, 2009; Buyse M. Use of meta-analysis for the validation of surrogate endpoints and biomarkers in cancer trials. Cancer J 15: 421-5, 2009).

Recently published meta-analysis performed with IDDI’s methodology skills have ranged over an array of therapeutic areas including solid tumors (The GASTRIC (Global Advanced/Adjuvant Stomach Tumor Research International Collaboration) Group. Benefit of adjuvant chemotherapy for resectable gastric cancer: a meta-analysis. J Am Med Assoc 303:1729-1737, 2010) as well as hematologic malignancies (Buyse M, Squifflet P, Lange BJ,
Alonzo T, Larson RA, KolitzJE, George SL, Bloomfield CD, Castaigne S, Chevret S, Blaise D, Lucchesi KJ, Burzykowski T. Individual patient data meta-analysis of randomized trials evaluating interleukin-2 monotherapy as remission maintenance therapy in acute myeloid leukemia. Blood 2011

Anti-cancer drug approved based on a surrogate endpoint

Success stories

Surrogate endpoint for overall survival

surrogate endpointWe managed to prove, using data from a randomized trial comparing Ceplene + IL-2 to no maintenance treatment, that leukemia free survival was a good surrogate endpoint for overall survival in patients in complete remission (Haematologica 2011). We also showed through meta-analysis that IL-2 alone was not better than no maintenance treatment in this patient population (Blood 2011). These facts resulted in the approval of Ceplene (from Epicept, then taken over by MEDA).

Using Minimization for a Complex Trial Design

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A multi-center phase II trial was conducted in just over 100 patients to compare metabolic changes in the prostate after administration of two treatments for locally advanced prostate cancer. The changes of interest were assessed by a biopsy taken at different randomized times and by magnetic resonance spectroscopy/magnetic resonance imaging (MRS/MRI) in about one third of randomly selected patients. In order to protect against chance imbalances, patients were additionally stratified by their level of prostate-specific antigen (PSA) at baseline. The methodology adopted to implement this complex trial design was minimization for the various randomized factors.