On a class of optimal covariate-adjusted response adaptive designs for survival outcomes

2016 ◽  
Vol 25 (6) ◽  
pp. 2444-2456 ◽  
Author(s):  
Atanu Biswas ◽  
Rahul Bhattacharya ◽  
Eunsik Park
Keyword(s):  
Treatment Effectiveness ◽  
Real Data ◽  
Phase Iii ◽  
Data Set ◽  
Phase Iii Clinical Trials ◽  
Covariate Information ◽  
Adaptive Procedures ◽  
Statistical Precision ◽  
Response Adaptive Designs ◽  
Ethical Requirement

A class of optimal covariate-adjusted response adaptive procedures is developed for phase III clinical trials when the treatment response is a survival time and there is random censoring. The basic aim is to develop an allocation design by combining the ethical aspects with statistical precision in a reasonable way under the presence of covariate information. Considering minimisation of total hazards as the ethical requirement, the proposed procedure is assessed in terms of the assignment to the better treatment and the efficiency (i.e. power) to detect a small departure in treatment effectiveness. The applicability of the proposed methodology is also illustrated using a real data set.

Bayesian optimal response-adaptive design for binary responses using stopping rule

2016 ◽  
Vol 27 (3) ◽  
pp. 891-904 ◽  
Author(s):  
Fumiyasu Komaki ◽  
Atanu Biswas
Keyword(s):  
Clinical Trials ◽  
Adaptive Design ◽  
Real Data ◽  
Adaptive Designs ◽  
Phase Iii ◽  
Data Set ◽  
Binary Responses ◽  
Phase Iii Clinical Trials ◽  
Number Of Patients ◽  
Response Adaptive Designs

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

SNP Associations with Event Free Survival in Myeloma from Two Phase III Clinical Trials Using the Bank On A Cure Chip.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 131-131
Author(s):  
Brian G. Van Ness ◽  
John C. Crowley ◽  
Christine Ramos ◽  
Suzanne M. Grindle ◽  
Antje Hoering ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Genetic Variations ◽  
Gene Set Enrichment Analysis ◽  
Phase Iii ◽  
Survival Outcomes ◽  
Cellular Functions ◽  
Two Phase ◽  
Data Set ◽  
Phase Iii Clinical Trials ◽  
Statistical Approaches

Abstract While there are certain common clinical features in myeloma, the disease shows significant heterogeneity with regard to disease progression, and responses to therapy, affecting both survival and toxicities. Heritable variations in a wide variety of genes and pathways affecting cellular functions and drug responses likely impact patient outcomes. In the Bank On A Cure (BOAC) program we have developed a custom chip that assesses 3,404 SNPs representing variations in cellular functions and pathways that may be involved in myeloma progression and response. The chip has gone through rigorous quality controls checks for high call rates, accuracy, and reproducibility that will be presented. Using the BOAC chip, we have conducted studies to look for SNPs that may identify biologic variations that are associated with good or poor response across a variety of treatments. In this study we looked for SNPs that may distinguish short term and long term survivors in two phase III clinical trials: ECOG E9486 and intergroup trial S9321. E9487 patients were treated with VBMCP followed by randomization to no further treatment, IFN-alpha, or cylcophosphamide; and, although there was variation in survival, no significant differences in survival were noted among the 3 arms of the trial. Patients included in this SNP study from S9321 received VAD induction followed by randomization to VBMCP or high dose melphalan + TBI. SNP profiles were obtained for patients with less than 1 year EFS (n=20 in E9487; n=50 in S9321) and patients showing greater than 3 years EFS (n=32 in E9486; n=41 in S9321). Statistical approaches were performed to identify single and groups of SNPs that best discriminated the survival groups. Previous studies have suggested genetic variations in drug metabolism genes, p-glycoprotein transport, and DNA repair genes may influence survival outcomes. Our results show significant survival associations of genetic variations in genes within these functional categories (eg. GST, XRCC, ABCB, and CYP genes). Although genetic variations were found that were uniquely associated with each clinical trial, several of these genetic variations show survival associations that increase in significance when the two trials were examined as a conglomerate data set. Grouping genetic variations through common pathway approaches using gene set enrichment analysis, as well as clustering or partitioning algorithms, further improve the value of the SNPs as potential prognostic markers of survival outcomes. These results and statistical approaches will be presented, and represent steps toward identifying patient variations in biologic mechanisms important in predicting therapeutic outcomes.

Validating the use of brain volume cutoffs to identify clinically relevant atrophy in RRMS

2017 ◽  
Vol 25 (2) ◽  
pp. 217-223 ◽  
Author(s):  
Francesca Bovis ◽  
Nicola De Stefano ◽  
Joshua R Steinerman ◽  
Volker Knappertz ◽  
Maria Pia Sormani
Keyword(s):  
Brain Volume ◽  
Phase Iii ◽  
Prognostic Impact ◽  
Two Phase ◽  
Data Set ◽  
Phase Iii Clinical Trials ◽  
Hazard Ratios ◽  
Baseline Variable ◽  
The Difference ◽  
Relapsing Remitting Multiple Sclerosis

Background: Baseline brain volume (BV) is predictive at a group level but is difficult to interpret at the single patient level. Objective: To validate BV cutoffs able to identify clinically relevant atrophy in relapsing–remitting multiple sclerosis (RRMS) patients. Methods: The expected normalized brain volume (NBV) for each patient was calculated using RRMS patients from two phase III clinical trials, applying a linear formula developed on the baseline variable of an independent data set. The difference between these expected NBV values and those actually observed was calculated and used to categorize the patients in the low-NBV, medium-NBV, and high-NBV groups. Results: The 2-year probability of 3-month confirmed disability worsening was significantly associated with the NBV categorization ( p = 0.006), after adjusting for treatment effect. Taking the high-NBV group as a reference, the hazard ratios for the medium-NBV and low-NBV groups were 1.22 (95% confidence interval (CI): 0.85–1.76, p = 0.27) and 1.69 (95% CI: 1.11–2.57, p = 0.01), respectively. Conclusion: This study validates the use of BV cutoffs to identify clinically relevant atrophy in RRMS study by showing that the three groups classified according to the baseline NBV adjusted for the other prognostic variables have a significant prognostic impact on the risk of disability progression.

scholarly journals Determination of Isavuconazole Susceptibility of Aspergillus and Candida Species by the EUCAST Method

2013 ◽  
Vol 57 (11) ◽  
pp. 5426-5431 ◽  
Author(s):  
Susan J. Howard ◽  
Cornelia Lass-Flörl ◽  
Manuel Cuenca-Estrella ◽  
Alicia Gomez-Lopez ◽  
Maiken C. Arendrup
Keyword(s):  
Aspergillus Fumigatus ◽  
Clinical Care ◽  
Clinical Isolates ◽  
Phase Iii ◽  
Data Sets ◽  
Wild Type ◽  
Data Set ◽  
Content Type ◽  
Phase Iii Clinical Trials ◽  
In The Wild

ABSTRACTIsavuconazole is a novel expanded-spectrum triazole, which has recently been approved by the FDA as an orphan drug to treat invasive aspergillosis and is currently being studied in phase III clinical trials for invasive candidiasis. The susceptibility of relatively few clinical isolates has been reported. In this study, the isavuconazole susceptibilities of 1,237Aspergillusand 2,010Candidageographically diverse clinical isolates were determined by EUCAST methodology at four European mycology laboratories, producing the largest multicenter data set thus far for this compound. In addition, a blinded collection of 30cyp51AmutantAspergillus fumigatusclinical isolates and 10 wild-type isolates was tested. From these two data sets, the following preliminary epidemiological cutoff (ECOFF) values were suggested: 2 mg/liter forAspergillus fumigatus,Aspergillus terreus, andAspergillus flavus; 4 mg/liter forAspergillus niger; 0.25 mg/liter forAspergillus nidulans; and 0.03 mg/liter forCandida albicans,Candida parapsilosis, andCandida tropicalis. Unfortunately, ECOFFs could not be determined forCandida glabrataorCandida kruseidue to an unexplained interlaboratory MIC variation. For the blinded collection ofA. fumigatusisolates, all MICs were ≤2 mg/liter for wild-type isolates. Differential isavuconazole MICs were observed for triazole-resistantA. fumigatusisolates with differentcyp51Aalterations: TR34/L98H mutants had elevated isavuconazole MICs, whereas isolates with G54 and M220 alterations had MICs in the wild-type range, suggesting that the efficacy of isavuconazole may not be affected by these alterations. This study will be an aid in interpreting isavuconazole MICs for clinical care and an important step in the future process of setting official clinical breakpoints.

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