The Experts below are selected from a list of 102825 Experts worldwide ranked by ideXlab platform
Meinhard Kieser - One of the best experts on this subject based on the ideXlab platform.
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Enhancing single-arm Phase II Trials by inclusion of matched control patients
arXiv: Methodology, 2020Co-Authors: Johannes Krisam, Dorothea Weber, Richard F. Schlenk, Meinhard KieserAbstract:When a novel treatment has successfully passed Phase I, different options to design subsequent Phase II Trials are available. One approach is a single-arm trial, comparing the response rate in the intervention group against a fixed proportion. Another alternative is to conduct a randomized Phase II trial, comparing the new treatment with placebo or the current standard. A significant problem arises in both approaches when the investigated patient population is very heterogeneous regarding prognostic factors. For the situation that a substantial dataset of historical controls exists, we propose an approach to enhance the classic single-arm trial design by including matched control patients. The outcome of the observed study population can be adjusted based on the matched controls with a comparable distribution of known confounders. We propose an adaptive two-stage design with the options of early stopping for futility and recalculation of the sample size taking the matching rate, number of matching partners, and observed treatment effect into account. The performance of the proposed design in terms of type I error rate, power, and expected sample size is investigated via simulation studies based on a hypothetical Phase II trial investigating a novel therapy for patients with acute myeloid leukemia.
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Sample size planning for Phase II Trials based on success probabilities for Phase III.
Pharmaceutical statistics, 2015Co-Authors: Heiko Götte, Armin Schüler, Marietta Kirchner, Meinhard KieserAbstract:In recent years, high failure rates in Phase III Trials were observed. One of the main reasons is overoptimistic assumptions for the planning of Phase III resulting from limited Phase II information and/or unawareness of realistic success probabilities. We present an approach for planning a Phase II trial in a time-to-event setting that considers the whole Phase II/III clinical development programme. We derive stopping boundaries after Phase II that minimise the number of events under side conditions for the conditional probabilities of correct go/no-go decision after Phase II as well as the conditional success probabilities for Phase III. In addition, we give general recommendations for the choice of Phase II sample size. Our simulations show that unconditional probabilities of go/no-go decision as well as the unconditional success probabilities for Phase III are influenced by the number of events observed in Phase II. However, choosing more than 150 events in Phase II seems not necessary as the impact on these probabilities then becomes quite small. We recommend considering aspects like the number of compounds in Phase II and the resources available when determining the sample size. The lower the number of compounds and the lower the resources are for Phase III, the higher the investment for Phase II should be. Copyright © 2015 John Wiley & Sons, Ltd.
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Adaptive designs for single-arm Phase II Trials in oncology.
Pharmaceutical statistics, 2012Co-Authors: Stefan Englert, Meinhard KieserAbstract:Clinical Phase II Trials in oncology are conducted to determine whether the activity of a new anticancer treatment is promising enough to merit further investigation. Two-stage designs are commonly used for this situation to allow for early termination. Designs proposed in the literature so far have the common drawback that the sample sizes for the two stages have to be specified in the protocol and have to be adhered to strictly during the course of the trial. As a consequence, designs that allow a higher extent of flexibility are desirable. In this article, we propose a new adaptive method that allows an arbitrary modification of the sample size of the second stage using the results of the interim analysis or external information while controlling the type I error rate. If the sample size is not changed during the trial, the proposed design shows very similar characteristics to the optimal two-stage design proposed by Chang et al. (Biometrics 1987; 43:865-874). However, the new design allows the use of mid-course information for the planning of the second stage, thus meeting practical requirements when performing clinical Phase II Trials in oncology.
Edward L Korn - One of the best experts on this subject based on the ideXlab platform.
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Single-Arm Phase II Trials of Combination Therapies: A Review of the CTEP Experience 2008-2017.
Journal of the National Cancer Institute, 2019Co-Authors: Jared C. Foster, Boris Freidlin, Charles A Kunos, Edward L KornAbstract:Designing and interpreting single-arm Phase II Trials of combinations of agents is challenging because it can be difficult, based on historical data, to identify levels of activity for which the combination would be worth pursuing. We identified Cancer Therapy Evaluation Program single-arm combination Trials that were activated in 2008-2017 and tabulated their design characteristics and results. Positive Trials were evaluated as to whether they provided credible evidence that the combination was better than its constituents. A total of 125 Trials were identified, and 120 Trials had results available. Twelve had designs where eligible patients were required to be resistant or refractory to all but one element of the combination. Only 17.8% of the 45 positive Trials were deemed to provide credible evidence that the combination was better than its constituents. Of the 10 positive Trials with observed rates 10 percentage points higher than their upper (alternative hypothesis) targets, only five were deemed to provide such credible evidence. Many Trials were definitively negative, with observed clinical activity at or below their lower (null hypothesis) targets. Ideally, use of single-arm combination Trials should be restricted to settings where each agent is known to have minimal monotherapy activity (and a randomized trial is infeasible). In these settings, an observed signal is attributable to synergy and thus could be used to decide whether the combination is worth pursuing. In other settings, credible evidence can still be obtained if the observed activity is much higher than expected, but experience suggests that this is a rare occurrence.
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borrowing information across subgroups in Phase II Trials is it useful
Clinical Cancer Research, 2013Co-Authors: Boris Freidlin, Edward L KornAbstract:Because of the heterogeneity of human tumors, cancer patient populations are usually composed of multiple subgroups with different molecular and/or histologic characteristics. In screening new anticancer agents, there might be a scientific rationale to expect some degree of similarity in clinical activity across the subgroups. This poses a challenge to the design of Phase II Trials assessing clinical activity: Conducting an independent evaluation in each subgroup requires considerable time and resources, whereas a pooled evaluation that completely ignores patient heterogeneity can miss treatments that are only active in some subgroups. It has been suggested that approaches that borrow information across subgroups can improve efficiency in this setting. In particular, the hierarchical Bayesian approach putatively uses the outcome data to decide whether borrowing of information is appropriate. We evaluated potential benefits of the hierarchical Bayesian approach (using models suggested previously) and a simpler pooling approach by simulations. In the Phase II setting, the hierarchical Bayesian approach is shown not to work well in the simulations considered, as there appears to be insufficient information in the outcome data to determine whether borrowing across subgroups is appropriate. When there is strong rationale for expecting a uniform level of activity across the subgroups, approaches using simple pooling of information across subgroups may be useful. Clin Cancer Res; 19(6); 1326–34. ©2012 AACR .
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meta analysis of Phase II cooperative group Trials in metastatic stage iv melanoma to determine progression free and overall survival benchmarks for future Phase II Trials
Journal of Clinical Oncology, 2008Co-Authors: Edward L Korn, Judith Anne W Chapman, Donna Niedzwiecki, Vera J Suman, James J Moon, Vernon K Sondak, Michael B Atkins, Elizabeth A Eisenhauer, Wendy R Parulekar, Svetomir N MarkovicAbstract:Purpose Objective tumor response rates observed in Phase II Trials for metastatic melanoma have historically not provided a reliable indicator of meaningful survival benefits. To facilitate using overall survival (OS) or progression-free survival (PFS) as an endpoint for future Phase II Trials, we evaluated historical data from cooperative group Phase II Trials to attempt to develop benchmarks for OS and PFS as reference points for future Phase II Trials. Patients and Methods Individual-level and trial-level data were obtained for patients enrolled onto 42 Phase II Trials (70 trial arms) that completed accrual in the years 1975 through 2005 and conducted by Southwest Oncology Group, Eastern Cooperative Oncology Group, Cancer and Leukemia Group B, North Central Cancer Treatment Group, and the Clinical Trials Group of the National Cancer Institute of Canada. Univariate and multivariate analyses were performed to identify prognostic variables, and between-trial(-arm) variability in 1-year OS rates and 6-month PFS rates were examined. Results Statistically significant individual-level and trial-level prognostic factors found in a multivariate survival analysis for OS were performance status, presence of visceral disease, sex, and whether the trial excluded patients with brain metastases. Performance status, sex, and age were statistically significant prognostic factors for PFS. Controlling for these prognostic variables essentially eliminated between-trial variability in 1-year OS rates but not in 6-month PFS rates. Conclusion Benchmarks are provided for 1-year OS or OS curves that make use of the distribution of prognostic factors of the patients in the Phase II trial. A similar benchmark for 6-month PFS is provided, but its use is more problematic because of residual between-trial variation in this endpoint.
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design issues of randomized Phase II Trials and a proposal for Phase II screening Trials
Journal of Clinical Oncology, 2005Co-Authors: Larry Rubinstein, Sally Hunsberger, Edward L Korn, Boris Freidlin, Percy S Ivy, Malcolm A. SmithAbstract:Future progress in improving cancer therapy can be expedited by better prioritization of new treatments for Phase III evaluation. Historically, Phase II Trials have been key components in the prioritization process. There has been a long-standing interest in using Phase II Trials with randomization against a standard-treatment control arm or an additional experimental arm to provide greater assurance than afforded by comparison to historic controls that the new agent or regimen is promising and warrants further evaluation. Relevant trial designs that have been developed and utilized include Phase II selection designs, randomized Phase II designs that include a reference standard-treatment control arm, and Phase II/III designs. We present our own explorations into the possibilities of developing “Phase II screening Trials,” in which preliminary and nondefinitive randomized comparisons of experimental regimens to standard treatments are made (preferably using an intermediate end point) by carefully adjusting the false-positive error rates ( or type I error) and false-negative error rates ( or type II error), so that the targeted treatment benefit may be appropriate while the sample size remains restricted. If the ability to conduct a definitive Phase III trial can be protected, and if investigators feel that by judicious choice of false-positive probability and falsenegative probability and magnitude of targeted treatment effect they can appropriately balance the conflicting demands of screening out useless regimens versus reliably detecting useful ones, the Phase II screening trial design may be appropriate to apply. J Clin Oncol 23:7199-7206.
A Tanovic - One of the best experts on this subject based on the ideXlab platform.
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trabectedin is a feasible treatment for soft tissue sarcoma patients regardless of patient age a retrospective pooled analysis of five Phase II Trials
British Journal of Cancer, 2013Co-Authors: Axel Le Cesne, I Judson, Robert G Maki, Federica Grosso, Scott M Schuetze, Margaret Von Mehren, S P Chawla, George D Demetri, Antonio Nieto, A TanovicAbstract:Background: This retrospective pooled analysis assessed the effect of age on the efficacy and safety of trabectedin in young and elderly patients with recurrent advanced soft tissue sarcoma (STS). Methods: Data from 350 adults with STS treated in five Phase II Trials with trabectedin were divided in the younger ( = 60 years; n = 83). Results: The response rate did not differ with age (younger: 10.1% vs elderly 9.6%). No significant differences were found in median progression-free survival (PFS) in younger (2.5 months) and older (3.7 months) cohort with a comparable PFS rates at 3 (45.1% vs 55.1%) and 6 months (29.5% vs 36.4%). Similar median overall survival was observed in both cohorts (13.0 vs 14.0 months). Reversible neutropenia and aspartate aminotransferase/alanine aminotransferase elevation were the most common abnormalities. A higher incidence of grade 3/4 neutropenia (43.6% vs 60.2%) and fatigue (6.3% vs 14.4%) was observed in older patients. In 24 patients aged >= 70 years, no significant differences in efficacy or safety outcomes were found. Conclusion: This analysis demonstrated that trabectedin is a feasible treatment in young and elderly patients with STS, with meaningful clinical benefits and an acceptable safety profile, essential in palliative treatment of elderly patients.
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Trabectedin is a feasible treatment for soft tissue sarcoma patients regardless of patient age: a retrospective pooled analysis of five Phase II Trials
British Journal of Cancer, 2013Co-Authors: Axel Le Cesne, I Judson, Federica Grosso, Scott M Schuetze, S P Chawla, George D Demetri, Antonio Nieto, R Maki, M V Mehren, A TanovicAbstract:Background: This retrospective pooled analysis assessed the effect of age on the efficacy and safety of trabectedin in young and elderly patients with recurrent advanced soft tissue sarcoma (STS). Methods: Data from 350 adults with STS treated in five Phase II Trials with trabectedin were divided in the younger ( < 60 years; n =267) and the older cohort (⩾60 years; n =83). Results: The response rate did not differ with age (younger: 10.1% vs elderly 9.6%). No significant differences were found in median progression-free survival (PFS) in younger (2.5 months) and older (3.7 months) cohort with a comparable PFS rates at 3 (45.1% vs 55.1%) and 6 months (29.5% vs 36.4%). Similar median overall survival was observed in both cohorts (13.0 vs 14.0 months). Reversible neutropenia and aspartate aminotransferase/alanine aminotransferase elevation were the most common abnormalities. A higher incidence of grade 3/4 neutropenia (43.6% vs 60.2%) and fatigue (6.3% vs 14.4%) was observed in older patients. In 24 patients aged ⩾70 years, no significant differences in efficacy or safety outcomes were found. Conclusion: This analysis demonstrated that trabectedin is a feasible treatment in young and elderly patients with STS, with meaningful clinical benefits and an acceptable safety profile, essential in palliative treatment of elderly patients.
Nigel Stallard - One of the best experts on this subject based on the ideXlab platform.
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A series of decision-theoretic Phase II Trials of related treatments
Trials, 2013Co-Authors: Siew Wan Hee, Nicholas R. Parsons, Matthew L. Costa, Nigel StallardAbstract:It is not uncommon for a pharmaceutical company to develop several new drugs simultaneously for the same indication. In a small population it may be infeasible to try all new drugs concurrently. A practical approach is to consider one at a time and if the drug is recommended for a Phase III trial to temporarily suspend development of other drugs. We propose a development plan that encompasses Phase II and III Trials, considering a series of sequential Phase II Trials with interim decision-making. At each stage of a Phase II trial, a decision is made whether to continue with participant recruitment to the current trial, stop the current trial and recommend the drug to be tried in a Phase III trial, stop the current trial and initiate a new Phase II trial with a different drug or stop the current trial and abandon the development. The unknown treatment effect for each drug is assumed to follow a prior distribution. In addition, as drugs are intended for the same population it is not unrealistic to consider treatment effects to be correlated, so that the prior distribution will reflect this. As data are observed from preceding and current Trials, prior densities for subsequent drugs are updated, informing us of the performance of the groups of drugs under evaluation. The application of the design is illustrated in the setting of severe arthritis of the hip Trials.
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Designing a series of decision‐theoretic Phase II Trials in a small population
Statistics in medicine, 2012Co-Authors: Siew Wan Hee, Nigel StallardAbstract:This paper introduces a decision-theoretic design for a series of Phase II Trials. Instead of designing Phase II Trials individually, we proposed a development plan that consists of a series of Phase II Trials and one Phase III trial such that the long-term expected utility on the whole is optimized. The Phase II Trials are conducted sequentially, and patients are recruited sequentially to each Phase II trial. At each interim stage, a decision is made to continue recruiting patients to the current trial, to stop and recommend the treatment proceeds to a Phase III trial, to stop and initiate a new Phase II trial or to stop and cease the development plan. The methodology uses a hybrid approach in which it is assumed that the data from the final Phase III trial will be analysed using a classical frequentist hypothesis test. The expected power of this test based on some specified prior distribution for the effect of the experimental treatment is then used in a utility function, which is used to obtain the optimal design for the whole series of Trials. Copyright © 2012 John Wiley & Sons, Ltd.
Axel Le Cesne - One of the best experts on this subject based on the ideXlab platform.
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trabectedin is a feasible treatment for soft tissue sarcoma patients regardless of patient age a retrospective pooled analysis of five Phase II Trials
British Journal of Cancer, 2013Co-Authors: Axel Le Cesne, I Judson, Robert G Maki, Federica Grosso, Scott M Schuetze, Margaret Von Mehren, S P Chawla, George D Demetri, Antonio Nieto, A TanovicAbstract:Background: This retrospective pooled analysis assessed the effect of age on the efficacy and safety of trabectedin in young and elderly patients with recurrent advanced soft tissue sarcoma (STS). Methods: Data from 350 adults with STS treated in five Phase II Trials with trabectedin were divided in the younger ( = 60 years; n = 83). Results: The response rate did not differ with age (younger: 10.1% vs elderly 9.6%). No significant differences were found in median progression-free survival (PFS) in younger (2.5 months) and older (3.7 months) cohort with a comparable PFS rates at 3 (45.1% vs 55.1%) and 6 months (29.5% vs 36.4%). Similar median overall survival was observed in both cohorts (13.0 vs 14.0 months). Reversible neutropenia and aspartate aminotransferase/alanine aminotransferase elevation were the most common abnormalities. A higher incidence of grade 3/4 neutropenia (43.6% vs 60.2%) and fatigue (6.3% vs 14.4%) was observed in older patients. In 24 patients aged >= 70 years, no significant differences in efficacy or safety outcomes were found. Conclusion: This analysis demonstrated that trabectedin is a feasible treatment in young and elderly patients with STS, with meaningful clinical benefits and an acceptable safety profile, essential in palliative treatment of elderly patients.
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Trabectedin is a feasible treatment for soft tissue sarcoma patients regardless of patient age: a retrospective pooled analysis of five Phase II Trials
British Journal of Cancer, 2013Co-Authors: Axel Le Cesne, I Judson, Federica Grosso, Scott M Schuetze, S P Chawla, George D Demetri, Antonio Nieto, R Maki, M V Mehren, A TanovicAbstract:Background: This retrospective pooled analysis assessed the effect of age on the efficacy and safety of trabectedin in young and elderly patients with recurrent advanced soft tissue sarcoma (STS). Methods: Data from 350 adults with STS treated in five Phase II Trials with trabectedin were divided in the younger ( < 60 years; n =267) and the older cohort (⩾60 years; n =83). Results: The response rate did not differ with age (younger: 10.1% vs elderly 9.6%). No significant differences were found in median progression-free survival (PFS) in younger (2.5 months) and older (3.7 months) cohort with a comparable PFS rates at 3 (45.1% vs 55.1%) and 6 months (29.5% vs 36.4%). Similar median overall survival was observed in both cohorts (13.0 vs 14.0 months). Reversible neutropenia and aspartate aminotransferase/alanine aminotransferase elevation were the most common abnormalities. A higher incidence of grade 3/4 neutropenia (43.6% vs 60.2%) and fatigue (6.3% vs 14.4%) was observed in older patients. In 24 patients aged ⩾70 years, no significant differences in efficacy or safety outcomes were found. Conclusion: This analysis demonstrated that trabectedin is a feasible treatment in young and elderly patients with STS, with meaningful clinical benefits and an acceptable safety profile, essential in palliative treatment of elderly patients.
