Predicting the Outcome of Phase III Trials using Phase II Data: A Case Study of Clinical Trial Simulation in Late Stage Drug Development

2520 Background: Clinical trials are increasingly funded by industry. High costs of drug development may lead to attempts to develop new drugs in more ‘profitable’ (i.e., more prevalent) as compared to ‘less profitable’ (i.e., more deadly) cancers. Here we determine the focus of current global drug development. Methods: We determined characteristics of phase II and III clinical trials evaluating new drugs in oncology, which were registered with WHO International Clinical Trial Registries between 01/2008 and 06/2008. Estimates of incidence, mortality, and prevalence in the more- and less-developed world (MDW, LDW) were obtained from GLOBOCAN 2002. Simple correlation analysis was performed between the number of clinical trials and incidence, mortality and prevalence per cancer site after log transformation of variables. Results: We identified 399 newly registered trials. Of 374 trials with information about recruitment, 322 (86.1%) and 39 (10.4%) recruited patients only from the MDW and LDW, respectively, while 13 (3.5%) had worldwide recruitment. 229 (58%) of trials were sponsored by industry and 324 trials were phase II (81%). Most trials (and most phase III trials) evaluated treatments for globally prevalent cancers: breast, lung, prostate, and colorectal cancer (Table). Prevalence of a particular cancer type in both the MDW and LDW correlated significantly with the number of clinical trials (Pearson r = 0.63 and 0.55; p = 0.01 and 0.03, respectively). In contrast, mortality in the MDW (Pearson r = 0.73; p= 0.002), but not in the LDW (Pearson r = 0.38; p= 0.17), correlated significantly with the number of clinical trials. Conclusions: Global drug development in cancer predominates in globally prevalent cancers, which are a more important cause of mortality in the MDW than in the LDW. Cancer sites that are major killers globally, and especially in the LDW (e.g., stomach, liver, and esophageal cancer) should receive priority for clinical research. [Table: see text] No significant financial relationships to disclose.

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Role of Sensitivity Analyses in Assessing Progression-Free Survival in Late-Stage Oncology Trials

Journal of Clinical Oncology ◽

10.1200/jco.2009.22.4329 ◽

2009 ◽

Vol 27 (35) ◽

pp. 5958-5964 ◽

Cited By ~ 28

Author(s):

Suman Bhattacharya ◽

Gwen Fyfe ◽

Robert J. Gray ◽

Daniel J. Sargent

Keyword(s):

Clinical Trial ◽

Late Stage ◽

Progression Free Survival ◽

Phase Iii ◽

Sensitivity Analyses ◽

Potential Bias ◽

Primary Analysis ◽

Free Survival ◽

End Point ◽

Phase Iii Trials

Sensitivity analysis is an important statistical technique that assesses whether the results of phase III trials are robust and likely to be generalizable. Until recently, sensitivity analyses were rarely included in phase III trials, and they remain poorly understood by many oncologists. Sensitivity analyses are critical to understanding the strength of conclusions made in the primary analysis of a late-stage clinical trial. They examine the influence of protocol design errors, unintended biases, deviations from assumptions underlying statistical models, and any unanticipated treatment delivery or practice patterns on trial results. In trials with complex or subjective end points, they also allow an understanding of the extent to which a positive outcome is driven by a single, possibly subjective, and therefore biased, element of an end point. The purposes of this article are to explain how sensitivity analyses are performed, to discuss areas of a clinical trial where sensitivity analyses should focus, and to illuminate the importance of this technique in the rigorous evaluation of late-stage clinical trial data, using specific examples. This article focuses on late-stage trials that use progression-free survival or time to progression as their primary end point, because sensitivity analyses are particularly important in these cases for which the end point is potentially subject to bias. Three sources of potential bias are explored: assessment time, symptomatic (ie, nonradiologic) disease progression, and missing data. For each source of potential bias, case studies are presented to highlight the role that sensitivity analyses play in determining whether the trial's conclusions are robust.

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Stratification, Hypothesis Testing, and Clinical Trial Simulation in Pediatric Drug Development

Therapeutic Innovation & Regulatory Science ◽

10.1177/2168479016651661 ◽

2016 ◽

Vol 50 (6) ◽

pp. 817-822 ◽

Cited By ~ 2

Author(s):

Ann W. McMahon ◽

Kevin Watt ◽

Jian Wang ◽

Dionna Green ◽

Ram Tiwari ◽

...

Keyword(s):

Clinical Trial ◽

Drug Development ◽

Hypothesis Testing ◽

Clinical Trial Simulation ◽

Pediatric Drug ◽

Pediatric Drug Development ◽

Trial Simulation

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Clinical trial risk reduction in non-small cell lung cancer though the use of biomarkers and receptor-targeted therapies.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.8040 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 8040-8040

Author(s):

Adam Falconi ◽

Gilberto Lopes ◽

Jayson L. Parker

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Drug Development ◽

Phase I ◽

Success Rate ◽

Targeted Therapies ◽

Phase Iii ◽

Clinical Testing ◽

Phase Ii Trials ◽

Phase Iii Trials

8040 Background: We analyzed the risk of clinical trial failure duringnon-small cell lung cancer (NSCLC) drug development between 1998 and 2012. Methods: NSCLC drug development was investigated using trial disclosures from publically available resources. Compounds were excluded from the analysis if they began phase I clinical testing before 1998 and if they did not use treatment relevant endpoints. Analysis was conducted in regards to treatment indication, compound classification and mechanism of action. Costs of clinical drug development for advanced NSCLC were calculated using industry data and assumptions, a 9% yearly discount rate and assuming a clinical trial length of 2.5 years for phase I trials, 4 years for phase II trials, 5 years for phase III trials and an average of 5 phase I trials, 7 phase II trials, and 4 phase III trials per approved drug. All funding costs are in US dollars (USD). Results: 2,407 clinical trials met search criteria. 676 trials and 199 unique compounds met our inclusion criteria. The likelihood, or cumulative clinical trial success rate, that a new drug would pass all phases of clinical testing and be approved was found to be 11%, which is less than the expected industry aggregate rates (16.5%). The success of phase III trials was found to be the biggest obstacle for drug approval with a success rate of only 28%. Biomarker-guided targeted therapies (with a success rate of 62%) and receptor targeted therapies (with a success rate of 31%) were found to have the highest likelihood of success in clinical trials. The risk-adjusted cost for NSCLC clinical drug development was calculated to be 1.89 billion US dollars. Use of biomarkers decreased drug development cost by 26% to 1.4 billion US dollars. Potential savings may be even higher if fewer clinical trials are required for successful development. Conclusions: Physicians that enroll patients in NSCLC trials should prioritize their participation in clinical trial programs that involve either a biomarker or receptor targeted therapy, which appear to carry the best chances for a successful treatment response. Given the high adjusted cost of clinical testing alone in NSCLC, efforts to mitigate the risk of trial failure need to explore these factors more fully.

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Strategic inclusion of regions in multiregional clinical trials

Clinical Trials ◽

10.1177/1740774518813573 ◽

2018 ◽

Vol 16 (1) ◽

pp. 98-105

Author(s):

Seung Yeon Song ◽

Deborah Chee ◽

EunYoung Kim

Keyword(s):

Clinical Trial ◽

Clinical Trials ◽

Phase I ◽

Phase Ii ◽

Phase Iii ◽

Local Study ◽

International Conference ◽

Trial Conduct ◽

Increasing Trend ◽

Phase Iii Trials

Background With the recent publication of the International Conference on Harmonisation E17 guideline and major reforms in China underway, the platform for clinical trial conduct is expected to change. This study aims to assess the strategic inclusion of regions in clinical trials and its change in trends over the past decade. Methods The ClinicalTrials.gov registry was searched for clinical trials registered by the top 10 pharmaceutical companies between 1 January 2008 and 31 December 2017. Extracted data included phase, disease type, intervention, study start year, and region. Trial type was classified as either a local study or a multiregional clinical trial as per the International Conference on Harmonisation E17 guideline. Results Of 2488 phase I, 1855 phase II, and 1999 phase III trials included, the majority of phase I trials were local studies (76.8%), while the majority of phase II (66.0%) and phase III (72.2%) trials were multiregional clinical trials. The proportion of multiregional clinical trials showed an increasing trend for all phases ( p < 0.01). Although North America and Europe remained the main locations, increasing trends of inclusion of other regions, such as East Asia, were noted. Conclusion Globalization of drug development is evident with the increasing trend of multiregional clinical trial. Regulatory authorities as well as the pharmaceutical industry should prepare for the evolving setting of clinical research and problems that can arise from these changes.

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