scholarly journals The Impact of Raising the Bar for Clinical Trials in Ulcerative Colitis

2019 ◽  
Vol 13 (9) ◽  
pp. 1217-1226 ◽  
Author(s):  
Bruce E Sands ◽  
Adam S Cheifetz ◽  
Chudy I Nduaka ◽  
Daniel Quirk ◽  
Wenjin Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Clinical Trials ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Regulatory Bodies ◽  
Effectiveness Studies ◽  
The Impact ◽  
Practical Implications ◽  
Necrosis Factor

Abstract In order to identify the practical implications for both health care practitioners and patients in understanding differences between the results of trials assessing therapies for ulcerative colitis [UC], we reviewed clinical trials of therapies for moderate to severe UC, with a focus on trial design. Over time, patient populations in UC trials have become more refractory, reflecting that patients are failing treatment with additional and different classes of drug, including conventional therapies, immunosuppressant drugs, and anti-tumour necrosis factor therapies. Outcomes used to measure efficacy have become increasingly stringent in order to meet the expectations of patients and physicians, and the requirements of regulatory bodies. Trial design has also evolved to integrate induction and maintenance therapy phases, so as to facilitate patient recruitment and to answer clinically important questions such as how efficacious therapies are in specific subpopulations of patients and during long-term use. As UC clinical trial design continues to evolve, and with limited head-to-head trials and real-world comparative effectiveness studies evaluating UC therapies, careful judgment is required to appreciate the differences and similarities in trial designs, and to understand how these variances may affect the observed efficacy and safety outcomes.

Cancer

2021 ◽  
pp. 627-638
Author(s):  
Rashi Rai ◽  
Prudhvilal Bhukya ◽  
Muneesh Kumar Barman ◽  
Meenakshi Singh ◽  
Kailash Chand ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Success Rates ◽  
Design Strategies ◽  
Safety Level ◽  
Key Steps ◽  
The Impact

Clinical trials are essential to govern the impact of a new possible treatment. It is utilized to determine the safety level and efficacy of a certain treatment. Clinical trial studies in cancer have provided successful treatment leading to longer survival span in the patients. The design of clinical trials for cancer has been done to find new ways to prevent, diagnose, treat, and manage symptoms of the disease. This chapter will provide detailed information on different aspects of clinical trials in cancer research. Protocols outlining the design and method to conduct a clinical trial in each phase will be discussed. The process and the conditions applied in each phase (I, II, and III) will be described precisely. The design of trials done in every aspect such as prevention, immunochemotherapy, diagnosis, and treatment to combat cancer will be illustrated. Also, recent innovations in clinical design strategies and principles behind it as well as the use of recent advances in artificial intelligence in reshaping key steps of clinical trial design to increase trial success rates.

scholarly journals A longitudinal model for the Mayo Clinical Score and its sub-components in patients with ulcerative colitis

2021 ◽  
Author(s):  
Sonoko Kawakatsu ◽  
Rui Zhu ◽  
Wenhui Zhang ◽  
Meina T. Tang ◽  
Tong Lu ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Placebo Response ◽  
Clinical Trial Design ◽  
Clinical Score ◽  
Prior Exposure ◽  
Tnf Α ◽  
Over Time

AbstractClinical trials in patients with ulcerative colitis (UC) face the challenge of high and variable placebo response rates. The Mayo Clinical Score (MCS) is used widely as the primary endpoint in clinical trials to describe the clinical status of patients with UC. The MCS is comprised of four subscores, each scored 0, 1, 2 and 3: rectal bleeding (RB), stool frequency (SF), physician’s global assessment (PGA), and endoscopy (ENDO) subscore. Excluding the PGA subscore gives the modified MCS. Quantitative insight on the placebo response, and its impact on the components of the MCS over time, can better inform clinical trial design and interpretation. Longitudinal modeling of the MCS, and the modified MCS, can be challenging due to complex clinical trial design, population heterogeneity, and limited assessments for the ENDO subscore. The current study pooled patient-level placebo/standard of care (SoC) arm data from five clinical trials in the TransCelerate database to develop a longitudinal placebo response model that describes the MCS over time in patients with UC. MCS subscores were modeled using proportional odds models, and the removal of patients from the placebo/SoC arm, or “dropout”, was modeled using logistic regression models. The subscore and dropout models were linked to allow for the prediction of the MCS and the modified MCS. Stepwise covariate modeling identified prior exposure to TNF-α antagonists as a statistically significant predictor on the RB + SF subscore. Patients with prior exposure to TNF-α antagonists had higher post-baseline RB + SF subscores than naive patients.

scholarly journals Interpretable Trials: Is Interpretability a Reason Why Clinical Trials Fail?

2021 ◽  
Vol 8 ◽  
Author(s):  
Yi-Sheng Chao ◽  
Chao-Jung Wu ◽  
Hsing-Chien Wu ◽  
Danielle McGolrick ◽  
Wei-Chih Chen
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Trial Design ◽  
Research Method ◽  
Clinical Trial Design ◽  
Independent Variables ◽  
Composite Measures ◽  
Unknown Status ◽  
The Impact ◽  
Trial Failure

Background: There are clinical trials using composite measures, indices, or scales as proxy for independent variables or outcomes. Interpretability of derived measures may not be satisfying. Adopting indices of poor interpretability in clinical trials may lead to trial failure. This study aims to understand the impact of using indices of different interpretability in clinical trials.Methods: The interpretability of indices was categorized as: fair-to-poor, good, and unknown. In the literature, frailty indices were considered fair to poor interpretability. Body mass index (BMI) was highly interpretable. The other indices were of unknown interpretability. The trials were searched at clinicaltrials.gov on October 2, 2018. The use of indices as conditions/diseases or other terms was searched. The trials were grouped as completed, terminated, active, and other status. We tabulated the frequencies of frailty, BMI, and other indices.Results: There were 263,928 clinical trials found and 155,606 were completed or terminated. Among 2,115 trials adopting indices or composite measures as condition or disease, 244 adopted frailty and 487 used BMI without frailty indices. Significantly higher proportions of trials of unknown status used indices as conditions/diseases or other terms, compared to completed and terminated trials. The proportions of active trials using frailty indices were significantly higher than those of completed or terminated trials.Discussion: Clinical trial databases can be used to understand why trials may fail. Based on the findings, we suspect that using indices of poor interpretability may be associated with trial failure. Interpretability has not been conceived as an essential criterion for outcomes or proxy measures in trials. We will continue verifying the findings in other databases or data sources and apply this research method to improve clinical trial design. To prevent patients from experiencing trials likely to fail, we suggest further examining the interpretability of the indices in trials.

scholarly journals Conceptual Framework to Support Clinical Trial Optimization and End-to-End Enrollment Workflow

2019 ◽  
pp. 1-10 ◽  
Author(s):  
Neha M. Jain ◽  
Alison Culley ◽  
Teresa Knoop ◽  
Christine Micheel ◽  
Travis Osterman ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Knowledge Representation ◽  
Conceptual Framework ◽  
Trial Design ◽  
Clinical Trial Design ◽  
Prospective Clinical Trial ◽  
Future Trends ◽  
Current State ◽  
Evaluation Strategies

In this work, we present a conceptual framework to support clinical trial optimization and enrollment workflows and review the current state, limitations, and future trends in this space. This framework includes knowledge representation of clinical trials, clinical trial optimization, clinical trial design, enrollment workflows for prospective clinical trial matching, waitlist management, and, finally, evaluation strategies for assessing improvement.

An oncology clinical trial design with randomization adaptive to both short- and long-term responses

2017 ◽  
Vol 28 (7) ◽  
pp. 2015-2031 ◽  
Author(s):  
Hao Liu ◽  
Xiao Lin ◽  
Xuelin Huang
Keyword(s):  
Trial Design ◽  
Clinical Trial Design ◽  
Therapeutic Benefit ◽  
Survival Outcome ◽  
Operating Characteristics ◽  
Short Term ◽  
Term Survival ◽  
Long Term Survival ◽  
Term Response

In oncology clinical trials, both short-term response and long-term survival are important. We propose an urn-based adaptive randomization design to incorporate both of these two outcomes. While short-term response can update the randomization probability quickly to benefit the trial participants, long-term survival outcome can also change the randomization to favor the treatment arm with definitive therapeutic benefit. Using generalized Friedman’s urn, we derive an explicit formula for the limiting distribution of the number of subjects assigned to each arm. With prior or hypothetical knowledge on treatment effects, this formula can be used to guide the selection of parameters for the proposed design to achieve desirable patient number ratios between different treatment arms, and thus optimize the operating characteristics of the trial design. Simulation studies show that the proposed design successfully assign more patients to the treatment arms with either better short-term tumor response or long-term survival outcome or both.

The impact of Vaccination worldwide on SARS-CoV-2 infection: A Review on Vaccine Mechanisms, Results of Clinical Trials, Vaccinal Coverage and Interactions with Novel Variants

2021 ◽  
Vol 28 ◽  
Author(s):  
Douglas Henrique Pereira Damasceno ◽  
Arthur Aguiar Amaral ◽  
Cecília Andrade Silva ◽  
Ana Cristina Simões e Silva
Keyword(s):  
Immune Response ◽  
Clinical Trials ◽  
Placebo Group ◽  
Mechanisms Of Action ◽  
Novel Variants ◽  
The Impact ◽  
Positive Results ◽  
Epidemiological Information ◽  
Long Term Studies

Background: The COVID-19 pandemic demanded a global effort towards quickly developing safe and effective vaccines against SARS-CoV-2. Objective: This review aimed to discuss the main vaccines available, their mechanisms of action, results of clinical trials and epidemiological behavior. The implications of viral variants were also debated. Methods: A non-systematic literature review was performed between February and March 2021 by searching the Pubmed, Scopus, and SciELO databases, using different combinations of the following terms: "vaccines", "clinical trials" , "SARS-CoV-2", "Coronavirus", "COVID-19", "mechanisms of action". Data regarding clinical trials of SARS-CoV-2 vaccines and epidemiological information were also searched. Results: The mechanisms of action included vector-virus, mRNA and inactivated virus vaccines. The vaccines showed positive results in phases 2/3 clinical trials. The efficacy of the mRNA 1273 and of mRNA BNT 162b2 vaccines were 94.1% and 95%, respectively. The effectiveness of the ChAdOx1 nCoV-19 vaccine varied according to the scheme, with an overall value of 70.4%. The Gam-COVID-Vac vaccine had an efficacy of 91.6%. Regarding the Ad26.COV2.S vaccine, 99% or more of seroconversion was observed in all subgroups 29 days after vaccination. The CoronaVac vaccine induced an immune response in 92% of the volunteers receiving 3ug and in 98% with 6ug, in comparison to 3% in the placebo group. Conclusion: Global efforts have resulted in vaccines available in record time, with good safety and immunogenicity profile. However, only long-term studies can provide more information on duration of immunity and the need for additional doses.

scholarly journals Opportunities and challenges of incorporating clinical outcome assessments in brain tumor clinical trials

2018 ◽  
Vol 6 (2) ◽  
pp. 81-92 ◽  
Author(s):  
Emanuela Molinari ◽  
Tito R Mendoza ◽  
Mark R Gilbert
Keyword(s):  
Clinical Trials ◽  
Brain Tumor ◽  
Clinical Outcome ◽  
Clinical Trial Design ◽  
Well Being ◽  
Successful Implementation ◽  
Outcome Assessments ◽  
Tumor Studies ◽  
Clinical Outcome Assessments ◽  
The Impact

Abstract Regulatory agencies have progressively emphasized the importance of assessing broader aspects of patient well-being to better define therapeutic gain. As a result, clinical outcome assessments (COAs) are increasingly used to evaluate the impact, both positive and negative, of cancer treatments and in some instances have played a major factor in the regulatory approval of drugs. Challenges remain, however, in the routine incorporation of these measures in cancer clinical trials, particularly in brain tumor studies. Factors unique to brain tumor patients such as cognitive decline and language dysfunction may hamper their successful implementation. Study designs often relegated these outcome measures to exploratory endpoints, further compromising data completion. New strategies are needed to maximize the complementary information that COAs could add to clinical trials alongside more traditional measures such as progression-free and overall survival. The routine incorporation of COAs as either primary or secondary objectives with attention to minimizing missing data should define a novel clinical trial design. We provide a review of the approaches, challenges, and opportunities for incorporating COAs into brain tumor clinical research, providing a perspective for integrating these measures into clinical trials.

scholarly journals Tumor Necrosis Factor Inhibition and Parkinson Disease

Neurology ◽  
2021 ◽  
Vol 96 (12) ◽  
pp. e1672-e1679
Author(s):  
Xiaoying Kang ◽  
Alexander Ploner ◽  
Nancy L. Pedersen ◽  
Sara Bandres-Ciga ◽  
Alastair J. Noyce ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Ulcerative Colitis ◽  
Tumor Necrosis Factor ◽  
Crohn Disease ◽  
Tumor Necrosis ◽  
Mendelian Randomization ◽  
Age At Onset ◽  
Multiple Sclerosis Risk ◽  
Necrosis Factor

ObjectiveTo evaluate the effects of long-term tumor necrosis factor (TNF) inhibition on the risk and age at onset of Parkinson disease (PD), we performed a 2-sample Mendelian randomization study using genome-wide association studies (GWAS) summary statistics.MethodsGenetic variants in the vicinity of TNFRSF1A, the gene encoding TNF receptor 1 (TNFR1), were identified as predictive of pharmacologic blockade of TNFR1 signaling by anti-TNF therapy, based on genetic associations with lower circulating C-reactive protein (CRP; GWAS n = 204,402). The effects of TNF-TNFR1 inhibition were estimated for PD risk (ncases/controls = 37,688/981,372) and age at PD onset (n = 28,568) using GWAS data from the International Parkinson's Disease Genomics Consortium and 23andMe, Inc. To validate variants as proxies of long-term anti-TNF treatment, we also assessed whether variant associations reflected anticipated effects of TNFR1 inhibition on Crohn disease, ulcerative colitis, and multiple sclerosis risk (n = 38,589-45,975).ResultsTNF-TNFR1 signaling inhibition was not estimated to affect PD risk (odds ratio [OR] per 10% lower circulating CRP = 0.99; 95% confidence interval [CI] 0.91–1.08) or age at onset (0.13 years later onset; 95% CI −0.66 to 0.92). In contrast, genetically indexed TNF-TNFR1 signaling blockade predicted reduced risk of Crohn disease (OR 0.75; 95% CI 0.65–0.86) and ulcerative colitis (OR 0.84; 95% CI 0.74–0.97) and increased multiple sclerosis risk (OR 1.57; 95% CI 1.36–1.81). Findings were consistent across models using different genetic instruments and Mendelian randomization estimators.ConclusionsOur findings do not imply that TNF-TNFR1 signaling inhibition will prevent or delay PD onset.Classification of EvidenceThis study provides Class II evidence that TNF-TNFR1 signaling inhibition is not associated with the risk or age at onset of PD.

scholarly journals Edaravone in Amyotrophic Lateral Sclerosis’Lessons from the Clinical Development Program and the Importance of a Strategic Clinical Trial Design

US Neurology ◽  
2018 ◽  
Vol 14 (1) ◽  
pp. 47 ◽  
Author(s):  
Said R Beydoun ◽  
Jeffrey Rosenfeld
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Amyotrophic Lateral Sclerosis ◽  
Trial Design ◽  
Development Program ◽  
Clinical Trial Design ◽  
Clinical Development ◽  
Disease Heterogeneity ◽  
Clinical Development Program ◽  
Lateral Sclerosis

Edaravone significantly slows progression of amyotrophic lateral sclerosis (ALS), and is the first therapy to receive approval by the Food and Drug Administration (FDA) for the disease in 22 years. Approval of edaravone has marked a new chapter in pharmaceutical development since the key trial included a novel strategic clinical design involving cohort enrichment. In addition, approval was based on clinical trials that had a relatively small patient number and were performed outside of the US. Edaravone was developed through a series of clinical trials in Japan where it was determined that a well-defined subgroup of patients was required to reveal a treatment effect within the study period. Amyotrophic lateral sclerosis is associated with wide-ranging disease heterogeneity (both within the spectrum of ALS phenotypes as well as in the rate of progression). The patient cohort enrichment strategy aimed to address this heterogeneity and should now be considered as a viable, and perhaps preferred, trial design for future studies. Future research incorporating relevant biomarkers may help to better elucidate edaravone’s mechanism of action, pharmacodynamics, and subsequently ALS phenotypes that may preferentially benefit from treatment. In this review, we discuss the edaravone clinical development program, outline the strategic clinical trial design, and highlight important lessons for future trials.

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