Appropriate dose of regorafenib based on body weight of colorectal cancer patients: a retrospective cohort study.

PURPOSE: Previous randomized studies have shown a survival benefit of using regorafenib but a high rate of adverse events in unresectable colorectal cancer patients. To reduce these adverse events and improve the tolerability, we examined the appropriate dose of regorafenib based on body weight. METHODS: We used a nationwide claims database in Japan and examined the efficacy and safety of regorafenib for patients with metastatic colorectal cancer between groups divided by body weight (60 kg) and median average dose (120 mg) between 2013 and 2018. We also assessed overall survival (OS) and adverse events between these groups. RESULTS: We identified 2530 Japanese patients (heavy weight/high dose: 513, light weight/low dose: 921, heavy weight/low dose: 452, and light weight/high dose: 644). There was no significant difference in the adverse events and OS after inverse probability treatment weighting (IPTW) adjustment between heavy weight/high dose group and light weight/low dose group (hazard ratio, HR=0.97). Among the light-weight patients, higher average dose was associated with shorter OS (IPTW adjusted HR=1.21, 95% CI 1.05 - 1.39, Table 3) while among the heavy-weight patients, there was no significant difference in OS between high and low dose groups (IPTW adjusted HR=1.14, 95% CI 0.95 - 1.37). CONCLUSION: The findings suggest that a low dose of regorafenib for light-weight patients may be as safe and effective as high doses for heavy-weight patients. Further studies should be conducted to identify an appropriate dose based on each patient's physique and condition.

Application of estimand framework in ICH E9 (R1) to vaccine trials.

Over the past decades, the primary interest in vaccine efficacy or immunogenicity evaluation mostly focuses on the biological effect of immunization in complying with the vaccination schedule in a targeted population. The safety questions, which are essential for vaccines as they are generally given to large healthy populations, need to be clearly defined to reflect the risk assessment of interest. ICH E9 (R1) provides a structured framework to clarify the clinical questions and formulate the treatment effect as an estimand. This paper applies the estimand framework to vaccine clinical trials on common clinical questions regarding efficacy, immunogenicity, and safety.

Bayesian hierarchical model for safety signal detection in multiple clinical trials.

Clinical safety signal detection is of great importance in establishing the safety profile of new drugs and biologics during drug development. Bayesian hierarchical meta-analysis has proven to be a very effective method of identifying potential safety signals by considering the hierarchical structure of clinical safety data from multiple randomized clinical trials conducted under an Investigational New Drug (IND) application or Biological License Application (BLA). This type of model can integrate information across studies, for instance by grouping related adverse events using the MedDRA system-organ-class (SOC) and preferred terms (PT). It therefore improves the precision of parameter estimates compared to models that do not consider the hierarchical structure of the safety data. We propose to extend an existing four-stage Bayesian hierarchical model and consider the exposure adjusted incidence rate, assuming the number of adverse events (AEs) follows a Poisson distribution. The proposed model is applied to a real-world example, using data from three randomized clinical trials of a neuroscience drug and examine in three simulation studies motivated by real-world examples. Comparison is made between the proposed method and other existing methods. The simulation results indicate that our proposed model outperforms other two candidate models in terms of power and false detection rate.

Industry Assessment of the Contribution of Patient Support Programs, Market Research Programs, and Social Media to Patient Safety.

BACKGROUND: Over the past decade, the volume of adverse events (AEs) reported to marketing authorization holders and regulators has been rapidly increasing each year, which has led to significant challenges in patient safety assessment. Three data sources that have largely contributed to the expansion in adverse event reports are patient support programs (PSPs), market research programs (MRPs), and social media. In this study, we sought to further understand the contribution of these safety data sources to the characterization of a product's safety profile. METHODS: Three separate approaches were taken that, when combined, can be used to evaluate each data source. The first identified any core company data sheet changes or drug safety label changes. The second evaluated the similarity of information through proportions of AEs between each solicited data source and spontaneous sources. Lastly, the completeness of information reported was evaluated through vigiGrade and compared across each data source. RESULTS: One drug safety label change was identified from a patient support program, which involved regular contact with health care providers. No label changes were identified from market research programs or social media. Patient support programs, market research programs, and social media report similar proportions for HLGT as spontaneous sources. Market research programs and social media display very low vigiGrade scores. When broken down by subtype, traditional PSPs display high vigiGrade scores, while patient assistance programs display lower vigiGrade scores that were program dependent. CONCLUSIONS: This study did not demonstrate that certain data sources such as market research programs, social media, and patient assistance programs meaningfully contributed to the further understanding of the characterization of a product's safety profile.

Bridging blinded and unblinded analysis for ongoing safety monitoring and evaluation.

In order to better characterize the safety profile of investigational new drugs (INDs) during clinical development, more interest and attention have been paid to ongoing safety monitoring and evaluation. The 2015 US FDA IND safety reporting draft guidance compels sponsors to periodically evaluate unblinded safety data. However, maintaining the trial blind is necessary to avoid jeopardizing the validity of study findings. In this article, we propose an innovative new approach which includes analyzing both blinded and unblinded data. The proposed two-stage framework incorporates periodic analyses of blinded safety data to detect and flag adverse events that may have potential risk elevation related to experimental treatment, as well as planned unblinded analyses to quantify associations between the drug and adverse events, and to determine thresholds for referring adverse events for medical review and safety reporting.