Application of estimand framework in ICH E9 (R1) to safety evaluation.

Defining the right question of interest is important to a clinical study. ICH E9 (R1) introduces the framework of an estimand and its five attributes, which provide a basis for connecting different components of a study with its clinical questions. Most of the applications of the estimand framework focus on efficacy instead of safety assessment. In this paper, we expand the estimand framework into the safety evaluation and compare/contrast the similarity and differences between safety and efficacy estimand. Furthermore, we present and discuss applications of a safety estimand to oncology trials and pooled data analyses. At last, we also discuss the potential usage of safety estimand to handle the impacts of COVID-19 pandemic on safety assessment.

Statistical inference following sample size adjustment based on the 50%-conditional-power principle.

Sample size adjustment at an interim analysis can mitigate the risk of failing to meet the study objective due to lower-than-expected treatment effect. Without modification to the conventional statistical methods, the type I error rate will be inflated, primarily caused by increasing sample size when the interim observed treatment effect is close to null or no treatment effect. Modifications to the conventional statistical methods, such as changing critical values or using weighted test statistics, have been proposed to address primarily such a scenario at the cost of flexibility or interpretability. In reality, increasing sample size when interim results indicate no or very small treatment effect could unnecessarily waste limited resource on an ineffective drug candidate. Such considerations lead to the recently increased interest in sample size adjustment based on promising interim results. The 50% conditional power principle allows sample size increase only when the unblinded interim results are promising or the conditional power is greater than 50%. The conventional unweighted test statistics and critical values can be used without inflation of type I error rate. In this paper, statistical inference following such a design is assessed. As shown in the numerical study, the bias of the conventional maximum likelihood estimate (MLE) and coverage error of its conventional confidence interval are generally small following sample size adjustment. We recommend use of conventional, MLE-based statistical inference when applying the 50% conditional power principle for sample size adjustment. In such a way, consistent statistics will be used in both hypothesis test and statistical inference.

Immunogenicity of the 9-Valent HPV Vaccine Using 2-Dose Regimens in Girls and Boys vs a 3-Dose Regimen in Women.

Importance: Human papillomavirus (HPV) infections cause anogenital cancers and warts. The 9-valent HPV vaccine provides protection against 7 high-risk types of HPV responsible for 90% of cervical cancers and 2 other HPV types accounting for 90% of genital warts. Objective: To determine whether HPV type-specific antibody responses would be noninferior among girls and boys aged 9 to 14 years after receiving 2 doses of the 9-valent HPV vaccine compared with adolescent girls and young women aged 16 to 26 years receiving 3 doses. Design, Setting, and Participants: Open-label, noninferiority, immunogenicity trial conducted at 52 ambulatory care sites in 15 countries. The study was initiated on December 16, 2013, with the last participant visit for this report on June 19, 2015. Five cohorts were enrolled: (1) girls aged 9 to 14 years to receive 2 doses 6 months apart (n = 301); (2) boys aged 9 to 14 years to receive 2 doses 6 months apart (n = 301); (3) girls and boys aged 9 to 14 years to receive 2 doses 12 months apart (n = 301); (4) girls aged 9 to 14 years to receive 3 doses over 6 months (n = 301); and (5) a control group of adolescent girls and young women aged 16 to 26 years to receive 3 doses over 6 months (n = 314). Interventions: Two doses of the 9-valent HPV vaccine administered 6 or 12 months apart or 3 doses administered over 6 months. Main Outcomes and Measures: The primary end point was prespecified as the antibody response against each HPV type assessed 1 month after the last dose using a competitive immunoassay. Each of the three 2-dose regimens was compared with the standard 3-dose schedule in adolescent girls and young women using a noninferiority margin of 0.67 for the ratio of the antibody geometric mean titers. Results: Of the 1518 participants (753 girls [mean age, 11.4 years]; 451 boys [mean age, 11.5 years]; and 314 adolescent girls and young women [mean age, 21.0 years]), 1474 completed the study and data from 1377 were analyzed. At 4 weeks after the last dose, HPV antibody responses in girls and boys given 2 doses were noninferior to HPV antibody responses in adolescent girls and young women given 3 doses (P < .001 for each HPV type). Compared with adolescent girls and young women who received 3 doses over 6 months, the 1-sided 97.5% CIs for the ratio of HPV antibody geometric mean titers at 1 month after the last dose across the 9 HPV subtypes ranged from 1.36 to ∞ to 2.50 to ∞ for girls who received 2 doses 6 months apart; from 1.37 to ∞ to 2.55 to ∞ for boys who received 2 doses 6 months apart; and from 1.61 to ∞ to 5.36 to ∞ for girls and boys who received 2 doses 12 months apart. Conclusions and Relevance: Among girls and boys aged 9 to 14 years receiving 2-dose regimens of a 9-valent HPV vaccine separated by 6 or 12 months, immunogenicity 4 weeks after the last dose was noninferior to a 3-dose regimen in a cohort of adolescent girls and young women. Further research is needed to assess persistence of antibody responses and effects on clinical outcomes. Trial Registration: clinicaltrials.gov Identifier: NCT01984697.

Global Landscape of Benefit-Risk Considerations for Medicinal Products: Current State and Future Directions.

In the last decade there has been a significant increase in the literature discussing the use of benefit-risk methods in medical product (including devices) development. Government agencies, medical product industry groups, academia, and collaborative consortia have extensively discussed the advantages of structured benefit-risk assessments. However, the abundance of information has not resulted in a consistent way to utilize these findings in medical product development. Guidelines and papers on methods, even though well structured, have not led to a firm consensus on a clear and consistent approach. This paper summarizes the global landscape of benefit-risk considerations for product- or program-level decisions from available literature and regulatory guidance, providing the perspectives of three stakeholder groups-regulators, collaborative groups and consortia, and patients. The paper identifies key themes, potential impact on benefit-risk assessments, and significant future trends.