End-of-study safety, immunogenicity, and efficacy of quadrivalent HPV (types 6, 11, 16, 18) recombinant vaccine in adult women 24-45 years of age.

BACKGROUND: Previous analyses from a randomised trial in women aged 24-45 years have shown the quadrivalent human papillomavirus (qHPV) vaccine to be efficacious in the prevention of infection, cervical intraepithelial neoplasia (CIN), and external genital lesions (EGLs) related to HPV 6/11/16/18. In this report, we present end-of-study efficacy, safety, and immunogenicity data with a median follow-up time of 4.0 years. METHODS: We enrolled 3819 24-45-year-old women with no history of cervical disease or genital warts in the past 5 years. Women received quadrivalent vaccine or placebo at day 1, and at months 2 and 6. Ascertainment of CIN/EGL was accomplished through Pap testing, genital inspection, and cervicovaginal sampling (every 6 months). The main analysis was conducted in a per-protocol efficacy population (that received three doses, was naive to the relevant HPV types at day 1, and remained free of infection through month 7). Efficacy was also estimated in other naive and non-naive populations. RESULTS: Vaccine efficacy against the combined incidence of persistent infection, CIN/EGL related to HPV6/11/16/18 in the per-protocol population was 88.7% (95% CI: 78.1, 94.8). Efficacy for women who were seropositive and DNA negative for the relevant vaccine HPV type at the time of enrolment who received at least 1 dose was 66.9% (95% CI: 4.3, 90.6). At month 48, 91.5, 92.0, 97.4, and 47.9% of vaccinated women were seropositive to HPV 6/11/16/18, respectively. No serious vaccine-related adverse experiences were reported. CONCLUSIONS: The qHPV vaccine demonstrated high efficacy, immunogenicity, and acceptable safety in women aged 24-45 years, regardless of previous exposure to HPV vaccine type.

A flexible stochastic curtailing procedure for the log-rank test.

For safety and ethical reasons, a data monitoring committee of a clinical trial may wish to assess the futility of continuing a trial if the currently available data at an interim look show no beneficial effect due to treatment, especially when accompanied by mounting evidence of treatment emergent adverse effects. Stochastic curtailing whereby conditional power is evaluated given currently observed data is one way of evaluating futility. In clinical trials that look at "time-to-event" as the primary outcome, difference between treatment groups with respect to the primary outcome is commonly evaluated using the log-rank test. Although the unconditional power function for the log-rank test has been described previously, its conditional power has not been widely investigated. We describe a method for evaluating conditional power when the log-rank test is used to assess the difference between the survival distributions of two treatment groups with respect to some failure-time outcome. The method is useful under a wide range of assumptions regarding the underlying survival distribution, patient entry distribution, losses to follow-up, and (if applicable) noncompliance, drop-ins, lag in treatment effect, and stratification. This level of applicability is attained by generalizing a flexible Markov chain approach to unconditional power computation, described previously, to compute conditional power.