11 research outputs found

    Twenty-four hour efficacy with preservative free tafluprost compared with latanoprost in patients with primary open angle glaucoma or ocular hypertension

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    10openopenKonstas A.G.; Quaranta L.; Katsanos A.; Riva I.; Tsai J.C.; Giannopoulos T.; Voudouragkaki I.C.; Paschalinou E.; Floriani I.; Haidich A.B.Konstas, A. G.; Quaranta, Luciano; Katsanos, A.; Riva, Ivano; Tsai, J. C.; Giannopoulos, T.; Voudouragkaki, I. C.; Paschalinou, E.; Floriani, I.; Haidich, A. B

    Current Statistical Considerations and Regulatory Perspectives on the Planning of Confirmatory Basket, Umbrella, and Platform Trials

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    Master protocols have received a growing interest during the last years. By assigning patients to specific substudies, they aim at targeting and accelerating clinical development. Given their complexity, basket, umbrella, and platform designs have raised challenging regulatory and statistical questions, especially the control of multiplicity in confirmatory trials. In basket trials, regulatory assessment of the benefit/risk in pooled populations and choice of the treatment indication is challenging. We provide here our perspectives on these topics. In master protocols, as long as the statistical hypotheses tested between the different substudies are independent, no supplementary adjustment for multiplicity over the different substudies should be required. Moreover, sharing a control arm within an umbrella or a platform trial investigating different drugs would not require a correction for the type I error rate, whereas the chance of multiple false positive regulatory decisions should be recognized. In basket trials, pooling across substudies requires a rationale supporting the intended indication and should be preplanned. Assessment of the benefit/risk in pooled target populations can be complicated by differences in design or in efficacy/safety signals between the substudies. While trials governed by a master protocol can offer logistic and financial advantages, more experience is needed to gain a deeper insight into this novel framework

    Mortality in systemic sclerosis: an international meta-analysis of individual patient data.

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    Contains fulltext : 48864.pdf (publisher's version ) (Closed access)PURPOSE: Studies on mortality associated with systemic sclerosis have been limited by small sample sizes. We aimed to obtain large-scale evidence on survival outcomes and predictors for this disease. METHODS: We performed a meta-analysis of individual patient data from cohorts recruited from seven medical centers in the United States, Europe, and Japan, using standardized definitions for disease subtype and organ system involvement. The primary outcome was all-cause mortality. Standardized mortality ratios and predictors of mortality were estimated. The main analysis was based only on patients enrolled at each center within 6 months of diagnosis (incident cases). RESULTS: Among 1645 incident cases, 578 deaths occurred over 11,521 person-years of follow-up. Standardized mortality ratios varied by cohort (1.5 to 7.2). In multivariate analyses that adjusted for age and sex, renal (hazard ratio [HR] = 1.9; 95% confidence interval [CI]: 1.4 to 2.5), cardiac (HR = 2.8; 95% CI: 2.1 to 3.8), and pulmonary (HR = 1.6; 95% CI: 1.3 to 2.2) involvement, and anti-topoisomerase I antibodies (HR = 1.3; 95% CI: 1.0 to 1.6), increased mortality risk. Renal, cardiac, and pulmonary involvement tended to occur together (P <0.001). For patients without adverse predictors for 3 years after enrollment, the subsequent risk of death was not significantly different from that for the general population in three cohorts, but was significantly increased in three cohorts that comprised mostly referred patients. Analyses that included all cases in each center (n = 3311; total follow-up: 19,990 person-years) yielded largely similar results. CONCLUSION: Systemic sclerosis confers a high mortality risk, but there is considerable heterogeneity across settings. Internal organ involvement and anti-topoisomerase I antibodies are important determinants of mortality
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