Publications by authors named "Nicolas M Ballarini"

Article Synopsis
  • The study investigates the impact of missing data and unmeasured confounding on external comparator studies through two case studies involving randomized controlled trials in multiple myeloma and prostate cancer.
  • By analyzing these cases and conducting simulations, researchers quantified how missingness and confounding variables affected bias and performance metrics of treatment effects.
  • Results varied: for multiple myeloma, findings aligned with trial results despite missing data; however, for prostate cancer, missing data led to inconclusive outcomes and highlighted limitations in eligibility criteria.
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Background: Severe traumatic brain injury (sTBI) is a public health issue with great disparity among low- and middle-income countries where the implementation of evidence-based guidelines is challenging because resources are often unavailable. A consensus process including experts in the prehospital, emergency department, neurosurgery, and intensive care unit took place in Colombia to develop a set of stratified protocols called BOOTStraP, targeting resource-poor environments, but it has not been systematically implemented and tested.

Objective: To identify the facilitators of, and barriers to, collecting data about patients with sTBI and to implement a stratified protocol across the treatment phases of prehospital, emergency department, neurosurgery, and intensive care unit in low-resource settings.

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We design two-stage confirmatory clinical trials that use adaptation to find the subgroup of patients who will benefit from a new treatment, testing for a treatment effect in each of two disjoint subgroups. Our proposal allows aspects of the trial, such as recruitment probabilities of each group, to be altered at an interim analysis. We use the conditional error rate approach to implement these adaptations with protection of overall error rates.

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In the analysis of survival times, the logrank test and the Cox model have been established as key tools, which do not require specific distributional assumptions. Under the assumption of proportional hazards, they are efficient and their results can be interpreted unambiguously. However, delayed treatment effects, disease progression, treatment switchers or the presence of subgroups with differential treatment effects may challenge the assumption of proportional hazards.

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Subgroup analyses are a routine part of clinical trials to investigate whether treatment effects are homogeneous across the study population. Graphical approaches play a key role in subgroup analyses to visualise effect sizes of subgroups, to aid the identification of groups that respond differentially, and to communicate the results to a wider audience. Many existing approaches do not capture the core information and are prone to lead to a misinterpretation of the subgroup effects.

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Background: Postoperative atrial fibrillation (POAF) occurs in up to 40% of patients undergoing cardiac surgery. Invasive stimulation of the vagal nerve previously demonstrated a reduced risk of POAF. Therefore, we examined the antiarrhythmic and anti-inflammatory effects of noninvasive low-level transcutaneous electrical stimulation (LLTS) of the greater auricular nerve in a pilot trial including patients undergoing cardiac surgery.

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Establishing comparability of the originator and its biosimilar at the structural and functional level, by analyzing so-called quality attributes, is an important step in biosimilar development. The statistical assessment of quality attributes is currently in the focus of attention because both the FDA and the EMA are working on regulatory documents for advising companies on the use of statistical approaches for strengthening their comparability claim. In this paper, we first discuss "comparable" and "not comparable" settings and propose a shift away from the usual comparison of the mean values: we argue that two products can be considered comparable if the range of the originator fully covers the range of the biosimilar.

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Identifying subgroups of treatment responders through the different phases of clinical trials has the potential to increase success in drug development. Recent developments in subgroup analysis consider subgroups that are defined in terms of the predicted individual treatment effect, i.e.

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Objective: Little is known about the critical care management of children with traumatic brain injury (TBI) in low middle income countries. We aimed to identify indicators of intensive care unit (ICU) treatments associated with favorable outcomes in Argentine children with severe TBI.

Methods: We conducted a secondary analysis of data from patients previously enrolled in a prospective seven center study of children with severe TBI who were admitted to an ICU in one of the seven study centers.

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Objective: There is little information on the type of early care provided to children with traumatic brain injury (TBI) in low middle income countries. We benchmarked early prehospital [PH] and emergency department [ED] pediatric TBI care in Argentina.

Methods: We conducted a secondary analysis of data from patients previously enrolled in a prospective seven center study of children with TBI.

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Objective: To develop, in partnership with families of children with traumatic brain injury, a postdischarge intervention that is effective, simple, and sustainable.

Design: Randomized Controlled Trial.

Setting: Seven Level 1 Pediatric Trauma Centers in Argentina.

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