Thomas Jaki

University of Cambridge, MRC Biostatistics Unit, Faculty Member

Lancaster University, Mathematics and Statistics, Faculty Member

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Supervisors: R. Webster West
Address: Medical and Pharmaceutical Statistics Research Unit
Department of Mathematics and Statistics
Lancaster University

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Noel B. Salazar

KU Leuven

Steven Pinker

Harvard University

James Elkins

School of the Art Institute of Chicago

Vivekanand Jha

Fortis Escorts Heart Institute

Aslı SUNER (KARAKÜLAH)

Ege University

Andreas Umland

National University of "Kyiv-Mohyla Academy"

Jayjit Majumdar

University of Kalyani

H.Eray Çelik

Yuzuncu Yil University

Remo Caponi

University of Cologne

John Johnson

Pennsylvania State University

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Papers by Thomas Jaki

Recovering Direct Effects in Genetics: A Comparison

In genetics it is often of interest to discover single nucleotide polymorphisms (SNPs) that are d... more In genetics it is often of interest to discover single nucleotide polymorphisms (SNPs) that are directly related to a disease, rather than just being associated with it. Few methods exist, however, addressing this so-called `true sparsity recovery' issue. In a thorough simulation study, we show that for moderate or low correlation between predictors, lasso-based methods perform well at true sparsity recovery, despite not being specifically designed for this purpose. For large correlations, however, more specialised methods are needed. Stability selection and direct effect testing perform well in all situations, including when the correlation is large.

Aspirin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

The Lancet

A benchmark for dose-finding studies with unknown ordering

Biostatistics

Summary An important tool to evaluate the performance of a dose-finding design is the nonparametr... more Summary An important tool to evaluate the performance of a dose-finding design is the nonparametric optimal benchmark that provides an upper bound on the performance of a design under a given scenario. A fundamental assumption of the benchmark is that the investigator can arrange doses in a monotonically increasing toxicity order. While the benchmark can be still applied to combination studies in which not all dose combinations can be ordered, it does not account for the uncertainty in the ordering. In this article, we propose a generalization of the benchmark that accounts for this uncertainty and, as a result, provides a sharper upper bound on the performance. The benchmark assesses how probable the occurrence of each ordering is, given the complete information about each patient. The proposed approach can be applied to trials with an arbitrary number of endpoints with discrete or continuous distributions. We illustrate the utility of the benchmark using recently proposed dose-fin...

An open label, adaptive, phase 1 trial of high-dose oral nitazoxanide in healthy volunteers: an antiviral candidate for SARS-CoV-2

Repurposing approved drugs may rapidly establish effective interventions during a public health c... more Repurposing approved drugs may rapidly establish effective interventions during a public health crisis. This has yielded immunomodulatory treatments for severe COVID-19, but repurposed antivirals have not been successful to date because of redundancy of the target in vivo or suboptimal exposures at studied doses. Nitazoxanide is an FDA approved antiparasitic medicine, that physiologically-based pharmacokinetic (PBPK) modelling has indicated may provide antiviral concentrations across the dosing interval, when repurposed at higher than approved doses. Within the AGILE trial platform (NCT04746183) an open label, adaptive, phase 1 trial in healthy adult participants was undertaken with high dose nitazoxanide. Participants received 1500mg nitazoxanide orally twice-daily with food for 7 days. Primary outcomes were safety, tolerability, optimum dose and schedule. Intensive pharmacokinetic sampling was undertaken day 1 and 5 with Cmin sampling on day 3 and 7. Fourteen healthy participants ...

Endpoints for randomized controlled clinical trials for COVID-19 treatments

Clinical Trials

Background: Endpoint choice for randomized controlled trials of treatments for novel coronavirus-... more Background: Endpoint choice for randomized controlled trials of treatments for novel coronavirus-induced disease (COVID-19) is complex. Trials must start rapidly to identify treatments that can be used as part of the outbreak response, in the midst of considerable uncertainty and limited information. COVID-19 presentation is heterogeneous, ranging from mild disease that improves within days to critical disease that can last weeks to over a month and can end in death. While improvement in mortality would provide unquestionable evidence about the clinical significance of a treatment, sample sizes for a study evaluating mortality are large and may be impractical, particularly given a multitude of putative therapies to evaluate. Furthermore, patient states in between “cure” and “death” represent meaningful distinctions. Clinical severity scores have been proposed as an alternative. However, the appropriate summary measure for severity scores has been the subject of debate, particularly ...

Thomas Jaki

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