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Laura Bonnett

Dr Laura Bonnett
PhD CStat SFHEA

Contact

L.J.Bonnett@liverpool.ac.uk

+44 (0)151 795 9686

Research

I specialise in the development, validation and implementation of clinical prediction models for chronic conditions such as epilepsy and asthma.

Clinical Prediction Models

My main research interest is statistical modelling, particularly the development, validation and implementation of clinical prediction models using state-of-the-art statistical methodology. I enjoy working with clinicians and the public to ensure that the outputs of statistical models are presented in a clinically meaningful and patient-friendly way. I lead the Department's Prediction Modelling Group and am part of the Faculty for a course at the University of Birmingham considering statistical methods for risk prediction and prognostic models.

Systematic Reviews & Meta-Analysis

I have considerable experience in undertaking and peer-reviewing systematic reviews and meta-analyses involving aggregate and individual participant data. I have some experience of undertaking network meta-analyses. In particular, I spent 2.5 years summarising all published literature (phase II and phase III studies) considering chemotherapy for people newly diagnosed with pulmonary tuberculosis.

Chronic Conditions

My research focuses on chronic conditions. In particular, I have worked with data from people with epilepsy since 2008 and I am familiar with the Standard Versus New Antiepileptic Drug (SANAD) Study, the Multicentre Study of Early Epilepsy and Single Seizures (MESS), the Medical Research Council Antiepileptic Drug Withdrawal (MRC AED) Study, and the National General Practice Survey of Epilepsy (NGPSE). I have also worked with data from the Optimum Patient Care Research Database (OPCRD) for people with asthma and various cardiology datasets.

Research grants

An international target trial emulation study assessing the mortality and morbidity risks of valproate withdrawal and developing a causal prediction model of the safest alternatives for young men and women with epilepsy

EPILEPSY RESEARCH INSTITUTE UK (UK)

August 2024 - August 2027

An international cohort study assessing the morbidity and mortality risks of valproate withdrawal in men and women aged 16–54 years with epilepsy

THE ACADEMY OF MEDICAL SCIENCES (UK)

May 2024 - April 2026

Developing a tool to predict Acute Kidney Injury in hospitalised children

KIDNEY RESEARCH UK (UK)

October 2024 - September 2026

Mental Health Research for Innovation Centre (M-RIC)

DEPARTMENT OF HEALTH & SOCIAL CARE (UK)

January 2023 - December 2027

Supplement to_Supporting the ambulance service to safely convey fewer patients to hospital by developing a risk prediction tool: Risk of ADverse Outcomes after a Suspected Seizure (RADOSS) (RADOSS)

DEPARTMENT OF HEALTH & SOCIAL CARE (UK)

November 2022 - July 2025

Academia and Industry United Innovation and Treatment for Tuberculosis ( UNITE4TB)

EUROPEAN COMMISSION

June 2021 - May 2028

Addressing the Social Determinants and Consequences of Tuberculosis in Nepal (ASCOT): a pilot randomised controlled trial and process evaluation

MEDICAL RESEARCH COUNCIL

March 2021 - August 2022

Multimorbidity of mental disorders and alcohol attributed conditions

MEDICAL RESEARCH COUNCIL

August 2020 - March 2021

Improving prediction of psychosis in ARMS using a clinically useful prognostic tool: IPPACT

DEPARTMENT OF HEALTH & SOCIAL CARE (UK)

October 2018 - October 2024

Predicting time to next event for patients with recurrent events Post Doctoral Research Fellowship for Laura Bonnett

DEPARTMENT OF HEALTH & SOCIAL CARE (UK)

December 2015 - November 2019

Discriminant Function Analysis for Longitudinal Data: Applications in Medical Research (DiALog)

MEDICAL RESEARCH COUNCIL

October 2014 - September 2017