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Personalised Treatment Trials (TOTEM)

Tracking to Optimise Treatment Matching for ME/CFS and Long COVID

Study AIM

The TOTEM study will deeply characterise patients before, during and after treatments are trialled through their General Practitioner (GP). Producing large scale data in combination with treatment outcome will be used to produce a predictive algorithm to improve the connection of patients to appropriate treatment options sooner.

INVESTIGATORS
  • Christopher Armstrong, PhD
  • David Fineberg, MBBS, FRACGP, DCH
  • Elena Schneider-Futschik, PhD
  • Natalie Thomas, PhD
  • Katherine Huang, PhD
  • Michael Menden, PhD
  • Wenjie Shan
  • Emily Allen, RN
  • Kate Tsui
Updates and Potential
  • We have trialled several devices in pilot trials for functional measures to test patient outcomes (blood pressure and heart rate wearables).
  • We are currently recruiting over 1000 ME/CFS patients to test FUNCAP as a “right now” measure of ME/CFS patient severity.
  • We developed a novel symptom tracker app that enables ME/CFS patients to develop an accurate and personalised symptom scale unique to them.
  • Recruitment is underway through a specialist-led clinic pathway.
  • For the most recent progress on the program, read the TOTEM precision medicine update.
  • Chris and David also discuss the program in this video update.
STUDY HYPOTHESIS AND DESCRIPTION

We are conducting a study to closely watch how different treatments affect ME/CFS and Long COVID patients, using a very tailored approach. We’ll collect samples from patients before, during, and after their treatment to see what biological changes happen and how these relate to whether they feel better or not. This method will help us figure out which treatments work, why they work, and who they work best for.

We plan to study 200 patients over three years. Each patient will be part of the study for about 3 to 4 months, during which they will try 2 to 3 different treatments. This includes three visits to the clinic and involves analysing many samples they provide, like blood and urine. This large collection of data from all the patients will help us make better predictions about which treatments are most likely to help others in the future.

OBJECTIVES

  1. Pattern biology that corresponds to symptom/disease changes induced by treatment.
  2. Sample blood before and after exertion as a measure of improved exertion tolerance.
  3. Cluster patients based on biology-symptom dynamic and identify effective treatments.