Clinical and technical evidence

A literature search was carried out for this briefing in accordance with the interim process and methods statement for medtech innovation briefings. This briefing includes the most relevant or best available published evidence relating to the clinical effectiveness of the technology. Further information about how the evidence for this briefing was selected is available on request by contacting

Published evidence

Two studies are summarised in this briefing. One study used the underlying signature for PredictSURE IBD and provided biochemical 'proof of concept' evidence for the signature underlying PredictSURE IBD (Lee et al. 2011). Biasci et al. (2019) is a prospective study of 123 people with inflammatory bowel disease (IBD), which examined the use of PredictSURE IBD in clinical practice.

The clinical evidence and its strengths and limitations are summarised in the overall assessment of the evidence.

Overall assessment of the evidence

Evidence on PredictSURE IBD for predicting ulcerative colitis prognosis is limited in quantity and quality. A prospective cohort study recruited patients with IBD using the PredictSURE IBD test to predict the flare-ups of IBD including ulcerative colitis from diagnosis (Biasci et al. 2019). The study described the use of the test in 3 cohorts including 2 training cohorts and 1 validation cohort. The PredictSURE IBD test stratified 2 patient subgroups by disease severity. Estimates of prognostic accuracy were available for the validation cohort, and the sample study for the estimates was small.

Biasci et al. (2019)

Intervention and comparator

PredictSURE IBD; no comparator.

Key outcomes

In the validation cohorts, PredictSURE IBD stratified patients into 2 distinct subgroups irrespective of their underlying diagnosis:

  • IBDhi patients (with a poor prognosis of IBD, equivalent to IBD1, T‑cell exhaustion low)

  • IBDlo patients (equivalent to IBD2, T‑cell exhaustion high).

Results suggested that people who were classified as IBDhi had significantly more aggressive diseases than those classified as IBDlo. The hazard ratio for an earlier need for treatment escalation in ulcerative colitis was 3.12 (95% confidence interval [CI] 1.25 to 7.72; p=0.015). The sensitivity and specificity for predicting the need for multiple escalations within the first 18 months were 100% and 48% in people with ulcerative colitis.

Strengths and limitations

This study also included 66 people with Crohn's disease. People included in the study had introduction treatment, which would likely influence the timing and frequency of subsequent escalations, and consequently sensitivity and specificity. The calculation of prognostic accuracy was based on a relatively small sample size.

Lee et al. (2011)

Intervention and comparator

Standard care step-up strategy given by doctors blinded to the PredictSURE IBD signature test results (note – this study did not use the actual test but did use the same signature that is used in PredictSURE IBD). No comparator.

Key outcomes

The study used statistical techniques to identify 2 subgroups of patients, IBD1 (characterised by upregulation of the majority of differentially expressed genes) and IBD2. This showed CD8+ T‑cell transcriptional signatures that identified 2 subgroups that had very different disease courses. Patients in the subgroup with elevated expression of genes involved in antigen-dependent T‑cell responses had a substantially higher incidence of frequently relapsing disease. The authors comment that this suggests that the course of otherwise distinct autoimmune and inflammatory conditions may be influenced by common pathways and identifies the biomarker that can predict prognosis in ulcerative colitis.

Strengths and limitations

This study also included 35 people with Crohn's disease. The patients were recruited specifically for this study and all treatment was blinded to the test results. The study is relatively small and gives basic demographic information for the patients. Detailed descriptions of the treatment course and outcomes are presented in the supplementary information as are details of the complex statistical methods used in the analysis.


This is a single-use technology. The company states that it works with suppliers including raw material manufacturers with sustainability plans focusing on reducing carbon emissions, rethinking packaging, plastics recycling and responsible water usage. It also works with its logistics partner to develop sustainable shipping to reduce CO2 emissions. There is no published evidence to support these claims.

Recent and ongoing studies