Editorial: a clinical decision tool to identify patients who might benefit most from intensified dosing in the biological era-getting nearer?

Specificity of clinical decision support tools for vedolizumab and ustekinumab in biologically naïve patients with Crohn's disease

BACKGROUND AND AIMS

Clinical decision support tools (CDST) were developed to predict drug response to various biological treatments for Crohn's disease (CD). This study investigated whether CDSTs for vedolizumab (V-CDST) and ustekinumab (U-CDST) can be used as prognostic or drug-specific markers to predict response.

METHODS

A hypothetical scenario involving 872 patients with CD who were exposed to the first biological therapy at Samsung Medical Center between 1995 and 2020 is presented. V-CDST & U-CDST were calculated based on clinical and laboratory data immediately before the first biologic was initiated. The Cumulative Link Mixed Model (CLMM) test, weighted Kappa and plot, and Spearman's correlation was used to determine the degree of agreement and difference between the two tools.

RESULTS

25% of all patients diagnosed with biologically naïve CD were categorized into different probability groups using V-CDST and U-CDST. The difference between the two tools was significantly based on a two-sample paired ordinal test with Cumulative Link Mixed Model (CLMM) (p-value < .001). Concordance between the two tools with a total of 654 subjects (75% of all patients) showed a similar probability (weighted Kappa: 0.47, 95% CI: 0.41-0.52).

CONCLUSIONS

V-CDST and U-CDST are useful in selecting vedolizumab or ustekinumab in 25% of biologically naïve CD patients in our hypothetical scenario.

Biomarker discovery for personalized therapy selection in inflammatory bowel diseases: Challenges and promises

The past decades witnessed a significant stride in deciphering the pathophysiology of inflammatory bowel disease, which further advanced drug development adding several new biologicals and small molecules to the arsenal of available therapies. Surprisingly, this wealth in therapeutic options did not yield the aspired high durable response rates. In addition, the increase in therapeutic availabilities ignited an increase in research toward biomarkers that could help assign therapies to patients with the highest probability of response. Luckily, major steps have been undertaken in this domain which resulted in the discovery of some interesting biomarkers that are still under validation. However, the pace in which this domain is progressing, the discordance between short-term endpoints in biomarker discovery studies and the ambition of the disease community in modifying disease course, and the uncertainties about the validity of discovered biomarkers highlight the need for a critical appraisal of research conduct in this domain. In this review, we shed light on areas of improvement in biomarker discovery studies that will help optimize the use of available therapies and break the current therapeutic ceiling.

Clinical experiences and predictors of success of treatment with vedolizumab in IBD patients: a cohort study

BACKGROUND

Vedolizumab has become a standard treatment for the inflammatory bowel diseases ulcerative colitis (UC) and Crohn's disease (CD). However, there is an ongoing debate on the ideal individual treatment algorithms and means to predict treatment response are not routinely established.

AIMS

We aimed to describe our experiences with vedolizumab at a large German tertiary referral center and to identify clinical predictors of success of vedolizumab treatment.

METHODS

We performed a retrospective single-center cohort study employing univariable and multivariable analyses as well as Kaplan-Meier analyses of persistence on treatment.

RESULTS

36% and 35% of the patients with UC and CD, respectively, reached clinical remission after 17 weeks. Patients with lower clinical disease activity were more likely to achieve remission. The median persistence on treatment was 33 months for UC and 29 months for CD.

CONCLUSION

Our study confirms that vedolizumab is an efficient option for the treatment of UC and CD. Clinical parameters of disease activity may help to predict the success of treatment.