The SWITCH algorithm: An expert consensus on treat-to-target criteria for chronic prurigo

To date, the management of chronic prurigo (CPG; prurigo nodularis) relies on expert consensus and guidelines without providing detailed recommendations on long-term treatment management.

This study was initiated by an expert committee to define, validate and reach consensus on treat-to-target (T2T) criteria and a decision-supporting treatment algorithm for CPG.

A prospective, single-centre, non-interventional study was conducted in adult CPG patients at a moderate-to-severe disease stage, experiencing intense itch (NRS ≥7; Group A), and in patients who considered themselves successfully treated (Group B). The patients answered questions about their most severe symptoms and essential therapy goals. A committee of 14 field experts evaluated the study results, identified outcome tools from clinical trials and defined and weighted T2T criteria. Based on this, a treatment algorithm was developed through an iterative consensus-building method and anonymous voting.

171 patients (Group A, n = 96; Group B, n = 75) were interviewed. Itch (99.4%), the need to scratch (48%), and pruriginous lesions (45.6%) were the most frequently reported severe symptoms. Pruritus relief (over complete pruritus resolution) and healing of lesions were the key therapeutic goals. In clinical trials, the most frequently used instruments were assessments of worst/peak itch intensity, disease severity via IGA, DLQI and sleep quality. According to the results, the experts defined initial itch control as NRS ≤3, lesion healing with IGA-S 0/1, and burden, along with their respective clinically measurable parameters, as T2T criteria. These criteria, with predefined cut-off values, serve as the decision-tree keys that constitute the treatment algorithm presented here, facilitating a decision to maintain or switch the treatment.

The T2T criteria and the SWITCH treatment algorithm offer a valid and systematic method for evaluating and refining CPG treatment based on patient-reported and expert-validated data. This will help to improve the treatment of patients with CPG.