The use of psoriasis biomarkers, including trajectory of clinical response, to predict clearance and remission duration to UVB phototherapy

Background Remission duration and treatment response following phototherapy for psoriasis are highly variable and factors influencing these are poorly understood. Objectives Our primary outcome was to investigate whether selected clinical/serum biomarkers were associated with remission duration, and secondly with psoriasis clearance at the end of phototherapy. In addition, we looked at whether early trajectory of UVB clearance was associated with final clearance outcome. Methods We performed a prospective cohort study of 100 psoriasis patients, routinely prescribed Narrowband UVB and measured selected clinical and biochemical biomarkers, including weekly PASI (psoriasis area and severity index) scores. Patients were followed up for 18 months. Results The median time to relapse was 6 months (95% CI 5-18) if PASI90 was achieved, and 4 months (95% CI 3-9) if less than PASI90 was achieved. Achieving PASI100 did not result in prolonged remission. On UVB completion, the median final PASI (n = 96) was 1.0 (IQR 0.5, 1.6) with 78 (81%) achieving PASI75 and 39 (41%) achieving PASI90. Improved PASI90 response was significantly associated with lower BMI, higher baseline PASI, non-smoking status and lower cumulative NbUVB. Serum levels of C-reactive protein (CRP) and vitamin D were not associated with clearance or remission duration. Early treatment response from weeks 2-3 was predictive of final outcome. For example, achieving PASI30 at week 3 was significantly associated with PASI90 at the end of the course [36/77 (51%) vs. 2/24 (8%), P Conclusions Raised BMI and positive smoking status predicted poorer phototherapy response. For the first time, we have shown that PASI clearance trajectory over the first 2-3 weeks of UVB, can predict psoriasis clearance. This is an important new step towards developing psoriasis personalized prescribing, which can now be formally tested in clinical trials. These simple clinical measures can be used to inform patient treatment expectations; allowing treatment modifications and/or switching to alternative therapies.