Table 1_Impact of temperature trend-defined seasonality on psoriasis treatment outcomes: a multicenter longitudinal study.docx

BackgroundPsoriasis severity and symptoms are widely known to vary seasonally. However, evidence on the impact of seasonality on treatment outcomes is limited, with vague season definitions. It also remains unclear whether seasons represent static meteorological levels or dynamic trends.
ObjectiveTo assess the impact of a novel temperature trend-defined seasonality on psoriasis treatment responses at 2 and 3 months.
MethodsData were derived from the Shanghai Psoriasis Effectiveness Evaluation CoHort (SPEECH), a prospective, multicenter registry assessing the effectiveness of biologics (adalimumab, ustekinumab, secukinumab and ixekizumab), conventional systemic therapies (acitretin and methotrexate), and phototherapy. Patients were categorized into warming (consistent temperature increase), transition (non-unidirectional changes), and cooling (consistent temperature decrease) groups based on ambient temperature trends during the treatment period. Effectiveness was defined as achieving Psoriasis Area and Severity Index (PASI) 75 (≥ 75% improvement in PASI), PASI 90 (≥ 90% improvement in PASI), Physician’s Global Assessment (PGA) of 0/1, and Dermatology Quality of Life Index minimal important difference (DLQI MID) (≥ 4 points improvement) at 2 and 3 months. Covariate balancing propensity score (CBPS) weighting was applied to balance baseline covariates, and odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Interaction analyses evaluated potential factors that may stratify treatment response.
ResultsIn the 3-month analysis of 1411 patients, the cooling group showed significantly lower odds of achieving PASI 75 (adjusted OR 0.70, 95% CI 0.61–0.80, P <.001), PASI 90 (adjusted OR 0.68, 95% CI 0.59–0.79, P <.001), PGA 0/1 (adjusted OR 0.65, 95% CI 0.57–0.75, P <.001), and DLQI MID (adjusted OR 0.86, 95% CI 0.75–0.99, P = .032) compared to the warming group. The transition group showed intermediate outcomes. Body mass index (BMI) significantly modified treatment effectiveness, with higher BMI associated with poorer responses, whereas treatment type did not alter the seasonal effect. Findings were largely consistent at 2 months.
ConclusionsCooling trends are associated with reduced treatment efficacy independently of static temperature, humidity, and ultraviolet levels. This BMI-modified effect underscores the importance of personalized management strategies addressing both environmental and patient-specific factors.