To the Editor,
Hidradenitis suppurativa (HS) is a systemic inflammatory disorder with a multifactorial pathophysiology that remains incompletely understood. Previous research has demonstrated that specific inflammatory markers, including leukocytes, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and interleukin-6 (IL-6) are significantly associated with severe disease as defined by HS-Physician Global Assessment (HSPGA) score.1 Importantly, however, no studies have validated the sensitivity of these markers with fluctuations in disease activity over time. Herein, we investigate the utility of various biomarkers in continuous outcome monitoring for patients with HS and assess their sensitivity in a real-world setting.
A retrospective chart review was conducted to identify patients seen at Montefiore Medical Center between September 1, 2017, and May 1, 2025. Patients were included if they had clinical and laboratory markers of disease severity at baseline and at ≥4 follow-up visits. Collected data included patient demographics, comorbid medical conditions, HS-PGA score, numerical rating scale for pain (NRS-pain) score, hemoglobin (Hgb), hematocrit (Hct), mean corpuscular volume (MCV), leukocyte count, ESR, CRP, and IL-6 across repeat patient visits.
Linear mixed-effects models with patient identifier (MRN) as a random intercept were employed to examine associations between disease severity and laboratory markers over time. Disease severity was modeled continuously using the HS-PGA score. Analyses were conducted using R (version 4.2.1).
The cohort was predominantly female (66%) and Black (49%). The average age at intake was 35.5 years (SD 13.52); consistent with the epidemiological profile of HS in the US population at large.2 Patients had a median of eight visits (IQR 6) where primary outcome measures were recorded, with a median interval between visits and a median follow-up duration of 70 days (IQR 84) and 878 days (IQR 695), respectively. A detailed summary of visit characteristics, demographic information, and comorbid medical conditions can be found in Table 1.
Longitudinal analysis of laboratory markers revealed positive associations between HS-PGA and leukocyte count (β=0.03, P<0.001), CRP (β = 0.14, P<0.001), ESR (β = 0.012, P<0.001), and IL-6 (β =0.005, P<0.001) indicating that higher inflammatory marker levels correlated with greater disease severity. Conversely, significant negative associations were observed between HSPGA and hemoglobin (β=-0.16, P<0.001), hematocrit (β=-0.05, P<0.001), and mean corpuscular volume (β=-0.02, P<0.001). A detailed summary of associations between clinical disease severity and the various inflammatory markers studied can be found in Table 2.
Extending beyond previous work, we demonstrate statistically significant longitudinal associations between clinical disease severity and serum biomarkers known to be associated with HS.1,3 Establishing the sensitivity of specific biomarkers to changes in disease state over time supports their use as validated primary endpoints for HS clinical trials and prospective studies, which largely rely on subjective outcome measures to evaluate drug efficacy at present.4,5 Moreover, the effect size estimates derived from longitudinal analyses that quantifiably assess relationships between specific biomarkers and clinical measures of disease severity may ultimately help inform power calculations and dose-response modeling during early-phase trial design. Taken together, these findings suggest a role for specific serum biomarkers across multiple stages of the clinical research process.
This study is limited by its retrospective nature and small samplesize; larger prospective studies must validate our findings before they can be applied in clinical research settings more broadly. Nevertheless, this study provides a strong foundation for integrating objective biomarkers into the broader framework of HS research and, pending further validation, may ultimately support more rigorous and reproducible approaches to disease monitoring and treatment evaluation moving forward.
Hidradenitis suppurativa (HS) is a systemic inflammatory disorder with a multifactorial pathophysiology that remains incompletely understood. Previous research has demonstrated that specific inflammatory markers, including leukocytes, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and interleukin-6 (IL-6) are significantly associated with severe disease as defined by HS-Physician Global Assessment (HSPGA) score.1 Importantly, however, no studies have validated the sensitivity of these markers with fluctuations in disease activity over time. Herein, we investigate the utility of various biomarkers in continuous outcome monitoring for patients with HS and assess their sensitivity in a real-world setting.
A retrospective chart review was conducted to identify patients seen at Montefiore Medical Center between September 1, 2017, and May 1, 2025. Patients were included if they had clinical and laboratory markers of disease severity at baseline and at ≥4 follow-up visits. Collected data included patient demographics, comorbid medical conditions, HS-PGA score, numerical rating scale for pain (NRS-pain) score, hemoglobin (Hgb), hematocrit (Hct), mean corpuscular volume (MCV), leukocyte count, ESR, CRP, and IL-6 across repeat patient visits.
Linear mixed-effects models with patient identifier (MRN) as a random intercept were employed to examine associations between disease severity and laboratory markers over time. Disease severity was modeled continuously using the HS-PGA score. Analyses were conducted using R (version 4.2.1).
The cohort was predominantly female (66%) and Black (49%). The average age at intake was 35.5 years (SD 13.52); consistent with the epidemiological profile of HS in the US population at large.2 Patients had a median of eight visits (IQR 6) where primary outcome measures were recorded, with a median interval between visits and a median follow-up duration of 70 days (IQR 84) and 878 days (IQR 695), respectively. A detailed summary of visit characteristics, demographic information, and comorbid medical conditions can be found in Table 1.
Longitudinal analysis of laboratory markers revealed positive associations between HS-PGA and leukocyte count (β=0.03, P<0.001), CRP (β = 0.14, P<0.001), ESR (β = 0.012, P<0.001), and IL-6 (β =0.005, P<0.001) indicating that higher inflammatory marker levels correlated with greater disease severity. Conversely, significant negative associations were observed between HSPGA and hemoglobin (β=-0.16, P<0.001), hematocrit (β=-0.05, P<0.001), and mean corpuscular volume (β=-0.02, P<0.001). A detailed summary of associations between clinical disease severity and the various inflammatory markers studied can be found in Table 2.
Extending beyond previous work, we demonstrate statistically significant longitudinal associations between clinical disease severity and serum biomarkers known to be associated with HS.1,3 Establishing the sensitivity of specific biomarkers to changes in disease state over time supports their use as validated primary endpoints for HS clinical trials and prospective studies, which largely rely on subjective outcome measures to evaluate drug efficacy at present.4,5 Moreover, the effect size estimates derived from longitudinal analyses that quantifiably assess relationships between specific biomarkers and clinical measures of disease severity may ultimately help inform power calculations and dose-response modeling during early-phase trial design. Taken together, these findings suggest a role for specific serum biomarkers across multiple stages of the clinical research process.
This study is limited by its retrospective nature and small samplesize; larger prospective studies must validate our findings before they can be applied in clinical research settings more broadly. Nevertheless, this study provides a strong foundation for integrating objective biomarkers into the broader framework of HS research and, pending further validation, may ultimately support more rigorous and reproducible approaches to disease monitoring and treatment evaluation moving forward.
