Management of Pilonidal Disease: A Review.

ABSTRACT

Importance The management of pilonidal disease continues to be a challenge due to high rates of recurrence and treatment-associated morbidity. Observations There is a heterogeneous repertoire of treatment modalities used in the management of pilonidal disease and wide practice variation among clinicians. Available treatment options vary considerably in their level of invasiveness, associated morbidity and disability, risks of complications, and effectiveness at preventing disease recurrence. Conservative nonoperative management strategies, including persistent improved hygiene, depilation, and lifestyle modification, focus on disease prevention and minimization of disease activity. Epilation techniques using both laser and intense pulse light therapy are also used as primary and adjunct treatment modalities. Other nonoperative treatment modalities include phenol and fibrin injection to promote closure of pilonidal sinuses. The traditional operative management strategy for pilonidal disease involves excision of affected tissue paired with a variety of closure types including primary midline closure, primary off-midline closure techniques (ie, Karydakis flap, Limberg flap, Bascom cleft lift), and healing by secondary intention. There has been a recent shift toward more minimally invasive operative approaches including sinusectomy (ie, trephination or Gips procedure) and endoscopic approaches. Overall, the current evidence supporting the different treatment options is limited by study quality with inconsistent characterization of disease severity and use of variable definitions and reporting of treatment-associated outcomes across studies. Conclusions and Relevance Pilonidal disease is associated with significant physical and psychosocial morbidity. Optimal treatments will minimize disease and treatment-associated morbidity. There is a need for standardization of definitions used to characterize pilonidal disease and its outcomes to develop evidence-based treatment algorithms.