title: Individualized risk of surgical-site infection: an application of the breast reconstruction risk assessment score.
abstract: BACKGROUND
  Risk factors for surgical-site infection following beast reconstruction have been thoroughly investigated at a population level. However, traditional population-based measures may not always capture the nuances of individual patients. The authors aimed to develop a validated breast reconstruction risk assessment calculator for surgical-site infection that informs risk at an individual level.
  
  
  METHODS
  Mastectomies with immediate reconstruction (n = 16,069) from 2005 to 2011 were identified from the National Surgical Quality Improvement Program database. A multiple logistic regression model was created for postoperative surgical-site infection. Hosmer-Lemeshow, C statistic, and Brier score were computed to assess model performance. Bootstrap analysis validated the model.
  
  
  RESULTS
  A robust, validated risk model for surgical-site infection was developed using 11 covariates. The model Hosmer-Lemeshow p value was 0.371, the Brier score was 0.0357, and the C statistic was 0.682 (optimism-corrected C statistic, 0.678). The distribution of individual risks demonstrated a positive skew. Population-derived risk underestimated or overestimated individual risk by at least 1.5-fold in nearly one-fifth of all patients.
  
  
  CONCLUSIONS
  The breast reconstruction risk assessment score risk calculator for surgical-site infection mitigates the potentially inaccurate interpolation of population-based risk to individual patients. The authors concomitantly developed an online interface-accessible by patients and surgeons alike-to quantify a patient's risk for surgical-site infection, better informing evidence-based decisions and managing patient expectations.
  
  
  METHODS
  Risk, III.
authors.affiliation: Chicago, Ill.; Memphis, Tenn.; and Atlanta, Ga. From the Division of Plastic and Reconstructive Surgery and the Lynn Sage Comprehensive Breast Center, Northwestern University, Feinberg School of Medicine; the Department of Plastic and Reconstructive Surgery, Baptist Cancer Center/Vanderbilt Ingram Cancer Center; and the Division of Plastic and Reconstructive Surgery, Emory University Hospital.
authors.forename: John Y S
authors.initials: JYS
authors.lastname: Kim
authors.forename: Nima
authors.initials: N
authors.lastname: Khavanin
authors.forename: Sumanas W
authors.initials: SW
authors.lastname: Jordan
authors.forename: Jon P
authors.initials: JP
authors.lastname: Ver Halen
authors.forename: Alexei S
authors.initials: AS
authors.lastname: Mlodinow
authors.forename: Kevin P
authors.initials: KP
authors.lastname: Bethke
authors.forename: Seema A
authors.initials: SA
authors.lastname: Khan
authors.forename: Nora M
authors.initials: NM
authors.lastname: Hansen
authors.forename: Albert
authors.initials: A
authors.lastname: Losken
authors.forename: Neil A
authors.initials: NA
authors.lastname: Fine
mesh_terms: D000328:Adult; D000368:Aged; D016208:Databases, Factual; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D016015:Logistic Models; D016462:Mammaplasty; D008408:Mastectomy; D008875:Middle Aged; D057285:Precision Medicine; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D013530:Surgical Wound Infection / Q000209:etiology / Q000517:prevention & control*