title: [Logistic regression analysis of platelet transfusion effects in cases of cancer patients].
abstract: OBJECTIVE
  To explore the influencing factors of platelet transfusion effects in cancer patients.
  
  
  METHODS
  A total of 363 cases of cancer patients undergoing platelet transfusion at our hospital from January 1, 2010 to June 30, 2011 were enrolled. Only one transfusion was randomly selected for each patient for single-factor analysis. Then a binary Logistic regression analysis was performed with transfusion effects as a dependent variable and the variables with P ≤ 0.2 as covariates in single-factor analysis.
  
  
  RESULTS
  Among them, there were 280 effective and 83 ineffective transfusions with an overall effective rate of 77.1%. The single-factor analysis revealed that the P values were < 0.05 for age, platelet transfusion history, fever and antibiotic. Logistic analysis of multiple variables showed that platelet transfusion history (1-4 times compared to none, OR = 1.969,95%CI: 1.135 - 3.417; ≥ 5 times compared to none, OR = 5.260,95% CI:2.344 - 11.806), antibiotic (OR = 2.020,95%CI: 1.139 - 3.583), fever(OR = 1.789,95%CI: 1.015 - 3.153) and storage days of platelets (OR = 1.559,95%CI: 1.112 - 2.186) were independent risk factors.
  
  
  CONCLUSIONS
  Influenced by multiple factors, the effects of platelet transfusion may be improved through reducing unreasonable transfusions, using fewer storage days of platelets and avoiding transfusions during fever and antibiotic uses.
authors.affiliation: Department of Transfusion, Chinese Academy of Medical Sciences, Beijing, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Peng
authors.forename: Guo-hua
authors.initials: GH
authors.lastname: Zhao
authors.forename: Min
authors.initials: M
authors.lastname: Liu
authors.forename: Wei-qi
authors.initials: WQ
authors.lastname: Zhao
authors.forename: Xi-ying
authors.initials: XY
authors.lastname: Li
authors.forename: Chun-hua
authors.initials: CH
authors.lastname: Wang
mesh_terms: D000328:Adult; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000453:epidemiology* / Q000628:therapy*; D017713:Platelet Transfusion; D012189:Retrospective Studies