title: Predicting neutropenia risk in patients with cancer using electronic data.
abstract: OBJECTIVE
  Clinical guidelines recommending the use of myeloid growth factors are largely based on the prescribed chemotherapy regimen. The guidelines suggest that oncologists consider patient-specific characteristics when prescribing granulocyte-colony stimulating factor (G-CSF) prophylaxis; however, a mechanism to quantify individual patient risk is lacking. Readily available electronic health record (EHR) data can provide patient-specific information needed for individualized neutropenia risk estimation. An evidence-based, individualized neutropenia risk estimation algorithm has been developed. This study evaluated the automated extraction of EHR chemotherapy treatment data and externally validated the neutropenia risk prediction model.
  
  
  METHODS
  A retrospective cohort of adult patients with newly diagnosed breast, colorectal, lung, lymphoid, or ovarian cancer who received the first cycle of a cytotoxic chemotherapy regimen from 2008 to 2013 were recruited from a single cancer clinic. Electronically extracted EHR chemotherapy treatment data were validated by chart review. Neutropenia risk stratification was conducted and risk model performance was assessed using calibration and discrimination.
  
  
  RESULTS
  Chemotherapy treatment data electronically extracted from the EHR were verified by chart review. The neutropenia risk prediction tool classified 126 patients (57%) as being low risk for febrile neutropenia, 44 (20%) as intermediate risk, and 51 (23%) as high risk. The model was well calibrated (Hosmer-Lemeshow goodness-of-fit test = 0.24). Discrimination was adequate and slightly less than in the original internal validation (c-statistic 0.75 vs 0.81).
  
  
  CONCLUSIONS
  Chemotherapy treatment data were electronically extracted from the EHR successfully. The individualized neutropenia risk prediction model performed well in our retrospective external cohort.
authors.affiliation: HealthPartners Institute, Minneapolis, Minnesota, USA.|Health Care Systems Research Network/National Cancer Institute Cancer Research Network, USA.|Regions Hospital Cancer Care Center, St. Paul, Minnesota, USA.
authors.forename: Pamala A
authors.initials: PA
authors.lastname: Pawloski
authors.affiliation: HealthPartners Institute, Minneapolis, Minnesota, USA.
authors.forename: Avis J
authors.initials: AJ
authors.lastname: Thomas
authors.affiliation: HealthPartners Institute, Minneapolis, Minnesota, USA.
authors.forename: Sheryl
authors.initials: S
authors.lastname: Kane
authors.affiliation: HealthPartners Institute, Minneapolis, Minnesota, USA.
authors.forename: Gabriela
authors.initials: G
authors.lastname: Vazquez-Benitez
authors.affiliation: Regions Hospital Cancer Care Center, St. Paul, Minnesota, USA.|Cancer Center of Western Wisconsin, New Richmond, Wisconsin, USA.
authors.forename: Gary R
authors.initials: GR
authors.lastname: Shapiro
authors.affiliation: Hutchinson Institute for Cancer Outcomes Research, Seattle, Washington, USA.|Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.|University of Washington School of Medicine, Seattle, Washington, USA.
authors.forename: Gary H
authors.initials: GH
authors.lastname: Lyman
mesh_terms: D000368:Aged; D000465:Algorithms; D000971:Antineoplastic Combined Chemotherapy Protocols / Q000009:adverse effects*; D057286:Electronic Health Records; D005260:Female; D016179:Granulocyte Colony-Stimulating Factor / Q000627:therapeutic use; D006801:Humans; D016247:Information Storage and Retrieval; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000150:complications* / Q000188:drug therapy; D009503:Neutropenia / Q000139:chemically induced*; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*
chemical_list: D016179:Granulocyte Colony-Stimulating Factor
keywords: chemotherapy; clinical decision support systems; computer-based decision support; febrile neutropenia; granulocyte-colony stimulating factor; risk model