title: Rapid learning in practice: a lung cancer survival decision support system in routine patient care data.
abstract: OBJECTIVE
  A rapid learning approach has been proposed to extract and apply knowledge from routine care data rather than solely relying on clinical trial evidence. To validate this in practice we deployed a previously developed decision support system (DSS) in a typical, busy clinic for non-small cell lung cancer (NSCLC) patients.
  
  
  METHODS
  Gender, age, performance status, lung function, lymph node status, tumor volume and survival were extracted without review from clinical data sources for lung cancer patients. With these data the DSS was tested to predict overall survival.
  
  
  RESULTS
  3919 lung cancer patients were identified with 159 eligible for inclusion, due to ineligible histology or stage, non-radical dose, missing tumor volume or survival. The DSS successfully identified a good prognosis group and a medium/poor prognosis group (2 year OS 69% vs. 27/30%, p<0.001). Stage was less discriminatory (2 year OS 47% for stage I-II vs. 36% for stage IIIA-IIIB, p=0.12) with most good prognosis patients having higher stage disease. The DSS predicted a large absolute overall survival benefit (∼40%) for a radical dose compared to a non-radical dose in patients with a good prognosis, while no survival benefit of radical radiotherapy was predicted for patients with a poor prognosis.
  
  
  CONCLUSIONS
  A rapid learning environment is possible with the quality of clinical data sufficient to validate a DSS. It uses patient and tumor features to identify prognostic groups in whom therapy can be individualized based on predicted outcomes. Especially the survival benefit of a radical versus non-radical dose predicted by the DSS for various prognostic groups has clinical relevance, but needs to be prospectively validated.
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia; Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, The Netherlands; Institute of Medical Physics, School of Physics, University of Sydney, Australia. Electronic address: andre.dekker@maastro.nl.
authors.forename: Andre
authors.initials: A
authors.lastname: Dekker
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia; South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia; School of Medicine, University of Western Sydney, Australia.
authors.forename: Shalini
authors.initials: S
authors.lastname: Vinod
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia; Institute of Medical Physics, School of Physics, University of Sydney, Australia; South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia; Centre for Medical Radiation Physics, University of Wollongong, Australia.
authors.forename: Lois
authors.initials: L
authors.lastname: Holloway
authors.affiliation: Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, The Netherlands.
authors.forename: Cary
authors.initials: C
authors.lastname: Oberije
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia.
authors.forename: Armia
authors.initials: A
authors.lastname: George
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia; South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia.
authors.forename: Gary
authors.initials: G
authors.lastname: Goozee
authors.affiliation: Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Australia; South Western Sydney Clinical School, University of New South Wales, Liverpool, Australia; School of Medicine, University of Western Sydney, Australia.
authors.forename: Geoff P
authors.initials: GP
authors.lastname: Delaney
authors.affiliation: Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Centre+, The Netherlands.
authors.forename: Philippe
authors.initials: P
authors.lastname: Lambin
authors.affiliation: Institute of Medical Physics, School of Physics, University of Sydney, Australia.
authors.forename: David
authors.initials: D
authors.lastname: Thwaites
mesh_terms: D000368:Aged; D002289:Carcinoma, Non-Small-Cell Lung / Q000401:mortality* / Q000473:pathology / Q000532:radiotherapy; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008175:Lung Neoplasms / Q000401:mortality* / Q000473:pathology / Q000532:radiotherapy; D008297:Male; D009367:Neoplasm Staging; D009426:Netherlands / Q000453:epidemiology; D009517:New South Wales / Q000453:epidemiology; D005791:Patient Care / Q000379:methods; D011364:Professional Practice; D011379:Prognosis
keywords: Decision support system; Lung cancer; Radiotherapy; Rapid learning