title: What factors are predictive of surgical resection and survival from localised non-small cell lung cancer?
abstract: OBJECTIVE
  To investigate opportunities to reduce lung cancer mortality after diagnosis of localised non-small cell lung cancer (NSCLC) in New South Wales through surgical resection.
  
  
  METHODS
  In this cohort study, resection rates and lung cancer mortality risk were explored using multivariate logistic regression and competing risk regression, respectively. Data for 3040 patients were extracted from the NSW Central Cancer Registry for the diagnostic period 1 January 2003 to 31 December 2007. Subset analyses for patients at low surgical risk indicated resection rates and outcomes under ideal circumstances.
  
  
  METHODS
  Resection rates and lung cancer mortality.
  
  
  RESULTS
  The resection rate in NSW was estimated to be between 38% and 43%, peaking at 59% by local health district (LHD) of residence. Not having a resection was associated with older age, lower socioeconomic status, lack of private health insurance, and residence by LHD. Adjusted 5-year cumulated probabilities of death were 76% in absence of resection, 30% for wedge resection, 18% for segmental resection, 22% for lobectomy and 45% for pneumonectomy. Of 255 "low surgical risk" patients, 71% had a resection. Those not receiving a resection had a higher probability of death (adjusted subhazard ratio, 14.1; 95% CI, 7.2-27.5). If the low overall resection rate of 38%-43% in NSW were increased to 59% (the highest LHD resection rate), the proportion of all patients with localised NSCLC dying of NSCLC in the 5 years from diagnosis would decrease by about 10%, based on differences in probabilities of death by resection estimated in this study.
  
  
  CONCLUSIONS
  Potential exists to reduce deaths from NSCLC in NSW through increased resection.
authors.affiliation: Cancer Institute NSW, Sydney, NSW, Australia. david.roder@unisa.edu.au.
authors.forename: David C
authors.initials: DC
authors.lastname: Currow
authors.affiliation: Information Analysis Unit, Cancer Institute NSW, Sydney, NSW, Australia.
authors.forename: Hui
authors.initials: H
authors.lastname: You
authors.affiliation: Cancer Institute NSW, Sydney, NSW, Australia.
authors.forename: Sanchia
authors.initials: S
authors.lastname: Aranda
authors.affiliation: Royal Prince Alfred Hospital, Sydney, NSW, Australia.
authors.forename: Brian C
authors.initials: BC
authors.lastname: McCaughan
authors.affiliation: Information Analysis Unit, Cancer Institute NSW, Sydney, NSW, Australia.
authors.forename: Stephen
authors.initials: S
authors.lastname: Morrell
authors.affiliation: Information Analysis Unit, Cancer Institute NSW, Sydney, NSW, Australia.
authors.forename: Deborah F
authors.initials: DF
authors.lastname: Baker
authors.affiliation: Information Analysis Unit, Cancer Institute NSW, Sydney, NSW, Australia.
authors.forename: Richard
authors.initials: R
authors.lastname: Walton
authors.affiliation: School of Population Health, University of South Australia, Adelaide, SA, Australia.
authors.forename: David M
authors.initials: DM
authors.lastname: Roder
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000175:diagnosis / Q000401:mortality* / Q000601:surgery; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis / Q000401:mortality* / Q000601:surgery; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D009517:New South Wales / Q000453:epidemiology; D011013:Pneumonectomy; D011379:Prognosis; D012042:Registries; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends; D013997:Time Factors