title: Analysis of regional bone scan index measurements for the survival of patients with prostate cancer.
abstract: BACKGROUND
  A bone scan is a common method for monitoring bone metastases in patients with advanced prostate cancer. The Bone Scan Index (BSI) measures the tumor burden on the skeleton, expressed as a percentage of the total skeletal mass. Previous studies have shown that BSI is associated with survival of prostate cancer patients. The objective in this study was to investigate to what extent regional BSI measurements, as obtained by an automated method, can improve the survival analysis for advanced prostate cancer.
  
  
  METHODS
  The automated method for analyzing bone scan images computed BSI values for twelve skeletal regions, in a study population consisting of 1013 patients diagnosed with prostate cancer. In the survival analysis we used the standard Cox proportional hazards model and a more advanced non-linear method based on artificial neural networks. The concordance index (C-index) was used to measure the performance of the models.
  
  
  RESULTS
  A Cox model with age and total BSI obtained a C-index of 70.4%. The best Cox model with regional measurements from Costae, Pelvis, Scapula and the Spine, together with age, got a similar C-index (70.5%). The overall best single skeletal localisation, as measured by the C-index, was Costae. The non-linear model performed equally well as the Cox model, ruling out any significant non-linear interactions among the regional BSI measurements.
  
  
  CONCLUSIONS
  The present study showed that the localisation of bone metastases obtained from the bone scans in prostate cancer patients does not improve the performance of the survival models compared to models using the total BSI. However a ranking procedure indicated that some regions are more important than others.
authors.affiliation: Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden. jonas.kalderstam@thep.lu.se.
authors.forename: Jonas
authors.initials: J
authors.lastname: Kalderstam
authors.forename: May
authors.initials: M
authors.lastname: Sadik
authors.forename: Lars
authors.initials: L
authors.lastname: Edenbrandt
authors.forename: Mattias
authors.initials: M
authors.lastname: Ohlsson
mesh_terms: D000368:Aged; D001859:Bone Neoplasms / Q000473:pathology* / Q000556:secondary*; D001842:Bone and Bones / Q000473:pathology*; D018450:Disease Progression; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized; D016571:Neural Networks, Computer; D016016:Proportional Hazards Models; D011471:Prostatic Neoplasms / Q000473:pathology*