Evaluation of prostate cancer patients receiving multiple staging tests, including ProstaScint scintiscans

BACKGROUND: Multiple serum tests were performed on archival samples from patients who participated in trials to assess the ProstaScint scan staging ability. Traditional statistical analysis as well as artificial neural network (ANN) analysis were employed to evaluate individual patients and the group as a whole. The results were evaluated so that each factor was tested for prognostic value. METHODS: Data obtained from serum tests, bone scans, and ProstaScint scans were evaluated by traditional statistical methods and ANN to determine the individual value in clinical staging of prostate cancer. RESULTS: Two hundred seventy-five patients (180 postprostatectomy, 95 intact prostate) with prostate cancer (14 with distant metastases) were available for analysis. Data available included: clinical state (remission or progression), most recent clinical TNM stage, bone scan, and ProstaScint scan. Serum was tested for prostate-specific membrane antigen(PSMA), prostate-specific antigen(PSA), free PSA (fPSA), and complexed PSA (cPSA). Additional calculations included percent free PSA, and percent complexed PSA. Spearman individual statistical assessment for traditional group evaluation revealed no significant factors for T-stage. The free PSA and complex PSA had a significant association with node (N)-status. The distant metastases (M) stage correlated well with the bone scan and clinical stage. ANN analysis revealed no significant T-stage factors. N-stage factors showed a 95% sensitivity and 49% specificity. These factors included the presence or absence of a prostate, PSA serum levels, bone scan, and ProstaScint scans as major associated indicators. ANN analysis of the important variables for M-stage included ProstaScint scan score, and PSA levels (total, percent complexed, percent free, and fPSA). These factors were associated with a 95% sensitivity and 15% specificity level. CONCLUSIONS: Two hundred seventy-five patients receiving treatment for prostate cancer were evaluated by ANN and traditional statistical analysis for factors related to stage of disease. ANN revealed that PSA levels, determined by a variety of ways, ProstaScint scan, and bone scan, were significant variables that had prognostic value in determining the likelihood of nodal disease, or distant disease in prostate cancer patients.