Catherine R. Stein

Development of a decision-making tool to predict risk of prostate cancer: The cancer of the prostate risk index (CAPRI) test

OBJECTIVES To provide a simple and reliable clinical prediction for an individual patients overall risk of cancer at biopsy by deriving an easily implemented test based on a generalizable model. Four variables are analyzed for inclusion in the model: prostate-specific antigen (PSA) level, digital rectal examination (DRE) results, race, and age. METHODS Two populations were used to develop and validate the test: a model (n = 633) and an independent, geographically separate, external population (n = 766). Pathology records for patients who underwent prostate biopsy between 1991 and 1995 were reviewed and screened for the presence of PSA and DRE results. Records where age and race could be determined were extracted. Multiple logistic regression was used with an iterative approach to optimize each test factor. The Wald chi-square test, receiver operating characteristic (ROC) curve, and Hosmer-Lemingshaw test were used to evaluate the models predictive capability in the two populations. RESULTS The model and external populations were significantly different for racial mix, PSA level, age, and biopsy detection rate, providing diverse populations to validate the test. Within a combined model, PSA, DRE, race, and age all demonstrated independent capability to predict cancer at biopsy. Predictive power of the overall test was high within the model population (ROC 80.8%), with minimal loss of power in the external population. The test demonstrated no significant lack of fit in either population. CONCLUSIONS Within a combined test, PSA, DRE, race, and age all contribute significantly to prediction of prostate cancer at biopsy in an individual patient. The test depicts individual risk in an easily understood, visually provocative manner and should assist the clinician and patient in reaching a decision as to whether biopsy is appropriate.

Use of New York medicaid PASs with emergency surgical episodes

The New York Products of Ambulatory Surgery (PAS) patient classification system was implemented by the state of New York for reimbursement of Medicaid ambulatory surgery claims. Using a national claims based database, the PAS system was evaluated for use with emergency department-generated surgical episodes. The PAS system performed well, but would benefit from the inclusion of age, comorbidity, and presence of multiple surgical procedures. Further, model power increased significantly when focused on total episode versus surgical charges alone. The study indicated the high degree to which emergency department-generated charges are closely tied to other charges in any overall care delivery system.