Risk Stratification Models (risk_stratification + models)

Distribution by Scientific Domains


Selected Abstracts


CT15 RISK STRATIFICATION MODELS FOR HEART VALVE SURGERY

ANZ JOURNAL OF SURGERY, Issue 2007
C. H. Yap
Purpose Risk stratification models may be useful in aiding surgical decision-making, preoperative informed consent, quality assurance and healthcare management. While several overseas models exist, no model has been well-validated for use in Australia. We aimed to assess the performance of two valve surgery risk stratification models in an Australian patient cohort. Method The Society of Cardiothoracic Surgeons of Great Britain and Ireland (SCTS) and Northern New England (NNE) models were applied to all patients undergoing valvular heart surgery at St Vincent's Hospital Melbourne and The Geelong Hospital between June 2001 and November 2006. Observed and predicted early mortalities were compared using the chi-square test. Model discrimination was assessed by the area under the receiver operating characteristic (ROC) curve. Model calibration was tested by applying the chi-square test to risk tertiles. Results SCTS model (n = 1095) performed well. Observed mortality was 4.84%, expected mortality 6.64% (chi-square p = 0.20). Model discrimination (area under ROC curve 0.835) and calibration was good (chi-square p = 0.9). the NNE model (n = 1015) over-predicted mortality. Observed mortality 4.83% and expected 7.54% (chi-square p < 0.02). Model discrimination (area under ROC curve 0.835) and calibration was good (chi-square p = 0.9). Conclusion Both models showed good model discrimination and calibration. The NNE model over-predicted early mortality whilst the SCTS model performed well in our cohort of patients. The SCTS model may be useful for use in Australia for risk stratification. [source]


Do nomograms predict aggressive recurrence after radical prostatectomy more accurately than biochemical recurrence alone?

BJU INTERNATIONAL, Issue 5 2009
Florian R. Schroeck
OBJECTIVE To compare the predictive accuracy (PA) of existing models in estimating risk of biochemical recurrence (BCR) vs aggressive recurrence (BCR with a prostate-specific antigen, PSA, doubling time, DT, of <9 months). PATIENTS AND METHODS The study included 1550 men treated with radical prostatectomy (RP) between 1988 and 2007 within the Shared Equal Access Regional Cancer Hospital database. The PA of nine different risk stratification models for estimating risk of BCR and risk of aggressive recurrence after RP was assessed using the concordance index, c. RESULTS The 10-year risks of BCR and aggressive recurrence were 47% and 9%, respectively. Across all nine models tested, the PA was a mean (range) of 0.054 (0.024,0.074) points higher for predicting aggressive recurrence than for predicting BCR alone (c = 0.756 vs 0.702). Similar results were obtained in four sensitivity analyses: (i) defining patients with BCR but unavailable PSADT (220) as having aggressive recurrence; (ii) defining these patients as not having aggressive recurrence; (iii) defining aggressive recurrence as a PSADT of <6 months; or (iv) defining aggressive recurrence as a PSADT of <12 months. The improvement in PA was greater for preoperative than for postoperative models (0.053 vs 0.036, P = 0.03). CONCLUSION Across nine different models the prediction of aggressive recurrence after RP was more accurate than the prediction of BCR alone. This is probably because current models mainly assess cancer biology, which correlates better with aggressive recurrence than with BCR alone. Overall, all models had relatively similar accuracy for predicting aggressive recurrence. [source]