Predictive models play a pivotal role in the provision of risk-adjusted, operative mortality rates.
The purpose of the study was to describe the development of a dedicated prognostic index for quantifying operative risk in colorectal cancer surgery.
Dr Fazio and colleagues collected data from 5,034 consecutive patients undergoing major surgery in a single center from October 1976 to July 2002.
The researcher’s primary end point was 30-day operative mortality.
The investigators developed a multilevel Bayesian logistic regression model to adjust for case-mix and accommodate the variability of outcomes between surgeons.
The model applied by the researchers was internally validated (split-sample) and tested using measures of discrimination, calibration, and subgroup analysis.
| The colorectal cancer model offered discrimination and agreement between outcomes over 10 major colorectal procedures|
|Diseases of the Colon & Rectum|
The researchers included patients between 18–98 (median age, 66) years of age.
The team found that operative mortality was 2.3 % with no significant variability between surgeons or through time.
The researchers used multivariate analysis and identified age; tumor, nodes, metastases staging; mode of surgery; no-cancer resection vs. cancer resection and hematocrit level to be independent risk factors.
The researchers reported that the model offered adequate discrimination and excellent agreement between observed and model-predicted outcomes over 10 major colorectal procedures.
The team noted that the Cleveland Clinic Foundation Colorectal Cancer Model provided an accurate means of estimating risk for individual patients in the preoperative setting.
Dr Fazio concluded that, “It has important implications in everyday practice, because it may be used as an adjunct in the process of informed consent and for monitoring surgical performance through time.”