Effect of including cancer‐specific variables on models examining short‐term outcomes

Abstract

The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) generally has not collected cancer-specific variables. Because increasing numbers of studies are using ACS NSQIP data to study cancer surgery, the objectives of the current study were 1) to examine differences between existing ACS NSQIP variables and cancer registry variables, and 2) to determine whether the addition of cancer-specific variables improves modeling of short-term outcomes. Data from patients in the ACS NSQIP and National Cancer Data Base (NCDB) who underwent colorectal resection for cancer were linked (2006-2008). By using regression methods, the relative importance of cancer staging and neoadjuvant therapy variables were assessed along with their effects on morbidity, serious morbidity, and mortality. From 146 hospitals, 11,405 patients were identified who underwent surgery for colorectal cancer (colon, 85%; rectum, 15%). The NCDB metastatic cancer variable and the ACS NSQIP disseminated cancer variables agreed marginally (Cohen kappa coefficient, 0.454). For mortality, only the ACS NSQIP disseminated cancer variable and the NCDB stage IV variable were identified as important predictors; whereas the variables stage I through III, tumor (T)-classification, and lymph node (N)-classification were not selected. Cancer stage variables were inconsistently important for serious morbidity (stage IV, T-classification), superficial surgical site infection (N-classification), venous thromboembolism (metastatic cancer), and pneumonia (T-classification). With respect to neoadjuvant therapy, ACS NSQIP and NCDB variables agreed moderately (kappa, 0.570) and predicted superficial surgical site infection, serious morbidity, and organ space surgical site infection. The model fit was similar regardless of the inclusion of stage and neoadjuvant therapy variables. Although advanced disease stage and neoadjuvant therapy variables were predictors of short-term outcomes, their inclusion did not improve the models.