Stage- and age-adjusted cost-effectiveness analysis of laparoscopic surgery in rectal cancer.

BACKGROUND: It has been argued that laparoscopy should be a standard treatment in rectal cancer due to its greater technical complexity. The objective of this study was to conduct a cost-effectiveness analysis to compare laparoscopy with open surgery for rectal cancer adjusting for age and clinical stage. METHODS: A real-world prospective cost-effectiveness cohort study was conducted with data on costs and effectiveness at individual patient level. A "genetic matching" algorithm was used to correct for selection bias. After balancing the sample groups, combined multivariate analysis of total costs and quality-adjusted life years (QALYs) was performed using seemingly unrelated regression (SUR) models. These models were first constructed without interactions and, subsequently, effects of any age-stage interaction were analyzed. RESULTS: The sample included 601 patients (400 by laparoscopy and 201 by open surgery). Crude cost-effectiveness analysis indicated that overall laparoscopy was cheaper and associated with higher QALYs. The SUR models without interactions showed that while laparoscopy remained dominant, the incremental effectiveness decreased to the point that it offered no statistically significant benefits over open surgery. In the subgroup analysis, at advanced stages of the disease, although none of the coefficients were significant, the mean incremental effectiveness (QALYs value) for laparoscopy was positive in younger patients and negative in older patients. Further, for advanced stages, the mean cost of open surgery was lower in both age subgroups but differences did not reach statistical significance. In early stages, laparoscopy cost was significantly lower in the subgroup younger than 70 and higher in the older subgroup. CONCLUSIONS: The cost-effectiveness of laparoscopy in surgery for rectal cancer justifies this being the standard surgical procedure in young patients and those at initial stages. The choice of procedure should be discussed with patients who are older and/or in advanced stages of the disease. Trial registration ClinicalTrials.gov Identifier: NCT02488161.

Combining statistical techniques to predict postsurgical risk of 1-year mortality for patients with colon cancer.

INTRODUCTION: Colorectal cancer is one of the most frequently diagnosed malignancies and a common cause of cancer-related mortality. The aim of this study was to develop and validate a clinical predictive model for 1-year mortality among patients with colon cancer who survive for at least 30 days after surgery. METHODS: Patients diagnosed with colon cancer who had surgery for the first time and who survived 30 days after the surgery were selected prospectively. The outcome was mortality within 1 year. Random forest, genetic algorithms and classification and regression trees were combined in order to identify the variables and partition points that optimally classify patients by risk of mortality. The resulting decision tree was categorized into four risk categories. Split-sample and bootstrap validation were performed. ClinicalTrials.gov Identifier: NCT02488161. RESULTS: A total of 1945 patients were enrolled in the study. The variables identified as the main predictors of 1-year mortality were presence of residual tumor, American Society of Anesthesiologists Physical Status Classification System risk score, pathologic tumor staging, Charlson Comorbidity Index, intraoperative complications, adjuvant chemotherapy and recurrence of tumor. The model was internally validated; area under the receiver operating characteristic curve (AUC) was 0.896 in the derivation sample and 0.835 in the validation sample. Risk categorization leads to AUC values of 0.875 and 0.832 in the derivation and validation samples, respectively. Optimal cut-off point of estimated risk had a sensitivity of 0.889 and a specificity of 0.758. CONCLUSION: The decision tree was a simple, interpretable, valid and accurate prediction rule of 1-year mortality among colon cancer patients who survived for at least 30 days after surgery.