The effect of BMI on long-term outcome in patients with rectal cancer and establishment of a nomogram prediction model

Background The effects of body mass index (BMI) in patients with rectal cancer have been poorly studied and are still controversial. In this study, we aimed to assess the effect of BMI on the long-term outcome in patients with rectal cancer after radical surgery. Materials and methods Between April 2012 and December 2020, patients who received total mesorectal excision (TME) surgery were enrolled in the study. Patients were divided into four groups according to BMI level. Kaplan–Meier survival curves with log-rank tests were used to analyze overall survival (OS), Disease-free survival (DFS), local recurrence-free survival and distant metastasis-free survival. Univariate and multivariate analyses were performed to identify the risk factors associated with the long-term outcome. Nomograms were developed to predict the OS and DFS based on independent prognostic factors. Results A total of 688 patients were included in this study. The median follow-up time was 69 months. The 5-year OS rates of the control, underweight, overweight and obese groups were 79.2%, 62.2%, 88.7% and 86.3%, respectively. The 5-year DFS rates were 74.8%, 58.2%, 80.5% and 81.4%, respectively. Overweight (HR 0.534; 95% CI 0.332–0.860, p = 0.010) was an independent protective factor for OS and DFS (HR 0.675; 95% CI 0.461–0.989, p = 0.044). Underweight was an independent risk factor for DFS (HR = 1.623; 95% CI 1.034–2.548; p = 0.035), and had a trend to be an independent risk factor for OS (HR 1.594; 95% 0.954–2.663; p = 0.075). Nomograms were established to predict the 2-year OS, 5-year OS, 2-year DFS and 5-year DFS with an area under curve (AUC) of 0.767, 0.712, 0.746 and 0.734, respectively. Conclusions For rectal cancer patients after radical surgery, overweight was an independent protective factor for OS and DFS. Underweight was an independent risk factor for DFS and had a trend to be an independent risk factor for OS. Nomograms incorporating BMI and other prognostic factors could be helpful to predict long-term outcome.