Nomogram based on albumin and neutrophil-to-lymphocyte ratio for predicting postoperative complications after pancreaticoduodenectomy

Background The aim of this study was to identify a preoperative inflammatory marker with the most predictive value for postoperative complications after pancreaticoduodenectomy (PD). We then combined it with other perioperative variables to construct and validate a nomogram for complications after PD. Methods A total of 223 patients who received PD from January 2014 to July 2019 at a high-volume (>60 PDs/year) pancreatic centers in China were included in this retrospective study. All of the PDs were performed by the same surgeon who is beyond the learning curve with more than 100 PDs over the previous 3 years before 2014. 15 preoperative inflammatory markers were collected, including neutrophils, lymphocytes, high-sensitivity C-reactive protein and lactic dehydrogenase. The inflammatory markers' predicting abilities for complications were analyzed by calculating the values of an area under the curve (AUC). The complications included surgical complications (such as pancreatic fistula, delayed gastric emptying and bile leakage) and medical complications (such as sepsis, pneumonia, urinary tract infection, acute heart failure and acute liver failure) in this study. Univariable and multivariable logistic regression analyses were performed to investigate the perioperative features for independent risk factors for complications after PD. Nomograms with or without the most predictive inflammatory for complications were subsequently developed based on multivariable logistic regression using Akaike information criterion. Nomograms' performance was quantified and compared in terms of calibration and discrimination. We studied the utility of the nomograms using decision curve analysis. Results The albumin/ NLR score (ANS) exhibited the highest AUC value (0.616) for predicting postoperative complications. ANS and approach method were identified as independent risk factors for complications. The nomogram with ANS had higher C-index (0.725) and better calibration. The NRI compared between nomograms was 0.160 (95% CI: 0.023-0.296; P=0.022). By decision curve analysis, the model with ANS had higher clinical value. Conclusions The ANS is a useful predictor and an independent risk factor for postoperative complications after PD. The nomogram with ANS was constructed with better performance and more clinical benefit for predicting postoperative complications.