Do Drains Contribute to Pancreatic Fistulae? Analysis of over 5000 Pancreatectomy Patients

INTRODUCTION

Conflicting evidence exists from randomized controlled trials supporting both increased complications/fistulae and improved outcomes with drain placement after pancreatectomy. The objective was to determine drain practice patterns in the USA, and to identify if drain placement was associated with fistula formation.

METHODS

Demographic, perioperative, and patient outcome data were captured from the most recent annual NSQIP pancreatic demonstration project database, including components of the fistula risk score. Significant variables in univariate analysis were entered into adjusted logistic regression models.

RESULTS

Of 5013 pancreatectomy patients, 4343 (87%) underwent drain placement and 18% of patients experienced a pancreatic fistula. When controlled for other factors, drain placement was associated with ducts < 3 mm, soft glands, and blood transfusion within 72 h of surgery. Age, obesity, neoadjuvant radiation, preoperative INR level, and malignant histology lost significance in the adjusted model. Drained patients experienced higher readmission rates (17 vs. 14%; p < 0.05) and increased (20 vs. 8%; p < 0.01) pancreatic fistulae. Fistula was associated with obesity, no neoadjuvant chemotherapy, drain placement, < 3 mm duct diameter, soft gland, and longer operative times. Drain placement remained independently associated with fistula after both distal pancreatectomy (OR = 2.84 (1.70, 4.75); p < 0.01) and pancreatoduodenectomy (OR = 2.29 (1.28, 4.11); p < 0.01).

CONCLUSIONS

Despite randomized controlled clinical trial data supporting no drain placement, drains are currently placed in the vast majority (87%) of pancreatectomy patients from > 100 institutions in the USA, particularly those with soft glands, small ducts, and perioperative blood transfusions. When these factors are controlled for, drain placement remains independently associated with fistulae after both distal and proximal pancreatectomy.

Gene-expression profiling to predict responsiveness to immunotherapy

Recent clinical successes with immunotherapy have resulted in expanding indications for cancer therapy. To enhance anti-tumor immune responses, and to better choose specific strategies matched to patient and tumor characteristics, genomic-driven precision immunotherapy will be necessary. Herein, we explore the role that tumor gene expression profiling (GEP) and transcriptome expression may play in the prediction of an immunotherapeutic response. Genetic markers associated with response to immunotherapy are addressed as they pertain to the tumor genomic landscape, the extent of DNA damage, tumor mutational load, and tumor-specific neoantigens. Furthermore, genetic markers associated with resistance to checkpoint blockade and relapse are reviewed. Finally, the utility of GEP to identify new tumor types for immunotherapy and implications for combinatorial strategies are summarized.