Smoking and body mass index and survival in pancreatic cancer patients

Pancreas. 2014 Jan;43(1):47-52. doi: 10.1097/MPA.0b013e3182a7c74b.

Abstract

Objective: The objective of this study was to provide further information on the role of personal characteristics and lifestyle factors, including obesity, diabetes, and tobacco smoking, on survival from pancreatic cancer.

Methods: We obtained follow-up data of pancreatic cancer patients enrolled in 2 Italian case-control studies. Information on characteristics and habits up to the time of diagnosis was collected by trained interviewers. Vital status was ascertained through population registers and record linkage with health system databases. Hazard ratios (HRs) of all-cause mortality and 95% confidence intervals (CIs) were estimated using Cox proportional hazards models.

Results: Follow-up information was retrieved for 648 cancer patients. Compared with subjects with body mass index of less than 25 kg/m, the HRs were 1.14 (95% CI, 0.94-1.39) for overweight (ie, 25-29.9 kg/m) and 1.32 (95% CI, 0.98-1.79) for obese (ie, ≥30 kg/m) patients (trend P = 0.046). The HRs were 1.37 (95% CI, 1.14-1.65) for ever, 1.30 (95% CI, 1.03-1.65) for ex-smokers, and 1.42 (95% CI, 1.16-1.73) for current versus never smokers. Increasing amount and duration of smoking were associated with reduced survival after pancreatic cancer. No association emerged with diabetes, alcohol consumption, and diet.

Conclusions: Smoking and overweight before diagnosis may play a role in the prognosis of pancreatic cancer, besides its etiology.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Body Mass Index*
  • Case-Control Studies
  • Comorbidity
  • Databases, Factual / statistics & numerical data
  • Female
  • Follow-Up Studies
  • Health Surveys / methods
  • Health Surveys / statistics & numerical data*
  • Humans
  • Italy / epidemiology
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Pancreatic Neoplasms / epidemiology*
  • Proportional Hazards Models
  • Registries / statistics & numerical data
  • Smoking / epidemiology*