STS: Bilateral Internal Thoracic Artery Graft Outperforms Single Graft for Survival Benefit

Bilateral internal thoracic artery (BITA) grafts improve survival over single internal thoracic artery (SITA) grafts starting at about 10 years after surgery, researchers reported here on January 26th at the Society of Thoracic Surgeons 40th Annual Meeting.

Results also show that the benefit becomes more pronounced with time and lasts through the second postoperative decade.

Dr. Bruce W. Lytle, The Cleveland Clinic, Cleveland, Ohio, United States, headed up a study that analysed outcomes in patients who received SITA or BITA grafts during primary isolated bypass operations for multi-vessel coronary disease between 1971 and 1989.

Because the trial was not randomised, the investigators adjusted for potential selection bias using pair matching based on propensity scores.

An analysis of 1,152 propensity-matched pairs followed for a mean of 16.2 years showed that the survival rate at 7 years was 89% in the BITA group and 87% in the SITA group. Ten-year survival rates were 81% and 78%, respectively, 15-year survival rates were 67% and 58%, and 20-year survival rates were 50% and 37%, respectively (P < .0001). “The observation that there is an average difference in survival between these two groups does not necessarily mean that the entire population benefits either equally or at all from this strategy,” Dr. Lytle noted. In fact, further analysis revealed that at the 20-year time point, 2.8% of patients could actually be expected to do worse with BITA graft. Patients who do not benefit from BITA graft are elderly patients with a small body surface area, he said. Dr. John Puskas, Associate Professor of Surgery, Division of Cardiothoracic Surgery, Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, United States, said that Dr. Lytle’s presentation is a “fundamentally important landmark paper that draws on several strengths.” These strengths, he said, include its rigorous statistical analysis that included a propensity matching model, a large sample size and a long follow-up period that was used to monitor a single hard end point – i.e., death.