A review of systemic therapy in biliary tract carcinoma.

Biliary tract carcinoma (BTC) has a poor prognosis and is increasing in incidence. Although surgery, chemotherapy and other treatment modalities have improved, surgery remains the only potential curative treatment and is appropriate for only those few patients who present with localized, resectable disease. However, for the majority of patients, unresectable disease is evident at diagnosis and about 95% of patients die within 10 years, despite the majority receiving chemotherapy. Long-term survival is significantly greater for patients with resected BTC compared to those with unresectable disease. In unresected disease, life expectancy is limited, with first-line gemcitabine/cisplatin (GEM/CIS) accepted as standard of care. Currently no standard second-line regimen which provides significant improvement of clinical outcomes exists for those who present with refractory disease or who relapse after first-line treatment. Of particular importance is establishing the impact of best supportive care (BSC) as a benchmark for survival outcomes to which the impact of treatment modalities can be compared. Survival outcome often differs significantly for patients with different prognostic factor profiles even when receiving the same therapy so that it can be difficult to predict which patient subgroup might benefit most from which therapy. Therefore, the influence of prognostic factors on survival under different therapies as well as under BSC needs to be further assessed in order to arrive at truly evidence-based, best therapeutic decisions for individual patients. Encouraging new research into the genomic landscape of BTC may help to further subdivide the BTC population into molecular-genetic clusters likely to be sensitive to different targeted therapy approaches leading to further improvements in survival. Consequently, an unmet need exists not only to develop new and more effective therapies for this devastating disease, but also to integrate original research findings into a more complex, dynamic, individualized therapeutic decision model to aid clinicians in making evidence-based, best therapeutic decisions for individual patients.