Accurate long‐term prediction of death for patients with cirrhosis. Issue 3 (1st April 2022) - Goldberg, David; Mantero, Alejandro; Kaplan, David; Delgado, Cindy; John, Binu; Nuchovich, Nadine; Emanuel, Ezekiel; Reese, Peter P.
Abstract: Background and Aims: Cirrhosis is a major cause of death and is associated with extensive health care use. Patients with cirrhosis have complex treatment choices due to risks of morbidity and mortality. To optimally counsel and treat patients with cirrhosis requires tools to predict their longer‐term liver‐related survival. We sought to develop and validate a risk score to predict longer‐term survival of patients with cirrhosis. Approach and Results: We conducted a retrospective cohort study of adults with cirrhosis with no major life‐limiting comorbidities. Adults with cirrhosis within the Veterans Health Administration were used for model training and internal validation, and external validation used the OneFlorida Clinical Research Consortium. We used four model‐building approaches including variables predictive of cirrhosis‐related mortality, focused on discrimination at key time points (1, 3, 5, and 10 years). Among 30, 263 patients with cirrhosis ≤75 years old without major life‐limiting comorbidities and complete laboratory data during the baseline period, the boosted survival tree models had the highest discrimination, with 1‐year, 3‐year, 5‐year, and 10‐year survival rates of 0.77, 0.81, 0.84, and 0.88, respectively. The 1‐year, 3‐year, and 5‐year discrimination was nearly identical in external validation. Secondary analyses with imputation of missing data and subgroups by etiology of liver disease had similar results to the primary model. Conclusions: We developed and validated (internally and externally) a risk score to predict longer‐term survival of patients with cirrhosis. This score would transform management of patients with cirrhosis in terms of referral to specialty care and treatment decision‐making for non‐liver‐related care. Abstract : Using more than 10 years of data, a model using boosted survival trees had the highest discrimination to predict survival of patients with cirrhosis at 1‐, 3‐, 5‐, and 10‐years. Model performance was nearly identical in external validation. The long‐term cirrhosis survival score had superior discrimination compared to other commonly used risk scores.