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Algorithm predicts patients with ESLD most likely to survive therapy

BARCELONA — A new allocation treatment algorithm was effective for predicting benefit and survival rate after treatment for end-stage liver disease when hospitalized, according to findings presented at International Liver Congress.

“When patients are very ill, physicians must ensure that our concern for the patient should not result in the recommendation of treatment that will be of no benefit. We now have well validated data that allow us to more accurately predict who is likely to benefit from treatment [of ESLD] compared with previous measures,” Katrine P. Lindvig, MD, department of gastroenterology and hepatology, Odense University Hospital, Denmark, said in a press release.

Katrine P. Lindvig

Lindvig and colleagues evaluated data of 354 patients hospitalized with cirrhosis from clinical centers across Belgium, Austria and Denmark. They used a new algorithm, based on commonly used scales, to measure the severity of liver disease, including Child Pugh score, MELD score and Chronic Liver Failure-Sequential Organ Failure Assessment score. Patients were separated into two groups: patients more likely to benefit from treatment and survive intensive care therapy (n = 294), and patients least likely to survive (n = 60).

“The aim of the study was to develop and evaluate an allocation algorithm to assist decision-making regarding benefit from intensive care therapy,” Lindvig and colleagues wrote. “We hypothesized that a combination of premorbid liver function and organ failures could help separate patients who were likely to benefit from ICU [vs.] those who would not, better than organ failure alone.”

Among the patients, 40.8% likely to benefit and 76.7% least likely to benefit died. The algorithm correctly predicted mortality outcomes in 96% of the patients who died (OR = 4.7; 95% CI, 2.5–9.05). Fourteen patients in the least likely to survive group survived, of which 2.5% were still alive after 1 year (n = 9).

The algorithm correctly categorized 92.5% of patients in the Belgian cohort, 93.3% in the Austrian cohort and 99.4% in the Danish cohort.

If the algorithm is based on the acute-on-chronic liver failure (ACLF) grade alone, 23.7% of patients would be considered unlikely to benefit, but 51.2% would have survived an admission to the ICU. Adding premorbid score increased the positive predictive value from 0.67 to 0.77, thus the algorithm is superior when the premorbid liver function is combined with ACLF grade, according to the research.

“[The] use of this score may support decision-making and reduce the number of futile ICU referrals,” Lindvig and colleagues concluded.

In a press release from EASL, Tom Hemming-Karlsen, MD, PhD, EASL vice-secretary, said, “If the first duty of a physician is to do no harm, then we must continually review our decision-making tools and favor those that have the highest predictive value of treatment and importantly, treatment failure. This study adds to our knowledge of existing, well-recognized scoring systems and provides an interesting approach for review and wider discussion by the liver community.” – by Melinda Stevens

Reference:

Lindvig K, et al. Abstract PS059. Presented at: International Liver Congress; April 13-17, 2016; Barcelona.

Disclosure: The researchers report no relevant financial disclosures.