Supplementary material: Evaluation of emerging NASH therapies: the impact of treatment efficacy profiles on long-term health outcomes

These are peer-reviewed supplementary materials for the article 'Evaluation of emerging NASH therapies: the impact of treatment efficacy profiles on long-term health outcomes' published in the Journal of Comparative Effectiveness Research.Model validationSupplementary Table 1: Validation of predicted outcomesSupplemental referencesAim: Evaluations of nonalcoholic steatohepatitis (NASH) treatments require predicting lifetime outcomes from short-term clinical trials. Materials & methods: A Markov model with NASH fibrosis stages F0–F3, NASH resolution, compensated cirrhosis (F4/CC), and liver-related complication (LRC) states was developed using literature-based standard of care (SoC) data. Hypothetical efficacy profiles were defined affecting resolution (100%-increase), fibrosis improvement (100% increase), or fibrosis worsening (50% decrease). Results: For the SoC, 10-year LRC rates increased with baseline fibrosis stage (F1: 3.0%; F2: 9.8%; F3: 27.2%; F4/CC: 64.9%). The fibrosis worsening profile reduced predicted 10-year LRC rates (F1: 1.9%; F2: 6.5%; F3: 19.1%; F4/CC: 55.0%) more than the resolution and fibrosis improvement profiles (F1: 2.6%/2.6%; F2: 8.5%/8.3%; F3: 23.3%/23.0%; F4/CC: NA/59.0%). Scenario analyses considered alternative SoC progression, treatment efficacy and treatment-stopping rules. Conclusion: Potential NASH efficacy profiles have differing impacts on predicted long-term outcomes, providing insights for future stakeholders.</p

The overall survival in the whole series.

<p>Kaplan–Meier curves were generated to show the overall survival of the whole HCC patients after SIRT.</p

Patient baseline demographics and tumor characteristics.

<p>[interquartile range] are shown. HBV, hepatitis B virus; HCV, hepatitis C virus; NASH, Non-alcoholic steatohepatitis; MELD, the model for end stage liver disease; CRP, C-reactive protein; AFP, a-fetoprotein. Number (proportion) or median </p

Univariate and Multivariate Analyses of Risk Factors for Survival.

<p> = viral, 0 = nonviral. Etiology: 1</p><p> = 1, 2 = 2–5, 3 = 5 or greater. Number of nodules: 1</p><p> = <3 cm, 2 = 3–10 cm, 3 = >10 cm. Size: 1</p><p> = PR or CR, 2 = SD, 3 = PD. Choi response: 1</p

The survival probabilities among patients with good, fair and poor prognosis.

<p>Kaplan–Meier curves were generated to compare survival among patients with good, fair, and poor prognosis defined by the score according to the model at one month post-SIRT.</p

Expected survival of three hypothetical patients.

<p>Base on the equation in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082225#pone-0082225-t004" target="_blank">Table 4</a>, the expected survival probability can be calculated in individual patients with score 2.1, 2.6, and 3.1, respectively.</p

Kaplan–Meier curves were generated to compare survival between PR, SD, and PD according to three radiological assessment methods.

<p>HCC patients undergoing SIRT had radiological responses, as evaluated by three criteria: (A) RECIST 1.1, (B) mRECIST, and (C) Choi, carried out at one month post-SIRT.</p

Definition of target radiological responses.

<p>Definition of target radiological responses.</p