Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study.

BACKGROUND: Cirrhosis is the result of advanced scarring (or fibrosis) of the liver, and is often diagnosed once decompensation with associated complications has occurred. Current non-invasive tests to detect advanced liver fibrosis have limited performance, with many indeterminate classifications. We aimed to identify patients with advanced liver fibrosis of all-causes using machine learning algorithms (MLAs). METHODS: In this retrospective study of routinely collected laboratory, clinical, and demographic data, we trained six MLAs (support vector machine, random forest classifier, gradient boosting classifier, logistic regression, artificial neural network, and an ensemble of all these algorithms) to detect advanced fibrosis using 1703 liver biopsies from patients seen at the Toronto Liver Clinic (TLC) between Jan 1, 2000, and Dec 20, 2014. Performance was validated using five datasets derived from patient data provided by the TLC (n=104 patients with a biopsy sample taken between March 24, 2014, and Dec 31, 2017) and McGill University Health Centre (MUHC; n=404). Patients with decompensated cirrhosis were excluded. Performance was benchmarked against aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 index (FIB-4), non-alcoholic fatty liver disease fibrosis score (NFS), transient elastography, and an independent panel of five hepatology experts (MB, GS, HK, KP, and RSK). MLA performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and the percentage of determinate classifications. FINDINGS: The best MLA was an ensemble algorithm of support vector machine, random forest classifier, gradient boosting classifier, logistic regression, and neural network algorithms, which achieved 100% determinate classifications (95% CI 100·0-100·0), an AUROC score of 0·870 (95% CI 0·797-0·931) on the TLC validation set (fibrosis stages F0 and F1 vs F4), and an AUROC of 0·716 (95% CI 0·664-0·766) on the MUHC validation set (fibrosis stages F0, F1, and F2 vs F3 and F4). The ensemble MLA outperformed all routinely used biomarkers and achieved comparable performance to hepatologists as measured by AUROC and percentage of indeterminate classifications in both the TLC validation dataset (APRI AUROC score 0·719 [95% CI 0·611-0·820], 83·7% determinate [95% CI 76·0-90·4]; FIB-4 AUROC score 0·825 [95% CI 0·730-0·912], 72·1% determinate [95% CI 63·5-80·8]) and the MUHC validation dataset (APRI AUROC score 0·618 [95% CI 0·548-0·691], 75·5% determinate [95% CI 71·5-79·2]; FIB-4 AUROC score 0·717 (95% CI 0·652-0·776), 75·5% determinate [95% CI 0·713-0·797]), and achieving only slightly lower AUROC than transient elastography (0·773 [95% CI 0·699-0·834] vs 0·826 [95% CI 0·758-0·889]). INTERPRETATION: We have shown that an ensemble MLA outperforms non-imaging-based methods in detecting advanced fibrosis across different causes of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with no indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could identify patients at high-risk of advanced hepatic fibrosis and cirrhosis among patients with chronic liver disease, allowing intervention before onset of decompensation. FUNDING: Toronto General Hospital Foundation.

Prevalence and predictors of nonalcoholic fatty liver disease in South Asian women with polycystic ovary syndrome.

BACKGROUND: Polycystic ovary disease (PCOS) may be a risk factor for nonalcoholic fatty liver disease (NAFLD) due to common pathogenetic pathways, including insulin resistance and obesity. Both PCOS and NAFLD are more severe in South Asian women. Data on NAFLD in South Asian women with PCOS are lacking. AIM: To investigate prevalence and predictors of NAFLD and liver fibrosis in PCOS patients from South Asia. METHODS: We conducted an observational routine screening program by means of transient elastography (TE) with associated controlled attenuation parameter (CAP). NAFLD was defined as CAP ≥ 288 decibels per meter. Significant liver fibrosis (stage 2 and higher out of 4) was defined as TE measurement ≥ 8.0 kilopascals. Elevated alanine aminotransferase (ALT) was defined as ALT > 24 IU/L, as per upper limit of normal reported in South Asian women. Biochemical hyperandrogenism was defined as free androgen index > 5. Predictors of NAFLD were determined by logistic regression analysis. RESULTS: 101 PCOS patients (mean age 36.3 years) with no significant alcohol intake or viral hepatitis were included. Prevalence of NAFLD and significant liver fibrosis was 39.6% and 6.9%, respectively. Elevated ALT was observed in 40% and 11.5% of patients with and without NAFLD, respectively. After adjusting for duration of PCOS and insulin resistance measured by homeostasis model for assessment of insulin resistance, independent predictors of NAFLD were higher body mass index [adjusted odds ratio (aOR) 1.30, 95% confidence interval (CI): 1.13-1.52], hyperandrogenism (aOR: 5.32, 95%CI: 1.56-18.17) and elevated ALT (aOR: 3.54, 95%CI: 1.10-11.47). Lifetime cardiovascular risk was higher in patients with NAFLD compared to those without NAFLD (0.31 ± 0.11 vs 0.26 ± 0.13). CONCLUSION: Despite their young age, NAFLD diagnosed by TE with CAP is a frequent comorbidity in South Asian women with PCOS and is strongly associated with higher body mass index and hyperandrogenism. Non-invasive screening strategies could help early diagnosis and initiation of interventions, including counselling on weight loss, cardiovascular risk stratification and linkage to hepatology care where appropriate.

NASH in HIV.

PURPOSE OF REVIEW: Aging-related comorbidities, including liver disease, represent the main drivers of morbidity and mortality in people with HIV (PWH). Nonalcoholic fatty liver disease (NAFLD) seems a frequent comorbidity in aging PWH nowadays. NAFLD results from a fat deposition into the liver parenchyma that may evolve to nonalcoholic steatohepatitis (NASH), a state of hepatocellular inflammation and injury in response to the accumulated fat leading to liver fibrosis and cirrhosis. We here review the current status of knowledge regarding this emerging comorbidity in PWH. RECENT FINDINGS: Recent studies suggest that PWH are at higher risk for both NASH and NASH-related liver fibrosis. Several hypothesized pathogenic mechanisms may account for this finding, including increased metabolic comorbidities, hepatotoxic effect of lifelong antiretroviral therapy, and chronic HIV infection. In clinical practice, non-invasive diagnostic tests, such as serum biomarkers and elastography, may help identify patients with NASH-related fibrosis, thus improving risk stratification, and enhancing clinical management decisions, including early initiation of interventions such as lifestyle changes and potential pharmacologic interventions. Clinicians should remain informed of the frequency, significance, and diagnostic and management approach to NASH in PWH.