Peri-complication diagnosis of hepatitis C infection: Risk factors and trends over time.

BACKGROUND & AIMS: Hepatitis C virus (HCV) is a common and treatable cause of cirrhosis and its complications, yet many chronically infected individuals remain undiagnosed until a late stage. We sought to identify the frequency of and risk factors for HCV diagnosis peri-complication, that is within six months of an advanced liver disease complication. METHODS: This was a retrospective cohort study of Ontario residents diagnosed with chronic HCV infection between 2003 and 2014. HCV diagnosis peri-complication was defined as the occurrence of decompensated cirrhosis, hepatocellular carcinoma or liver transplant within ±6 months of HCV diagnosis. Multivariable logistic regression was used to identify risk factors for peri-complication diagnosis among all those diagnosed with HCV infection. RESULTS: Our cohort included 39,515 patients with chronic HCV infection, of whom 4.2% (n = 1645) were diagnosed peri-complication; these represented 31.6% of the 5,202 patients who developed complications in the follow-up period. Peri-complication diagnosis became more common over the study period and was associated with increasing age among baby boomers, alcohol use, diabetes mellitus, chronic HBV co-infection and moderate to high levels of morbidity. Female sex, immigrant status, having more previous outpatient physician visits, a previous emergency department visit, a history of drug use or mental health visits were associated with reduced risk of peri-complication diagnosis. CONCLUSIONS: Over a quarter of HCV-infected patients with complications were diagnosed peri-complication. This problem increased over time, suggesting a need to further expand HCV screening.

The applicability of hepatocellular carcinoma risk prediction scores in a North American patient population with chronic hepatitis B infection.

BACKGROUND: Patients with chronic hepatitis B (CHB) infection are at an increased risk of developing hepatocellular carcinoma (HCC). Risk scores have been developed in Asian populations to predict HCC risk over time. AIM: To assess the performance of HCC risk prediction models in a heterogeneous population of patients with CHB. METHODS: Scores were calculated at baseline using CU-HCC, REACH-B, NGM1-HCC, NGM2-HCC and GAG-HCC models and the incidence of HCC was determined. The predictive ability of each score was evaluated using the area under the receiver operating characteristic curve (AUROC), Cox regression and plots of observed versus predicted HCC. The predictive value of the scores was compared between Asian and non-Asian patients and between cirrhotic versus non-cirrhotic with and without treatment. RESULTS: Of 2105 patients, 70 developed HCC. Increasing risk score was associated with HCC in all models. The CU-HCC model had the highest AUROC in Asian (0.85) and non-Asian (0.91) patients. Patients identified as low risk by any model had a very low incidence of HCC (0-0.15 per year), with the highest proportion of patients identified as low risk using CU-HCC (67%) or GAG-HCC (78%). The risk of HCC was similar to predicted for low-risk and medium-risk patients but was lower than predicted for high-risk patients. Treated patients had a lower than predicted risk of HCC, particularly in non-cirrhotic high-risk patients with longer follow-up. CONCLUSIONS: Although all models predicted the risk of HCC, models that incorporated parameters of liver function or cirrhosis (CU-HCC/GAG-HCC) were most accurate. Low-risk patients likely require reduced HCC surveillance.

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.

Evaluation of liver enzyme elevations and hepatotoxicity in patients treated with checkpoint inhibitor immunotherapy.

BACKGROUND AND AIMS: Immune checkpoint inhibitors (ICI) are increasingly used in cancer therapy. Elevated liver enzymes frequently occur in patients treated with ICI but evaluation is poorly described. We sought to better understand causes of liver enzyme elevation, investigation and management. METHODS: Patients treated with anti-PD-1, PDL-1 or CTLA-4 therapy in Phase I/II clinical trials between August 2012 and December 2018 were included. Clinical records of patients with significant liver enzyme elevations were retrospectively reviewed. RESULTS: Of 470 ICI-treated patients, liver enzyme elevation occurred in 102 (21.6%), attributed to disease progression (56; 54.9%), other drugs/toxins (7; 6.9%), other causes (22; 21.6%) and ICI immunotoxicity (17; 16.7%; 3.6% of total cohort). Immunotoxicity was associated with higher peak ALT than other causes of enzyme elevation (N = 17; M = 217, 95% CI 145-324 for immunotoxicity, N = 103; M = 74, 95% CI 59-92 for other causes; ratio of means 0.34, 95% CI 0.19-0.60, p = <0.001) and higher ALT:AST ratio (M = 1.27, 95% CI 0.78-2.06 for immunotoxicity, M = 0.69, 95% CI 0.59-0.80 for other causes, ratio of means 0.54, 95% CI 0.36-0.82, p = 0.004). Immunotoxicity was more often seen in patients with prior CPI exposure (41.2% of immunotoxicity vs 15.9% of patients without, p = 0.01), anti-CTLA-4 -containing ICI treatments (29.4% of immunotoxicity vs 6.8% of patients without, p = <0.001) and other organ immunotoxicity (76.5% of immunotoxicity vs 19.2% of patients without, p = <0.001). Cause for enzyme elevation was established in most patients after non-invasive investigation. Liver biopsy was reserved for four patients with atypical treatment response. CONCLUSIONS: Liver enzyme elevation is common in patients receiving ICI, but often has a cause other than immunotoxicity. A biochemical signature with higher ALT and ALT/AST ratio, a history of prior ICI exposure and other organ immunotoxicities may help to identify patients at a higher likelihood of immunotoxicity. Liver biopsy can be safely deferred in most patients. We propose an approach to diagnostic evaluation in patients with liver enzyme elevations following ICI exposure.

Noninvasive Predictors of High-Risk Varices in Patients with Non-Cirrhotic Portal Hypertension.

Non-cirrhotic portal hypertension (NCPH) comprises a heterogeneous group of liver disorders causing portal hypertension without cirrhosis and carries a high risk of variceal bleeding. Recent guidelines, based largely on patients with viral cirrhosis, suggest low likelihood of high risk varices (HRV) in patients with a liver stiffness measurement (LSM) <20 kPa and platelet count >150 × 109/L. In NCPH, LSM is often higher than healthy controls but lower than matched cirrhotic patients. The aim of this study was to assess whether LSM or other noninvasive assessments of portal hypertension could predict HRV in NCPH patients. Methods. Records of patients with NCPH seen at a single centre between 2007 and 2018 were reviewed retrospectively. Primary outcome measure was presence or absence of HRV at gastroscopy within 12 months of clinical assessment. Association of LSM or other clinical features of portal hypertension (spleen size, platelet count, platelet count/spleen length ratio (PSL), LSM-spleen length/platelet count ratio score (LSP)) with HRV and ability of these variables to predict HRV was analysed. Results. Of 44 patients with NCPH who met inclusion criteria, 34% (15/44) had HRV. In a multivariate model, spleen size and PSL correlated with HRV but platelet count, LSM, and LSP did not (spleen size: ß = 0.35, p = 0.02; OR 1.42, 95% CI 1.06-1.92; PSL: ß = -1.47, p = 0.02; OR 0.23, 95% CI 0.07-0.80). There was no significant difference between spleen size and PSL in predicting HRV (AUROC 0.81 (95% CI 0.66 - 0.91) versus 0.71 (95% CI 0.54 - 0.84), respectively, p = 0.400). Spleen size >17.2cm had sensitivity 78.6% and specificity 64.3% for prediction of HRV. Conclusions. In NCPH patients, spleen size may predict risk of HRV at gastroscopy within 12 months. LSM and platelet count are not useful to assess risk of HRV in NCPH.

Identifying cirrhosis, decompensated cirrhosis and hepatocellular carcinoma in health administrative data: A validation study.

BACKGROUND: To evaluate screening and treatment strategies, large-scale real-world data on liver disease-related outcomes are needed. We sought to validate health administrative data for identification of cirrhosis, decompensated cirrhosis and hepatocellular carcinoma among patients with known liver disease. METHODS: Primary patient data were abstracted from patients of the Toronto Center for Liver Disease with viral hepatitis (2006-2014), and all patients with liver disease from the Kingston Health Sciences Centre Hepatology Clinic (2013). We linked clinical information to health administrative data and tested a range of coding algorithms against the clinical reference standard. RESULTS: A total of 6,714 patients had primary chart data abstracted. A single physician visit code for cirrhosis was sensitive (98-99%), and a single hospital diagnostic code for cirrhosis was specific (91-96%). The most sensitive algorithm for decompensated cirrhosis was one cirrhosis code with any of: a hospital diagnostic code, death code, or procedure code for decompensation (range 88-99% across groups). The most specific was one cirrhosis code and one hospital diagnostic code (range 89-98% across groups). Two physician visit codes or a single hospital diagnostic code, death code, or procedure code combined with a code for cirrhosis were sensitive and specific for hepatocellular carcinoma (sensitivity 94-96%, specificity 93-98%). CONCLUSION: These sensitive and specific algorithms can be used to define patient cohorts or detect clinical outcomes using health administrative data. Our results will facilitate research into the adequacy of screening and treatment for patients with chronic viral hepatitis or other liver diseases.

Increased COX-2 expression in human vaginal epithelial cells exposed to nonoxynol-9, a vaginal contraceptive microbicide that failed to protect women from HIV-1 infection.

PROBLEM: Despite displaying virucidal activity in vitro, nonoxynol-9 (N-9), a vaginal contraceptive microbicide candidate, failed to reduce the rate of human immunodeficiency virus (HIV) transmission in clinical trials. With frequent use, it even increased the risk of HIV acquisition. Such outcome was postulated to be because of N-9-induced mucosal inflammation, which resulted in recruitment of HIV-target immune cells to the sites of virus entry. Understanding the mechanism underlying the response of the vaginal epithelium to N-9 is critical to properly evaluate the safety of prospective vaginal microbicides and contraceptives. METHODS AND RESULTS: Using DNA microarray and quantitative RT-PCR techniques, we observed that N-9 initiated a strong transcriptional upregulation of cyclooxygenase-2 (COX-2) in immortalized human vaginal epithelial cells (VK2/E6E7 cell line). Increased COX-2 protein expression evaluated by immunoblotting was dose- and time-dependent. The level of prostaglandin E(2) (PGE(2) ) increased subsequently to COX-2 elevation. This upregulation was in part because of NF-kB activation. CONCLUSION: Expression of COX-2, a potent inflammation-related enzyme, as well as increased secretion of PGE(2) , an important local mediator of mucosal immunoinflammatory responses, by human vaginal epithelial cells exposed to vaginal microbicide and contraceptive candidates may be used as a biomarker of undesirable compound properties.