Wednesday, February 24, 2016

Predicting the Development of Liver Cirrhosis by Simple Modelling in Patients With Chronic Hepatitis C

Alimentary Pharmacology & Therapeutics

Predicting the Development of Liver Cirrhosis by Simple Modelling in Patients With Chronic Hepatitis C

S. Lens; F. Torres; M. Puigvehi; Z. Mariño; M.-C. Londoño; S. M. Martinez; I. García-Juárez; Á. García-Criado; R. Gilabert; C. Bru; R. Solà; J. M. Sanchez-Tapias; J. A. Carrión; X. FornsDisclosures

Aliment Pharmacol Ther. 2016;43(3):364-374.


Background Data are scarce on the natural history of chronic hepatitis C (CHC) in patients with mild hepatitis C who did not respond to anti-viral therapy.

Aim To predict the risk of progression to cirrhosis, identifying patients with the more urgent need for therapy with effective anti-virals.

Methods A cohort of 1289 noncirrhotic CHC patients treated with interferon-based therapy between 1990 and 2004 in two referral hospitals were followed up for a median of 12 years.

Results Overall, SVR was achieved in 46.6% of patients. Data from a randomly split sample (n = 832) was used to estimate a model to predict outcomes. Among nonresponders (n = 444), cirrhosis developed in 123 (28%) patients. In this group, the 3, 5 and 10-year cumulative probabilities of cirrhosis were 4%, 7% and 22%, respectively, compared to <1% in the SVR-group (P < 0.05). Baseline factors independently associated with progression to cirrhosis in nonresponders were: fibrosis ≥F2, age >40 years, AST >100 IU/L, GGT >40 IU/L. Three logistic regression models that combined these simple variables were highly accurate in predicting the individual risk of developing cirrhosis with areas under the receiving operating characteristic curves (AUC) at 5, 7 and 10 years of ~0.80. The reproducibility of the models in the validation cohort (n = 457, nonresponders = 244), was consistently high.

Conclusions Modelling based on simple laboratory and clinical data can accurately identify the individual risk of progression to cirrhosis in nonresponder patients with chronic hepatitis C, becoming a very helpful tool to prioritise the start of oral anti-viral therapy in clinical practice.

Discussion Only
Full Text Available At Medscape

IFN-based therapies are being replaced by all-oral combinations, at least in those areas of the world in which these molecules are approved and affordable. In this setting, the correct identification of patients at risk of progression to cirrhosis, as well as those with a very low likelihood of progression, is very relevant. However, data on the natural history of patients with mild CHC are scarce, since large cohorts and long follow-up periods are required to assess clinical outcomes.

Evaluation of liver fibrosis is crucial in the assessment of chronic liver disease. However, liver biopsy is an invasive procedure and its accuracy may be limited by sampling error and inter and intra-observer validation.[15] Besides, liver biopsy cannot be repeated during follow-up to assess disease progression, as it may be associated with higher morbidity. In recent years, efforts have been made to develop non-invasive methods for fibrosis staging. Some of the surrogate markers of liver fibrosis have shown a good accuracy; however, data on the usefulness of such methods to predict clinical outcomes are scarce as most studies are transversal and others aim to predict liver-related events in patients who already present advanced liver disease.[16]

The main aim of our study was to develop and validate a simple model to accurately predict individual probabilities to develop liver cirrhosis. We retrospectively assessed a large number of patients mainly with mild stages of fibrosis at baseline, who underwent anti-viral therapy and were prospectively followed up for a median of 12 years. As expected, patients who achieved an SVR had excellent outcomes, with a very low incidence of cirrhosis (<1% at 10 years) and no cases of clinical decompensation. In accordance to previous data,[17, 18]the risk of HCC remained very low after SVR [two patients (0.33%), both with baseline bridging fibrosis]. On the contrary, the cumulative probability of developing cirrhosis during follow-up was remarkably high in nonresponders (7% at 5 years and 22% at 10 years), reinforcing the need of tools to accurately predict the risk of fibrosis progression. The clinical variables associated with the development of liver cirrhosis were the presence of significant fibrosis at baseline, older age, and high AST and GGT levels, which have been previously shown to be related to fibrosis progression in patients with CHC.[19–21]

According to the more recent international guidelines, all patients with chronic hepatitis C infection should be referred and considered for anti-viral therapy. The appropriate drug combination should be chosen depending on HCV genotype and subtype, the severity of liver disease and the availability of the different therapies in each country. IFN-containing regimens have globally been replaced by all-oral, IFN-free therapies with DAAs, at least in those areas of the world where these regimens are approved and their cost is covered.[22]Nevertheless, the huge economical differences between countries make IFN-free therapies not affordable for all Health Care systems. In countries where the indication of DAAs may be restricted because of budget constraints, a careful selection of candidates at risk of disease progression is crucial.

Using baseline variables with an independent predictive value, we constructed three models to forecast individual probabilities for developing liver cirrhosis over time. Model I included AST, GGT, age and fibrosis stage, while model II was simplified by excluding the information provided by liver histology. Model III was generated by including well-known and validated non-invasive fibrosis scores. All three models were equally accurate at estimating the individual risk of progression to cirrhosis among nonresponders in the long-term. Moreover, the classification of nonresponder patients according to the associated baseline probability of developing cirrhosis obtained from the multivariate logistic model was discriminative in our sample throughout the follow-up period: the highest risk group had a probability of developing cirrhosis greater than 20% over 10 years, while the lowest risk group was associated with a very low probability of developing cirrhosis (<5%). The latter may be reassuring (both for doctors and patients) if these individuals are advised to defer therapy.

Figures for models I and III are almost identical as both take into account fibrosis stage either by histological assessment or by Forns index value (Figures 2 and 4). Model II, which is based only in three variables, was accurate at identifying those patients with a very lower risk of progression but did not discriminate between individuals with intermediate and high risk of cirrhosis development (Figure 3). Importantly, the assessment of the reproducibility of the models in the validation cohort showed equally good results even in the long-term follow-up, thus strengthening the statistical power of the models.

Our study has several limitations. The first derives from the lack of paired biopsies in order to establish the diagnosis of cirrhosis, which would have provided further validation to our findings. Nevertheless, we believe that the established criteria for diagnosing liver cirrhosis were those used in routine clinical practice[12, 13] and are very accurate. For those patients in whom the diagnosis relied on US, and in order to exclude inter-observation bias, the US images were recovered and blindly re-assessed by expert radiologists to confirm the diagnosis of cirrhosis. Nonetheless, the fact that the same variables of the models were also associated with clinical decompensation or HCC (outcomes not subjected to inconsistencies) strengthens the criteria used to diagnose cirrhosis in this cohort.

A second limitation is the lack of a baseline transient elastography (TE), which is widely used in Europe to assess the fibrosis stage.[23, 24] However, the method was implemented in our Unit in 2005 and thus, the data was not available in most patients. If a baseline TE might improve the predictability of our current models needs to be assessed in future studies. Third, a selection bias cannot be excluded due to the retrospective nature of the study; our models would need further validation in a prospectivelyfollowed cohort.

Finally, in a few years from now and in a decreasing-cost scenario, anti-viral therapy might be offered to the patients even if they have a very low risk of cirrhosis after 10 years.

The strengths of our study are the large cohort of patients with a well-characterised disease and the fact that patients were followed in two large referral centres by an established protocol and the long follow-up period. An additional strength is that besides identifying patients at highest risk of progression of cirrhosis, our models are able to recognise those patients with a remarkably low risk of progression, thus facilitating clinical decisions in routine practice.

In conclusion, sustained virological response to interferon-based therapy in patients with noncirrhotic CHC eliminates liver-related complications in the long term. Among patients with chronic hepatitis C, modelling based on simple laboratory and clinical data is helpful at identifying the individual risks of progression to cirrhosis and could be used in clinical practice to better allocate patients in treatment protocols.

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