Hepatitis C/Effectiveness of Sofosbuvir, Ledipasvir/Sofosbuvir, or Paritaprevir/Ritonavir/Ombitasvir and Dasabuvir

September 2016 Gastroenterology.
Volume 151, Issue 3, Pages 457–471.e5

Effectiveness of Sofosbuvir, Ledipasvir/Sofosbuvir, or Paritaprevir/Ritonavir/Ombitasvir and Dasabuvir Regimens for Treatment of Patients With Hepatitis C in the Veterans Affairs National Health Care System

George N. Ioannou, Lauren A. Beste, Michael F. Chang, Pamela K. Green, Elliott Lowy, Judith I. Tsui, Feng Su, Kristin Berry

DOI: http://dx.doi.org/10.1053/j.gastro.2016.05.049

Background & Aims
We investigated the real-world effectiveness of sofosbuvir, ledipasvir/sofosbuvir, and paritaprevir/ritonavir/ombitasvir and dasabuvir (PrOD) in treatment of different subgroups of patients infected with hepatitis C virus (HCV) genotypes 1, 2, 3, or 4.

We performed a retrospective analysis of data from 17,487 patients with HCV infection (13,974 with HCV genotype 1; 2131 with genotype 2; 1237 with genotype 3; and 135 with genotype 4) who began treatment with sofosbuvir (n = 2986), ledipasvir/sofosbuvir (n = 11,327), or PrOD (n = 3174), with or without ribavirin, from January 1, 2014 through June 20, 2015 in the Veterans Affairs health care system. Data through April 15, 2016 were analyzed to assess completion of treatments and sustained virologic response 12 weeks after treatment (SVR12). Mean age of patients was 61 ± 7 years, 97% were male, 52% were non-Hispanic white, 29% were non-Hispanic black, 32% had a diagnosis of cirrhosis (9.9% with decompensated cirrhosis), 36% had a Fibrosis-4 index score >3.25 (indicator of cirrhosis), and 29% had received prior antiviral treatment.

An SVR12 was achieved by 92.8% (95% confidence interval [CI], 92.3%–93.2%) of subjects with HCV genotype 1 infection (no significant difference between ledipasvir/sofosbuvir and PrOD regimens), 86.2% (95% CI, 84.6%–87.7%) of those with genotype 2 infection (treated with sofosbuvir and ribavirin), 74.8% (95% CI, 72.2%–77.3%) of those with genotype 3 infection (77.9% in patients given ledipasvir/sofosbuvir plus ribavirin, 87.0% in patients given sofosbuvir and pegylated-interferon plus ribavirin, and 70.6% of patients given sofosbuvir plus ribavirin), and 89.6% (95% CI 82.8%–93.9%) of those with genotype 4 infection. Among patients with cirrhosis, 90.6% of patients with HCV genotype 1, 77.3% with HCV genotype 2, 65.7% with HCV genotype 3, and 83.9% with HCV genotype 4 achieved an SVR12. Among previously treated patients, 92.6% with genotype 1; 80.2% with genotype 2; 69.2% with genotype 3; and 93.5% with genotype 4 achieved SVR12. Among treatment-naive patients, 92.8% with genotype 1; 88.0% with genotype 2; 77.5% with genotype 3; and 88.3% with genotype 4 achieved SVR12. Eight-week regimens of ledipasvir/sofosbuvir produced an SVR12 in 94.3% of eligible patients with HCV genotype 1 infection; this regimen was underused.

High proportions of patients with HCV infections genotypes 1–4 (ranging from 75% to 93%) in the Veterans Affairs national health care system achieved SVR12, approaching the results reported in clinical trials, especially in patients with genotype 1 infection. An 8-week regimen of ledipasvir/sofosbuvir is effective for eligible patients with HCV genotype 1 infection and could reduce costs. There is substantial room for improvement in SVRs among persons with cirrhosis and genotype 2 or 3 infections.

Discussion Only
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LDV/SOF, PrOD, and SOF-based antiviral regimens resulted in remarkably high SVR rates in the VA national health care system, approaching the rates reported in clinical trials. This is in contrast to previous interferon-based regimens, which consistently resulted in much lower SVR rates in real-world clinical practice than in clinical trials.12, 13, 14, 15, 16, 17 SVR rates were higher in genotype 1– (SVR 92.8%) and genotype 4–infected patients (SVR 89.6%) than genotype 2– (SVR 86.2%) or 3–infected patients (SVR 74.8%), and these differences were even greater among cirrhotic and treatment-experienced patients. Among genotype 1–infected patients, there was no significant difference in SVR rates between LDV/SOF and PrOD regimens in either unadjusted or multivariable, propensity-score-adjusted analyses, and SVR rates >90% were achieved even in subgroups such as treatment-experienced or cirrhotic patients. The short, 8-week LDV/SOF monotherapy regimen resulted in excellent SVR rate (94.3%), but was used in only 48.6% of genotype 1–infected patients eligible for 8-week therapy (ie, treatment-naïve patients with viral load <6 million IU/mL, without cirrhosis). Long, 24-week regimens did not result in higher SVR rates and were rarely used, despite being FDA-approved and American Association for the Study of Liver Diseases/Infectious Diseases Society of America–recommended32 for certain genotype 1 patients with cirrhosis.

Among a total of 17,487 patients, our study included 5250 patients with a diagnosis of cirrhosis and 5960 with a FIB-4 score >3.25 (which is highly suggestive of cirrhosis), who achieved surprisingly high overall SVR rates of 86.8% and 87.4%, respectively. These high SVR rates were driven by genotype 1–infected cirrhotic patients who had much higher SVR (90.6%; 95% CI, 89.7%–91.5%) than genotype 2 (77.3%; 95% CI 73.3%–80.9%) or genotype 3 (65.7%; 95% CI, 61.2%–69.8%). To our knowledge, this is the largest study of DAAs in cirrhotic patients and the SVR rates in genotype 1–infected patients are the highest reported in real-world clinical practice. LDV/SOF, PrOD, and SOF regimens have allowed patients with cirrhosis to be cured of HCV in substantial numbers and proportions for the first time ever. Longer follow-up of these patients is necessary to determine whether patients with cirrhosis who achieve SVR by DAAs are protected from developing progressive liver dysfunction, liver failure, or HCC and, whether they are capable of liver remodeling and regression of cirrhosis.

American Association for the Study of Liver Diseases/Infectious Diseases Society of America guidelines during the time period of our study,32 as well as the LDV/SOF package insert,33 recommend that LDV/SOF regimens should extend for 12 or 24 weeks, with the single exception of a short, 8-week LDV/SOF monotherapy regimen that “can be considered,”33 “with caution and at the discretion of the practitioner”32 in treatment-naïve, genotype 1–infected patients without cirrhosis with an HCV viral load <6 million IU/mL. This is based on a post-hoc analysis of the ION-3 clinical trial showing higher relapse rates in those treated for 8 weeks who had a viral load ≥6 million (9 of 92 [10%]) compared with those with a viral load <6 million IU/mL (2 of 123 [2%]).3 VA treatment guidelines explicitly recommended 8 weeks of treatment for this subgroup of patients.34 Indeed, our study confirmed that 8 weeks of LDV/SOF monotherapy had similarly high SVR rates (94.8%) as 12 weeks (95.3%) in this favorable subgroup. However, our results also showed that treatment was unnecessarily extended beyond 8 weeks in 1833 of 4066 patients in this subgroup, dramatically increasing the cost of treatment without increasing SVR. Our results should offer reassurance to treatment providers that 8 weeks of LDV/SOF monotherapy is sufficient duration in this subgroup.

VA treatment guidelines during the study period designated PrOD as the preferred regimen in genotype 1–infected patients except for prior null responders, those previously treated with protease inhibitors, and patients with Child’s B or C cirrhosis (in whom the preferred regimen was LDV/SOF and ribavirin for 12 weeks) and except for treatment naïve, non-cirrhotics with a viral load <6 million (in whom 8-week LDV/SOF and 12-week PrOD regimens were equally preferred). This was due to the lower cost of 12 weeks of PrOD ($22,850) compared with 12 weeks of LDV/SOF ($37,157) in the VA system during the study period and the absence of evidence that one is more effective than the other in the subgroups for which PrOD was preferred. Our data support the VA treatment recommendations because we found no difference in SVR between PrOD and LDV/SOF regimens in either adjusted or unadjusted analyses, in the entire population or in clinically relevant subgroups (cirrhosis or not, treatment-experienced or naïve). Despite these recommendations and the higher cost, LDV/SOF regimens constituted 77% and PrOD only 23% of regimens in genotype-1–infected patients. This could be due to higher prevalence of drug–drug interactions, higher pill burden, and more frequent requirement for co-prescription of ribavirin in PrOD regimens compared with LDV/SOF regimens.

After the end of the study period, and after FDA approval of elbasvir/grazoprevir as an additional regimen for genotype 1 HCV on January 28, 2016, regimen costs in the VA were further reduced dramatically, to approximately $17,000 per 12-week course for LDV/SOF, PrOD, and elbasvir/grazoprevir and treatment recommendations changed to “equally recommend” all 3 agents as of March 2016.

Genotype 3–infected patients had the lowest SVR rates in our study, just as in clinical trials. We found that the non-FDA–approved regimen of LDV/SOF and ribavirin had a higher SVR rate (77.9%; 95% CI, 73.1%–82.0%) than the longer and more expensive FDA-approved regimen of SOF and ribavirin for 24 weeks (70.6%; 95% CI, 66.9%–74.1%). However, the highest SVR rate in genotype 3–infected patients was observed in the regimen that included PEG together with SOF and ribavirin (87.0%; 95% CI, 80.0%–91.8%), the only interferon-containing regimen that is still recommended.32
Few large real-world studies of interferon-free regimens are currently available for comparison with ours. The HCV-TARGET, a prospective cohort study of patients undergoing HCV treatment in routine clinical care in academic centers, reported SVR rate to SOF and simeprevir in genotype 1–infected patients of 88% among 151 transplant recipients and 84% among 836 non-transplant recipients.35, 36 This regimen has been superseded by LDV/SOF and PrOD-based regimens. Among 487 patients with decompensated cirrhosis treated in the United Kingdom under an Expanded Access Programme with SOF, LDV/SOF, or daclatasvir, SVR was achieved in 90.5% of genotype 1– and 68.8% of genotype 3–infected patients37—very similar to our findings. A smaller VA study looked at only treatment-naïve, genotype 1–infected patients treated with LDV/SOF and reported SVR rates almost identical to ours among this subgroup.38 The TRIO Network, which compiles data from participating “real-world” academic and community HCV treatment clinics in the United States, reported in an abstract an SVR rate of 94% among 1521 genotype 1–infected patients treated with LDV/SOF monotherapy.39
The main limitation of our study was that SVR data were unavailable in 9% of patients, which can lead to overestimated SVR rates among those with available SVR data. We think this is unlikely for 2 reasons. First, patients with missing SVR data were similar to those with available SVR data (Supplementary Table 2). Although early discontinuation of treatment in <8 weeks was more common in patients with missing SVR data (25% vs 4.4%), the majority of patients with missing SVR completed 8 or more weeks of treatment, demonstrating that patients with missing SVR data were not patients who “dropped out” of treatment or were “lost to follow-up,” but rather patients (or physicians) who were simply delinquent in getting their SVR viral load measured after the end of their treatment—not an uncommon phenomenon outside of clinical trials. Second, we used comprehensive multiple imputation models that included duration of treatment in addition to baseline, pretreatment characteristics to impute the missing SVR data and found only a non-substantial reduction in SVR after imputation (Table 5), suggesting that it is unlikely that our results of observed SVR are biased toward overestimation due to the missing SVR data. Important strengths of the study include the complete ascertainment of filled pharmacy prescriptions and the utilization of complete electronic medical records since 1999 from a national health care system that treats the greatest number of HCV-infected patients in the United States.

Our results demonstrate that LDV/SOF, PrOD, and SOF regimens can achieve remarkably high SVR rates in real-world clinical practice, especially in genotype 1–infected patients. The main obstacle to curing HCV infection in the maximum possible number of patients is currently the cost of HCV antiviral regimens. It is expected that cost will decline dramatically as more antiviral regimens become FDA-approved, resulting in competition between manufacturers. In fact, costs decreased dramatically within the VA after the completion of our study and after the FDA approval of elbasvir/grazeprevir in January 2016. The VA health care system has budgeted $1.5 billion nationally for antiviral medications for fiscal year 2016, while every health care organization in the United States is faced with similar budgetary constraints due to the cost of antiviral medications. We hope that our results will be used to determine the most cost-effective ways to treat HCV-infected patients and to reassure patients, clinicians, and health care systems that current treatments for HCV, though costly, appear to be effective in the real-world setting.

Author contributions: George Ioannou: Study concept and design, acquisition of data, statistical analysis and interpretation of data, drafting of the manuscript, critical revision of the manuscript, obtained funding. Pamela Green: Analysis of data. Elliott Lowy: Analysis of data. Kristin Berry: Study design and analysis of data. Feng Su: Study design and critical revision of the manuscript. Michael F. Chang: Study design and critical revision of the manuscript. Judith Tsui: Study design and critical revision of the manuscript. Lauren Beste: Study design and critical revision of the manuscript. George Ioannou is the guarantor of this paper. All authors approved the final version of the manuscript.

Article Outline
  1. Methods
    1. Data Source: The Veterans Affairs Corporate Data Warehouse
    2. Study Population and Antiviral Regimens
    3. Baseline Characteristics
    4. Sustained Virologic Response
    5. Statistical Analysis
  2. Results
    1. Treatment Regimens by Genotype
    2. Patient Characteristics
    3. Early Discontinuation of Treatment
    4. Overall Sustained Virologic Response Rates by Genotype
    5. Utilization and Sustained Virologic Response Rates of 8-Week Ledipasvir/Sofosbuvir Regimens
    6. Utilization and Sustained Virologic Response Rates of 24-Week Ledipasvir/Sofosbuvir and Paritaprevir/Ritonavir/Ombitasvir Regimens
    7. Sustained Virologic Response Rates in Patients With Cirrhosis
    8. Sustained Virologic Response Rates in Treatment-Experienced vs Treatment-Naïve Patients
    9. Independent Predictors of Sustained Virologic Response
    10. Impact of Missing Sustained Virologic Response Data and Imputation for Missing Sustained Virologic Response
  3. Discussion
  4. Supplementary Material
  5. References

Australia/Liver cancer time-bomb as up to 70% people with Hep C miss out on follow-up testing

Liver cancer time-bomb as up to 70% people with Hep C miss out on follow-up testing

Up to 70 per cent of Victorians with suspected hepatitis C may not have received follow-up testing, putting them at risk of chronic liver disease and even cancer, University of Melbourne researchers say.

Testing rates for the disease — which affects almost 10 times more Australians than HIV — were lowest among young people aged 15-24, representing a massive missed opportunity for treatment before the disease becomes serious, according to a paper in the Australian and New Zealand Journal of Public Health.

Lead author Kathryn Snow, of the University’s School of Population and Global Health, warned that liver cancer rates — which have tripled in Australia since 1982 — could spiral without a concerted effort to raise awareness of hepatitis C among GPs and people living with the disease.

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Association of Sjögrens Syndrome in Patients with Chronic Hepatitis Virus Infection: A Population-Based Analysis

Research Article
Association of Sjögrens Syndrome in Patients with Chronic Hepatitis Virus Infection: A Population-Based Analysis
Chih-Ching Yeh, Wen-Chang Wang, Chien-Sheng Wu, Fung-Chang Sung, Chien-Tien Su, Ying-Hua Shieh, Shih-Ni Chang, Fu-Hsiung Su PLOS Published: August 25, 2016

The association between Sjögren’s syndrome (SS) and chronic hepatitis virus infection is inconclusive. Hepatitis B (HBV) and hepatitis C virus (HCV) infections are highly prevalent in Taiwan. We used a population-based case-control study to evaluate the associations between SS and HBV and HCV infections.

Materials and Methods
We identified 9,629 SS patients without other concomitant autoimmune diseases and 38,516 sex- and age-matched controls without SS from the Taiwan National Health Insurance claims data between 2000 and 2011. We utilized multivariate logistic regression to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of the associations between SS and HBV and HCV infections. Sex- and age-specific (<55 and ≥55 years) risks of SS were evaluated.

The risk of SS was higher in patients with HCV than in those without chronic viral hepatitis (OR = 2.49, 95% CI = 2.16–2.86). Conversely, HBV infection was not associated with SS (OR = 1.10, 95% CI = 0.98–1.24). Younger HCV patients were at a higher risk for SS (<55 years: OR = 3.37, 95% CI = 2.62–4.35; ≥55 years: OR = 2.20, 95% CI = 1.84–2.62). Men with HCV were at a greater risk for SS (women: OR = 2.26, 95% CI = 1.94–2.63; men: OR = 4.22, 95% CI = 2.90–6.16). Only men with chronic HBV exhibited a higher risk of SS (OR = 1.61, 95% CI = 1.21–2.14).

HCV infection was associated with SS; however, HBV only associated with SS in men

Discussion Only
Full Text Available @ PLOS ONE

In this large-scale, population-based case-control study in a highly prevalent chronic HBV and HCV infection area, we observed a positive significant association between SS and chronic HCV infection. Sex-stratification analysis also revealed that HBV-infected men had a significantly higher risk of SS.

In 1992, Haddad et al. reported lymphocytic sialadenitis in 57% of HCV-infected patients and 5% of controls [10]; hence, the debate over the association between SS with HCV began two decades ago. Accordingly, numerous HCV-associated SS cases have been reported. SS has been suggested as one of the systematic autoimmune diseases most closely associated with HCV [29]. A higher prevalence of SS was noted in patients with HCV infection (25.9%) than in those with HBV infection (3.4%) in a Japanese study [9]. Ramos-Casals et al. reported that 13% of patients with chronic HCV infection in Spain also had SS [8]. A significant overall association between HCV infection and SS was observed in a recent meta-analysis [11]. There is increasing evidence from experimental [30], virological [31,32], and clinical studies [13,33,34] suggesting that HCV and SS may share some overlapping etiological characteristics. Ramos-Casals and his colleagues proposed the term SS “secondary to HCV” (SS-HCV) to implicate the development of SS in a particular subset of HCV patients [6]. Although there is no significant difference in any histological examination between the groups, SS-HCV tends to present at an older age and at a reduced female to male ratio when compared with primary SS patients without HCV. Ramos-Casals reported a reduced female:male ratio (3:1) and older age (58.3± 1.17 vs 52.7±0.85) of SS-HCV compared with primary SS patients [6]. In the study of Brito-Zeron et al., SS-HCV patients showed a reduced female:male ratio (5:1 vs 14:1) and an older age (mean age of 62.9 years) when compared with primary SS [5]. In our study, the female:male ratio and median age of the SS subjects were 6.7:1 and 55, respectively. Another Taiwanese group reported the female:male ratio of SS to be 7.9 [3]. In Taiwan, in order to be considered for a CIC for SS, patients must fulfill at least four criteria of the 2002 European classification for SS with at least one of the two mandatory criteria (positive salivary gland biopsy or anti-Ro/La antibodies). The application is then reviewed by rheumatologists commissioned by the Bureau of the NHI system for CIC eligibility and coded specifically with ICD-9-CM 710.2 for subsequent services. Although Ramos-Casals et al. proposed the term ‘‘SS secondary to HCV” for patients who fulfill the 2002 classification criteria for SS [6], we still feel confident with our data source. In addition, our data also showed that young HCV carriers carry a higher risk of SS when compared with non-HCV carriers.

SS-HCV patients also demonstrate lower frequencies of autoantibodies against Ro and La human ribonucleoproteins and complementaemia and a higher prevalence of cryoglobulinmic-related immunological markers including rheumatoid factor (RF) than primary SS patients without HCV [7,35]. However, the pathogenesis from autoantibody formation to the full clinical manifestation of HCV-associated SS is not well established. The proposed mechanism involves cross-reactivity between the HCV envelope and host salivary tissue or HCV envelope-mediated immune reaction against salivary glands [36]. Hence, Ramos-Casals et al. suggested that primary SS and SS-HCV are two separate processes [6]. However, whether HCV mimics primary SS or is directly responsible for the development of primary SS in a subset of patients remains controversial [35]. Further studies are needed to clarify this issue.

Some comorbidities have been associated with HCV in the literature including diabetes and CAD [37,38]. Hence, we further analyzed DM and CAD to investigate any possible interaction between HCV and the comorbidities that may have contributed to the association detected in this study between HCV and SS. Our results indicate that CAD and liver cirrhosis are independent risk factors of SS (OR = 1.28, 95% CI = 1.20–1.37 and OR = 2.74, 95% CI = 2.19–3.44, respectively) (Table 5). Interestingly, DM demonstrated an independent protective effect toward SS (OR = 0.78, 95% CI = 0.72–0.84). Further prospective studies are warranted to verify this finding.

In our study, we detected a higher odds ratio among younger patients with SS and HCV. We hypothesize that a gradual change in the HCV genotype and its interaction with environmental factors may underlie this observation. In Taiwan, the 1b HCV genotype has historically been the most prevalent in the general population, dwarfing the prevalence of subtype 2a [39]. The most suspected routes of transmission included illegal medical interventions, such as the use of nondisposable needles, the sharing of syringes and fluid for injection, and blood transfusion-related infections and may have been responsible for the spread of the 1b HCV genotype among older Taiwanese [39]. However, in recent years the 2a genotype has been observed with increasing frequency among younger individuals. These young people are often HIV-positive persons with a history of injection drug use [40]. One study demonstrated a high prevalence of HCV infection among HIV-infected intravenous drug users in Taiwan with a predominance of infection due to genotypes 1a, 6a, and 3a, instead of 1b [41]. 2a was a predominant genotype among acute hepatitis C among HIV-infected individuals in another matched case-control study in Taiwan [42].

HBV-related SS has rarely been investigated and remains controversial. Aprosin et al. suggested the involvement of the virus in the etiology of SS in early 1990 [14,4346]. Marcos et al. reported that only 5 (0.83%) of 603 patients with SS tested positive for HBsAg, which hints at a null association between chronic HBV infection and SS [15]. In Taiwan, Chen et al. observed that 18 of 175 patients with SS were positive for HBsAg, revealing that SS has a significantly lower prevalence of HBV than the general population (10.3% vs. 17.3%, p < 0.001) [47]. In another Taiwanese study, the prevalence of anti-SSA and anti-SSB autoantibodies was lower in HBV carriers (1.9% and 0%) than in HCV carriers (12.8% and 9.7%). Both anti-SSA and anti-SSB antibodies are critical markers of SS [48]. In a study by Nagao et al., the prevalence of SS in patients with chronic HCV infection was significantly higher than that in patients with chronic HBV infection [9]. Recently, Ram et al. suggested that HBV infection protects against autoimmune disorders, including SS [14].

In our study, we clearly observed that patients with chronic HBV infection are at a lower risk for SS than those with chronic HCV infection. This may be explained through increased an increased risk of extrahepatic manifestations among HCV patients, involving renal, rheumatologic, dermatologic, as well as hematologic abnormalities [49]. Such extrahepatic manifestations are likely to arise from immunologically triggered mechanisms and virus invasion and replication. In HCV, lymphatropic character may explain the cause of HCV-associated extrahepatic manifestations [50] and may also explain why patients with HCV were observed to have a greater risk of SS than those infected with HBV.

A strength of this study is that it is the first to use a nationwide population-based data set to investigate the association between SS and chronic viral hepatitis. The statistical power offered by our large sample size enabled us to stratify our estimates of association by both sex and age, thus allowing us to provide the first sex and age specific estimates to the literature.

Several limitations of this study should be considered. First, it is possible that some patients with hepatitis were misclassified and were included in the control group. This may have occurred if they did not elect to seek medical treatment for their condition and thus did not receive a diagnosis. In any case, assuming that there is a causal association between viral hepatitis infection and SS, this misclassification would bias our estimate toward the null, thus leaving us with a more conservative estimate and greater confidence in the presence of the association.

Second, using ICD-9-CM diagnosis codes to identify patients with SS, HBV, and HCV infections, and comorbidities may not be as accurate as identifying patients in a clinical setting according to more standardized diagnostic criteria. However, the NHI Bureau has several self-policing mechanisms to better ensure for higher coding accuracy and quality of care. These include the scheduled random review of charts and claims along with patient interviews at every hospital with punitive measures being imposed for inconsistencies. The diagnostic accuracy among SS patients can be expected to be particularly high. SS patients are closely vetted prior to their inclusion in the CIC category due to the high economic burden incurred by the state which takes responsibility for the patient’s medical treatment. To minimize the possibility of enrolling patients with secondary SS in our case group, we excluded patients who were diagnosed with other autoimmune diseases before or after SS diagnosis.

Third, while our use of the CIC category enhanced our case validity, our utilization of two data bases may have biased the results of our analysis. By only selecting CIC cases, we may have been able to avoid recruiting patients with sicca syndrome, which is only defined by symptoms, and solely recruit SS cases that require rheumatologists to assess specific diagnostic criteria. However, we used the LHID2000 to select our controls. The stringent diagnostic criteria required for the CIC program produces a difference in the severity of disease found among CIC patients and the general population in the LHID2000. Thus, it is possible that the LHID2000 contained less severe version of SS that were not included in the CIC program. If this were the case, some of our controls may have had mild versions of SS which would have worked to bias our results towards the null and produce a more conservative estimate.

Fourth, some may argue that HBsAg and anti-HCV are not reliable metrics for defining chronic viral hepatitis infections. However, in our previous study, the predictive value of HBsAg testing alone was 97% among 367 adults born prior to the national HBV vaccination [51]. In addition, to further increase the diagnostic accuracy, this study only considered subjects to have HBV and HCV if they received at least three out-patient diagnoses or at least one in-patient diagnosis.

Fifth, nearly all the residents of Taiwan are of Han Chinese ethnicity and our results should be generalized with caution. Due to epidemiological, demographic, and cultural differences, it is likely that the transmission route of viral hepatitis differs between locations and peoples.

Sixth, it is possible that viral hepatitis patients were more likely to be diagnosed with SS purely on account of their increased exposure to the medical community. However, on account of the low out-of-pocket costs, lack of barriers to specialist care, and convenient access across the country provided by the Taiwanese national insurance program, Taiwanese readily seek medical care in the event of any discomfort, thus making this type of bias highly unlikely.

Seventh, laboratory data were unavailable in the claims records; therefore, we could not analyze the risk factors for SS in detail. Finally, according to both prior research and the results of this study presented in Table 5, it is evident that liver cirrhosis is an independent risk factor for SS. While we have statistically adjusted for the effect of liver cirrhosis in each of the analyses performed in this study, it remains possible that our results suffered from residual confounding.

We found evidence indicating that chronic HCV infection associates with SS. However, our results also indicate that patients with chronic HBV infection are at a lower risk for SS when compared with those with chronic HCV infection. Additional studies are warranted to apply our findings to other geographical regions or races, and for clarifying the biological mechanisms underlying the associations detected in this study.

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Liver Cancer is one of eight cancers linked to overweight and obesity

Liver Cancer is one of eight cancers linked to overweight and obesity

A Working Group of 21 independent international experts met at the International Agency for Research on Cancer (IARC) on 5–12 April 2016 to assess the cancer-preventive effects of the absence of excess body fatness. A summary of the evaluations has now been published in The New England Journal of Medicine.

The systematic review which involved more than 1000 studies on the link between overweight/obesity and cancer found obesity is linked to the following types of cancer: stomach, gall bladder, liver, pancreas, meningioma (a brain tumor), ovary, multiple myeloma (a blood cancer) and thyroid.

The detailed assessments will be published as Volume 16 of the IARC Handbooks of Cancer Prevention. Also available is a Q&A on the Handbooks Volume 16 evaluations.

IARC identifies eight additional cancer sites linked to overweight and obesity

Press Release
Lyon, France, 25 August 2016 – A new evaluation carried out by the IARC Handbooks of Cancer Prevention programme has concluded that overweight/obesity is a risk factor for more cancer sites than previously established. Based on a systematic review of the published scientific literature, the Working Group for IARC Handbooks of Cancer Prevention Volume 16: Body Fatness provided the latest evaluation of the cancer-preventive effects of the absence of excess body fatness. A summary of the results is published today in The New England Journal of Medicine.

A Working Group of 21 independent international experts, convened by the International Agency for Research on Cancer (IARC), assessed more than 1000 studies, including intervention trials, cohort and case–control studies, studies in experimental animals, and studies on the mechanisms linking excess body fatness and cancer.

“This comprehensive evaluation reinforces the benefits of maintaining a healthy body weight in order to reduce the risk of several different types of cancer,” says Dr Béatrice Lauby-Secretan, lead author of the new article.

Link between overweight/obesity and cancer
The experts confirmed the previous evaluation of the IARC Handbooks (Volume 6, published in 2002) that the absence of excess body fatness reduces the risk of cancers of the colon and rectum, oesophagus (adenocarcinoma), kidney (renal cell carcinoma), breast in postmenopausal women, and endometrium of the uterus.

In addition, the review of the available literature for middle-aged adults showed that there is sufficient evidence in humans that the absence of excess body fatness reduces the risk of cancers of the gastric cardia, liver, gallbladder, pancreas, ovary, and thyroid, and meningioma, and multiple myeloma. There is also limited evidence that the absence of excess body fatness reduces the risk of fatal cancer of the prostate, cancer of the breast in men, and diffuse large B-cell lymphoma.

The Working Group also reviewed data pertaining to body fatness in children, adolescents, and young adults (aged up to 25 years) to assess whether obesity at earlier periods of life is linked with cancer in adult life. For several cancer sites, including the colon and the liver, associations between excess body weight and cancers were observed that were similar to those reported in adults.

It is well established that overweight in experimental animals increases the incidence of several types of cancer. Studies in overweight animals showed that caloric or dietary restriction reduces the risk of cancers of the mammary gland, colon, liver, pancreas, skin, and pituitary gland.

Global burden of overweight and obesity Body fatness is assessed primarily by body mass index (BMI), defined as a person’s weight in kilograms divided by the square of their height in metres (kg/m2). In adults, overweight is defined as BMI ≥ 25 kg/m2, and obesity as BMI ≥ 30 kg/m2. Worldwide, an estimated 640 million adults were obese in 2014 (a 6-fold increase since 1975) and 110 million children and adolescents were obese in 2013 (a 2-fold increase since 1980).

The estimated age-standardized prevalence of obesity in 2014 was 10.8% in men, 14.9% in women, and 5.0% in children, and globally more people are overweight or obese than are underweight.

In 2013, an estimated 4.5 million deaths worldwide were attributable to overweight and obesity. The identification of new obesity-related cancer sites will add to the number of deaths worldwide attributable to obesity.

“The new evidence emphasizes how important it is to find effective ways, at both the individual and societal level, to implement World Health Organization recommendations on improving diets and physical activity patterns throughout life if the burden of cancer and other noncommunicable diseases is to be tackled,” says IARC Director Dr Christopher Wild.

Listen: LA County treating few people for hepatitis C

  • Wednesday, August 24, 2016
  • Posted by HCV New Drugs
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LA County treating few people for hepatitis C
Rebecca Plevin
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Health Services, which provides health care for about half a million low-income people, started dispensing these drugs a little over a year ago. As of the beginning of this month, the department had approved hepatitis C treatment for a total of 160 people; 81 have completed or begun treatment.

Compare that with the San Francisco Health Network, which serves about 65,000 people overall. It began treating patients for hepatitis C a little less than two years ago. As of late June, it had treated 631 people for hepatitis C.

Read the article or listen to the program..

The Complex Math Behind Spiraling Prescription Drug Prices

The Complex Math Behind Spiraling Prescription Drug Prices

This is an update of an article that was published earlier this year.

The soaring cost of prescription drugs has generated outrage among politicians and patients. Some cancer drugs carry price tags of more than $100,000 a year, and health plans are increasingly asking people to shoulder a greater share of the cost.

What is the controversy over drug pricing all about?
Much of the attention has focused on a handful of pharmaceutical companies that have snapped up old drugs and then aggressively raised prices, sometimes by more than 1,000 percent.

Read the article, here...

August - Recruiting and upcoming hepatitis C clinical trials

August - Recruiting and upcoming hepatitis C clinical trials 

This is not a complete list of HCV clinical trials, to find out if a study is enrolling patients in your area please click here, or here for hepatitis trials listed by state.

Learn more about drugs used to treat hepatitis C by viewing the following links;

I highly suggest you begin with this incredible new blog recently launched by HCV Advocate; HCV Medications Blog. The blog is easy to navigate with treatment information listed clearly by HCV genotype. ​In addition each month HCV Advocate puts out a newsletter with helpful articles about living with or treating the virus. An overview of approved drugs or agents still under investigation is offered as well.

Hepatitis C Cures: New Drugs and Treatment Discussed
Hepatitis C can now be cured. There are new FDA approved medicines to treat hepatitis C with over a 95% cure rate. Dr. Joseph Galati with Liver Specialists of Texas discusses the new drugs including Epclusa, Zepatier, Harvoni, Sovaldi, Viekira Pak, and Olysio.

News Updates - Epclusa
Gilead's Epclusa®  FDA approved June 28,2016 is a once-daily, fixed-dose combination of Sovaldi with velpatasvir (GS-5816) a pangenotypic NS5A inhibitor, for the treatment of genotype 1-6 chronic hepatitis C virus (HCV) infection.

Category: Epclusa

Approved Treatments for Hepatitis C

Treating HCV According To Genotype

August - Recruiting and upcoming hepatitis C clinical trials

This study is currently recruiting participants
Efficacy and Safety of Sofosbuvir/Velpatasvir Fixed Dose Combination (FDC) and Sofosbuvir/Velpatasvir FDC and Ribavirin in Participants With Chronic Genotype 3 HCV Infection and Cirrhosis
Please refer to this study by its ClinicalTrials.gov identifier: NCT02781558
Contacts - Locations
Contact: Gilead Study Team 342-2097alerts@gilead.com
Condition: Hepatitis C Virus Infection
Interventions: Drug: SOF/VEL; Drug: RBV

Find Out More

This study is currently recruiting participants
Safety, Tolerability and Efficacy of Sofosbuvir, Velpatasvir, and GS-9857 in Subjects With Previous DAA Experience
Please refer to this study by its ClinicalTrials.gov identifier: NCT02745535
Condition: Chronic Hepatitis C
Intervention: Drug: Sofosbuvir/Velpatasvir/GS-9857
Contact: Eleanor Wilson, MD 410-706-1710 ewilson@ihv.umaryland.edu
Contact: Jennifer Hoffmann, MSN/MPH 410-706-0294 jhoffmann@som.umaryland.edu 
United States, Maryland
Institute of Human Virology Recruiting
Baltimore, Maryland, United States, 21201

This study is not yet open for participant recruitment
Please refer to this study by its ClinicalTrials.gov identifier: NCT02783976
Contacts - Locations
Contact: 334-1685 Gilead Study Team GS-US-334-1685@gilead.com
Condition: HCV Infection Intervention: Drug: SOF Sponsor: Gilead Sciences
verified May 2016 (Source: ClinicalTrials.gov)
May 24, 2016

This study is currently recruiting participants
Sofosbuvir/Velpatasvir Fixed Dose Combination in Participants With Chronic Hepatitis C Virus Infection Who Have Received a Liver Transplant
Please refer to this study by its ClinicalTrials.gov identifier: NCT02781571
Contacts - Locations
Contact: Gilead Study Team 342-2104alerts@gilead.com
Condition: Hepatitis C Virus Infection Intervention: Drug: SOF/VEL Sponsor: Gilead Sciences

Some locations are open for participant recruitment
Please refer to this study by its ClinicalTrials.gov identifier: NCT02786537
Contact: Gilead Study Team 342-2104alerts@gilead.com  
Condition: Chronic Hepatitis C Interventions
Drug: sofosbuvir/ledipasvir; Drug: ombitasvir/paritaprevir/ritonavir and dasabuvir; Drug: elbasvir/grazoprevir
Sponsors: University of North Carolina, Chapel Hill; Patient-Centered Outcomes Research Institute; Merck Sharp & Dohme Corp.; AbbVie - verified May 2016 (Source: ClinicalTrials.gov)

United States, Arkansas
Liver Wellness Center
Not yet recruiting
Little Rock, Arkansas, United States, 72205
Contact: Lynn Frazier, ARNP    501-687-9300    LFRAZIER@ADCLR.COM   
Principal Investigator: Alonzo Williams, MD         
United States, California
UCSD Medical Center
Not yet recruiting
San Diego, California, United States, 92103
Contact: Sharon Quigley    858-657-5147    sjquigley@ucsd.edu   
Principal Investigator: Alexander Kuo, MD         
UCSF/San Fran General Hospital
Not yet recruiting
San Francisco, California, United States, 94110
Contact: Yu-Chi Lapid       Yu-Chi.Lapid@ucsf.edu   
Principal Investigator: Mandana Khalili, MD         
Univ of California, San Francisco
San Francisco, California, United States, 94143
Contact: Daisy Rios    415-476-8063    daisy.rios@ucsf.edu   
Principal Investigator: Nora Terrault, MD         
United States, Connecticut
Yale University Digestive Diseases
New Haven, Connecticut, United States, 06520
Contact: Claudia Bertuccio    203-785-2204      
Principal Investigator: Joseph Lim, MD         
United States, District of Columbia
Georgetown University
Washington, District of Columbia, United States, 20007
Contact: Erica Christian       erica.christian@gunet.georgetown.edu   
Principal Investigator: Coleman Smith, MD         
United States, Florida
University of Florida
Gainesville, Florida, United States, 32610-0272
Contact: Patrick Horne, ARNP    352-273-9500    PATRICK.HORNE@MEDICINE.UFL.EDU   
Contact: Briana Foerman, BS    352-294-5152    briana.foerman@medicine.ufl.edu   
Principal Investigator: Giuseppe Morelli, M.D.         
University of Florida, Jacksonville
Jacksonville, Florida, United States, 32209
Contact: Kelly Jackman, PHD    904-633-0070    kelly.jackman@jax.ufl.edu   
Principal Investigator: Miguel Malespin, MD         
University of Miami/Schiff Center for Liver Diseases
Miami, Florida, United States, 33136
Contact: Eva Pavicic       epavicic@med.miami.edu   
Contact: Maria Onate-Silva       mlourdeso@med.miami.edu   
Principal Investigator: Eugene Schiff         
Orlando Immunology Center
Orlando, Florida, United States, 32803
Contact: Jeff Dinsmore    407-409-7125    jdinsmore@oicorlando.com   
Principal Investigator: Federico Hinestrosa, MD         
United States, Georgia
Internal Medicine Associates of Wellstar Atlanta Medical Center
Atlanta, Georgia, United States, 30312
Contact: Howard Brown    404-265-4194    dyardmon3@gmail.com   
Principal Investigator: Brian Pearlman, MD         
United States, Illinois
Northwestern University
Not yet recruiting
Chicago, Illinois, United States, 60611
Contact: Sara Lescano    312-694-0243    sara.lake@northwestern.edu   
Principal Investigator: Josh Levitsky, MD         
United States, Indiana
Indiana University Medical Center
Not yet recruiting
Indianapolis, Indiana, United States, 46202
Contact: Martha Mendez, RN    317-278-4633    mwmendez@iupui.edu   
Principal Investigator: Paul Kwo, MD         
United States, Maryland
John Hopkins University
Lutherville, Maryland, United States, 21093
Contact: Stephanie Katz, MSN,RN    443-287-9605    SSNEDDO2@JHMI.EDU   
Contact: Stacey Reese    410-955-9944    SREESE2@JHMI.EDU   
Sub-Investigator: Mark Sulkowski, MD         
Principal Investigator: Juhi Moon, MD         
United States, Michigan
University of Michigan
Ann Arbor, Michigan, United States, 48109
Contact: Diane White, CCRP    734-763-6647    dfwhite@umich.edu   
Principal Investigator: Anna SF Lok, MD         
United States, Minnesota
University of Minnesota
Minneapolis, Minnesota, United States, 55455
Contact: Stacy Valenzuela    612-624-9926      
Principal Investigator: Mohamed Hassan, MD         
United States, Missouri
Saint Louis University
Saint Louis, Missouri, United States, 63104
Contact: Kristina L Wriston, RN    314-977-9400    KWRISTON@SLU.EDU   
Contact: Caroline Vemulapalli-Forrest       cvemulap@slu.edu   
Principal Investigator: Adrian DiBisceglie, MD         
United States, Nebraska
University of Nebraska Medical Ctr
Omaha, Nebraska, United States, 68198
Contact: Beth Kos, BSN    402-559-3652    MEKOS@UNMC.EDU   
Principal Investigator: Mark Mailliard, MD         
United States, New Mexico
Southwest CARE Center
Santa Fe, New Mexico, United States, 87505
Contact: Joanna Pierce       jpierce@southwestcare.org   
Contact: Christopher Gallegos       cgallegos@southwestcare.org   
Principal Investigator: Joel N Gallant, MD         
United States, New York
Weill Cornell Medical College
New York, New York, United States, 10021
Contact: Marlene Feron-Rigodon, RN    646-962-2085    maf2062@med.cornell.edu   
Principal Investigator: Robert Brown, MD         
Columbia University Medical Center
New York, New York, United States, 10032
Contact: Jennie Chavis    212-305-3839    jc4380@cumc.columbia.edu   
Principal Investigator: Elizabeth Verna, MD         
Mountain View Medical Center
Valatie, New York, United States, 12184
Contact: Ananth Ramani    518-943-1943    ramani489@yahoo.com   
Principal Investigator: Anathakrishnan Ramani, MD         
United States, North Carolina
University of North Carolina at Chapel Hill
Chapel Hill, North Carolina, United States, 27599
Contact: Tiffany Pritchett, B.A.       tpritch@med.unc.edu   
Contact: Renee Blanchard    919-843-5936    renee_blanchard@med.unc.edu   
Principal Investigator: Michael W. Fried, M.D         
Duke University Medical Center
Durham, North Carolina, United States, 27710
Contact: Loranda Ross    919-681-2941    loranda.ross@duke.edu   
Principal Investigator: Andrew Muir, MD         
United States, Ohio
University of Cincinnati
Cincinnati, Ohio, United States, 45267
Contact: Liz Stambrook, BSN    513-584-2363    LIZ.STAMBROOK@UCHEALTH.COM   
Contact: Diane Daria       dariade@ucmail.uc.edu   
Principal Investigator: Kenneth Sherman, MD         
United States, Pennsylvania
University of Pennsylvania
Philadelphia, Pennsylvania, United States, 19104
Contact: Kelly Borges    215-615-3755    kelly.borges@uphs.upenn.edu   
Principal Investigator: Rajender Reddy, MD         
United States, Texas
Research Specialist of Texas
Houston, Texas, United States, 77030
Contact: Christina McNeil    713-634-5110    cmcneil@texasliver.com   
Contact: Wilma Regalado       wregalado@texasliver.com   
Principal Investigator: Joseph Galati, MD         
United States, Virginia
Bon Secours St. Mary 's Hospital of Richmond (Liver Institute of Virginia)
Richmond, Virginia, United States, 23226
Contact: Susan Vollum, RN, CRC    804-977-8921    susan_vollum@bshsi.org   
Principal Investigator: Mitchell L. Shiffman, MD         

Please refer to this study by its ClinicalTrials.gov identifier: NCT02581189
Contact: Nabil Ackad, MD 514-832-7439 nabil.ackad@abbvie.com
Contact: Catherine Pinsonnault, BS 514-832-7015 catherine.pinsonnault@abbvie.com

Condition: Chronic Hepatitis C

This study is currently recruiting participants
Efficacy and Safety of Sofosbuvir/Velpatasvir Fixed Dose Combination for 12 Weeks in Participants With Chronic HCV
Please refer to this study by its ClinicalTrials.gov identifier: NCT02671500
Condition: Hepatitis C Virus Infection
Intervention: Drug: SOF/VEL

University of Malaya Recruiting
Kuala Lumpur, Malaysia, 59100
Hospital Tengku Ampuan Afzan Recruiting
Pahang, Malaysia, 25100
National University Hospital Recruiting
Singapore, Singapore, 119074
Singapore General Hospital Recruiting
Singapore, Singapore, 169608

This study is currently recruiting participants
Ledipasvir/Sofosbuvir Fixed-Dose Combination for 12 Weeks in Participants With Chronic Genotype 2 HCV Infection
Please refer to this study by its ClinicalTrials.gov identifier: NCT02738333
Locations -  Japan
Contact: Gilead Study Team GS-US-337-1903@gilead.com
Condition: Hepatitis C Virus Infection
Interventions: Drug: LDV/SOF; Drug: SOF; Drug: RBV  

This study is currently recruiting participants
Please refer to this study by its ClinicalTrials.gov identifier: NCT02615145
Condition: Chronic Hepatitis C

This study is currently recruiting participants
Real World Evidence of the Effectiveness of Paritaprevir/r - Ombitasvir, ± Dasabuvir, ± Ribavirin in Patients With Chronic Hepatitis C - An Observational Study in Hungary - VERITAS
Please refer to this study by its ClinicalTrials.gov identifier: NCT02636608
Condition: Chronic Hepatitis C

This study is currently recruiting participants
Effectiveness of Paritaprevir/r - Ombitasvir, ± Dasabuvir, ± Ribavirin in Patients With Chronic Hepatitis C - An Observational Study
Please refer to this study by its ClinicalTrials.gov identifier: NCT02798315
Condition: Chronic Hepatitis C

This study is currently recruiting participants
The Effectiveness of Paritaprevir/r - Ombitasvir, ± Dasabuvir, ± Ribavirin in France
Please refer to this study by its ClinicalTrials.gov identifier: NCT02618928
Condition: Chronic Hepatitis C

Elderly patients with chronic hepatitis C: Efficacy and safety of direct acting antiviral treatment and clinical significance of drug–drug interactions

The efficacy and safety of direct acting antiviral treatment and clinical significance of drug–drug interactions in elderly patients with chronic hepatitis C virus infection

Vermehren, K.-H. Peiffer, C. Welsch, G. Grammatikos, M.-W. Welker, N. Weiler, S. Zeuzem, T. M. Welzel, C. Sarrazin
First published: 23 August 2016
Full publication history DOI: 10.1111/apt.13769

Direct antiviral therapies for chronic hepatitis C virus (HCV) infection have expanded treatment options for neglected patient populations, including elderly patients who are ineligible/intolerant to receive interferon (IFN)-based therapy.

AimTo investigate the efficacy, tolerability and potential for drug–drug interactions (DDIs) of IFN-free treatment in patients aged ≥65 years in a large real-world cohort.

MethodsA total of 541 patients were treated with different combinations of direct antiviral agents (DAAs: ledipasvir/sofosbuvir ±ribavirin; daclatasvir/sofosbuvir ±ribavirin; paritaprevir/ombitasvir ±dasabuvir ±ribavirin or simeprevir/sofosbuvir ±ribavirin in genotype 1/4, and daclatasvir/sofosbuvir ±ribavirin or sofosbuvir/ribavirin in genotype 2/3). Efficacy, safety and potential DDIs were analysed and compared between patients aged <65 years (n = 404) and patients aged ≥65 years (n = 137) of whom 41 patients were ≥75 years.

ResultsSustained virological response rates were 98% and 91% in patients aged ≥65 years and <65 years, respectively. Elderly patients took significantly more concomitant medications (79% vs. 51%; P < 0.0001). The number of concomitant drugs per patient was highest in patients ≥65 years with cirrhosis (median, three per patient; range, 0–10). Based on the hep-druginteractions database, the proportion of predicted clinically significant DDIs was significantly higher in elderly patients (54% vs. 28%; P < 0.0001). The number of patients who experienced treatment-associated adverse events was similar between the two age groups (63% vs. 65%; P = n.s.).

ConclusionsElderly patients are at increased risk for significant DDIs when treated with DAAs for chronic HCV infection. However, with careful pre-treatment assessment of concomitant medications, on-treatment monitoring or dose-modifications, significant DDIs and associated adverse events can be avoided.

Chronic infection with the hepatitis C virus (HCV) is a major health burden worldwide and approximately 500 000 people die each year from HCV related liver diseases.[1]
According to estimates by the Centers for Disease Control (CDC), elderly persons are disproportionally affected by HCV and despite the recent approval of highly efficient direct antiviral agents (DAAs) the rates of cirrhosis and hepatocellular carcinoma are predicted to rise in the near future.[2]

Age has been a major limitation of interferon-based treatment, mainly due to increasing prevalence of comorbidity, poor tolerability and overall reduced efficacy in this population.[3] Patients aged 65 years and older were mostly excluded from clinical trials while large-scale real-world database studies showed lower sustained virological response rates and higher withdrawal rates due to side effects in this patient population.[4]

With the recent approval of all-oral DAAs, treatment access has expanded to interferon ineligible/intolerant patient populations, including persons of older age. However, despite the overall excellent tolerability of interferon-free DAA combination therapies, elderly patients, especially those aged 75 years and older were again excluded from most clinical trials.[5-8] In a recent retrospective analysis of four phase 3 trials of the HCV NS5A inhibitor ledipasvir plus the HCV polymerase inhibitor sofosbuvir in patients with HCV genotype 1 infection, only 24/2293 (1%) of the study population were aged 75 or older.[9]

Given the fact that current HCV treatment regimens are both more efficient and better tolerated than interferon-based therapies, the number of elderly patients who will receive anti-HCV treatments is likely to increase. Whether the increased prevalence of comorbidity and concurrent medications in elderly patients is associated with higher rates of adverse events and/or treatment failure is not known. Moreover, the use of ribavirin in these patients may pose a greater risk for associated side effects such as cough, rash and haemolytic anaemia.[10]

In this study, we aimed to assess the efficacy and safety of DAA regimens as well as the clinical significance of potential drug–drug interactions with concomitant medications in patients aged ≥65 years (including subgroup analysis of patients ≥75 years) in a large real-world cohort.

Study cohortConsecutive patients who presented to our outpatient clinic for treatment of chronic HCV infection after the approval of sofosbuvir (January 2014) until September 2015 were included in the analysis. Patients with HIV and/or HBV co-infection and patients with previous solid organ transplantation (kidney, liver, pancreas) were excluded. Patients who received pegylated interferon as part of their treatment regimen and those who received DAA combinations that are currently no longer recommended (e.g. sofosbuvir and ribavirin in HCV genotype 1) were also excluded.

Thus, all patients received one of the following five regimens: (i) sofosbuvir (SOF; nucleoside NS5B polymerase inhibitor) and ledipasvir (LDV; NS5A inhibitor) ± ribavirin (RBV) in genotypes 1, and 4–6, (ii) SOF and daclatasvir (DCV; NS5A inhibitor) ± RBV in genotypes 1 and 3, (iii) paritaprevir/ritonavir (PTV; ritonavir boosted protease inhibitor), ombitasvir (OBV; NS5A inhibitor) and dasabuvir (DSV; non-nucleoside NS5B polymerase inhibitor) ± RBV in genotype 1 (3D regimen), (iv) SOF and simeprevir (SMV; NS3 protease inhibitor) ± RBV in genotype 1 and (v) SOF + RBV in genotypes 2 and 3. RBV was administered based on current guideline recommendations.[11, 12] RBV dose adjustments were done according to the label recommendations.

Assessment of baseline and treatment-related patient parametersDemographic baseline parameters, concomitant medications, laboratory tests as well as safety and efficacy data were retrospectively and anonymously analysed from electronic hospital charts. Efficacy was assessed at 12 weeks after the end of treatment. A sustained virologic response (SVR) was defined as negative HCV RNA at this time point.

Definition of old age Patients of old age were defined as being 65 years and older. This population can be divided into the young-old (ages 65–74), the old-old (ages 75–84), and the oldest-old (85 years and older) as previously described.[13]

Baseline and efficacy data as well as safety and clinical significance of drug–drug interactions were assessed in patients aged 65 years and older. Comparisons were made between groups of patients aged ≥65 years and <65 years. Subgroup analyses were performed for patients aged 75 years and older (old-old and oldest-old combined). No subgroup analysis was performed for the only patient aged 86 years.

Assessment of drug–drug interactions (DDIs) and treatment modificationsA web-based tool developed by the University of Liverpool (available at www.hep-druginteractions.org) was used for risk assessment of potential drug–drug interactions (DDIs) based on patients concomitant medications and the respective antiviral regimen. The DDI database is free for use. Interactions can be assessed by first choosing one or more DAAs from a context menu followed by choosing one or more combination drugs or drug classes. A summary of results and detailed descriptions are displayed hereafter. In addition, the respective prescribing information was also used (as of January 2016).

Potential DDIs were assigned to distinct risk categories according to the predicted level of significance (based on hep-druginteractions.org nomenclature); that is, 0 = interaction has not been assessed; 1 = no clinically significant interaction expected; 2 = potential interaction that may require close monitoring, alteration of drug dosage or timing of administration; 3 = co-administration either not recommended or contraindicated. Thus, category 2 and 3 DDIs were considered clinically significant. Outpatient medications with category 3 DDIs were either stopped prior to antiviral therapy or a different DAA regimen was chosen.

In patients taking medications with category 2 DDIs, the respective drugs were either stopped, dose-modified or closely monitored, as previously recommended.[14]

Calculation of glomerular filtration rateThe Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was used for estimating the glomerular filtration rate (GFR) in this study. The CKD-EPI equation uses a 2-slope ‘spline’ to model the relationship between GFR and serum creatinine, age, sex and race.[15]

Assessment of ribavirin-induced haemolytic anaemiaThe occurrence of RBV induced haemolytic anaemia was assessed at treatment weeks 2, 4, 8 and 12 relative to the baseline haemoglobin level.
Significant anaemia was defined as an absolute decline in haemoglobin levels <10 g/dL and/or a decline of greater than 3 g/dL. Ribavirin dose reductions were made according to the manufacturer's recommendations and no erythropoetin was used in this study.

All statistical analyses were performed using GraphPad Prism version 5 for Mac (La Jolla, CA, USA). Descriptive statistics are shown as mean ± s.d. or median and range. Comparisons between groups were made using parametric t-tests or nonparametric Mann–Whitney U-tests, where appropriate. P < 0.05 were considered statistically significant.

The study was conducted according to the declaration of Helsinki. The ethics committee of the University Hospital Frankfurt approved the retrospective analysis of anonymous patient data.

Baseline characteristics
A total of 541 patients treated with all-oral DAA combination regimens were included in this study. One hundred and thirty-seven subjects were aged 65 years and older. Of these, 96 were aged 65–74 years, 40 were aged 75–84 years and one patient was 86 years old at the start of antiviral therapy.

Among patients aged ≥65 years, the mean age was 71 years (range, 65–86 years), 47% were men (n = 66/137), genotype 1b was the predominant HCV subtype (n = 84/137; 61%) and 47% (n = 64/137) had cirrhosis. The majority (n = 76/137; 56%) of patients aged ≥65 years had failed a prior course of interferon-based therapy. Baseline characteristics of the total study population according to age groups are shown in Table 1.

Table 1. Demographic and clinical characteristics of the study cohort (n = 541)

<65 years n = 404≥65 years n = 13765–74 years n = 96≥75 years n = 41
  1. eGFR, estimated glomerular filtration rate; SD, standard deviation.
  2. a Treatment experienced = nonresponse or relapse to prior peg-Interferon/ribavirin therapy.
Mean age (range)51 (18–64)72 (65–86)69 (65–74)78 (75–86)
Male gender, n (%)252 (62)64 (47)46 (48)18 (44)
HCV Genotypea, n (%)
1a124 (31)36 (26)26 (27)10 (24)
1b171 (42)84 (61)58 (61)26 (64)
2/383 (21)15 (11)10 (10)5 (12)
Other26 (6)2 (2)2 (2)
Cirrhosis, n (%)157 (39)64 (47)40 (42)24 (59)
Treatment experienced, n (%)a229 (57)76 (55)55 (57)21 (51)
Mean HCV RNA [log10] (SD)6.0 (0.8)6.1 (0.6)6.1 (0.7)6.1 (0.5)
Mean eGFR [mL/min] (SD)97.5 (16.7)76.5 (17.4)78.9 (17.3)70.3 (16.5)
Mean haemoglobin [g/dL] female/male (SD)14.8 (1.8)/13.7 (1.3)13.4 (1.6)/14 (1.9)13.9 (1.9)/13.5 (1.4)13.1 (1.8)/14.2 (2.0)

Treatment regimens and efficacy
The distribution of treatment regimens across the different age groups is shown in Table 2.
Table 2. Treatment regimens according to age groups (patients aged 65 years and older are subdivided into patients aged 65–74 years and patients aged 75 years and older)

Treatment regimen, n (%)<65 years (n = 404)≥65 years (n = 137)65–74 years (n = 96)≥75 years (n = 41)
  1. SOF, sofosbuvir; LDV, ledipasvir; RBV, ribavirin; DCV, daclatasvir; PTV, paritraprevir; OBV, ombitasvir; DSV, dasabuvir; SMV, simeprevir.
SOF/LDV ±RBV185 (46)68 (50)48 (50)20 (48)
SOF +DCV ±RBV75 (19)21 (15)12 (13)9 (22)
PTV/OBV ±DSV ±RBV57 (14)22 (15)18 (19)4 (10)
SOF +SMV ±RBV46 (11)13 (10)9 (9)4 (10)
SOF +RBV40 (10)13 (10)9 (9)4 (10)

Overall, SVR was achieved by 98% (n = 134/137) of patients aged 65 years and older. There was no virological treatment failure in patients who received at least 80% of the intended treatment duration and the SVR rate in these patients was 100% (n = 134/134).

Two patients stopped treatment prematurely and one patient died during treatment and the cause of death was considered unrelated to the antiviral treatment (see below). Two patients aged ≥65 years discontinued treatment prematurely: One GT1b patient treated with LDV/SOF discontinued all medications after 2 weeks due to acute kidney injury, and one GT1b patient treated with PTV/OBV +DSV +RBV discontinued all medications after 1 week due to grade 3 hyperbilirubinaemia. This patient was later diagnosed with gilbert's syndrome, which most likely explains the unusually high PTV-associated hyperbilirubinaemia. Both patients had positive HCV RNA during follow-up. One patient died during the treatment period. The cause of death (multi-organ failure following haemorrhagic shock after femoral arterial catheterisation) was considered unrelated to the DAA therapy.

SVR was observed in 91% (n = 369/404) of patients <65 years. A total of 21 patients experienced virological relapse or nonresponse. Two patients stopped treatment prematurely: One patient discontinued treatment because of worsening of pre-existing depression after 6 weeks and one patient discontinued treatment after 4 weeks because of debilitating fatigue. Eleven patients were lost to follow-up during or after antiviral therapy. One patient died during the treatment period. The cause of death (multi-organ failure following haemorrhagic shock after variceal bleeding) was considered unrelated to the DAA therapy.

If only patients <65 years of age with known virological outcome and who received at least 80% of the intended treatment duration were considered, the SVR rate was 95% (n = 369/390; see Figures 1 and 2 for an overview of SVR rates according to genotypes, age and treatment regimen).

Figure 1. SVR rates in patients with HCV genotype 1/4 infection (n = 430) according to treatment regimen and age groups. Only patients who completed ≥80% of the intended treatment duration and who had a known virological outcome are included. Treatment regimens included the following: ledipasvir/sofosbuvir ±ribavirin (LDV/SOF±RBV), daclatasvir +sofosbuvir ±ribavirin (DCV+SOF±RBV), paritaprevir/r/ombitasvir±dasabuvir ±ribavirin (PTV/OBV±DSV±RBV) and simeprevir +sofosbuvir ±ribavirin (SMV+SOF±RBV). SVR data are shown for patients <65 years vs. patients ≥65 years of age. In addition, a subgroup analysis is shown for patients ≥75 years of age.

Figure 2.
SVR rates in patients with HCV genotype 3 infection (n = 57) according to treatment regimen and age groups. Only patients who completed ≥80% of the intended treatment duration and who had a known virological outcome are included. Treatment regimens included the following: daclatasvir +sofosbuvir ±ribavirin (DCV+SOF±RBV), ledipasvir/sofosbuvir ±ribavirin (LDV/SOF ±RBV), and sofosbuvir +ribavirin (SOF+RBV). SVR data are shown for patients <65 years vs. patients ≥65 years of age. In addition, a subgroup analysis is shown for patients ≥75 years of age. **no patients aged 65 years and older were treated with LDV/SOF or SOF+RBV.

All genotypes and treatment regimens were affected by virological failure: LDV/SOF ± RBV (n = 4), SOF and DCV ± RBV (n = 6), PTV/OBV + DSV (n = 2), SOF and SMV ± RBV (n = 6) and SOF + RBV (n = 3).

Frequencies of concomitant medications

A total of 152 different concomitant medications were taken by the patients in our study cohort (n = 81 in patients ≥65 years). The most common drug classes that were taken by >5% of the study cohort included proton pump inhibitors (10%), nonselective beta-blocking agents (9%), thyroid hormones (8%), loop diuretics (8%), angiotensin-converting enzyme inhibitors (8%), vitamin D supplements (7%), selective beta-blocking agents (6%) and insulin preparations (5%).

Overall, the number of patients who took concomitant medications was significantly higher in patients aged ≥65 years compared to <65 years (79% vs. 51%; P < 0.0001). Furthermore, the number of patients who took 4 or more regular concomitant medications was significantly higher in patients ≥65 years compared to <65 years (34% vs. 17%; P < 0.0001).

In patients <65 years, the median number of drugs per patient was 1 (range, 0–12). In patients ≥65 years, the median number of drugs per patient was 2 (range, 0–10). In patients ≥75 years vs. 65–74 years, the number of drugs per patients was not different.

The median number of drugs per patient was increased in patients ≥65 years who also had cirrhosis (3; range, 0–10). In cirrhotic patients ≥75 years, the median number of drugs was higher compared to patients without cirrhosis (median no. of drugs, 3 vs. 2).
Potential for drug–drug interactions between DAAs and concomitant medications

Based on DDI risk classification from the hep-druginteractions.org database, category 2/3 DDIs were predicted for 35% (n = 189/541) of the total study population (60% of patients with concomitant medications).

The proportion of predicted category 2/3 DDIs was significantly higher in patients ≥65 years compared to patients <65 years (54% vs. 28%; P < 0.0001). There was no difference in category 2/3 DDIs between patients aged 65–74 years vs. ≥75 years (55% vs. 51%; P = N.S.). The frequencies of potentially clinically significant DDIs (category 2/3) according to age and DAA regimen are shown in Figure 3.

Figure 3.
Frequencies of predicted clinically significant drug–drug interactions (defined as category 2/3 interactions according to the hep-druginteractions.org database) between concomitant medications and antiviral therapy according to treatment regimen and age groups (n = 541). All listed patients had ≥1 drug of concomitant medications predicted to cause DDIs.

For patients treated with LDV/SOF±RBV, the most common concomitant drug classes involved in potentially significant DDIs (DDI category 2/3) were beta-blocking agents in 16% (n = 30/185) and 34% (n = 23/68) and proton pump inhibitors in 11% (n = 21/185) and 25% (n = 16/68) of patients <65 and ≥65 years of age respectively. For patients treated with DCV+SOF±RBV, the most common concomitant medications at risk for significant interactions were beta-blocking agents in 19% (n = 14/75) and 29% (n = 6/21) and thyroid hormones in 11% (n = 8/75) and 24% (n = 5/21) of patients <65 and ≥65 years of age respectively. For patients treated with PTV/OBV±DSV±RBV, significant interactions were primarily expected for thyroid hormones in 12% (n = 7/57) and 45% (n = 10/21) and alfa- and beta-blocking agents in 14% (n = 8/57) and 23% (n = 5/22) of patients <65 and ≥65 years of age respectively. Finally, for SMV-containing regimens, the most common drug classes at risk for clinically significant interactions were beta-blocking agents in 13% (n = 6/46) of patients <65 years and statins that were co-administered in 15% (n = 2/13) of patients ≥65 years of age.

The most common concomitant medications with potential category 2/3 DDIs and respective action taken before and during antiviral therapy to avoid such DDIs are shown in Table 3.
Table 3. Description of potential drug–drug interactions (DDIs) with commonly used co-medications in patients with chronic HCV infection. The colour scheme represents a traffic light labelling system to highlight the signficance level of expected DDIs according to the hep-druginteractions.org website: green = no DDI expected; amber = potential DDI expected; red = co-administration not recommended/contraindicated. Suggested actions that should be taken to avoid DDI-related adverse events are also given

Safety and adverse events
The occurrence of adverse events was documented in 77% (n = 417/541) of patients. A total of 63% (n = 264/417) patients experienced at least one adverse event during the treatment period. Adverse events were generally mild and the number of adverse events was not significantly different between patients <65 years and patients ≥65 years respectively (63% vs. 65%; P = N.S.). We observed no significant increase in adverse events potentially related to DDIs (e.g. dizziness, bradycardia or GI disturbances in patients with concomitant carvedilol treatment; TSH changes in patients treated with levothyroxine).

The most common adverse events were fatigue (35% and 37%), dyspnoea (11% and 15%; only patients on RBV treatment affected), headache (22% and 11%), pruritus (7% and 10%), rash (7% and 2%) and insomnia (6% and 7%) in patients <65 and ≥65 years of age respectively.
Estimated glomerular filtration rate (eGFR)

At baseline, the eGFR (CKD-EPI) was 97.5 mL/min for patients <65 and 76.5 mL/min for ≥65 years of age (P < 0.0001). The eGFR in patients between 65 and 74 years was 78.9 mL/min and 70.3 mL/min in patients ≥75 years of age (P = 0.0038). For all age groups and treatment regimens with and without SOF, eGFR values showed no significant changes over the course of antiviral treatment (P = N.S.).

Ribavirin-induced anaemia
RBV was co-administered in 42% (n = 168/404), 43% (n = 59/137) and 49% (n = 20/41) of patients <65 years, ≥65 years and ≥75 years of age respectively. Significant anaemia occurred in 34% (n = 20/59) and 35% (n = 7/20) of ≥65 years and ≥75 years of age respectively.

The rates of patients aged ≥65 years who experienced at least one adverse event (any event) were 68% (n = 40/59) and 32% (n = 25/78) with and without RBV respectively. In patients aged ≥75 years, these rates were 70% (n = 14/20) and 38% (n = 8/21) with and without RBV respectively. Side effects typically associated with RBV use, including haemolytic anaemia, skin rash and cough were observed in 42% (n = 25/59) and 55% (n = 11/21) of patients ≥65 years and ≥75 years of age respectively.

Until recently, treatment options in elderly patients with chronic HCV infection were limited, mainly due to contraindications and side effects associated with IFN-based therapies.[3] Moreover, lower SVR rates and higher rates of treatment discontinuation were reported.[4, 16-18] The recent approval of highly effective IFN-free regimens has led to a paradigm change with improved options for difficult-to-cure patients, including those of older age.[19] Interestingly, despite improved safety profiles of all-oral DAA treatments, elderly patients were once again excluded from most clinical trials. Despite this, a recent retrospective analysis of the LDV/SOF approval trials showed high SVR rates in patients ≥65 years of age.[9] However, older patients represented a mere 12% of the total study population and the proportion of patients aged 75 years and older was only 1% (n = 24).

In our retrospective study, we included a large proportion of elderly patients (25%). The different combinations of all-oral DAA therapies showed comparable efficacy in patients aged ≥65 years and younger patients. Moreover, when specifically looking at genotype 1 patients treated with the currently most widely used regimens (LDV/SOF ±RBV or PTV/OBV +DSV ±RBV), SVR rates exceeded 95% in both age cohorts, and this was also true in the subgroup of patients ≥75 years of age. While DAA treatment seems to be feasible in virtually all patients regardless of age and comorbidities, the question arises whether old patients should always be considered for antiviral therapy. On the one hand, progression to cirrhosis has been shown to be an age-dependent process.[20] However, given the high costs of current DAA regimens, treatment priority should clearly be given to patients with advanced liver disease whereas treatment is not recommended in patients with limited life expectancy.[12] Obviously, the decision to treat elderly patients or not is greatly influenced by local guidelines and/or reimbursement policies as well as societal considerations. On the other hand, if cirrhosis is not present in elderly patients despite a long history of HCV infection, progression to cirrhosis may never occur. In our study, 41% of patients aged 75 and older had no cirrhosis at the time of DAA treatment. Thus, prevention of fibrosis progression was not the main driver for treatment initiation in these patients. Indeed, only a mild disease progression has been observed in several studies, particularly in women, despite a long history of HCV infection.[21, 22] However, despite this favourable course of disease, high levels of psychological distress and impaired quality of life due to debilitating fatigue may still be present in many of these patients.[21] Presence of such factors and other extrahepatic manifestations which have been shown to increase with age[23] may justify the decision to treat older patients, even in case advanced liver disease is not present. This is supported by recent data that suggest that DAA therapies are associated with significantly improved patient-reported outcomes and even favourable short-term health economic outcomes.[24, 25]

While more and more patients are being treated for HCV infection outside of clinical trials, the risk for potentially serious DDIs is increasing.[14] In our study, older patients took significantly more concomitant medications, which reflects the increasing morbidity in the ageing HCV population.[26] Moreover, our study showed that the number of drugs taken by an individual patient was highest in patients aged 65 and older who also had cirrhosis. This may be attributable to the particularly high number of cardiovascular drugs and diuretics in this population.

Management of potential DDIs had become particularly important after the approval of the first-generation protease inhibitors telaprevir and boceprevir which are strong inhibitors and substrates of the P-glycoprotein (P-gp) and cytochrome P450 3A4.[27, 28] This led to a greater awareness of potential DDIs in patients treated for HCV infection. Consequently, a DDI website was launched by the University of Liverpool in 2010 that provides a comprehensive DDI database (www.hep-druginteractions.org) that is free for use.

Currently recommended DAAs still show some interactions with P-gp and cytochrome P450 enzymes, albeit only to a much lesser extent than telaprevir and boceprevir.[27]

Our study had a high proportion of patients taking concomitant medications that could potentially lead to significant DDIs during antiviral therapy. The predicted proportion of potentially significant DDIs was particularly high in elderly patients. More than half of elderly patients were predicted to have significant DDIs. Interestingly, all DAA regimens were affected by potentially significant DDIs. In elderly patients, the risk was highest in patients treated with DCV and SOF whereas similar frequencies of potential DDIs were predicted for patients treated with LDV/SOF and the OBV/PTV+DSV regimen.

Proton pump inhibitors (PPIs) have recently been associated with a higher risk of virological failure in patients treated with LDV/SOF.[29] The negative impact of PPIs, however, does not seem to derive from true DDIs but changes in drug absorption.[30] Simultaneous administration of PPIs resulted in only slightly decreased LDV AUC and Cmax that were not judged to be clinically relevant. In contrast, co-administration of PPIs and PTV/ritonavir significantly decreased omeprazole AUC and Cmax due to induction of CYP2C19 by ritonavir which may lead to decreased PPI efficacy.[31]

In our study, actions were taken to reduce the impact of potentially significant DDIs as previously proposed.[14] However, for many concomitant medications, no reliable prediction for potential DDIs is available because of the lack of clinical data. Here, potential DDIs are predicted based upon metabolic pathway interactions. This emphasises the need for comprehensive pharmacovigilance networks to meet the challenges of treating elderly and/or multimorbid patients.

In our study, no significant adverse events attributable to DDIs were noted. Indeed, despite the higher number of drugs taken and the higher frequency of predicted DDIs in elderly patients, the number of adverse events was not different between the two age groups. This may again be attributable to the meticulous DDI assessment before treatment initiation and careful monitoring thereafter. In addition, although the use of RBV increased the number of adverse events particularly in elderly patients, significant anaemia was not higher than in younger patients.

Our study has several limitations, including the retrospective design and the heterogeneous number of treatment regimens. However, this is currently the largest real-world DAA experience among elderly patients that also assesses the potential clinical impact of DDIs.

In conclusion, our study shows that all approved IFN-free DAA regimens are highly effective in elderly patients, especially those aged 75 years and older, while concomitant drugs pose a risk for potentially serious DDIs. Use of a free accessible Internet-database and careful management during therapy can effectively prevent DDI-associated adverse events and treatment failure.

Guarantor of the article: JV.
Author contributions: JV, CW and CS contributed to the study design and concept. All authors contributed to the acquisition of data and reviewed versions of the manuscript and provided critical comments. JV interpreted the data and drafted the manuscript.

All authors approved the final version of the manuscript.

Declaration of personal interests: JV served as a speaker and/or consultant for Abbott, AbbVie, Bristol-Myers Squibb, Medtronic and Gilead. MWW served as a speaker and/or consultant for Amgen, Bayer, Bristol-Myers Squibb, Gilead, Novartis and Roche. SZ served as a speaker and/or consultant for AbbVie, Bristol-Myers Squibb, Gilead, Janssen and Merck. TMW served as a speaker and/or consultant for AbbVie, Bristol-Myers Squibb, Boehringer-Ingelheim and Janssen. CS served as a speaker and/or consultant for Abbott, AbbVie, Achillion, Bristol-Myers Squibb, Gilead, Janssen, Merck, Qiagen, Roche and Siemens. He also received research grants from Abbott, Gilead, Janssen, Qiagen, Roche and Siemens. All other authors declare that they have no competing interests.

Declaration of funding interests: None.