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Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Background

Insulin resistance has been strongly associated with the attainment of sustained viral response (SVR) in hepatitis C patients.

Aim

To determine, in a cohort of Spanish patients with chronic hepatitis C treated with peginterferon plus ribavirin (P+R), whether insulin resistance predicts SVR independently of interleukin-28B rs12979860 polymorphism.

Methods

Insulin resistance was measured as [HOMA-IR = Insulin (IU/mL)*glucose (mmol/L)/22.5]. Genotype, viral load and histological fibrosis using Scheuer score were also measured. Binary logistic regression analysis was used for statistical purposes.

Results

In a cohort of 240 patients [78% genotype 1, 24% showing advanced fibrosis, 71% high viral load (≥800 000 IU/mL), 31% IL28b genotype CC and 50% with HOMA >2] treated with P+R, 126 (53%) reached SVR. HOMA-IR index (HOMA <2: 63% vs. HOMA >2: 42%; = 0.001 and IL28b (genotype CC: 68% vs. genotype CT/TT: 45%; = 0.002) were significantly associated with SVR. In multivariable logistic regression analysis in the overall cohort, variables independently associated were: viral genotype OR: 0.29 (95% CI: 0.11–0.78), = 0.01; fibrosis OR: 1.62 (95% CI: 1.22–2.16), = 0.001; HOMA-IR OR: 1.22 (95% CI: 1.02–1.47), = 0.03; and IL28B genotype OR: 2.43 (95% CI: 1.45–4.07), = 0.001. The analyses also showed that degree of steatosis, HOMA-IR >2, mild fibrosis and IL28B CC genotype were significantly related to SVR in patients infected with HCV genotypes 1&4, but not in those with genotypes 2&3. No differences were seen in glucose, insulin level or HOMA-IR index segregated according to IL28B genotypes.

Conclusion

Our results suggest that insulin resistance, fibrosis stage and IL28B polymorphisms were independent variables associated with sustained viral response.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

In patients with chronic hepatitis C infection, sustained virological response (SVR) rate variability is extremely high following standard care therapy with peginterferon + ribavirin (P+R). Viral genotype, viral load, fibrosis stage and metabolic disturbances including obesity, insulin resistance and steatosis have been shown to be the main factors influencing SVR.[1] In two recent meta-analyses, insulin resistance was strongly associated with the probability of achieving SVR.[2, 3] Furthermore, Ge et al.[4] conducted a Genome Wide Association Study (GWAS) in 1137 patients and demonstrated that in patients bearing CC in the position rs12979860 in 19q13 region, the probability of achieving SVR was double that of those with CT/TT. The IL28B rs12979860 polymorphism was associated with a higher probability of achieving SVR independently of fibrosis stage, viral genotype and viral load.[5] Ogawa et al.[6] showed that, in Japanese HCV genotype 1-infected patients, both IL28B rs8099917 polymorphism and baseline HOMA-IR were independent pre-treatment predictors of SVR in patients treated with P+R, and that HOMA-IR appeared to underline IL28B predictability of response. However, these findings need to be validated in Occidental patients. SVR rate seems to be similar in patients receiving dual or triple therapy when genotype CC is present, or in patients achieving rapid virological response (RVR).[7] Indeed, RVR was more often seen in patients with genotype CC.[8] Thus, definitions of host and viral factors influencing RVR rates in patients with genotype CC could be extremely useful in clinical practice.

The main aim of the present study was to determine, in a cohort of Spanish patients with chronic hepatitis C treated with P+R, whether insulin resistance predicts SVR independently of interleukin-28B rs12979860 polymorphism. The impact of genotype on RVR and SVR in patients receiving P+R treatment was also assessed.

Patients and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Consecutive treatment-naïve patients with chronic hepatitis C attending our outpatient clinic since 2007 were recruited to receive treatment with P+R. All patients received peginterferon alfa-2a (180 μg/kg bodyweight) plus genotype- and weight-related ribavirin (genotypes 1&4 received 1000 mg/d when weight <75 kg and 1200 mg/d when weight ≥75 kg; genotypes 2&3 received 800 mg/d in all cases). Based on viral genotype, the treatment was for 24 weeks (genotypes 2 and 3) or 48 weeks (genotypes 1 and 4). The Valme University Hospital Ethics Committee approved the protocol and fully informed written consent was obtained from all patients prior to entry into the study. History of alcohol consumption was obtained by two clinical researchers using standardised interview. No patient had been previously treated with direct antiviral drugs. Patients with a type 2 diabetes mellitus, or showing fasting glucose >7 mmol/L, were also excluded.

Laboratory investigations

An overnight (12 h) fasting blood sample was taken for routine clinical chemistry analyses. These included ALT, AST, alkaline phosphatase, γGT, cholesterol and triglycerides. All patients had positive anti-HCV as measured using EIA3 (Abbott Laboratories, Chicago, IL, USA), increased ALT and positive HCV RNA in serum. HBsAg, anti-HBc, anti-HIV were tested using commercially available kits (Abbott Laboratories). All patients were negative for HBsAg and anti-HIV. Fasting samples of serum obtained after centrifugation were stored in aliquots at −70°C until assayed. Serum insulin levels were measured by electrochemiluminescence immunoassay, (ECLIA) using an Elecsys 1010/2010 autoanalyser (Elecsys MODULAR ANALYTICS E170; Roche, Basil, Switzerland). The insulin resistance index was calculated using fasting values of plasma glucose and insulin, according to the HOMA model formula:

  • display math

As previously recommended, insulin resistance was arbitrarily considered altered when higher than 2.[1] Height and weight were determined at baseline and the body mass index (BMI) was calculated as weight (in kg) ÷ height (in m2).

Liver histology

Percutaneous liver biopsy was performed under ultrasound control. We assessed grading and staging separately. Stage was defined according to the Scheuer fibrosis score in which F0 = absence, F1 = enlarged portal tracts, F2 = periportal or portoportal septa, F3 = fibrosis with architectural distortion, and F4 = cirrhosis. Necroinflammatory activity was determined by combining scores for portal inflammation (0–4) and lobular necrosis (0–4). Steatosis was quantified as the percentage of hepatocytes that contained fat droplets between <5% (absent) and 100% (all hepatocytes containing fat droplets). The grades assigned were: 0 if no steatosis (<5%), grade 1 when <25% of hepatocytes contained fat droplets, grade 2 when between 25% and 50% showed steatosis and grade 3 when >50% of hepatocytes showed fat storage. For statistical purposes, patients were classified as ‘no steatosis’ (grade 0) and ‘steatosis’ (grades 1, 2 and 3).

Virology assessments

HCV genotyping was performed with INNO-LIPA HCV II kits (Innogenetics, Zwijnaarden, Belgium), which were used according to the manufacturer's instructions. A Cobas Taqman (Perkin-Elmer, Norwalk, CT, USA) was used to quantify the HCV RNA levels in serum. Serum samples were diluted for measurement when values were beyond the linear range of the method. The level of detection was 15 IU/mL, and all patients were HCV RNA-positive.

IL28B genotyping

DNA from patients was extracted from peripheral blood using standard methods. Genotyping of the rs12979860 was performed using a TaqMan 5′ allelic discrimination assay (Applied Biosystems, Foster City, CA, USA). The primers used were 5′ GCCTGTCGTGTACTGAACCA 3′ (forward) and 5′ GCGCGGAGTGCAATTCAAC 3′ (reverse), and the TaqMan MGB probe sequences were 5′ TGGTTCGCGCCTTC 3′ and 5′ CTGGTTCACGCCTTC 3′. The probes were labelled with the fluorescent dyes VIC and FAM respectively. PCR reactions were performed in a total volume of 8 μL with the following amplification protocol: denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 92°C for 15 s and finished with annealing and extension at 60°C for 1 min. Genotyping of each sample was automatically attributed by the SDS 1.3 software (Applied Biosystems, Grand Island, NY, USA) for allelic discrimination.

Statistical analyses

Comparisons between groups were made using the Mann–Whitney U-test, the Student t-test or anova for continuous variables, and the χ2 or the Fisher exact probability test for categorical data. The Spearman coefficient was used to correlate numerical variables that were nonnormally distributed. All values are presented as means ±s.d. A probability value of < 0.05 was considered statistically significant. Backward logistic regression was used in the multivariate analysis to determine the factors associated with sustained response. These included baseline variables and, in a second pass, included on-treatment variables such as rapid virological response (RVR). RVR was also evaluated as a treatment outcome. Variables included in the analyses were age, gender, hepatic steatosis, BMI, GGT, insulin resistance, fibrosis, viral genotype, HCV RNA levels and IL28B genotypes.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Baseline characteristics of the overall cohort

Patients (= 240) with biopsy-proven chronic hepatitis C (HCV RNA positive) were treated with peginterferon alfa-2a plus ribavirin (P+R). Gender distribution was 60% (144/240) male and 40% (96/240) female, with an overall mean age of 45 ± 10 years (range: 18–69). Genotype distributions were: genotype 1 (= 188), genotype 2 (= 3), genotype 3 (= 30) and genotype 4 (= 19).

Baseline variables associated with sustained virological response (SVR)

In the univariate analysis, factors associated with SVR in genotypes 1&4 were: age, steatosis degree, fibrosis stage, HOMA index and interleukin 28B polymorphisms. SVR was achieved in 49.3% (102/207) of cases with genotypes 1&4 (Table 1). The SVR rate was 70% in those with mild fibrosis (F0–F2) and 30% in advanced fibrosis (F3–F4) (= 0.0001). Hepatocyte steatosis was associated with poorer SVR rates (32.3% vs. 61%; = 0.001). HOMA-IR >2 was associated with poorer SVR response (39.3% vs. 58.7%; = 0.007). Younger age was associated with poorer response (42.9 ± 10.6 vs. 46.2 ± 9.4; = 0.02). Lastly, IL28B genotypes were significantly (= 0.004) associated with SVR genotype CC 39/58 (67.2%) vs. genotype CT/TT 59/145 (40.7%). Using reverse stepwise logistic multivariable regression analysis, the independent variables related to SVR were: steatosis degree (OR: 0.22; 95% CI: 0.09–0.53; = 0.001), HOMA-IR >2 (OR: 0.44; 95% CI: 0.17–0.97; P = 0.04), mild fibrosis (OR: 1.97; 95% CI: 1.28–3.03; P = 0.002) and IL28B genotype CC (OR: 2.25 95% CI: 1.12–4.56; = 0.024). There were no statistically significant associations with gender distribution, viral load, body mass index, alcohol consumption or cholesterol concentrations. Conversely, patients with HOMA-IR >2 showed steatosis in 50% of cases, while steatosis was present in 39.7% of cases when HOMA-IR was <2 (> 0.05).

Table 1. Analysis of variables associated with sustained virological response (SVR) in patients with genotypes 1&4
= 203Univariate analysisLogistic regression
VariableSVRNon-SVR P OR (95% CI) P
  1. Bold values indicate P < 0.05.

  2. Analyses applied were univariate analysis (χ2 test or Fisher test for categorical variables and Student t-test or U-Mann–Whitney for continuous variables) and multivariable analysis (binary logistic regression).

IL28B
CC39 (67.2%)19 (32.8%) 0.004 2.25 (1.12–4.56)0.024
CT48 (41.7%)67 (58.3%)
TT11 (39.3%)17 (60.7%)
Gender
Male56 (46.7%)64 (53.3%)0.378  
Female46 (52.9%)41 (47.1%) 
Age42.9 ± 10.646.2 ± 9.40.020  
Viral load (VL)
High VL71 (47.7%)78 (52.3%)0.387  
Low VL31 (54.4%)26 (45.6%) 
Rapid viral response (RVR)
RVR24 (100%)0 (0%) 0.0001   
Non-RVR35 (42.2%)48 (57.8%) 
HOMA-IR
>235 (39.3%)54 (60.7%) 0.007 0.44 (0.17–0.97)0.04
≤261 (58.7%)43 (41.3%)
Steatosis
Yes20 (32.3%)42 (67.7%) 0.001 0.22 (0.09–0.53)0.001
No50 (61.0%)32 (39.0%)
Fibrosis
F0–F147 (64.4%)26 (35.6%) 0.002 1.97 (1.28–3.03)0.002
F221 (37.5%)35 (62.5%)
F3–F415 (30%)35 (70%)
Viral load (log IU/mL)6.16 ± 0.806.29 ± 0.760.264  
Viral load week 4 (log IU/mL)2.63 ± 1.644.85 ± 1.09 0.0001   
Viral load week 12 (log IU/mL)1.23 ± 0.543.05 ± 1.68 0.0001   
BMI26.43 ± 6.1325.78 ± 3.310.372  
Glycaemia (mg/dL)94.24 ± 21.27100.24 ± 27.690.086  
HOMA-IR2.20 ± 1.333.12 ± 2.54 0.002   
ALT (UI/mL)93.79 ± 62.43101.94 ± 95.210.466  
GGT (UI/mL)64 ± 73.4896.79 ± 105.88 0.011   
Total cholesterol (mg/dL)177.48 ± 40.5170.75 ± 30.030.177  
LDL (mg/dL)91.80 ± 45.1493.31 ± 30.710.852  
Triglycerides (mg/dL)99.71 ± 60.3697.94 ± 69.070.846  
Platelets (K/μL)218000 ± 61948195570 ± 63632 0.011   

By contrast, we did not find factors associated with SVR in patients with genotypes 2&3. There were no significant associations with age, gender distribution, steatosis degree, fibrosis stage, viral load, HOMA index, body mass index, alcohol consumption or cholesterol concentrations. SVR was achieved in 72.7% of cases (24/33) with genotypes 2&3. The SVR was not associated with fibrosis, steatosis or IL28B polymorphisms in genotypes 2/3 patients (Table 2).

Table 2. Analysis of variables associated with sustained virological response (SVR) in patients with genotypes 2&3
= 33Univariate analysis
VariableSVRNon-SVR P
  1. Analyses applied: univariate analysis (χ2 test or Fisher test for categorical variables and Student t-test or U-Mann–Whitney for continuous variables).

IL28B
CC9 (69.2%)4 (30.8%)0.523
CT11 (68.8%)5 (31.2%)
TT3 (100%)0 (0%)
Gender
Male18 (75%)6 (25%)0.677
Female6 (66.7%)3 (33.3%)
Age43.63 ± 8.645.7 ± 9.80.590
Viral load
High VL14 (70%)6 (30%)0.999
Low VL10 (76.9%)3 (23.1%)
RVR
Non-RVR

13 (86.7%)

2 (100%)

2 (13.3%)

0 (0%)

0.999
HOMA-IR
>210 (58.8%)7 (41.2%)0.229
≤211 (84.6%)2 (15.4%) 
Steatosis
Yes8 (61.5%)5 (38.5%)0.405
No8 (80%)2 (20%)
Fibrosis
F0–F16 (85.7%)1 (14.3%)0.572
F27 (77.7%)2 (22.3%)
F3–F44 (50%)4 (50%)
Viral Load (log IU/mL)5.97 ± 0.756.24 ± 0.460.215
BMI26.33 ± 3.7825.9 ± 1.480.655
Glycaemia (mg/dL)95.79 ± 14.8399.89 ± 14.410.482
HOMA-IR2.24 ± 0.892.87 ± 2.350.452
ALT (UI/mL)114.67 ± 75.94131.89 ± 73.470.561
GGT (UI/mL)48.61 ± 32.0382.22 ± 44.320.061
Total cholesterol (mg/dL)162.88 ± 43.26146.56 ± 32.970.261
LDL (mg/dL)102.20 ± 26.2287.47 ± 33.930.399
Triglycerides (mg/dL)80.29 ± 30.8180.67 ± 27.860.974
Platelets (K/μL)195458 ± 72573163666 ± 540640.189

In patients with the IL28B genotype CC, SVR was achieved in 48 of 71 patients (68%). Genotype 1&4 patients without SVR bearing the IL28B genotype CC had higher HOMA-IR scores (3.37 ± 3.07 vs. 2.13 ± 0.98; = 0.023) and more advanced stage of fibrosis (2.53 ± 0.97 vs. 1.59 ± 1.04; = 0.02). In multivariable analysis using logistic regression, higher values of HOMA-IR were independently related to non-SVR in genotype CC IL28B patients (OR: 1.43 (95% CI: 1.03–2.01; = 0.022). However, we observed no influence of viral load or hepatocyte steatosis. We observed no significant associations in patients with genotypes 2&3.

Factors associated with IL28B polymorphism

Insulin resistance values were not related to IL28B genotypes (HOMA-IR in genotype CC: 2.54 ± 1.97 vs. genotype CT: 2.88 ± 2.36 vs. genotype TT: 2.68 ± 2.44; = 0.59). Neither were fibrosis (genotype CC: 2.08 ± 1.14 vs. genotype CT: 1.87 ± 1.20 vs. genotype TT: 1.92 ± 1.18; = 0.51); viral load (genotype CC: 6.27 ± 0.77 vs. genotype CT: 6.16 ± 0.74 vs. genotype TT: 6.09 ± 0.85; = 0.47); and body mass index (genotype CC: 26.9 ± 6.6 vs. genotype CT: 25.8 ± 3.7 vs. genotype TT: 25.6 ± 3.6; = 0.32) related to IL28B genotypes (Figure 1).

image

Figure 1. Insulin resistance (HOMA-IR), fibrosis stage and viral load are not related to IL28B polymorphism. The relationship between: (a) insulin resistance (HOMA-IR), (b) fibrosis stage and (c) viral load vs. rs12979860 polymorphism were evaluated in chronic hepatitis C patients. No statistically significant associations were observed.

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Factors associated with rapid virological response

In genotypes 1&4, viral clearance at week 4 was more often seen in younger patients, low viral load and genotype IL28B CC. However, HOMA-IR <2 was associated with lower HCVRNA at week 4 (3.23 ± 1.64 vs. 4.05 ± 1.87 Log10IU/mL). Body weight and fibrosis stage did not reach statistical significance. Binary logistic regression confirmed IL28B genotype CC (OR: 20; 95% CI: 3.86–90.9); fibrosis (OR: 0.51; 95% CI: 0.26–1.03) and low viral load (OR: 6.99; 95% CI: 1.46–33.33) as independent variables associated with RVR. In patients bearing IL28B genotype CC, viral load was the only independent variable associated with RVR. We did not find any statistically significant association in patients with genotypes 2&3.

Impact of RVR on sustained virological response (SVR)

RVR values were available in 124 patients, 107 infected by genotypes 1&4 and 17 patients with genotypes 2&3. RVR was closely related to SVR; 37 of 39 patients (95%) with RVR achieved SVR. Introducing RVR together with baseline variables into the multivariable analysis showed that RVR (OR: 34; 95% CI: 5–216; < 0.0001) and HOMA-IR >2 (OR: 0.63; 95% CI: 0.45–0.87; < 0.005) were independently related to SVR, while other markers of interferon sensitivity such as IL28B genotype CC, HCV genotype and fibrosis stage did not enter into the final equation.

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Our results indicate that insulin resistance, together with fibrosis stage and IL28B polymorphisms, was independently associated with sustained virological response in patients with chronic hepatitis C treated with peginterferon plus ribavirin (P+R). The outcomes were confined to patients with genotypes 1&4, and not with genotypes 2&3. IL28B genotypes 1&4 have been reported to be strongly related to SVR,[3, 9] but not genotypes 2&3 and, as such, suggests a predictive capacity of this baseline variable in difficult-to-treat subgroups of patients.[10] However, the functionality of the rs12979860 polymorphism remains controversial. This genetic variant does not promote changes in the IL28B protein and the mechanism by which this mutation can modify interferon sensitivity remains unclear.[11] Viral load and viral genotypes are the major viral factors influencing SVR, while fibrosis stage, metabolic disorders and IL28B polymorphisms remain as major host factors related to SVR. Close co-linearity has been reported among several variables e.g. insulin resistance, age, fibrosis stage, steatosis, obesity and GGT levels,[12] while HOMA index has been strongly related to SVR.[2] This association can be of considerable importance as it has been well documented that hepatitis C is closely related to insulin resistance and type 2 diabetes mellitus, the prevalence of which has been shown to be increased in this patient population. Despite our data being based on only 33 subjects with genotypes 2/3 included in the current cohort, our findings are in accord with previous reports from Stättermayer et al.[10] However, there may be insufficient power to find a relationship between these variables and SVR.

The relationship between insulin resistance measured by HOMA and IL28B genotype is subject to debate. Stättermayer et al.[13] reported a strong association between IL28B genotype CC and lower HOMA score in a cohort of 202 patients with chronic hepatitis C genotype 1 or 4, suggesting a link between insulin resistance and genetic variant that could help explain the association between HOMA and SVR. However, our study (and that by Huang et al.[14]) observed no such association between baseline HOMA values and IL28B genotypes. A recent study by Ogawa et al.[6] showed that the distributions of the IL28B rs8099917 polymorphism were not related to HOMA-IR values and, also, the polymorphism was an independent baseline predictor of SVR response to treatment. Despite insulin resistance being associated with fibrosis stage, both variables remained independently associated with SVR. However, Fattovich et al.[15] found that in HCV genotype 1 patients, IL28B polymorphisms, HCV RNA load and IP-10 could independently predict SVR. These authors found that HOMA-IR score was not associated with viral response. On the other hand, our results showed that IL28B polymorphisms were not related to fibrosis stage or HOMA score, which highlights the weakness of the interaction between them and strength of the relationship with SVR. Hepatitis C virus could influence insulin signalling by promoting insulin resistance mediated by IRS-1 and IRS-2 degradation by several pathways, depending on viral genotype.[16] The influence of host genetic factors on this interaction needs to be validated in further studies. For example, hepatitis C virus appears to modify lipid metabolism, according to IL28B genotype. Lower pre-treatment serum low-density lipoprotein cholesterol (LDL-C) levels have been shown to be associated with poor response to peginterferon/ribavirin therapy in patients with chronic hepatitis C.[17, 18] IL28B polymorphisms influence the biological relationships between HCV infection and serum LDL and the clinical value of LDL in predicting response to pegIFN/RBV therapy,[19] the conclusion being that the clinical value of serum LDL in predicting SVR is clear only for those patients heterozygous for IL28B genotype.

Insulin resistance appears not to be predictive of SVR in patients receiving telaprevir-based triple therapy,[20] at least in treatment-naïve and relapser patients. The impact of insulin resistance in more difficult-to-treat patients such as null-responders requires further investigation. Interestingly, our present study demonstrated that viral clearance was associated with improvement in insulin sensitivity, thus supporting the link between viral replication and insulin resistance.

In treatment-naïve genotype 1&4 patients bearing IL28B genotype CC and patients reaching RVR (which could be tested during the lead-in-phase, at least in patients scheduled to receive boceprevir), similar SVR rates were achieved when treated with double or triple therapy.[21] In these groups of patients, adding HOMA-IR could help in clinical decision making. Indeed, nonresponder patients bearing IL28B genotype CC appear to have more advanced disease and higher HOMA-IR index. Despite the association of HOMA-IR with SVR noted in this study being modest, there is a potential use of this index in patients with chronic hepatitis C and favourable genotype CC. In such circumstances, HOMA-IR could help segregate treatment-resistant subgroups of patients who may benefit, instead, from triple therapy. However, these postulations need to be demonstrated and validated in further studies.

In summary, our data indicate that IL28B genotypes, HOMA-IR and fibrosis remain the independent variables predicting SVR in patients treated with peginterferon + ribavirin, particularly in patients with genotypes 1&4. RVR is a major on-treatment variable together with insulin resistance index, while all of the other variables studied (HOMA-IR, IL28B genotype CC, RVR) could be very useful in decision making in the management of hepatitis C infection.

Authorship

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Guarantor of the article: Prof. Manuel Romero-Gómez.

Author contributions: JAdC, JA, JRGL, MFGE and MRG designed research study, analysed the data and wrote the paper. LR, MC, AR, MGV, MM and RM collected and analysed the data. All authors approved the final version of the manuscript.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References

Declaration of personal interests: Writing support was provided by Peter R. Turner from Tscimed.com.

Declaration of funding interests: This study was funded by Junta de Andalucia (CS 448/09) and Instituto Carlos III (PI 10/00611).

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Patients and Methods
  5. Results
  6. Discussion
  7. Authorship
  8. Acknowledgements
  9. References