Publications

Background. Millions of people are infected with hepatitis C virus (HCV) worldwide and 30% spontaneously clear the infection. Reasons for HCV clearance without antiviral treatment are not well understood. Methods. Blood was collected for DNA analysis from patients with chronic HCV infection or evidence of spontaneous clearance. To overcome anticipated limitations of small sample size, primary analyses consisted of a candidate gene analysis of 12 preselected genes based on known association with host immunologic response to HCV infection. To further reduce the impact of multiple testing on power, a single likelihood ratio test was conducted for each gene using all associated SNPs assayed on the Illumina Quad 610/660W chip. Step-down permutation methods were used to adjust for multiple testing in all analyses. Results. Ninety-five and 62 patients with HCV chronic infection or spontaneous clearance, respectively, were included for analysis. HLA-DQB1 (p = 1.76⁎10(-5)) and IL-6 (p = 0.0007) genes were significantly associated with spontaneous HCV clearance. IL-28B was not significantly associated with spontaneous clearance (p = 0.17). Conclusion. Our whole-gene analytic strategy identified a previously unreported association of IL-6 with spontaneous clearance of HCV infection. We also confirmed the finding that HLA-DQB1 is associated with spontaneous resolution of HCV infection.

BACKGROUND

Data describing patients' priorities, or main concerns, are essential to inform important decisions in healthcare, including treatment planning, diagnostic testing, and the development of programs to improve access and delivery of care. To date, the majority of studies performed does not account for variability in patients' priorities, and as a consequence may not effectively inform end users. The objective of this study was to examine the value of segmentation analysis as a method to illustrate variability in priorities for treatment of chronic hepatitis C (HCV).

METHODS

We elicited patients' main concerns when considering antiviral therapy for HCV using a Best-Worst Scaling experiment (Case 1) with ten objects. Latent class analysis was used to estimate part-worth utilities and the probability that each respondent belongs to each segment.

RESULTS

In the aggregate, subjects (N = 162) had three main concerns: (1) not being cured; (2) experiencing a lot of side effects; and (3) developing viral resistance to therapy. Segmentation into two groups demonstrated that both groups prioritized the likelihood of cure and coping with side effects, but that only one group (n = 78) was concerned about developing viral resistance to therapy, while subjects in the second group (n = 84) prioritized being able to keep up with their responsibilities. Further segmentation revealed distinct clusters of patients with unique priorities.

CONCLUSIONS

Patients' priorities vary significantly. Preference studies should consider including methods to determine whether distinct clusters of priorities and/or concerns exist in order to accurately inform end users' decision making.