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IIR 03-162 – HSR Study

IIR 03-162
Patient Preferences for Treatment of Hepatitis C
Liana Fraenkel, MD MPH FRCPC
VA Connecticut Healthcare System West Haven Campus, West Haven, CT
West Haven, CT
Funding Period: October 2003 - September 2008
The immediate goal of this project is to develop a psychometrically robust tool using Adaptive Conjoint Analysis (ACA) that can be applied to improve patient education about antiviral treatment for HCV, elicit patient treatment preferences (i.e., whether or not to accept antiviral therapy), and facilitate decision-making at the individual patient level. If positive, the results from this project will support an intervention trial to determine whether explicit elicitation of individual patient preferences using ACA facilitates decision-making and improves clinical outcomes in veterans with HCV. Our long-term goal is to disseminate a reliable and valid tool for use throughout the Veterans Affairs (VA) healthcare systems in order to improve delivery of health services to veterans with HCV.

SPECIFIC AIM 1: To develop an Adaptive Conjoint Analysis questionnaire for patients with HCV.
1a. To determine which attributes physicians take into consideration when deciding whether or not patients should receive antiviral therapy for HCV.
1b. To determine which attributes patients take into consideration when deciding whether or not to accept antiviral therapy for HCV.
1c. To design and pilot an ACA questionnaire, and to subsequently revise the questionnaire, based on patient and physician feedback.
SPECIFIC AIM 2: To describe patient preferences for treatment of HCV using ACA.
2a. To quantify the influence of specific medication characteristics on treatment preference.
2b. To describe the proportion of patients willing to accept antiviral therapy.
2c. To describe how patients' sociodemographic characteristics, comorbidity, and health beliefs relate to treatment preferences.
2d.To compare treatment preferences in veteran and nonveteran populations.

SPECIFIC AIM 3: To test the value and acceptability of ACA as a decision aid for patients with HCV in clinical practice.
3a. To test the psychometric properties of the ACA questionnaire.
3b. To determine whether patients and their treating physicians consider ACA to be an acceptable tool to facilitate decision-making in clinical practice.

We recruited consecutive patients eligible for treatment of HCV. Baseline data were collected in face-to-face interviews with a research assistant. Participants then completed an ACA task designed to help patients evaluate the pros and cons related to treatment of HCV with pegylated interferon and ribavirin before seeing their physician. Attributes for the ACA questionnaire were chosen based on patient testimonials obtained from focus groups. Preferences were measured for two choices: 1. Treatment associated with mild side effects versus no treatment, and 2. Treatment associated with severe side effects versus no treatment. Criterion validity was assessed by measuring the association between preferences predicted by ACA and the treatment plan, as well as by ascertaining the correlations between preferences predicted by ACA and patient values.

Patient Characteristics
Of 212 eligible subjects, 178 agreed to participate and 140 completed the ACA task. The computer task was not performed in 38 eligible patients for the following reasons: 21 patients cancelled or did not come to their appointment, six patients did not have the time to complete the task, eight could not participate because of a scheduling error, and the computer malfunctioned on three occasions. The mean ( SD) age of the sample was 51 8, 85% were male, 59% were White and 30% Black. Further details regarding subjects' characteristics are provided in Table 1.
Treatment Preferences
Sixty-seven percent (N=94) of subjects' preferred treatment for HCV if associated with mild side effects. The percentage of subjects preferring therapy decreased to 51% (N=72) when it was described as being associated with severe side effects.
In unadjusted analyses, preferences for treatment of HCV were stronger among women, as well as subjects with a higher perceived risk of developing cirrhosis, more severe liver disease, and worse HCV-related quality of life. Those with greater decisional conflict had weaker preferences for treatment. In this model, female gender and extent of underlying liver disease were the strongest predictors of preference for HCV treatment. We found no other relationships between the remaining demographic characteristics, the use of drugs or alcohol, current health status, social support or trust in physician and treatment preference. No differences were found when the analyses were repeated for treatment associated with mild side effects.
Given that we recruited patients from two distinct sites, we also performed exploratory subgroup analyses by site (Tables 4a and 4b). In these analyses, patients reporting a history of mental illness were more likely to prefer treatment at the VA (60% versus 37%, p=0.02), but less likely to prefer treatment at the University Clinic (44% versus 71%, p=0.07). In addition, the extent of underlying liver disease was a strong predictor of preference at the VA, but not at the University Clinic. At both sites, the majority of patients with either moderate or severe fibrosis preferred treatment. However, subjects at the University Clinic with mild or no fibrosis were more likely to prefer treatment compared to those recruited from the VA (50% versus 24%, p=0.08).
Overall, the likelihood of benefit was most important to subjects and the need for blood test monitoring least important. The risk of fatigue, depression and flu-like illness all had similar influences on subjects' preferences. Table 6 displays the impact of each characteristic by severity of liver disease. These results demonstrate significant associations between the severity of liver disease on biopsy and the relative impact of risk and benefits, with subjects having more severe disease placing greater weight on the importance of expected benefits and less on the risk of toxicity compared to those with mild or no fibrosis. This pattern was also observed in subgroup analyses by site.

We have now described patients percepectives related to the decision making process in HCV - and veterans' experiences related to adverse effects of treatment. The updated abstract represents the results of the latest paper and describes the variability of veterans' preferences for treatment of HCV.

External Links for this Project

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Journal Articles

  1. Grayson PC, Amudala NA, McAlear CA, Leduc RL, Shereff D, Richesson R, Fraenkel L, Merkel PA. Causal attributions about disease onset and relapse in patients with systemic vasculitis. The Journal of rheumatology. 2014 May 1; 41(5):923-30. [view]
  2. Abraham NS, Naik AD, Street RL, Castillo DL, Deswal A, Richardson PA, Hartman CM, Shelton G, Fraenkel L. Complex antithrombotic therapy: determinants of patient preference and impact on medication adherence. Patient preference and adherence. 2015 Nov 19; 9(1):1657-68. [view]
  3. Fraenkel L, Lim J, Garcia-Tsao G, Reyna V, Monto A. Examining Hepatitis C Virus Treatment Preference Heterogeneity Using Segmentation Analysis: Treat Now or Defer? Journal of clinical gastroenterology. 2016 Mar 1; 50(3):252-7. [view]
  4. Hodgson EJ, Collier C, Hayes L, Curry LA, Fraenkel L. Family planning and contraceptive decision-making by economically disadvantaged, African-American women. Contraception. 2013 Aug 1; 88(2):289-96. [view]
  5. Fraenkel L. Incorporating patients' preferences into medical decision making. Medical care research and review : MCRR. 2013 Feb 1; 70(1 Suppl):80S-93S. [view]
  6. Hsieh E, Fraenkel L, Han Y, Xia W, Insogna KL, Yin MT, Zhu T, Cheng X, Li T. Longitudinal increase in vitamin D binding protein levels after initiation of tenofovir/lamivudine/efavirenz among individuals with HIV. AIDS. 2016 Jul 31; 30(12):1935-42. [view]
  7. Fraenkel L, McGraw S. Participation in medical decision making: the patients' perspective. Medical Decision Making. 2007 Sep 1; 27(5):533-8. [view]
  8. Fraenkel L, Peters E. Patient responsibility for medical decision making and risky treatment options. Arthritis Rheum. 2009 Dec 15; 61(12):1674-6. [view]
  9. Fraenkel L, McGraw S, Wongcharatrawee S, Garcia-Tsao G. Patients' experiences related to anti-viral treatment for hepatitis C. Patient education and counseling. 2006 Jul 1; 62(1):148-55. [view]
  10. Fraenkel L, Chodkowski D, Lim J, Garcia-Tsao G. Patients' preferences for treatment of hepatitis C. Medical Decision Making. 2010 Jan 1; 30(1):45-57. [view]
  11. Makris UE, Higashi RT, Marks EG, Fraenkel L, Gill TM, Friedly JL, Reid MC. Physical, Emotional, and Social Impacts of Restricting Back Pain in Older Adults: A Qualitative Study. Pain medicine (Malden, Mass.). 2017 Jul 1; 18(7):1225-1235. [view]
  12. Janke EA, McGraw S, Garcia-Tsao G, Fraenkel L. Psychosocial issues in hepatitis C: a qualitative analysis. Psychosomatics. 2008 Nov 1; 49(6):494-501. [view]
  13. Kohler MJ, Amezaga M, Drozd J, Crowley ST, Gulanski B, Anderson DR, Fraenkel L. Use of a computerized order set to increase prescription of calcium and vitamin D supplementation in patients receiving glucocorticoids. Journal of general internal medicine. 2013 Jun 1; 28(6):825-9. [view]
  14. Fraenkel L, Lim J, Garcia-Tsao G, Reyna V, Monto A, Bridges JF. Variation in Treatment Priorities for Chronic Hepatitis C: A Latent Class Analysis. The patient. 2016 Jun 1; 9(3):241-9. [view]
  15. Fraenkel L, McGraw S, Wongcharatrawee S, Garcia-Tsao G. What do patients consider when making decisions about treatment for hepatitis C? The American journal of medicine. 2005 Dec 1; 118(12):1387-91. [view]

DRA: Health Systems
DRE: none
Keywords: Chronic disease (other & unspecified), Communication -- doctor-patient, Patient preferences
MeSH Terms: none

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