Can the General Public Be a Proxy for an "At-Risk" Group in a Patient Preference Study? A Disease Prevention Example in Rheumatoid Arthritis

BACKGROUND

When selecting samples for patient preference studies, it may be difficult or impractical to recruit participants who are eligible for a particular treatment decision. However, a general public sample may not be an appropriate proxy.

OBJECTIVE

This study compares preferences for rheumatoid arthritis (RA) preventive treatments between members of the general public and first-degree relatives (FDRs) of confirmed RA patients to assess whether a sample of the general public can be used as a proxy for FDRs.

METHODS

Participants were asked to imagine they were experiencing arthralgia and had screening tests indicating a 60% chance of developing RA within 2 yrs. Using a discrete choice experiment, participants were offered a series of choices between no treatment and 2 unlabeled hypothetical treatments to reduce the risk of RA. To assess data quality, time to complete survey sections and comprehension questions were assessed. A random parameter logit model was used to obtain attribute-level estimates, which were used to calculate relative importance, maximum acceptable risk (MAR), and market shares of hypothetical preventive treatments.

RESULTS

The FDR sample (n = 298) spent more time completing the survey and performed better on comprehension questions compared with the general public sample (n = 982). The relative importance ranking was similar between the general public and FDR participant samples; however, other relative preference measures involving weights including MARs and market share differed between groups, with FDRs having numerically higher MARs.

CONCLUSION

In the context of RA prevention, the general public (average risk) may be a reasonable proxy for a more at-risk sample (FDRs) for overall relative importance ranking but not weights. The rationale for a proxy sample should be clearly justified.

HIGHLIGHTS

Participants from the general public were compared to first-degree relatives on their preferences for rheumatoid arthritis (RA) preventive treatments using a discrete choice experiment.Preferences were similar between groups in terms of the most important and least important attributes of preventive treatments, with effectiveness being the most important attribute. However, relative weights differed.Attention to the survey and predicted market shares of hypothetical RA preventive treatments differed between the general public and first-degree relatives.The general public may be a reasonable proxy for an at-risk group for patient preferences ranks but not weights in the disease prevention context; however, care should be taken in sample selection for patient preference studies when choosing nonpatients.

Developing Trauma-Informed Research Methods: Using Proxy Respondents to Assess Sexual Assault Survivors' Experiences Seeking Medical Forensic Exams

In research on sexual assault victims' help-seeking, proxy data sources are often utilized because outreach to survivors immediately postassault may increase a study's risk-to-benefit ratio. Victim advocates and services providers are common proxy respondents, but empirical research comparing the accuracy of their information is needed. We collaborated with seven sexual assault nurse examiner (SANE) programs to collect de-identified, paired data from nurses and advocates regarding the help-seeking experiences of N = 744 adult victims. Using pairwise McNemar tests, we found statistically significant agreement on victim demographics, assault characteristics, and victims' decisions regarding medical forensic exams, sexual assault kit (SAK) collection, and release of SAKs for forensic DNA testing. Nurses and advocates had different information regarding victims' disclosure histories and their reasons for seeking SANE care.

Does the Relationship of the Proxy to the Target Person Affect the Concordance between Survey Reports and Medicare Claims Measures of Health Services Use?

OBJECTIVES

To compare concordance of survey reports of health service use versus claims data between self respondents and spousal and nonspousal relative proxies.

DATA SOURCES

1995-2010 data from the Survey on Assets and Health Dynamics among the Oldest Old and 1993-2010 Medicare claims for 3,229 individuals (13,488 person-years).

STUDY DESIGN

Regression models with individual fixed effects were estimated for discordance of any hospitalizations and outpatient surgery and for the numbers of under- and over-reported physician visits.

PRINCIPAL FINDINGS

Spousal proxies were similar to self respondents on discordance. Nonspousal proxies, particularly daughters/daughters-in-law and sons/sons-in-law, had less discordance, mainly due to reduced under-reporting.

CONCLUSIONS

Survey reports of health services use from nonspousal relatives are more consistent with Medicare claims than spousal proxies and self respondents.

Statistical analysis with missing exposure data measured by proxy respondents: a misclassification problem within a missing-data problem

In studies of older adults, researchers often recruit proxy respondents, such as relatives or caregivers, when study participants cannot provide self-reports (e.g., because of illness). Proxies are usually only sought to report on behalf of participants with missing self-reports; thus, either a participant self-report or proxy report, but not both, is available for each participant. Furthermore, the missing-data mechanism for participant self-reports is not identifiable and may be nonignorable. When exposures are binary and participant self-reports are conceptualized as the gold standard, substituting error-prone proxy reports for missing participant self-reports may produce biased estimates of outcome means. Researchers can handle this data structure by treating the problem as one of misclassification within the stratum of participants with missing self-reports. Most methods for addressing exposure misclassification require validation data, replicate data, or an assumption of nondifferential misclassification; other methods may result in an exposure misclassification model that is incompatible with the analysis model. We propose a model that makes none of the aforementioned requirements and still preserves model compatibility. Two user-specified tuning parameters encode the exposure misclassification model. Two proposed approaches estimate outcome means standardized for (potentially) high-dimensional covariates using multiple imputation followed by propensity score methods. The first method is parametric and uses maximum likelihood to estimate the exposure misclassification model (i.e., the imputation model) and the propensity score model (i.e., the analysis model); the second method is nonparametric and uses boosted classification and regression trees to estimate both models. We apply both methods to a study of elderly hip fracture patients.

Evaluating the quality of life of cancer patients: assessments by patients, significant others, physicians and nurses

This study examined the usefulness of caregiver ratings of cancer patients' quality of life (QOL), an issue of relevance to both adequate patient care and to the possible use of proxy QOL raters in clinical studies. We compared QOL ratings of 90 cancer patients receiving inpatient chemotherapy with those provided by their significant others (most often the spouse), physicians and nurses. During patients' scheduled appointment for receiving chemotherapy on a clinical ward, all raters completed independently the Dartmouth COOP Functional Health Assessment charts/WONCA, an instrument developed by a cooperative group of primary care physicians to briefly assess a core set of seven QOL domains (physical fitness, feelings, daily and social activities, overall health, pain and quality of life) by single items with five response options. With few exceptions, mean scores of the proxy raters were equivalent or similar to those of the patients. Most patient-proxy correlations varied between 0.40 and 0.60, indicating a moderate level of agreement at the individual level. Of all comparisons made, 41% were in exact agreement and 43% agreed within one response category, leaving 17% more profound patient-proxy discrepancies. Disagreement was not dependent on the type of proxy rater, or on raters' background characteristics, but was influenced by the QOL dimension under consideration and the clinical status of the patient. Better patient-proxy agreement was observed for more concrete questions (daily activities, pain) and for patients with either a very good (ECOG 0) or poor (ECOG 3) performance status. The results indicate that both significant others and health care providers can be useful sources of information about cancer patients' QOL.