Dennis G. Fryback

The Efficacy of Diagnostic Imaging

The authors discuss the assessment of the contribution of diagnostic imaging to the patient management process. A hierarchical model of efficacy is presented as an organizing structure for appraisal of the literature on efficacy of imaging. Demonstration of efficacy at each lower level in this hierarchy is logically necessary, but not sufficient, to assure efficacy at higher levels. Level 1 concerns technical quality of the images; Level 2 addresses diagnostic ac curacy, sensitivity, and specificity associated with interpretation of the images. Next, Level 3 focuses on whether the information produces change in the referring physicians diagnostic thinking. Such a change is a logical prerequisite for Level 4 efficacy, which concerns effect on the patient management plan. Level 5 efficacy studies measure (or compute) effect of the information on patient outcomes. Finally, at Level 6, analyses examine societal costs and benefits of a diagnostic imaging technology. The pioneering contributions of Dr. Lee B. Lusted in the study of diagnostic imaging efficacy are highlighted.

US norms for six generic health-related quality-of-life indexes from the National Health Measurement study.

Background:A number of indexes measuring self-reported generic health-related quality-of-life (HRQoL) using preference-weighted scoring are used widely in population surveys and clinical studies in the United States. Objective:To obtain age-by-gender norms for older adults on 6 generic HRQoL indexes in a cross-sectional US population survey and compare age-related trends in HRQoL. Methods:The EuroQol EQ-5D, Health Utilities Index Mark 2, Health Utilities Index Mark 3, SF-36v2™ (used to compute SF-6D), Quality of Well-being Scale self-administered form, and Health and Activities Limitations index were administered via telephone interview to each respondent in a national survey sample of 3844 noninstitutionalized adults age 35–89. Persons age 65–89 and telephone exchanges with high percentages of African Americans were oversampled. Age-by-gender means were computed using sampling and poststratification weights to adjust results to the US adult population. Results:The 6 indexes exhibit similar patterns of age-related HRQoL by gender; however, means differ significantly across indexes. Females report slightly lower HRQoL than do males across all age groups. HRQoL seems somewhat higher for persons age 65–74 compared with people in the next younger age decade, as measured by all indexes. Conclusions:Six HRQoL measures show similar but not identical trends in population norms for older US adults. Results reported here provide reference values for 6 self-reported HRQoL indexes.

Report of nationally representative values for the noninstitutionalized US adult population for 7 health-related quality-of-life scores

Background. Despite widespread use of generic health-related quality-of-life (HRQoL) scores, few have publicly published nationally representative US values. Purpose. To create current nationally representative values for 7 of the most common HRQoL scores, stratified by age and sex. Methods. The authors used data from the 2001 Medical Expenditures Panel Survey (MEPS) and the 2001 National Health Interview Survey (NHIS), nationally representative surveys of the US noninstitutionalized civilian population. The MEPS was used to calculate 6 HRQoL scores: categorical self-rated health, EuroQoL-5D with US scoring, EuroQoL-5D with UK scoring, EuroQol Visual Analog Scale, mental and physical component summaries from the SF-12, and the SF-6D. The authors estimated Quality of Well-being scale scores from the NHIS. Results. They included 22,523 subjects from MEPS 2001 and 32,472 subjects from NHIS 2001. Most age and sex categories had instrument completion rates above 85%. Females reported lower scores than males across all ages and instruments. In general, those in older age groups reported lower scores than younger age groups, with the exception of the mental component summary from the SF-12. Conclusion. This is one of the first sets of publicly available, nationally representative US values for any standardized HRQoL measure. These values are important for use in both generalized comparisons of health status and in cost-effectiveness analyses.

Predicting Quality of Well-being Scores from the SF-36: Results from the Beaver Dam Health Outcomes Study

Background. The SF-36 and the Quality of Well-being index (QWB) both quantify health status, yet have very different methodologic etiologies. The authors sought to develop an empirical equation allowing prediction of the QWB from the SF-36. Data. They used empirical observations of SF-36 profiles and QWB scores collected in in terviews of 1,430 persons during the Beaver Dam Health Outcomes Study, a com munity-based population study of health status, and 57 persons from a renal dialysis clinic. Method. The eight scales of the SF-36, their squares, and all pairwise cross- products, were used as candidate variables in stepwise and best-subsets regressions to predict QWB scores using 1,356 interviews reported in a previous paper. The re sulting equation was cross-validated on the remaining 74 cases and using the renal dialysis patients. Results. A six-variable regression equation drawing on five of the SF- 36 components predicted 56.9% of the observed QWB variance. The equation achieved an R2 of 49.5% on cross-validation using Beaver Dam participants and an R2 of 58.7% with the renal dialysis patients. An approximation for computing confidence intervals for predicted QWB mean scores is given. Conclusion. SF-36 data may be used to predict mean QWB scores for groups of patients, and thus may be useful to modelers who are secondary users of health status profile data. The equation may also be used to provide an overall health utility summary score to represent SF-36 profile data so long as the profiles are not severely limited by floor or ceiling effects of the SF-36 scales. The results of this study provide a quantitative link between two important measures of health status. Key words: health status; SF-36; Quality of Well- being index; quality of life; health-state utility; population study. (Med Decis Making 1997;17:1-9

Cost-effectiveness of digital mammography breast cancer screening.

BACKGROUND The DMIST (Digital Mammography Imaging Screening Trial) reported improved breast cancer detection with digital mammography compared with film mammography in selected population subgroups, but it did not assess the economic value of digital relative to film mammography screening. OBJECTIVE To evaluate the cost-effectiveness of digital mammography screening for breast cancer. DESIGN Validated, discrete-event simulation model. DATA SOURCES Data from DMIST and publicly available U.S. data. TARGET POPULATION U.S. women age 40 years or older. TIME HORIZON Lifetime. PERSPECTIVE Societal and Medicare. INTERVENTION All-film mammography screening; all-digital mammography screening; and targeted digital mammography screening, which is age-targeted digital mammography (for women <50 years of age) and age- and density-targeted digital mammography (for women <50 years of age or women > or =50 years of age with dense breasts). OUTCOME MEASURES Cost per quality-adjusted life-year (QALY) gained. RESULTS OF BASE-CASE ANALYSIS All-digital mammography screening cost

Cost-effectiveness of strategies for detecting diabetic retinopathy.

331,000 (95% CI,

Health status and hypertension: A population-based study

268,000 to

Bayes' theorem and conditional nonindependence of data in medical diagnosis

403,000) per QALY gained relative to all-film mammography screening but was more costly and less effective than targeted digital mammography screening. Targeted digital mammography screening resulted in more screen-detected cases of cancer and fewer deaths from cancer than either all-film or all-digital mammography screening, with cost-effectiveness estimates ranging from

Gender differences in health-related quality-of-life are partly explained by sociodemographic and socioeconomic variation between adult men and women in the US: evidence from four US nationally representative data sets

26,500 (CI,

Comparison of 5 Health-Related Quality-of-Life Indexes Using Item Response Theory Analysis:

21,000 to