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a TRIGR, Trial to Reduce Type 1 Diabetes in the Genetically At-Risk; ENDIT, European Nicotinamide Diabetes Intervention Trial; DPT-1, Diabetes Prevention Trial-1; DIPP, Diabetes Prediction and Prevention Project.

Note: HLA-DQ Screening

TRIGR, Positive for DQB1*0302 and/or *0201; negative for DQB1*0602/3 or *0301.

ENDIT, no genetic screening.

DPT-1, done for ICA+ individuals only; negative DQA1*0102-DQB1*0602.

DIPP, DQB1*02/*0302 or DQB1*0302/X (X = allele other than *02, *0301, or *0602).

ICA Screening

TRIGR, no ICA screening, P-cell autoantibodies are endpoints.

ENDIT, ICA titrs > 20 JDF units on two occasions.

DPT-1, ICA titrs > 20 JDF units; if positive, continue with additional screening tests.

DIPP, no ICA screening, P-cell autoantibodies are endpoints.

a TRIGR, Trial to Reduce Type 1 Diabetes in the Genetically At-Risk; ENDIT, European Nicotinamide Diabetes Intervention Trial; DPT-1, Diabetes Prevention Trial-1; DIPP, Diabetes Prediction and Prevention Project.

Note: HLA-DQ Screening

TRIGR, Positive for DQB1*0302 and/or *0201; negative for DQB1*0602/3 or *0301.

ENDIT, no genetic screening.

DPT-1, done for ICA+ individuals only; negative DQA1*0102-DQB1*0602.

DIPP, DQB1*02/*0302 or DQB1*0302/X (X = allele other than *02, *0301, or *0602).

ICA Screening

TRIGR, no ICA screening, P-cell autoantibodies are endpoints.

ENDIT, ICA titrs > 20 JDF units on two occasions.

DPT-1, ICA titrs > 20 JDF units; if positive, continue with additional screening tests.

DIPP, no ICA screening, P-cell autoantibodies are endpoints.

Several of these studies are now closed to recruitment (119,120). Although these trials are based on first-degree relatives, about 90% of individuals who develop type 1 diabetes have a negative family history of the disease. For interventions to have a public health impact, they must be based on the general population. Unfortunately, the genetic and autoantibody screening strategies used in families of affected individuals are not as effective in the general population (41,42). However, one primary prevention trial based on genetic screening in the general population has recently been initiated [i.e., Diabetes Prediction and Prevention Project (DIPP) (121)].

Although the potential therapies being offered to eligible high-risk individuals are controversial and others may be associated with acute or long-term complications, positive preliminary results are now appearing in the literature (122-124). Thus, there is a critical need to reconsider, from an epidemiologic perspective, the risks and benefits of genetic/autoantibody screening and possible participation in prevention trials for type 1 diabetes. It is also necessary to develop thoughtful approaches for translating the findings from epidemiology into public health practice. This begins with public education, continues with an assessment of the efficacy of the intervention, and includes an evaluation of the effectiveness of the program.

Education and Screening

The final report of the Task Force on Genetic Testing recently noted that "a knowledge base on genetics and genetic testing should be developed for the general public. Without a sound knowledge base, informed decisions are impossible and claims of autonomy and informed consent are suspect" (125). Because genetic screening for type 1 diabetes is currently being performed, it is essential that we begin to address this issue in epidemiology.

Translation involves the utilization of epidemiologic data for public health practice and the development of appropriate policy recommendations. For type 1 diabetes, data collected from population-based epidemiologic studies, such as the WHO DiaMond Molecular Epidemiology Project, provide an excellent foundation for translation. We currently know that for individuals with two HLA-DQ susceptibility haplotypes, the cumulative risk of type 1 diabetes in the general Caucasian population is approximately 5% (25). However, it may range from 0.1% to >90%, depending on one's risk factor profile, which includes age, ethnic, familial, genetic, environmental, and autoimmune determinants. Population-based epidemiologic studies that have investigated these potential determinants are able to generate risk-factor-specific rates. These data can be used to "individualize" risk estimates for those who carry (or do not carry) particular susceptibility genes and have had (or have not had) specific exposures or life experiences. The availability of this information to investigators and potential participants in current type 1 diabetes intervention trials would facilitate education and counseling, before and after genetic/autoantibody screening. In this manner, individuals would be able to make more informed decisions about the risks and benefits of genetic and autoantibody screening and participation in intervention trials.

Economic and Social Issues

The real value of the effect of any prevention program is not just its ability to prevent type 1 diabetes but also its impact on a range of economic, public health, and ethical issues. Concerns that merit strenuous debate include not just the efficacy of a particular prevention program but also its efficiency, equity, and protection of human subjects. At the moment, with yet incomplete data regarding the efficacy of prevention, several alternatives are being discussed: Screening in high-risk populations or screening in the community? Screening with genetic or immunologic or metabolic markers? Treatment with immunologic vaccines or dietary supplements? Each alternative poses different questions regarding the implementation and effect of the prevention program. Several investigators recognize the need to assess the relative costs and benefits (or efficiency) of the programs. It is not clear, though, that equity, accessibility, or privacy issues are included in the requested evaluations. These are the hidden risks that underlie any subsequent program. The privacy of screening data is of noted importance in type 1 diabetes. We have highlighted that persons and families living with type 1 diabetes face meaningful insurance and employment issues. Disregarding this impact is short-sighted.

Equity issues remain one of the most important considerations for determining the success of any intervention program. The data showing the economic influences on the use of diabetes care raise questions about the availability of health care to all. Will diabetes prevention even be available to those who could benefit from it, or will we have another situation of "boutique medicine" (of benefit to a selected few)? There are serious concerns regarding the viability of prevention programs in type 1 diabetes in the whole population and a noted need for more information to more completely evaluate their impact.

Several potential risks of prevention programs are not yet fully understood. Reports in other diseases note a psychological stress or anxiety impact related to screening itself and to false positives in screening tests in particular. At this point, we do not adequately know what impact this may have in screening for type 1 diabetes. What are the ramifications of being falsely told that your son or daughter is very likely to develop diabetes? How will it affect the lifestyle decisions in these families?

Other considerations relate to the desire for information and perceptions of risk. For example, some family members or individuals from the general population actively solicit information regarding their type 1 diabetes risk. However, others prefer not to know their likelihood of developing the disease. This is an extremely important ethical issue because there is currently no cure for diabetes. In addition, the interventions being tested are not appropriated for all individuals at risk. A wide variety of factors may influence one's perception of risk (126,127).

Thus, education programs must be developed with considerable input from those for whom they are targeted. Participation from lay organizations and health departments would be invaluable. Possible strategies for the development of education programs include focus groups and personal interviews conducted in accordance with existing behavioral models, such as the Expanded Health Belief Model (128). Once created, these programs must be made widely available. Self-education packets could be distributed to potential participants in the intervention trials. In addition, an interactive website could be developed. This could not only increase knowledge of type 1 diabetes risk but also improve perception and awareness of the risk and benefits of potential therapies that may become available in the near future.

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