The report, published by the Department of Health's Human Genomics Strategy Group, is focused on the use of different forms of testing to stratify disease as a means of guiding clinical care. In the longer term the report advocates the routine use of whole genome sequencing as the bedrock for nearly all areas of biomedicine.
There is much to be welcomed in the report. It rightly points to the broad range of tests which are now beginning to find their way into clinical practice and it illustrates how some of these are already benefiting patient care. The report makes important points about the need for a framework for evaluating new tests before they enter routine clinical practice and identifies key areas where translation of basic science into clinically useful technologies and practices might occur.
However, in its enthusiasm for continuing heavy investment in genomics, it may be in danger of overselling what it claims will be 'a revolution in healthcare' (p14). The report describes genomic medicine as a 'major step-change in medical practice', but history suggests that diagnostic innovation is incremental and additive, not revolutionary. There is no reason to suppose that this is about to change. Whilst molecular diagnostics are having a growing impact in medical practice, the scale and pace of change thus far does not suggest a fundamental transformation is underway. The example of testing for the human papilloma virus (HPV) in cervical cancer screening (cited in chapter three) perfectly illustrates that point. In the USA it has not replaced cytology-based screening, it is used as an additional screen or to investigate borderline cytology results (incidentally, HPV testing is presented as a recent advance but it has been a standard of care in the USA for over a decade) (1).
Another instance of overselling in the report's vision statement (chapter one) is a serious overstatement of the current utility of testing for risk of common, complex disease. The truth is that few strongly predictive genetic markers for common complex disease have been found and, for the most part, at the moment we can do no more than tell people that they are at slightly higher than average risk or slightly lower than average risk - information which makes little difference to the kind of disease prevention strategies we should all be following (healthy diet, moderate alcohol intake, regular exercise etc.).
The report's overenthusiasm creates a fundamental tension between the authors' call for more systematic and rigorous evaluation of the evidence supporting the use of new diagnostic tests and their argument for the adoption of routine genome sequencing. The report suggests that once an individual has their genome sequenced, then that data will be used to guide 'every clinical decision' about the person, even if that data has only 'a small relevance' to a given clinical decision (p54). The assumption is that the incremental benefit of using genomic data in a variety of clinical contexts over the course of an individual's life will justify the cost of sequencing. This argument flies in the face of the report's detailed case for a rigorous and robust framework for introducing new diagnostic tests into the NHS. Rather than assuming that we should apply genomic data in any and every clinical situation, what we need are rigorous, well-powered studies which investigate the utility of specific testing applications in particular diseases or clinical contexts. These kinds of trials are expensive and there is little likelihood that the private sector will pay for them, so the onus will fall on government to support those efforts that bring maximum benefit to public health. We have to assume that, as with trials of pharmaceuticals, there will be a high failure rate and that progress will be slow.
There is no doubt that genomics will have a growing impact on healthcare; the scale and pace of that impact remains a matter of conjecture. We can predict with confidence that genome sequencing will continue to become cheaper and faster, but this rapid technological progress should not blind us to the complexity of diagnostic innovation and the challenge of establishing clinical utility for new tests. No matter how cheap genomic data becomes, cost cannot be allowed to trump clinical relevance.