Evidence in personalised medicine
Personalised medicine is the potential capacity to systematically use information about an individual patient in order to select or optimise that patient’s therapeutic care and tailor individual preventive treatments. Biomarkers need to be used as objective parameters in order to determine a patient’s individual risk profile. The role that features detected by genetic tests play in the causal mechanism of diseases and whether they are suitable starting points for preventive and therapeutic treatments is not always clear.
Drug's Don't Work - Does personalised medicine help?
© The Council on Alcohol and Drugs, Inc.
It is envisaged that large-scale sequencing projects such as the International Cancer Genome Project that are currently progressing with breathtaking, and costly, speed will create the conditions to allow patients to be treated according to individual requirements, including the selection of proper medication and the tailoring of dosages to a patient's specific needs.
In all conditions for which no or inadequate biomarkers are available for making a decision on therapy (and this is the majority of cases), the analysis of the genome, including the epigenome and transcriptome, would make it possible to identify which patients would benefit from a certain medication. There would then be no need to administer an ineffective medication to other patients, who would thus be spared any unpleasant side effects. The selection of appropriate drug therapy also contributes to healthcare cost savings. The dire warning "Drugs don't work" would thus become obsolete.
This is at least the promise behind individualised medicine. Its supporters often also refer to it as “personalised medicine”, a term that sounds a little more modest in its pretensions, since the goal is to find therapies tailored to the needs of certain groups of patients, rather than tailor treatments to the needs of individual patients. It is envisaged that biomarkers will contribute to making diagnosis more accurate and to tailoring a therapy to a particular patient’s needs. In addition, biomarkers also have the potential to contribute to the prevention of diseases as they allow risk profiles to be determined. For example, genetic testing involving biomarkers could be used to predict the risk of (still) healthy people of developing coronary heart disease or diabetes mellitus sometime in their lives; people at risk would then be able to change their dietary habits, stop smoking and remain healthy.
Re-evaluation of existing guidelines
12th Annual Meeting of DNEbM, 24th - 26th March 2011
© DNEbM
But how useful is "biomarker-based predictive-probabilistic health information" for people undergoing genetic testing? Does this information help them to change unhealthy life styles, prevent or positively affect the progression of disease? Do biomarkers really contribute to cost savings, or does this information promote a health economy labelled ‘personalised medicine' for which revenues are really more important than patients?
The 12th Annual Meeting of the German Network of Evidence-based Medicine (DNEbM) focusing on "Evidence and individualised medicine" to be held from 24th to 26th March 2011, will deal with such issues.
Evidence-based medicine is the basis for decisions made by the Joint Federal Committee, the supreme decision-making body of the so-called self-governing system in Germany. Physicians, dentists, psychotherapists, hospitals and sickness funds are represented in the Joint Federal Committee, which issues directives on the benefit package of the statutory health insurance which then makes reimbursement decisions. The guidelines issued by the Joint Federal Committee are based on established methods for assessing the clinical effectiveness of treatments according to the criteria: "sufficient - appropriate - economic - necessary".
It appears that the criteria of evidence-based medicine need to be reviewed and re-evaluated when applied to personalised medicine; for example, in terms of the cost efficiency of new, effective therapeutics used in personalised medicine, conditions other than those used in traditional medicine apply. In addition, the decision on the number of volunteers or patients enrolled in clinical trials - one of the most important measures for determining the efficacy of a drug - needs be take into account new aspects.
Predictive diagnostics of hereditary cancer
It is envisaged that a concept of personalised medicine based on biomarkers will achieve its greatest success in the field of oncology. In many cases, it is only the genetic profile of patients that enable assessments to be made on the type or subtype of tumours and on the efficacy of certain medications. Big hospitals have already put in place routine genetic testing involving genetic markers for breast cancer, certain types of lung and colon cancer and leukaemia before applying targeted therapies involving new drugs such as trastuzumab (Herceptin), cetuximab (Erbitux) or imatinib (Glivec).
The determination of individual risk profiles using biomarkers is quite problematic as the case of the hereditary type of breast cancer shows. Twenty years ago, the American geneticist Mary-Claire King identified the BRCA1 gene on chromosome 17. Women who have inherited certain mutations in this gene have an increased risk of developing breast cancer. BRCA1 and BRCA2, which was later discovered on chromosome 13, are tumour suppressor genes. Around five per cent of all breast cancer patients suffer from hereditary breast cancer, and most of these women have mutations in BRCA1 and BRCA2.
Prof. Dr. Claus Bartram, Institute of Human Genetics, Dean of the Medical Faculty at the University of Heidelberg
© University Hospital Heidelberg
Women carrying BRCA1 and BRCA2 mutations also have an increased risk of developing ovarian cancer. Recently, a German group of researchers discovered another gene (RAD51C) that increases the risk of women developing hereditary breast and ovarian cancer (Meindl et al., Nature Genetics, 18. 04. 2010) during their lifetimes. Genetic tests based on these genes are not used for treatment purposes, but rather as predictive diagnostic tests that might have severe consequences on the way a woman lives her life. Therefore, such predictive diagnostic tests must only be carried out under professional supervision. German Cancer Aid has established twelve "Centres for Familial Breast and Ovarian Cancer" in Germany which offer patients and people with a family history of breast and ovarian cancer the possibility to take part in comprehensive consultations on the probability of developing these cancers, the informative value of diagnostic tests, clinical consequences and psychological problems. The Heidelberg-based Centre for Familial Breast and Ovarian Cancer involves the Heidelberg-based Women's Hospital, the Psychosomatic Hospital and the Division of Molecular Diagnostics in Familiar Cancers of the Institute of Human Genetics (Director: Prof. Dr. Claus Bartram)
Causal relationship between genotype and phenotype
The “Zukunftsreport Individualisierte Medicine und Gesundheitssystem” (Report on Future Individualised Medicine and the Health System) published by the Committee for Education, Research and Technology Assessment of the German Bundestag (Official Record 16/12000 of 17th Feb. 2009) states the following: Biomarkers are objective parameters that can be used for the “assessment of normal biological processes, pathological processes, pharmacological reactions to therapeutic interventions or the assessment of reactions to preventive or other treatment interventions”. Familial breast cancer genetic tests have certain restrictions because it is still difficult to predict the effect certain mutations have on the risk of developing familial breast cancer or on the clinical symptoms.
The relationship between genotype and phenotype is a broad and largely unknown area. The chairman of the German Network of Evidence-Based Medicine, Professor Dr. David Klemperer will highlight in his welcome address to the upcoming congress in 2011: “Disease and health are the results of a unique causal mechanism involving biological, mental and social factors.” The importance of features identified by biomarkers in this causal mechanism, whether the causal factors are necessary or even adequate and whether they can offer starting points for effective interventions, still needs to be investigated.