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Peripheral arterial disease (PAD), a marker of elevated vascular risk, is highly prevalent in
general practice. We aimed to investigate patient characteristics and outcomes of PAD patients treated according to the guidelines versus those who were not.
Methods. PACE-PAD was a multicentre, cluster - randomised prospective, longitudinal cohort study of patients with PAD in primary care, who were followed-up for death or vascular events over 18 months. Guideline-orientation was assumed, if patients received anti¬coagu¬lant/antiplatelet therapy, exercise training, and (if applicable) advice for smoking cessation and therapy of
diabetes mellitus, hypertension, or hypercholesterolemia, respectively.
Results. The 5099 PAD patients (mean age 68.0 ± 9.0 years, 68.5% males) who were followed-up were in Fontaine stages I, IIa, IIb, III, and IV in 22.5%, 34.6%, 30.1%, 7.8%, and 3.5%
(1.5% not specified). Comprehensive guideline orientation was reported in 28.4% only, however, patients in lower Fontaine stages received more often guideline-oriented therapy (I: 30.3%; IIa: 31.6%, IIb: 29.1%, III: 9.8%, IV: 18.0%). During 18 months, 457 patients died (224 due to cerebrovascular or coronary deaths), 319 had instable angina pectoris, 116 myocardial infarction, and 140 an ischemic stroke event. In total, 24% of patients had experienced any vascular event (19.1% a first event). Event rates did not differ between patients treated according to guidelines, and those who were not.
Conclusion. The present PAD cohort was a high-risk sample with an unexpectedly high rate of deaths and vascular events. While physicians appear to focus on the treatment of individual risk factors, rates of comprehensive PAD management in line with guideline recommendations are still suboptimal. Factors contributing to the lacking difference between outcomes in the guideline-oriented and non-guideline-oriented groups may comprise low treatment intensity or other reasons for unsatisfactory effect of treatment, misclassification of events, patient's non-compliance with therapy.
We analyze risks and crises for healthcare providers and discuss the impact of cloud computing in such scenarios. The analysis is conducted in a holistic way, taking into account organizational and human aspects, clinical, IT-related, and utilities-related risks as well as incorporating the view of the overall risk management.
A crucial attribute of genetically stratifying personalised medicine technologies is the combination of a biomarker test (or a set of more than one) and a therapeutic decision which is made according to the test results. The biomarker test – often called a ‘companion diagnostic’ – is an essential part of the personalised medicine treatment strategy. The US FDA (Food and Drug Administration) approval agency even stated in a recent reflection paper that it would not approve a new drug without the companion biomarker test if a marker is known (FDA, 2011).
According to drug manufacturers, the pharmaceutical industry is suffering from an ‘innovation crisis’. Nowadays, the development of new products requires significantly more investment than in the past. Most of the simple but useful chemical entities seem to have been discovered already. Moreover, many topselling drugs lose their patent protection (‘patent cliff ’) and, subsequently, prices and sales of the original drug are undermined by competing generics. Producers try to compensate for the loss of sales by launches of new molecular entities (Jimenez, 2012). However, the new compounds generate fewer sales. As market observers calculated, new products launched in the period from 2001 to 2005 achieved annual average sales of USD 208 million after three years. New products of the period from 2006 to 2010 reached only USD 143 million (Rockoff and Winslow, 2013). Development of a drug which yields more than a billion USD per year (‘blockbuster’) succeeds less often. Drugs combined with biomarker-based diagnostic tests, stratifying patients into groups characterised by different drug reactions, appear to be one way out of trouble, because a new generation of patented products seems attainable (Scollen and Phelan, 2014).
‘Personalised medicine’ (PM) has raised great hopes and expectations among researchers, patients, health-care providers and politicians in past years. Although the term ‘person’ in PM suggests an approach of medicine which takes into account psychosocial and value aspects of the patient as human being, most articles refer to PM as strategies limited to biological features of individuals which are used to stratify patient groups for the purposes of prevention, diagnosis and treatment of disease.