An increased number of available medications, people requiring them, and concomitant disease states in one individual, inevitably lead to greater medication use at the population level. Pharmacoepidemiological studies in older adults have shown an increasing use of several classes of medications over time [1–3]. In this issue of the journal, Gao et al.  investigate the temporal trends in the use of medications in older adults in England in two comparable cohorts participating in the Cognitive Function and Aging Study I (CFAS I, n = 7,359, period 1991–94) and the Cognitive Function and Aging Study II (CFAS II, n = 7,614, period 2008–11). Participants in both studies underwent similar structured interviews regarding the use of prescribed and over the counter medications, including their name, dose, frequency and quantity, as well as clinical and demographic characteristics. The proportion of participants taking ≥5 medications, which commonly indicates polypharmacy, was 12.2% in CFAS I and 49.6% in CFAS II, whereas the proportion of participants taking no medication was 19.9% in CFAS I and 7.8% in CFAS II. The observed temporal trends in medication use in participants aged 65–74 years were similar to those in participants aged ≥75 years. Lipid lowering drugs, angiotensin converting enzyme inhibitors and antiplatelet drugs accounted for the largest increase in medication use between the two cohorts, with additional contributions by endocrine and nutrition/blood drugs, anticholinergic drugs, and proton pump inhibitors. In regression analysis, age, number of long-term conditions, living in an institution, and specific study cohort (CFAS I or CFAS II) were independently associated with increased use of medications . An important strength of the study by Gao et al. is the collection of data from patients in both cohorts using similar interviewing techniques, instead of accessing remote prescription and/or insurance claim databases, which allowed capturing reliable information about prescribed as well as over the counter medications. One limitation is the lack of information, barring self-reported health, regarding whether medication use and its temporal changes had any impact on specific health domains, physical and cognitive function and quality of life. While temporal increases in medication use in the older population have been previously reported, the results of this study indicate a staggering fourfold increase in the proportion of people exposed to polypharmacy in England over a relatively short period of time, 20 years. This is in contrast with recent studies in USA, reporting a prevalence of polypharmacy of 24% in 1990–2000 and of 39% in 2011–12 . As suggested by Gao et al., the increasing number and dissemination of clinical guidelines, the establishment of the National Institute for Clinical Excellence, and the introduction of the Quality and Outcomes Framework in the National Health Service during the study period might have significantly contributed to the findings. However, the lack of available data between CFAS I and CFAS II does not allow establishing whether the temporal increase in medication use was progressive or, rather, stepwise. A variable that was independently associated with medication use in the study by Gao et al. was the number of diagnosed long-term conditions (incidence rate ratio 1.27, 95% CI 1.26–1.28) . While long-term conditions are primarily managed by General Practitioners it is important to emphasise that a significant number of long-term medications, particularly those for secondary prevention in patients surviving an acute event, such as acute coronary syndrome and ischaemic stroke, are typically commenced by hospitalists. However, the latter have limited opportunities for undertaking effective medication reviews, given the ever-growing pressures to maintain inpatient flow and discharge rates, which might result in an increase in the number of medications, medication complexity and polypharmacy after each hospitalisation . Two further points arising from the study by Gao et al. deserve discussion. First, there is a significant debate regarding the appropriateness, efficacy and safety of long-term treatment with several drug classes in older adults, including statins, proton pump inhibitors and anticholinergic drugs [6–8]. Notably, these drugs largely accounted for the significant increase in medication use and polypharmacy between CFAS I and CFAS II . For other increasingly used medications, such as the antiplatelet agent clopidogrel, uncertainty also exists regarding the best treatment duration following an acute event . Second, there are increasing concerns regarding the routine application of the evidence-based knowledge in clinical guidelines to the care of older adults, particularly frail subjects. Whilst clinical guidelines have undoubtedly facilitated a more consistent and rational approach to patient care over the last 20 years, the focus on individual medical conditions and the general nature of their recommendations fail, by definition, to account for specific patient characteristics in the context of complex co-morbidities, drug–drug and drug–disease interactions [10, 11]. Furthermore, the use of disease-centred end-points, based on the assessment of objective parameters in traditional clinical trials, might be of uncertain significance in frail older patients with significant disability and limited life expectancy . The assessment of the impact of disease states and therapies on patient-centred end-points, such as measures of functional status and quality of life, might be useful for the identification of specific co-morbidities that might benefit, more than others, from targeted management strategies in this group. Further research, involving an increasing participation of older adults in clinical trials, is required to ascertain whether the combined use of patient-centred and disease-centred end-points might facilitate the development of new management principles that improve quality of life, and reduce medication use and health care-associated costs, in old age. Key points This study reports a marked increase in medication use in old age in England between the periods 1991–94 and 2008–11. The association between number of long-term conditions and medication use suggests an increasing adherence to guidelines. However, greater medication use exposes older patients to the risk of drug–drug and drug–disease interactions. The combined use of patient- and disease-centred end points might rationalise the future use of medications in old age. Conflict of interest None. Funding None. References 1 Kantor ED, Rehm CD, Haas JS, Chan AT, Giovannucci EL. Trends in prescription drug use among adults in the United States from 1999-2012. JAMA 2015; 314: 1818– 31. Google Scholar CrossRef Search ADS PubMed 2 Sumukadas D, McMurdo ME, Mangoni AA, Guthrie B. Temporal trends in anticholinergic medication prescription in older people: repeated cross-sectional analysis of population prescribing data. Age Ageing 2014; 43: 515– 21. Google Scholar CrossRef Search ADS PubMed 3 Hollingworth S, Duncan EL, Martin JH. Marked increase in proton pump inhibitors use in Australia. Pharmacoepidemiol Drug Saf 2010; 19: 1019– 24. Google Scholar CrossRef Search ADS PubMed 4 Gao L, Maidment I, Matthews FE, Robinson L, Brayne C, Medical Research Council Cognitive F, et al. . Medication usage change in older people (65+) in England over 20 years: findings from CFAS I and CFAS II. Age Ageing 2017; 26: 1– 6. 5 Nobili A, Licata G, Salerno F, Pasina L, Tettamanti M, Franchi C et al. . Polypharmacy, length of hospital stay, and in-hospital mortality among elderly patients in internal medicine wards. The REPOSI study. Eur J Clin Pharmacol 2011; 67: 507– 19. Google Scholar CrossRef Search ADS PubMed 6 Han BH, Sutin D, Williamson JD, Davis BR, Piller LB, Pervin H et al. . Effect of statin treatment vs usual care on primary cardiovascular prevention among older adults: the ALLHAT-LLT randomized clinical trial. JAMA Intern Med 2017; 177: 955– 65. Google Scholar CrossRef Search ADS PubMed 7 Maes ML, Fixen DR, Linnebur SA. Adverse effects of proton-pump inhibitor use in older adults: a review of the evidence. Ther Adv Drug Saf 2017; 8: 273– 97. Google Scholar CrossRef Search ADS PubMed 8 Ruxton K, Woodman RJ, Mangoni AA. Drugs with anticholinergic effects and cognitive impairment, falls and all-cause mortality in older adults: a systematic review and meta-analysis. Br J Clin Pharmacol 2015; 80: 209– 20. Google Scholar CrossRef Search ADS PubMed 9 Palmerini T, Della Riva D, Benedetto U, Bacchi Reggiani L, Feres F, Abizaid A et al. . Three, six, or twelve months of dual antiplatelet therapy after DES implantation in patients with or without acute coronary syndromes: an individual patient data pairwise and network meta-analysis of six randomized trials and 11 473 patients. Eur Heart J 2017; 38: 1034– 43. Google Scholar PubMed 10 Mangoni AA, Jackson SH. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol 2004; 57: 6– 14. Google Scholar CrossRef Search ADS PubMed 11 Reeve E, Wiese MD, Mangoni AA. Alterations in drug disposition in older adults. Expert Opin Drug Metab Toxicol 2015; 11: 491– 508. Google Scholar CrossRef Search ADS PubMed 12 Mangoni AA, Pilotto A. New drugs and patient-centred end-points in old age: setting the wheels in motion. Expert Rev Clin Pharmacol 2016; 9: 81– 9. Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: email@example.com
Age and Ageing – Oxford University Press
Published: Mar 1, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud