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      Clinical decision making in cancer care: a review of current and future roles of patient age

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          Abstract

          Background

          Patient age is among the most controversial patient characteristics in clinical decision making. In personalized cancer medicine it is important to understand how individual characteristics do affect practice and how to appropriately incorporate such factors into decision making. Some argue that using age in decision making is unethical, and how patient age should guide cancer care is unsettled. This article provides an overview of the use of age in clinical decision making and discusses how age can be relevant in the context of personalized medicine.

          Methods

          We conducted a scoping review, searching Pubmed for English references published between 1985 and May 2017. References concerning cancer, with patients above the age of 18 and that discussed age in relation to diagnostic or treatment decisions were included. References that were non-medical or concerning patients below the age of 18, and references that were case reports, ongoing studies or opinion pieces were excluded. Additional references were collected through snowballing and from selected reports, guidelines and articles.

          Results

          Three hundred and forty-seven relevant references were identified. Patient age can have many and diverse roles in clinical decision making: Contextual roles linked to access (age influences how fast patients are referred to specialized care) and incidence (association between increasing age and increasing incidence rates for cancer); patient-relevant roles linked to physiology (age-related changes in drug metabolism) and comorbidity (association between increasing age and increasing number of comorbidities); and roles related to interventions, such as treatment (older patients receive substandard care) and outcome (survival varies by age).

          Conclusions

          Patient age is integrated into cancer care decision making in a range of ways that makes it difficult to claim age-neutrality. Acknowledging this and being more transparent about the use of age in decision making are likely to promote better clinical decisions, irrespective of one’s normative viewpoint. This overview also provides a starting point for future discussions on the appropriate role of age in cancer care decision making, which we see as crucial for harnessing the full potential of personalized medicine.

          Electronic supplementary material

          The online version of this article (10.1186/s12885-018-4456-9) contains supplementary material, which is available to authorized users.

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          Most cited references43

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          Validation of a Prediction Tool for Chemotherapy Toxicity in Older Adults With Cancer.

          Older adults are at increased risk for chemotherapy toxicity, and standard oncology assessment measures cannot identify those at risk. A predictive model for chemotherapy toxicity was developed (N = 500) that consisted of geriatric assessment questions and other clinical variables. This study aims to externally validate this model in an independent cohort (N = 250).
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            Examining the evidence: a systematic review of the inclusion and analysis of older adults in randomized controlled trials.

            Due to a shortage of studies focusing on older adults, clinicians and policy makers frequently rely on clinical trials of the general population to provide supportive evidence for treating complex, older patients. To examine the inclusion and analysis of complex, older adults in randomized controlled trials. A PubMed search identified phase III or IV randomized controlled trials published in 2007 in JAMA, NEJM, Lancet, Circulation, and BMJ. Therapeutic interventions that assessed major morbidity or mortality in adults were included. For each study, age eligibility, average age of study population, primary and secondary outcomes, exclusion criteria, and the frequency, characteristics, and methodology of age-specific subgroup analyses were reviewed. Of the 109 clinical trials reviewed in full, 22 (20.2%) excluded patients above a specified age. Almost half (45.6%) of the remaining trials excluded individuals using criteria that could disproportionately impact older adults. Only one in four trials (26.6%) examined outcomes that are considered highly relevant to older adults, such as health status or quality of life. Of the 42 (38.5%) trials that performed an age-specific subgroup analysis, fewer than half examined potential confounders of differential treatment effects by age, such as comorbidities or risk of primary outcome. Trials with age-specific subgroup analyses were more likely than those without to be multicenter trials (97.6% vs. 79.1%, p < 0.01) and funded by industry (83.3% vs. 62.7%, p < 0.05). Differential benefit by age was found in seven trials (16.7%). Clinical trial evidence guiding treatment of complex, older adults could be improved by eliminating upper age limits for study inclusion, by reducing the use of eligibility criteria that disproportionately affect multimorbid older patients, by evaluating outcomes that are highly relevant to older individuals, and by encouraging adherence to recommended analytic methods for evaluating differential treatment effects by age.
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              The changing prevalence of comorbidity across the age spectrum.

              The purpose of the research was to demonstrate that comorbid health conditions disproportionately affect elderly cancer patients. Descriptive analyses and stacked area charts were used to examine the prevalence and severity of comorbid ailments by age of 27,506 newly diagnosed patients treated at one of eight cancer centers between 1998 and 2003. Hypertension was the most common ailment in all patients, diabetes was the second most prevalent ailment in middle-aged patients, and previous solid tumor(s) were the second most prevalent ailment in patients aged 74 and older. Although the prevalence and severity of comorbid ailments including dementia and congestive heart failure increased with age, some comorbidities such as HIV/AIDS and obesity decreased. Advances in cancer interventions have increased survivorship, but the impact of the changing prevalence and severity of comorbidities at different ages has implications for targeted research into targeted clinical and psychosocial interventions.
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                Author and article information

                Contributors
                eirik.tranvag@uib.no
                ole.norheim@uib.no
                Trygve.ottersen@fhi.no
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                9 May 2018
                9 May 2018
                2018
                : 18
                : 546
                Affiliations
                [1 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Department of Global Public Health and Primary Care, , University of Bergen, ; Bergen, Norway
                [2 ]ISNI 0000 0004 1936 7443, GRID grid.7914.b, Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, , University of Bergen, ; Bergen, Norway
                [3 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Oslo Group on Global Health Policy, Department of Community Medicine and Global Health and Centre for Global Health, , University of Oslo, ; Oslo, Norway
                [4 ]ISNI 0000 0001 1541 4204, GRID grid.418193.6, Division for Health Services, Norwegian Institute of Public Health, ; Oslo, Norway
                Article
                4456
                10.1186/s12885-018-4456-9
                5944161
                29743048
                02a2162e-b892-4c14-8eb5-80b2e46a6edf
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 5 October 2017
                : 30 April 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100005036, Universitetet i Bergen;
                Funded by: FundRef http://dx.doi.org/10.13039/501100005366, Universitetet i Oslo;
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Oncology & Radiotherapy
                decision making,clinical practice,age,age factors,personalized medicine,oncology,priority setting

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