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Radiation treatment in older patients: a framework for clinical decision making.

ABSTRACT: In older patients, radiation treatment plays a vital role in curative and palliative cancer therapy. Radiation treatment recommendations should be informed by a comprehensive, personalized risk-benefit assessment that evaluates treatment efficacy and toxicity. We review several clinical factors that distinctly affect efficacy and toxicity of radiation treatment in older patients. First, locoregional tumor behavior may be more indolent in older patients for some disease sites but more aggressive for other sites. Assessment of expected locoregional relapse risk informs the magnitude and timeframe of expected radiation treatment benefits. Second, assessment of the competing cancer versus noncancer mortality and morbidity risks contextualizes cancer treatment priorities holistically within patients' entire spectrum and time course of health needs. Third, assessment of functional reserve helps predict patients' acute treatment tolerance, differentiating those patients who are unlikely to benefit from treatment or who are at high risk for treatment complications. Potential radiation treatment options include immediate curative treatment, delayed curative treatment, and no treatment, with additional consideration given to altered radiation target, dose, or sequencing with chemotherapy and/or surgery. Finally, when cure is not feasible, palliative radiation therapy remains valuable for managing symptoms and achieving meaningful quality-of-life improvements. Our proposed decision-making framework integrates these factors to help radiation oncologists formulate strategic treatment recommendations within a multidisciplinary context. Future research is still needed to identify how advanced technologies can be judiciously applied in curative and palliative settings to enhance risk-benefit profiles of radiation treatment in older patients and more accurately quantify treatment efficacy in this group.

SUBMITTER: Smith GL

PROVIDER: S-EPMC4876341 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

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Radiation treatment in older patients: a framework for clinical decision making.

Smith Grace L GL Smith Benjamin D BD

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20140728 24

In older patients, radiation treatment plays a vital role in curative and palliative cancer therapy. Radiation treatment recommendations should be informed by a comprehensive, personalized risk-benefit assessment that evaluates treatment efficacy and toxicity. We review several clinical factors that distinctly affect efficacy and toxicity of radiation treatment in older patients. First, locoregional tumor behavior may be more indolent in older patients for some disease sites but more aggressive ...[more]

PMID: 25071132

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Project description:Background: This study's objectives were to describe community oncologists' beliefs about and confidence with geriatric care and to determine whether geriatric-relevant information influences cancer treatment decisions. Methods: Community oncologists were recruited to participate in 2 multisite geriatric oncology trials. Participants shared their beliefs about and confidence in caring for older adults. They were also asked to make a first-line chemotherapy recommendation (combination vs single-agent vs no chemotherapy) for a hypothetical vignette of an older patient with advanced pancreatic cancer. Each oncologist received one randomly chosen vignette that varied on 3 variables: age (72/84 years), impaired function (yes/no), and cognitive impairment (yes/no). Other patient characteristics were held constant. Logistic regression models were used to identify associations between oncologist/vignette-patient characteristics and treatment decisions. Results: Oncologist response rate was 61% (n=305/498). Most oncologists agreed that "the care of older adults with cancer needs to be improved" (89%) and that "geriatrics training is essential" (72%). However, <25% were "very confident" in recognizing dementia or conducting a fall risk or functional assessment, and only 23% reported using the geriatric assessment in clinic. Each randomly varied patient characteristic was independently associated with the decision to treat: younger age (adjusted odds ratio [aOR], 5.01; 95% CI, 2.73-9.20), normal cognition (aOR, 5.42; 95% CI, 3.01-9.76), and being functionally intact (aOR, 3.85; 95% CI, 2.12-7.00). Accounting for all vignettes across all scenarios, 161 oncologists (52%) said they would offer chemotherapy. All variables were independently associated with prescribing single-agent over combination chemotherapy (older age: aOR, 3.22; 95% CI 1.43-7.25, impaired cognition: aOR, 3.13; 95% CI, 1.36-7.20, impaired function: aOR, 2.48; 95% CI, 1.12-5.72). Oncologists' characteristics were not associated with decisions about providing chemotherapy. Conclusion: Geriatric-relevant information, when available, strongly influences community oncologists' treatment decisions.

Project description:BackgroundThe COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies.MethodsThe information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented.ResultsThe Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher d-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level.InterpretationThe COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the opportunity to build predictive models with a machine learning approach to identify undescribed clinical phenotypes and to foster hospital networks. A real-time updated dashboard built from the Data Mart may represent a valid tool for a better knowledge of epidemiological and clinical features of COVID-19, especially when multiple waves are observed, as well as for epidemic and pandemic events of the same nature (e. g. with critical clinical conditions leading to severe pulmonary inflammation). Therefore, we believe the approach presented in this paper may find several applications in comparable situations even at region or state levels. Finally, models predicting the course of future waves or new pandemics could largely benefit from network of DataMarts.

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Radiation treatment in older patients: a framework for clinical decision making.

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Radiation treatment in older patients: a framework for clinical decision making.

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