Dataset Information

Helping patients to reduce tobacco consumption in oncology: a narrative review.

ABSTRACT: The present overview focuses on evidence of smoking cessation approaches in oncology settings with the aim to provide health personnel a critical perspective on how to help their patients. This narrative review is structured in two main sections: the first one describes the psycho-cognitive variables involved in the decision to continue smoking after a cancer diagnosis and during the treatment; the second section relates methods and tools may be recommended, being evidence-based, to support smoking cessation in oncology settings. Active smoking increases not only susceptibility to common cancers in the general population, but also increases disease severity and comorbidities in cancer patients. Nowadays, scientific evidence has identified many strategies to give up smoking, but a lack of knowledge exists for treatment of nicotine dependence in the cancer population. Health personnel is often ambiguous when approaching the problem, while their contribution is essential in guiding patients towards healthier choices. We argue that smoking treatments for cancer patients deserve more attention and that clinical features, individual characteristics and needs of the patient should be assessed in order to increase the attempts success rate. Health personnel that daily work and interact with cancer patients and their caregivers have a fundamental role in the promotion of the health changing. For this reason, it is important that they have adequate knowledge and resources in order to support cancer patients to stop tobacco cigarette smoking and promoting and healthier lifestyle.

SUBMITTER: Lucchiari C

PROVIDER: S-EPMC4954805 | biostudies-other | 2016

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Helping patients to reduce tobacco consumption in oncology: a narrative review.

Lucchiari Claudio C Masiero Marianna M Botturi Andrea A Pravettoni Gabriella G

SpringerPlus 20160720 1

The present overview focuses on evidence of smoking cessation approaches in oncology settings with the aim to provide health personnel a critical perspective on how to help their patients. This narrative review is structured in two main sections: the first one describes the psycho-cognitive variables involved in the decision to continue smoking after a cancer diagnosis and during the treatment; the second section relates methods and tools may be recommended, being evidence-based, to support smok ...[more]

PMID: 27504234

Similar Datasets

Project description:Background and objectiveMachine learning (ML) models are increasingly being utilized in oncology research for use in the clinic. However, while more complicated models may provide improvements in predictive or prognostic power, a hurdle to their adoption are limits of model interpretability, wherein the inner workings can be perceived as a "black box". Explainable artificial intelligence (XAI) frameworks including Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) are novel, model-agnostic approaches that aim to provide insight into the inner workings of the "black box" by producing quantitative visualizations of how model predictions are calculated. In doing so, XAI can transform complicated ML models into easily understandable charts and interpretable sets of rules, which can give providers with an intuitive understanding of the knowledge generated, thus facilitating the deployment of such models in routine clinical workflows.MethodsWe performed a comprehensive, non-systematic review of the latest literature to define use cases of model-agnostic XAI frameworks in oncologic research. The examined database was PubMed/MEDLINE. The last search was run on May 1, 2022.Key content and findingsIn this review, we identified several fields in oncology research where ML models and XAI were utilized to improve interpretability, including prognostication, diagnosis, radiomics, pathology, treatment selection, radiation treatment workflows, and epidemiology. Within these fields, XAI facilitates determination of feature importance in the overall model, visualization of relationships and/or interactions, evaluation of how individual predictions are produced, feature selection, identification of prognostic and/or predictive thresholds, and overall confidence in the models, among other benefits. These examples provide a basis for future work to expand on, which can facilitate adoption in the clinic when the complexity of such modeling would otherwise be prohibitive.ConclusionsModel-agnostic XAI frameworks offer an intuitive and effective means of describing oncology ML models, with applications including prognostication and determination of optimal treatment regimens. Using such frameworks presents an opportunity to improve understanding of ML models, which is a critical step to their adoption in the clinic.

Project description:BackgroundIn 2005, the World Health Organization Framework Convention on Tobacco Control (WHO FCTC) entered into force. This treaty was developed in response to the global tobacco epidemic, and it includes measures to reduce both demand for and supply of tobacco. The measures related to demand reduction include raising tax, providing cessation services, promoting smoke free public places, banning advertising, and raising awareness. However, there are a limited number of measures for supply reduction, and these mainly include fighting illicit trade, banning sales to minors and providing alternatives to tobacco workers and growers. Unlike regulation of many other goods and services that have been subjected to retail restrictions, there is a lack of resources about restricting tobacco availability through regulation of tobacco retail environment. Considering the potential of retail environment regulations in reducing tobacco supply and consequently reducing tobacco use, this scoping review aims to identify relevant measures.MethodsThis review examines interventions, policies, and legislations to regulate tobacco retail environment to reduce tobacco availability. This was done by searching the WHO FCTC and its Conference of Parties decisions, a gray literature search including tobacco control databases, a scoping communication with the Focal Points of the 182 WHO FCTC Parties, and a databases search in PubMed, EMBASE, Cochrane Library, Global Health, and Web of Science.ResultsThemes of policies were identified to reduce tobacco availability by regulating retail environment: four WHO FCTC and twelve non-WHO FCTC policies. The WHO FCTC policies included requiring a license to sell tobacco, banning tobacco sale via vending machines, promoting economically alternative activities to individual sellers, and banning ways of sale that constitute a way of advertising, promotion, and sponsorships. The Non-WHO FCTC policies included banning tobacco home delivery, tray sale, tobacco retail outlets in or within a minimum distance from specific facilities, sale in specific retail outlets, and sale of tobacco or one or more of its products, in addition to restricting tobacco retail outlets per density of population and per geographic area, capping the tobacco amount allowed per purchase, limiting the number of hours or days in which tobacco can be sold, requiring a minimum distance between tobacco retailers, reducing tobacco products availability and proximity within a retail outlet, and restricting sale to government controlled outlets.Discussion and conclusionStudies show the effects of regulation of the retail environment in influencing overall tobacco purchases, and there is evidence that having fewer retails reduces the level of impulse purchasing of cigarettes and tobacco goods. The measures covered by WHO FCTC are much more implemented than ones not covered by it. Although not all widely implemented, many themes of limiting tobacco availability by regulating tobacco retail environment are available. Further studies to explore such measures and the adoption of the effective ones under the WHO FCTC decisions, could possibly increase their implementation globally to reduce tobacco availability.

Dataset Information

Helping patients to reduce tobacco consumption in oncology: a narrative review.

Publications

Helping patients to reduce tobacco consumption in oncology: a narrative review.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets