scholarly journals The Supportive Care Needs of Cancer Patients: a Systematic Review

2021 ◽  
Author(s):  
Madeleine Evans Webb ◽  
Elizabeth Murray ◽  
Zane William Younger ◽  
Henry Goodfellow ◽  
Jamie Ross
Keyword(s):  
Cancer Patients ◽  
Healthcare Professionals ◽  
Treatment Options ◽  
Complex Nature ◽  
Narrative Synthesis ◽  
Care Needs ◽  
Wide Range ◽  
Need Support ◽  
Lack Of Control ◽  
Everyday Work

AbstractCancer, and the complex nature of treatment, has a profound impact on lives of patients and their families. Subsequently, cancer patients have a wide range of needs. This study aims to identify and synthesise cancer patients’ views about areas where they need support throughout their care. A systematic  search of the literature from PsycInfo, Embase and Medline databases was conducted, and a narrative. Synthesis of results was carried out using the Corbin & Strauss “3 lines of work” framework. For each line of work, a group of key common needs were identified. For illness-work, the key needs idenitified were; understanding their illness and treatment options, knowing what to expect, communication with healthcare professionals, and staying well. In regards to everyday work, patients wanted to maintain a sense of normalcy and look after their loved ones. For biographical work, patients commonly struggled with the emotion impact of illness and a lack of control over their lives. Spiritual, sexual and financial problems were less universal. For some types of support, demographic factors influenced the level of need reported. While all patients are unique, there are a clear set of issues that are common to a majority of cancer journeys. To improve care, these needs should be prioritised by healthcare practitioners.

The role of healthcare professionals in HPV communication with head and neck cancer patients: A narrative synthesis of qualitative studies

2020 ◽  
Vol 29 (4) ◽  
Author(s):  
Mairead O’Connor ◽  
Bernadine O’Donovan ◽  
Jo Waller ◽  
Alan Ó. Céilleachair ◽  
Pamela Gallagher ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Healthcare Professionals ◽  
Qualitative Studies ◽  
Narrative Synthesis

scholarly journals Pattern and Predictors of Unmet Supportive Care Needs in Cancer Patients

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 117s-117s
Author(s):  
P. Okediji ◽  
O. Salako ◽  
O. Fatiregun
Keyword(s):  
Quality Of Life ◽  
Supportive Care ◽  
Cancer Patients ◽  
Cancer Care ◽  
Unmet Needs ◽  
Supportive Care Needs ◽  
Emotional Instability ◽  
Care Needs ◽  
Wide Range

Background: The incidence of cancers is increasing, and this is associated with an increase in the burden of the disease. Patients with cancer have to deal with reduced physical functioning, emotional instability, difficulty in concentrating, and an overall diminished feeling of well-being. This creates deficits that have not been well catered for by traditional cancer care, leading to an overall dissatisfaction with care, and a reduced quality of life. Aim: This review aims at assessing the pattern of unmet needs in cancer patients and to provide information as to the factors that influence the perception of unmet needs. Methods: Studies directly focused on unmet needs in cancer patients were retrieved from MEDLINE, PubMed, PsychINFO, Embase, and Google Scholar; from the earliest records until 2016. Unmet needs in cancer patients have been measured with a wide variety of tools, with the Supportive Care Needs Survey (SCNS) being the most commonly used as a result of its strong psychometric properties, ease of use, responsiveness, and its coverage of all the domains of unmet needs. Results: The most common unmet needs were in the domains of health system and information, psychological, and physical and daily living. These needs were influenced by sociodemographic factors such as age, sex, marital status, income level; and clinical factors such as location of cancer, stage of disease, and tumor size. Conclusion: It is clear that cancer patients experience a wide range of unmet supportive needs, for which efforts need to be desperately made to improve the supportive care services for these patients and their quality of life. While it may not be possible to meet all the needs of every cancer patient, routine and regular monitoring of unmet needs using the appropriate tools is crucial so that cancer care and other health professionals can develop, implement, and streamline specific aspects of cancer care to strategically meet the specific needs of their patients.

scholarly journals Cancer Healthcare Workers’ Perceptions toward Psychedelic-Assisted Therapy: A Preliminary Investigation

2021 ◽  
Vol 18 (15) ◽  
pp. 8160
Author(s):  
Lisa M. Reynolds ◽  
Amelia Akroyd ◽  
Frederick Sundram ◽  
Aideen Stack ◽  
Suresh Muthukumaraswamy ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Advanced Cancer ◽  
Healthcare Professionals ◽  
Treatment Options ◽  
Preliminary Investigation ◽  
Structured Interview ◽  
Future Research ◽  
Advanced Cancer Patients ◽  
Transformative Approach ◽  
Potential Use

Recent clinical trials suggest that psychedelic-assisted therapy is a promising intervention for reducing anxiety and depression and ameliorating existential despair in advanced cancer patients. However, little is known about perceptions toward this treatment from the key gatekeepers to this population. The current study aimed to understand the perceptions of cancer healthcare professionals about the potential use of psychedelic-assisted therapy in advanced cancer patients. Twelve cancer healthcare professionals including doctors, nurses, psychologists and social workers took part in a semi-structured interview which explored their awareness and perceptions toward psychedelic-assisted therapy with advanced cancer patients. Data were analysed using thematic analysis. Four inter-connected themes were identified. Two themes relate to the role and responsibility of being a cancer healthcare worker: (1) ‘beneficence: a need to alleviate the suffering of cancer patients’ and (2) ‘non-maleficence: keeping vulnerable cancer patients safe’, and two themes relate specifically to the potential for psychedelic-assisted therapy as (3) ‘a transformative approach with the potential for real benefit’ but that (4) ‘new frontiers can be risky endeavours’. The findings from this study suggest intrigue and openness in cancer healthcare professionals to the idea of utilising psychedelic-assisted therapy with advanced cancer patients. Openness to the concept appeared to be driven by a lack of current effective treatment options and a desire to alleviate suffering. However, acceptance was tempered by concerns around safety and the importance of conducting rigorous, well-designed trials. The results from this study provide a useful basis for engaging with healthcare professionals about future research, trial design and potential clinical applications.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

Using Naïve Bayes Algorithm to Estimate the Response to Drug in Lung Cancer Patients

2019 ◽  
Vol 21 (10) ◽  
pp. 734-748 ◽  
Author(s):  
Baoling Guo ◽  
Qiuxiang Zheng
Keyword(s):  
Lung Cancer ◽  
Side Effects ◽  
Cancer Patients ◽  
Drug Response ◽  
Treatment Options ◽  
Clinical Manifestations ◽  
Treatment Strategies ◽  
Cancer Resistance ◽  
Lung Cancer Patients ◽  
Bayes Algorithm

Aim and Objective: Lung cancer is a highly heterogeneous cancer, due to the significant differences in molecular levels, resulting in different clinical manifestations of lung cancer patients there is a big difference. Including disease characterization, drug response, the risk of recurrence, survival, etc. Method: Clinical patients with lung cancer do not have yet particularly effective treatment options, while patients with lung cancer resistance not only delayed the treatment cycle but also caused strong side effects. Therefore, if we can sum up the abnormalities of functional level from the molecular level, we can scientifically and effectively evaluate the patients' sensitivity to treatment and make the personalized treatment strategies to avoid the side effects caused by over-treatment and improve the prognosis. Result & Conclusion: According to the different sensitivities of lung cancer patients to drug response, this study screened out genes that were significantly associated with drug resistance. The bayes model was used to assess patient resistance.

Selecting a PRO-CTCAE based subset for patient reported symptom monitoring during lung cancer treatment (Preprint)

2020 ◽  
Author(s):  
Evalien Veldhuijzen ◽  
Iris Walraven ◽  
Jose Belderbos
Keyword(s):  
Lung Cancer ◽  
Clinical Practice ◽  
Cancer Patients ◽  
Treatment Modalities ◽  
European Organization ◽  
Specific Patient ◽  
Symptom Monitoring ◽  
Lung Cancer Patients ◽  
Wide Range ◽  
Patient Reported

BACKGROUND The Patient Reported Outcomes Version of the Common Terminology Criteria of Adverse Events (PRO-CTCAE) item library covers a wide range of symptoms relevant for oncology care. To enable implementation of PRO-CTCAE-based symptom monitoring in clinical practice, there is a need to select a subset of items relevant for specific patient populations. OBJECTIVE The aim of this study was to develop a PRO-CTCAE subset relevant for patients with lung cancer. METHODS The PRO-CTCAE-based subset for lung cancer patients was generated using a mixed methods approach based on the European Organization for Research and Treatment of Cancer (EORTC) guidelines for developing questionnaires, consisting of a literature review and semi-structured interviews with both lung cancer patients and health care practitioners (HCPs). Both patients and HCPs were queried on the relevance and impact of all PRO-CTCAE items. Results were summarized and, after a final round of expert review, a selection of clinically relevant items for lung cancer patients was made. RESULTS A heterogeneous group of lung cancer patients (n=25) from different treatment modalities and HCPs (n=22) participated in the study. A final list of eight relevant PRO-CTCAE items was created: decreased appetite, cough, shortness of breath, fatigue, constipation, nausea, sadness, and pain (general). CONCLUSIONS Based on literature and both professional and patient input, a subset of PRO-CTCAE items has been identified for use in lung cancer patients in clinical practice. Future work is needed to confirm the validity and effectiveness of this PRO-CTCAE lung cancer subset internationally, and in the real-world clinical practice setting.

scholarly journals What makes palliative care needs “complex”? A multisite sequential explanatory mixed methods study of patients referred for specialist palliative care

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Anne M. Finucane ◽  
Connie Swenson ◽  
John I. MacArtney ◽  
Rachel Perry ◽  
Hazel Lamberton ◽  
...  
Keyword(s):  
Palliative Care ◽  
Focus Groups ◽  
Healthcare Professionals ◽  
Psychological Needs ◽  
Care Providers ◽  
Specialist Palliative Care ◽  
Care Needs ◽  
Complex Needs ◽  
Sequential Explanatory ◽  
Palliative Care Needs

Abstract Background Specialist palliative care (SPC) providers tend to use the term ‘complex’ to refer to the needs of patients who require SPC. However, little is known about complex needs on first referral to a SPC service. We examined which needs are present and sought the perspectives of healthcare professionals on the complexity of need on referral to a hospice service. Methods Multi-site sequential explanatory mixed method study consisting of a case-note review and focus groups with healthcare professionals in four UK hospices. Results Documentation relating to 239 new patient referrals to hospice was reviewed; and focus groups involving 22 healthcare professionals conducted. Most patients had two or more needs documented on referral (96%); and needs were recorded across two or more domains for 62%. Physical needs were recorded for 91% of patients; psychological needs were recorded for 59%. Spiritual needs were rarely documented. Referral forms were considered limited for capturing complex needs. Referrals were perceived to be influenced by the experience and confidence of the referrer and the local resource available to meet palliative care needs directly. Conclusions Complexity was hard to detail or to objectively define on referral documentation alone. It appeared to be a term used to describe patients whom primary or secondary care providers felt needed SPC knowledge or support to meet their needs. Hospices need to provide greater clarity regarding who should be referred, when and for what purpose. Education and training in palliative care for primary care nurses and doctors and hospital clinicians could reduce the need for referral and help ensure that hospices are available to those most in need of SPC input.

scholarly journals Data Driven Mathematical Model of FOLFIRI Treatment for Colon Cancer

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2632
Author(s):  
Aparajita Budithi ◽  
Sumeyye Su ◽  
Arkadz Kirshtein ◽  
Leili Shahriyari
Keyword(s):  
Mathematical Model ◽  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Cell ◽  
Treatment Options ◽  
Data Driven ◽  
T Helper ◽  
Primary Tumors ◽  
Cell Fractions

Many colon cancer patients show resistance to their treatments. Therefore, it is important to consider unique characteristic of each tumor to find the best treatment options for each patient. In this study, we develop a data driven mathematical model for interaction between the tumor microenvironment and FOLFIRI drug agents in colon cancer. Patients are divided into five distinct clusters based on their estimated immune cell fractions obtained from their primary tumors’ gene expression data. We then analyze the effects of drugs on cancer cells and immune cells in each group, and we observe different responses to the FOLFIRI drugs between patients in different immune groups. For instance, patients in cluster 3 with the highest T-reg/T-helper ratio respond better to the FOLFIRI treatment, while patients in cluster 2 with the lowest T-reg/T-helper ratio resist the treatment. Moreover, we use ROC curve to validate the model using the tumor status of the patients at their follow up, and the model predicts well for the earlier follow up days.

scholarly journals A Systematic Review of Healthcare Professionals’ Knowledge, Self-Efficacy and Attitudes Towards Working with Autistic People

2021 ◽  
Author(s):  
Kirsten Corden ◽  
Rebecca Brewer ◽  
Eilidh Cage
Keyword(s):  
Health Professionals ◽  
Self Efficacy ◽  
Healthcare Professionals ◽  
Assessment Tool ◽  
Vital Role ◽  
Narrative Synthesis ◽  
Quality Assessment Tool ◽  
Professional Background ◽  
Autistic People

AbstractHealthcare professionals play a vital role in identifying and supporting autistic people. This study systematically reviewed empirical research examining healthcare professionals’ knowledge, self-efficacy and attitudes towards working with autistic people. Thirty-five studies were included. The included studies sampled a range of countries and professional backgrounds. A modified quality assessment tool found the quality of the included studies was moderately good. Narrative synthesis indicated that healthcare professionals report only moderate levels of autism knowledge and self-efficacy, and often lack training. Variation within and between countries and professional background was not explained by demographic factors. The reviewed evidence suggests health professionals’ limited knowledge and self-efficacy in working with autistic people is a challenge to the provision of healthcare for autistic individuals.

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