Optimal Care Pathways for People with Lung Cancer- a Scoping Review of the Literature

Understanding the impact of distance and disadvantage on lung cancer care and outcomes: a study protocol

BACKGROUND

Lung cancer is the third most common cancer in the UK and the leading cause of cancer mortality globally. NHS England guidance for optimum lung cancer care recommends management and treatment by a specialist team, with experts concentrated in one place, providing access to specialised diagnostic and treatment facilities. However, the complex and rapidly evolving diagnostic and treatment pathways for lung cancer, together with workforce limitations, make achieving this challenging. This place-based, behavioural science-informed qualitative study aims to explore how person-related characteristics interact with a person's location relative to specialist services to impact their engagement with the optimal lung pathway, and to compare and contrast experiences in rural, coastal, and urban communities. This study also aims to generate translatable evidence to inform the evidence-based design of a patient engagement intervention to improve lung cancer patients' and informal carers' participation in and experience of the lung cancer care pathway.

METHODS

A qualitative cross-sectional interview study with people diagnosed with lung cancer < 6 months before recruitment (in receipt of surgery, radical radiotherapy, or living with advanced disease) and their informal carers. Participants will be recruited purposively from Barts Health NHS Trust and United Lincolnshire Hospitals NHS Trusts to ensure a diverse sample across urban and rural settings. Semi-structured interviews will explore factors affecting individuals' capability, opportunity, and motivation to engage with their recommended diagnostic and treatment pathway. A framework approach, informed by the COM-B model, will be used to thematically analyse facilitators and barriers to patient engagement.

DISCUSSION

The study aligns with the current policy priority to ensure that people with cancer, no matter where they live, can access the best quality treatments and care. The evidence generated will be used to ensure that lung cancer services are developed to meet the needs of rural, coastal, and urban communities. The findings will inform the development of an intervention to support patient engagement with their recommended lung cancer pathway.

PROTOCOL REGISTRATION

The study received NHS Research Ethics Committee (Ref: 23/SC/0255) and NHS Health Research Authority (IRAS ID 328531) approval on 04/08/2023. The study was prospectively registered on Open Science Framework (16/10/2023; https://osf.io/njq48 ).

VER-Net: a hybrid transfer learning model for lung cancer detection using CT scan images

BACKGROUND

Lung cancer is the second most common cancer worldwide, with over two million new cases per year. Early identification would allow healthcare practitioners to handle it more effectively. The advancement of computer-aided detection systems significantly impacted clinical analysis and decision-making on human disease. Towards this, machine learning and deep learning techniques are successfully being applied. Due to several advantages, transfer learning has become popular for disease detection based on image data.

METHODS

In this work, we build a novel transfer learning model (VER-Net) by stacking three different transfer learning models to detect lung cancer using lung CT scan images. The model is trained to map the CT scan images with four lung cancer classes. Various measures, such as image preprocessing, data augmentation, and hyperparameter tuning, are taken to improve the efficacy of VER-Net. All the models are trained and evaluated using multiclass classifications chest CT images.

RESULTS

The experimental results confirm that VER-Net outperformed the other eight transfer learning models compared with. VER-Net scored 91%, 92%, 91%, and 91.3% when tested for accuracy, precision, recall, and F1-score, respectively. Compared to the state-of-the-art, VER-Net has better accuracy.

CONCLUSION

VER-Net is not only effectively used for lung cancer detection but may also be useful for other diseases for which CT scan images are available.

Improving the quality of patient care in lung cancer: key factors for successful multidisciplinary team working

International Guidelines as well as Cancer Associations recommend a multidisciplinary approach to lung cancer care. A multidisciplinary team (MDT) can significantly improve treatment decision-making and patient coordination by putting different physicians and other health professionals "in the same room", who collectively decide upon the best possible treatment. However, this is not a panacea for cancer treatment. The impact of multidisciplinary care (MDC) on patient outcomes is not univocal, while the effective functioning of the MDT depends on many factors. This review presents the available MDT literature with an emphasis on the key factors that characterize high-quality patient care in lung cancer. The study was conducted with a bibliographic search using different electronic databases (PubMed Central, Scopus, Google Scholar, and Google) referring to multidisciplinary cancer care settings. Many key elements appear consolidated, while others emerge as prevalent and actual, especially those related to visible barriers which work across geographic, organizational, and disciplinary boundaries. MDTs must be sustained by strategic management, structured within the entity, and cannot be managed as a separate care process. Furthermore, they need to coordinate with other teams (within and outside the organization) and join with the broad range of services delivered by multiple providers at various points of the cancer journey or within the system, with the vision of integrated care.

A systematic review on the qualitative experiences of people living with lung cancer in rural areas

PURPOSE

To synthesize the qualitative literature exploring the experiences of people living with lung cancer in rural areas.

METHODS

Searches were performed in MEDLINE, CINAHL, and PsycINFO. Articles were screened independently by two reviewers against pre-determined eligibility criteria. Data were synthesized using Thomas and Harden's framework for the thematic synthesis of qualitative research. The CASP qualitative checklist was used for quality assessment and the review was reported in accordance with the ENTREQ and PRISMA checklists.

RESULTS

Nine articles were included, from which five themes were identified: (1) diagnosis and treatment pathways, (2) travel and financial burden, (3) communication and information, (4) experiences of interacting with healthcare professionals, (5) symptoms and health-seeking behaviors. Lung cancer diagnosis was unexpected for some with several reporting treatment delays and long wait times regarding diagnosis and treatment. Accessing treatment was perceived as challenging and time-consuming due to distance and financial stress. Inadequate communication of information from healthcare professionals was a common concern expressed by rural people living with lung cancer who also conveyed dissatisfaction with their healthcare professionals. Some were reluctant to seek help due to geographical distance and sociocultural factors whilst others found it challenging to identify symptoms due to comorbidities.

CONCLUSIONS

This review provides a deeper understanding of the challenges faced by people with lung cancer in rural settings, through which future researchers can begin to develop tailored support to address the existing disparities that affect this population.

Role of digital health in coordinating patient care in a hub-and-spoke hierarchy of cancer care facilities: a scoping review

Background

Coordinating cancer care is complicated due to the involvement of multiple service providers which often leads to fragmentation. The evolution of digital health has led to the development of technology-enabled models of healthcare delivery. This scoping review provides a comprehensive summary of the use of digital health in coordinating cancer care via hub-and-spoke models.

Methods

A scoping review of the literature was undertaken using the framework developed by Arksey and O'Malley. Research articles published between 2010 and 2022 were retrieved from four electronic databases (PubMed/MEDLINE, Web of Sciences, Cochrane Reviews and Global Health Library). The preferred reporting items for systematic reviews and meta-analyses extension for the scoping reviews (PRISMA-ScR) checklist were followed to present the findings.

Result

In total, 311 articles were found of which 7 studies that met the inclusion criteria were included. The use of videoconferencing was predominant across all the studies. The number of spokes varied across the studies ranging from 1 to 63. Three studies aimed to evaluate the impact on access to cancer care among patients, two studies were related to capacity building of the health care workers at the spoke sites, one study was based on a peer review of radiotherapy plans, and one study was related to risk assessment and patient navigation. The introduction of digital health led to reduced travel time and waiting period for patients, and standardisation of radiotherapy plans at spokes. Tele-mentoring intervention aimed at capacity-building resulted in higher confidence and increased knowledge among the spoke learners.

Conclusion

There is limited evidence for the role of digital health in the hub-and-spoke design. Although all the studies have highlighted the digital components being used to coordinate care, the bottlenecks, Which were overcome during the implementation of the interventions and the impact on cancer outcomes, need to be rigorously analysed.

Implementing Optimal Care Pathways for Aboriginal and Torres Strait Islander People With Cancer: A Survey of Rural Health Professionals’ Self-Rated Learning Needs

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Prognostic value of symptoms at lung cancer diagnosis: a three-year observational study

Background

Lung cancer is mainly diagnosed at advanced or locally advanced stages, usually when symptoms become evident. However, sometimes it may be diagnosed incidentally during routine care, while patients are still asymptomatic. Prognosis differences based on symptomatic presentation have been partially explored. Our aim was to analyze the prognostic value of the initial symptomatic state of the patients in a general lung cancer cohort.

Methods

Observational ambispective study including patients consecutively diagnosed with primary lung cancer between January 2016 and December 2018 via the lung cancer Fast Diagnostic Track (FDT). Patients were followed up until death or the end of the study in September 2019. Asymptomatic patients were compared with patients presenting symptoms. Overall survival (OS) of both groups was compared using the log-rank test. Cox regression analysis was performed to clarify the effect of the symptomatic status at diagnosis on survival. Additionally, propensity score (PS) matching analysis was performed.

Results

A total of 267 patients were analyzed; 83.5% were men, with a mean (SD) age at diagnosis of 68 (10.7) years. Incidental diagnosis was ascertained in 24.7% of cases. Asymptomatic patients presented more frequently stage I and II disease compared to symptomatic patients (51.5% vs. 14%), and exhibited a significantly better prognosis, with a 3-year OS of 63.6% (vs. 30.3%) and a median OS that was not reached during follow-up (vs. 10.3 months). With an adjusted multivariate Cox proportional hazard model, we obtained a HR (95% CI) of 2.63 (95% CI, 1.6-4.2; P<0.0001) associated with symptomatic presentation independently of age, sex, stage at diagnosis and ECOG scale. In addition, after performing the propensity score matching analysis, the Cox regression model continued to show a significantly worse prognosis for patients presenting with symptoms (P=0.041).

Conclusions

Lung cancer patients who are asymptomatic at diagnosis exhibit a significantly better prognosis, regardless of the stage of the disease, underlining the importance of an early diagnosis.