Lung Cancer Screening: Implementation Challenges and Health Equity Considerations For the Western Pacific Region

Nightingale, Claire; Bavor, Claire; Rankin, Nicole

doi:10.1200/go.22.00329

Cited by 3 publications

(2 citation statements)

References 75 publications

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“…Nevertheless, only 22% of the countries in the Western Pacific Region have implemented lung cancer screening. Nightingale et al 6 summarized the numerous barriers and challenges for lung cancer screening in this area, including limited evidence about the effective recruitment strategies of high-risk individuals in the region, resource limitation, and infrastructure challenges. The review addresses the importance of primary care practitioners in encouraging the participation of high-risk individuals, the need to improve health care professionals' competency in interpreting LDCT, and subsequently managing suspicious nodules or incidental findings.…”

Section: Cancer Screening and Treatment Patterns In Apmentioning

confidence: 99%

Improving Equity Across Cancer Care Continuum in Asia Pacific

Martina

Segelov

2023

JCO Global Oncology

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Section: Cancer Screening and Treatment Patterns In Apmentioning

confidence: 99%

Improving Equity Across Cancer Care Continuum in Asia Pacific

Martina

Segelov

2023

JCO Global Oncology

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“…Although significant progress has been made in the early detection of lung cancer in recent years, early detection is still inaccurate. The majority of techniques and methods currently in use cannot effectively avoid a diagnosis of advanced stage lung cancer, and so the early detection of lung cancer remains difficult ( Mohan et al, 2020 ; Nightingale et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

A lung cancer risk warning model based on tongue images

et al. 2023

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Objective: To investigate the tongue image features of patients with lung cancer and benign pulmonary nodules and to construct a lung cancer risk warning model using machine learning methods.Methods: From July 2020 to March 2022, we collected 862 participants including 263 patients with lung cancer, 292 patients with benign pulmonary nodules, and 307 healthy subjects. The TFDA-1 digital tongue diagnosis instrument was used to capture tongue images, using feature extraction technology to obtain the index of the tongue images. The statistical characteristics and correlations of the tongue index were analyzed, and six machine learning algorithms were used to build prediction models of lung cancer based on different data sets.Results: Patients with benign pulmonary nodules had different statistical characteristics and correlations of tongue image data than patients with lung cancer. Among the models based on tongue image data, the random forest prediction model performed the best, with a model accuracy of 0.679 ± 0.048 and an AUC of 0.752 ± 0.051. The accuracy for the logistic regression, decision tree, SVM, random forest, neural network, and naïve bayes models based on both the baseline and tongue image data were 0.760 ± 0.021, 0.764 ± 0.043, 0.774 ± 0.029, 0.770 ± 0.050, 0.762 ± 0.059, and 0.709 ± 0.052, respectively, while the corresponding AUCs were 0.808 ± 0.031, 0.764 ± 0.033, 0.755 ± 0.027, 0.804 ± 0.029, 0.777 ± 0.044, and 0.795 ± 0.039, respectively.Conclusion: The tongue diagnosis data under the guidance of traditional Chinese medicine diagnostic theory was useful. The performance of models built on tongue image and baseline data was superior to that of the models built using only the tongue image data or the baseline data. Adding objective tongue image data to baseline data can significantly improve the efficacy of lung cancer prediction models.

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The geriatric Asia-Pacific oncology nursing imperative

Boyle

2023

Asia-Pacific Journal of Oncology Nursing

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Lung Cancer Screening: Implementation Challenges and Health Equity Considerations For the Western Pacific Region

Cited by 3 publications

References 75 publications

Improving Equity Across Cancer Care Continuum in Asia Pacific

Improving Equity Across Cancer Care Continuum in Asia Pacific

A lung cancer risk warning model based on tongue images

The geriatric Asia-Pacific oncology nursing imperative

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