Optimizing target and diaphragmatic configuration, and dosimetric benefits using continuous positive airway pressure in stereotactic ablative radiotherapy for lung tumors.

PURPOSE: This study aimed to evaluate the impact of facilitating target delineation of continuous positive airway pressure (CPAP) in patients undergoing stereotactic ablative radiation therapy (SABR) for lung tumors by lung expansion and respiratory motion management. MATERIALS AND METHODS: We performed a prospective single-institutional trial of patients who were diagnosed with either primary lung cancer or lung metastases and received SABR with a dose of 40 to 60 Gy in 4 fractions. Four-dimensional computed tomography simulations were conducted for each patient: once without CPAP and again with CPAP. RESULTS: Thirty-two patients with 39 tumors were analyzed, after the withdrawal of five patients due to discomfort. For 26 tumors separated from the diaphragm, CPAP significantly increased the superoinferior distance between the tumor and the diaphragm (5.96 cm vs. 8.06 cm; p < 0.001). For 13 tumors located adjacent to the diaphragm, CPAP decreased the overlap of planning target volume (PTV) with the diaphragm significantly (6.32 cm3 vs. 4.09 cm3; p = 0.002). PTV showed a significant reduction with CPAP (25.06 cm3 vs. 22.52 cm3, p = 0.017). In dosimetric analyses, CPAP expanded lung volume by 58.4% with a significant reduction in mean dose and V5 to V40. No more than grade 2 adverse events were reported. CONCLUSION: This trial demonstrated significant improvement of CPAP in target delineation uncertainties for lung SABR, with dosimetric benefits, a favorable safety profile and tolerability. Further investigation is warranted to explore the role of CPAP as a novel strategy for respiratory motion management.

A pilot study of precision treatment for patients with lung cancer pain by Longteng Tongluo recipe using serum genomics.

OBJECTIVE: To investigate the efficacy of Longteng Tongluo recipe (, LTTL) combined with three-step analgesia for the treatment of lung cancer pain, and the changes in serum miRNA expressions before- and after treatment with LTTL and its correlation with lung cancer pain. The possible mechanism underlying LTTL effects on the treatment of lung cancer pain was conducted. METHODS: The pilot study was conducted at the oncology ward of the Yueyang Hospital and the Longhua Hospital between March 2018 and October 2019. A prospective, single-blind, placebo controlled, randomized clinical trial of LTTL or placebo combined with three-step analgesia treatments were administered to 24 cancer pain patients diagnosed with lung cancer. Analgesic efficacy was investigated as the primary outcome. Equivalent morphine consumption and numerical rating scale (NRS) scores were used as the secondary outcome. In the present study, we utilized deep sequencing techniques to compare the differential miRNA expressions in serum samples obtained from two groups: the lung cancer pain treatment group (LTTL + three-step analgesia) and the control group (placebo + three-step analgesia). Next, we employed the target prediction database to investigate the target genes for differential miRNA expressions and Gene Ontology (GO) analysis along with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to examine the roles and the major biochemical and signaling pathways related to the differentially expressed target genes, respectively. RESULTS: LTTL treatment significantly reduces the NRS score (P = 0.021) as compared to those before treatment, along with significant reductions in the total morphine equivalent consumption (P = 0.007) and the average daily equivalent morphine consumption (P = 0.003) as opposed to the control group. The expressions of 31 miRNAs differed considerably between the two groups of patients (≥ 2 times up-modulated or down-regulated between these groups, P<0.05). For instance, the miRNAs expression levels for patients before treatment (has-miR-2110 and has-miR-7d-3p) were significantly enhanced as compared to the healthy people, after LTTL treatment, the expressions of miR-2110 and miR-7d-3p in patients with lung cancer pain reduced significantly. Studies show that the above two miRNAs were significantly associated with lung cancer pain, which could mediate lung cancer pain. Furthermore, we identified 355 genes as potential targets of the 31 differentially expressed miRNAs. Pathway enrichment analyses using KEGG and GO analysis indicated that these target genes may play a crucial role in the development and modulation of lung cancer pain. CONCLUSION: LTTL demonstrated a discernible impact on alleviating lung cancer pain and its mechanism of action may be related to the downregulation of has-miR-2110 and has-miR-7d-3p expressions. This pilot study provides support for further exploration of LTTL in patients with lung cancer pain.

Thyroid autoantibodies at baseline predict longer survival in non-small cell lung cancer patients treated with anti-programmed cell death-1 blockade: a prospective study.

The presence of anti-thyroid antibodies (ATAs) is a biomarker for the development of thyroid dysfunction induced by anti-programmed cell death-1 antibodies (PD-1-Abs). While patients with thyroid dysfunction reportedly showed better overall survival (OS), it remains unknown if ATAs at baseline can predict OS. Therefore, in this study, we examined the association of ATAs at baseline with OS in non-small cell lung cancer (NSCLC) patients with different levels of programmed cell death-1 ligand 1 (PD-L1) positivity associated with PD-1-Ab treatment efficacy. A total of 81 NSCLC patients treated with PD-1-Abs were evaluated for ATAs at baseline and prospectively for OS. Among the 81 patients, 49 and 32 patients had ≥50% (group A) and <50% (group B) PD-L1 positivity, respectively. Median OS did not differ significantly between patients with (n = 13) and without (n = 36) ATAs at baseline in group A. In contrast, median OS was significantly longer in patients with (n = 10) versus without (n = 22) ATAs at baseline in group B (not reached vs 378 days, respectively; 95% CI, 182 to 574 days, p = 0.049). These findings suggest that the presence of ATAs at baseline is a biomarker to predict better treatment efficacy of PD-1-Abs in NSCLC patients with low PD-L1 positivity, while the difference in OS in those with high PD-L1 positivity may be masked by increased tumor expression of PD-L1.

Standardized intrapulmonary lymph node dissection in lung cancer specimens: A national Colombian analysis.

Objective: In patients with non-small cell lung cancer, lymph node assessment is essential for appropriate staging. The intrapulmonary lymph nodes (IPLNs) should be considered when assigning the N stage but are infrequently evaluated in Colombian centers, resulting in understaging that may hinder optimal treatment. Methods: We conducted a prospective study of IPLN dissection in patients with clinical stage I or II non-small cell lung cancer who underwent surgical resection at 9 institutions in Colombia between 2021 and 2023. IPLN dissection was performed by trained surgeons who collected lymph nodes from fresh specimens after resection and before formalin fixation. Results: One hundred patients were eligible for the analysis. Their mean age was 67 ± 10.9 years, and 76% were women. Most (74%) had adenocarcinoma, 20% had neuroendocrine tumors, and 6% had squamous cell carcinoma. Successful sampling and histopathologic analysis of at least one IPLN station was obtained in 85% of patients, 9% had upstaging due to positive N2 lymph nodes, and 5% had upstaging due to positive N1 lymph nodes. Among the patients with pN0 or pN1 disease, 3.2% (3 out of 91) were upstaged exclusively due to positive IPLNs. Conclusions: Fresh-specimen dissection to collect IPLNs is appropriate and feasible to achieve more accurate pathological staging in Colombian lung cancer patients. In clinical N0 patients, IPLN dissection maximizes selection for adjuvant therapy.

[Isoliquiritigenin Modulates the Effect of LINC01503 
on Lung Squamous Carcinoma Cells].

BACKGROUND: Isoliquiritigenin (ISL) is an important pharmacological constituent of Glycyrrhiza glabra, which possesses a range of physiological and pharmacological activities, as well as significant antitumor activity, and can be used as a potential drug for targeted cancer therapy. LINC01503 is an oncogene, which has been closely associated with the malignant biological processes of many cancers. The aim of this study was to investigate the effects of ISL on the proliferation, apoptosis, invasion and migration of lung squamous carcinoma cells by regulating LINC01503. METHODS: Plasma was collected from lung squamous carcinoma patients and healthy individuals treated at Tangshan People's Hospital from January 2021 to December 2022. The expression of LINC01503 in lung squamous carcinoma plasma, tissues and cells was detected by real-time quantitative fluorescence polymerase chain reaction (qRT-PCR). Lung squamous carcinoma cells were treated with different concentrations of ISL for 24 h, and LINC01503 expression was detected by qRT-PCR. The cells were treated in groups: si-NC group, si-LINC01503 group, DMSO (0.1% dimethyl sulfone) group, ISL group, pc DNA3.1(+)-NC group, pc DNA3.1(+)-LINC01503 group, ISL+pc DNA3.1(+)-NC group and ISL+pc DNA3.1(+)- LINC01503 groups. CCK-8 assay, clone formation assay, flow cytometry, Transwell assay and scratch assay were used to explore the effect of LINC01503 on the functional phenotype of lung squamous carcinoma cells. RESULTS: Fluorescence in situ hybridization results showed that the average fluorescence intensity of LINC01503 in tissue microarrays of lung squamous carcinoma patients was higher than that in paracancerous tissues (P<0.05). The expression of LINC01503 in the plasma of patients with lung squamous carcinoma was higher than that in the plasma of healthy individuals (P<0.05). Knockdown of LINC01503 inhibited the proliferation, invasion and migration of lung squamous carcinoma cells and promoted apoptosis (P<0.05). ISL inhibited the proliferation, invasion, migration and promoted apoptosis of lung squamous carcinoma cells (P<0.05). Overexpression of LINC01503 followed by intervention with ISL reversed the promotional effect of overexpression of LINC01503 on the proliferation, invasion and migration of lung squamous carcinoma cells as well as the inhibitory effect on apoptosis (P<0.05). CONCLUSIONS: LINC01503 was highly expressed in lung squamous carcinoma, and LINC01503 could promote the proliferation, invasion and migration of lung squamous carcinoma cells and inhibit the apoptosis, ISL could inhibit the proliferation, invasion and migration of lung squamous carcinoma cells and promote apoptosis of lung squamous carcinoma cells by regulating the expression of LINC01503.

[Advances in Diagnosis and Targeted Therapy of G719X/L861Q/S768I Mutant 
Non-small Cell Lung Cancer].

Lung cancer accounts for the highest proportion of cancer deaths in the world and poses a great threat to human health. About 30% to 40% of non-small cell lung cancer (NSCLC) is caused by point mutations, exon insertion and exon deletion of the epidermal growth factor receptor (EGFR). In addition to the common exon 19 deletion mutation and exon 21 L858R mutation, exon 18 G719X mutation, exon 21 L861Q mutation and exon 20 S768I mutation are the most important rare mutations. At present, the diagnostic methods for major rare mutations are mainly next-generation sequencing (NGS), digital polymerase chain reaction (dPCR), droplet digital PCR (ddPCR), etc. Regarding the targeted therapy of G719X/L861Q/S768I mutant NSCLC, the first generation EGFR-tyrosine kinase inhibitors (TKIs) have poor efficacy, while the second and third generation EGFR-TKIs have similar efficacy. The novel third generation EGFR-TKIs and combination therapy show a good therapeutic prospect. This article summarized the progress in the diagnosis and targeted therapy of G719X/L861Q/S768I mutant NSCLC, so as to provide reference for subsequent clinical drug use and research.
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[Molecular Subtype of Small Cell Lung Cancer: 
Challenge for Transforming into Clinical Practice].

Small cell lung cancer (SCLC), one of the histological subtypes of lung cancer, is characterized by high proliferation, early metastasis, susceptibility to drug resistance and recurrence. For several years, SCLC has always been regarded as a homogeneous disease, treated with a unified radiotherapy and chemotherapy strategy. Despite significant early therapeutic effects, drug resistance and recurrence occur quickly, and there is a lack of satisfactory treatment results, which may be due to insufficient understanding of the tumor heterogeneity of SCLC at present. Recently, the concept of SCLC molecular subtype based on the definition of relatively high expression of lineage transcription factors has been proposed in preclinical studies. This article mainly elaborates on the current status and latest findings of SCLC molecular subtype, emphasizing the potential problems that molecular typing may encounter in clinical practice, aiming to promote understanding of the research progress of molecular subtype in SCLC.
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[EGFR Exon 20 Insertion Mutation: Research Status and New Treatment Strategies].

In non-small cell lung cancer (NSCLC), as an improtant oncogenic driver gene, epidermal growth factor receptor exon 20 insertion (EGFR ex20ins) has a unique protein structure and is primarily drug-resistant to traditional EGFR-tyrosine kinase inhibitors (EGFR-TKIs). In recent years, exploration of targeted therapy for EGFR ex20ins has never stopped. Firstly Mobocertinib and Amivantamab obtained approval from U.S. Food and Drug Administration (FDA) for EGFR ex20ins mutant NSCLC patients, then other drugs, such as Sunvozertinib, made breakthroughs and combination therapies also obtained gains. Multi-pronged measures are hopeful to overcome EGFR ex20ins drug resistance. As mentioned above, it's definitely important to gain deeper understanding of molecular mechanism of EGFR ex20ins and assess effect and difference between novel drugs. This review is devoted to make a summary about newest achievement so to provide valuable reference about precise therapy for patients with EGFR ex20ins.
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[Research Progress of Circular RNA CircHIPK3 in Non-small Cell Lung Cancer].

Lung cancer ranks among the most prevalent and deadliest malignancies worldwide. Despite significant strides in targeted therapies and immunotherapy for lung cancer, curing the disease remains a highly prioritized issue. Circular RNAs (circRNAs), recently discovered RNA molecules characterized by covalently closed loop structures, possess features such as structural stability, sequence conservation, and disease-specific expression. Cutting-edge medical research has linked circRNA dysregulation to the progression of various cancers. Among these, circular RNA HIPK3 (circHIPK3), an oncogenic gene primarily derived from the second exon of the HIPK3 gene, has emerged as a focal point of investigation. Increasing evidences suggest that circHIPK3 is involved in the development of non-small cell lung cancer (NSCLC) and other malignancies. Aberrant expression of circHIPK3 is closely associated with the disease mechanisms, diagnosis, treatment, and prognosis of NSCLC. This review discusses the latest research advancements on circHIPK3 in NSCLC, aiming to promote precise diagnosis and treatment of lung cancer.
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[Advancements in Radiomics for Immunotherapy of Non-small Cell Lung Cancer].

Lung cancer is the main cause of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the predominant subtype. At present, immunotherapy represented by immune checkpoint inhibitors (ICIs) of programmed cell death receptor 1 or its ligand has been widely used in the clinical diagnosis and treatment of patients with NSCLC. However, only a few patients can benefit from it, and reliable predictive markers for immunotherapy are lacking. Radiomics is a tool that uses computer software and algorithms to extract a large amount of quantitative information from biomedical images. A large number of studies have confirmed that the radiomic model that predicts the immune efficacy of NSCLC can be used as a new type of immune efficacy predictive marker, which is expected to guide the individualized diagnosis and treatment decisions for patients with lung cancer and has a bright application prospect. This article reviews the research progress of radiomics in predicting the immune therapy response of NSCLC, identifying pseudo-progression and hyperprogression, ICIs-related pneumonia, cachexia risk, and combining with other genomics.
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Additional benefit of endoscopic ultrasound with bronchoscope-guided fine needle aspiration to endobronchial ultrasound-guided transbronchial needle aspiration in the evaluation of lung cancer: a systematic review and meta-analysis.

Background: Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and endoscopic ultrasound with bronchoscope-guided fine needle aspiration (EUS-B-FNA) are minimally invasive procedures for the diagnosis and staging of lung cancer. This study aimed to investigate the additional diagnostic value of EUS-B-FNA following EBUS-TBNA. Methods: We performed a systematic literature review of PubMed, Embase, and the Cochrane Central Register databases and extracted the studies reporting the implementation of the combined EBUS-TBNA/EUS-B-FNA. A proportional meta-analysis was conducted to determine the pooled diagnostic yield of this procedure. Results: We identified nine studies involving 2,375 patients. The overall pooled diagnostic yield of EBUS-TBNA alone and combined EBUS-TBNA/EUS-B-FNA was 0.87 [95% confidence interval (CI): 0.79-0.95, I2=96.55%] and 0.92 (95% CI: 0.85-0.99, I2=97.89%), respectively. Adding EUS-B-FNA to EBUS-TBNA increased the diagnostic yield by approximately 0.05. There was statistical heterogeneity among the studies (I2=54.49%). Among the 832 patients in seven studies, additional diagnostic benefits of EUS-B-FNA were observed in 37 lesions. The most common diagnosed lesion was in station 4L (n=10), followed by station 5 (n=8) and station 7 (n=8). Conclusions: In pooled estimates, the addition of EUS-B-FNA to EBUS-TBNA increased the diagnostic yield for the diagnosis and staging of lung cancer. Nodal station 4L, station 5, and station 8 were lesions frequently diagnosed by the addition of EUS-B-FNA. Because of statistical between-study heterogeneity, our findings should be interpreted with caution.

Beyond lung cancer screening, an opportunity for early detection of COPD and cardiovascular diseases.

INTRODUCTION: Lung cancer (LC)-screening programs concern smokers at risk for cardiovascular diseases (CVDs) and chronic obstructive pulmonary disease (COPD). The LUMASCAN study aimed to evaluate the acceptability and feasibility of screening for these 3 diseases in a community population with centralized organization and to determine low-dose computed tomography (LDCT) markers associated with each disease. METHODS: This cohort enrolled subjects meeting NCCN criteria (v1.2014) in an organized LC-screening program including LDCT-scans, spirometry, evaluations of coronary artery calcifications (CACs), and a smoking-cessation plan at inclusion, 1 and 2-year, then telephone follow-up. Outcomes were the participation rate and the proportion of participants affected by LC, obstructive lung disease (OLD) or CVD events. Logistic-regression models were used to identify radiological factors associated with each disease. RESULTS: Between 2016 and 2019, 302 subjects were enrolled: 61% men, median age 58.8 years, 77% active smoker, 11% diabetes, 38% hypertension, 27% taking lipid-lowering agents. Inclusion, 1-year and 2-year participation rate were 99%, 81%, 79%, respectively. After a median follow-up of 5.81 years, screenings detected 12 (4%) LCs, 9/12 via LDCT (78% localized) and 3/12 during follow-up (all stage IV), 83 (27%) unknown OLD, and 131 (43.4%) moderate/severe CACs warranting a cardiology consultation. Preexisting COPD and moderate/severe CACs were associated with major CVD events with odds ratios of 1.98 [95% confident interval (CI) 1.00-3.88] and 3.27 [95% CI 1.72-6.43] respectively. CONCLUSION: The LUMASCAN study demonstrated the feasibility of combined screening for LC, COPD and CVD in a community population. Its centralized organization enabled high participation and coordination of care providers.

Postoperative rehabilitation management self-efficacy and its relationship with symptoms in the patients with lung cancer: A latent profile analysis.

Objective: To identify the potential subgroups of postoperative rehabilitation management self-efficacy in patients with lung cancer and explore the association between these subgroups and symptom burden. Methods: This cross-sectional study enrolled 231 lung cancer patients who underwent surgery between May and August 2023. Latent profile analysis, univariate analysis, and disordered multinomial logistic regression were performed to explore postoperative rehabilitation management self-efficacy profiles and identify interindividual variability. ANOVA, LSD, and Tamhane's T2 method were used for multiple comparisons between symptom burden and self-efficacy subgroups. Results: The three subgroups of postoperative rehabilitation management self-efficacy identified included low level group (17.7%), medium level group (63.2%), and high level group (19.0%). Patients with junior high school education were more likely to be classified as medium level groups, and patients with higher levels of social support and better resilience were more likely to be classified as medium and high level groups. Symptom severity and symptom interference of lung cancer patients after surgery varied considerably among the three classes. In the lung cancer module, the high level group had fewer symptoms than the medium level group (P < 0.05). Conclusions: Postoperative rehabilitation management self-efficacy has different classification features among patients with lung cancer. Educational background, resilience, and social support were the influencing factors of postoperative rehabilitation management self-efficacy. Lung cancer patients with higher self-efficacy in postoperative rehabilitation management showed fewer symptom burdens. Medical staff should actively pay attention to patients with low self-efficacy and provide precise interventions for patients with different subgroups.

Incorporation of Whole-Body Metabolic Tumor Burden into Current Prognostic Models for Non-Small Cell Lung Cancer patients with Spine metastasis.

BACKGROUND CONTEXT: Numerous prognostic models are utilized for surgical decision and prognostication in metastatic spine tumors. However, these models often fail to consider the whole-body tumor burden into account, which may be crucial for the prognosis of metastatic cancers. A potential surrogate marker for tumor burden, whole-body metabolic tumor burden (wMTB), can be calculated from total lesion glycolysis (TLG) obtained from 18F-Fludeoxyglucose positive emission tomography (18F-FDG PET) images. PURPOSE: We aimed to improve prognostic power of current models by incorporating wMTB for non-small cell lung cancer (NSCLC) patients with spine metastases. DESIGN: Retrospective analysis using a review of electrical medical records and survival data. PATIENT SAMPLE: In this study, we included 74 NSCLC patients with image proven spine metastases. OUTCOME MEASURES: Increase in Integrated Discrimination Improvement (IDI) index after incorporation of wMTB into prognostic scores. METHODS: Enrolled patients' baseline data, cancer characteristics and survival status were retrospectively collected. Five widely used prognostic scores (Tomita, Katagiri, Tokuhashi, Global Spine Tumor Study Group [GSTSG], New England Spine Metastasis Score [NESMS]), and TLG indexes were calculated for all patients. The relationships among survival time, prognostic models and TLG values were analyzed. Improvement of prognostic power was validated by incorporating significant TLG index into significant current models. RESULTS: Among current prognostic models, Tomita (EGFR wild-type), Katagiri, GSTSG and Tokuhashi were significantly related to patient survival. Among TLG indexes, LogTLG3 was significantly related to survival. Incorporation of LogTLG3 into significant prognostic models resulted in positive IDI index until three years in all models. CONCLUSION: This study showed that incorporation of wMTB improved prognostic power of current prognostic models of metastatic spine tumors.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Introduction.

Lung cancer is the leading cause of cancer death in the United States and across the world. The American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) was established in 2017 as a consortium of public, private, and voluntary organizations with a mission to lower the impact of lung cancer via prevention, early detection, and optimal therapy. The ACS NLCRT supports a comprehensive scope of work that covers the lung cancer continuum, from risk reduction, tobacco prevention and control, and early detection (screening and incidental lung nodule management) to guideline-based staging, biomarker testing, treatment, and survivorship and overarching issues such as stigma and nihilism, health equity, and tactical approaches such as state coalition efforts and policy initiatives. Applying a multidimensional and multisector approach, over 220 public, private, and government agency member organizations and 250 volunteer experts, patients, and caregiver advocate representatives collaborate to address challenges across the lung cancer continuum by catalyzing action to conceive, build, and strengthen innovative solutions. The wide-ranging membership allows the ACS NLCRT to harness the collective power and expertise of the entire lung cancer community by connecting leaders, communities, and systems to improve equity and access. These national, state, and local relationships provide partnerships for the dissemination of ACS NLCRT-developed tools and resources. This article describes the ACS NLCRT and introduces the series of accompanying and future articles that together make up the ACS NLCRT strategic plan, which provides a roadmap for future research, investment, and collaboration to reduce lung cancer mortality and lung cancer-related stigma and enhance survivorship.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Implementation of high-quality lung cancer screening.

More than a decade has passed since researchers in the Early Lung Cancer Action Project and the National Lung Screening Trial demonstrated the ability to save lives of high-risk individuals from lung cancer through regular screening by low dose computed tomography scan. The emergence of the most recent findings in the Dutch-Belgian lung-cancer screening trial (Nederlands-Leuvens Longkanker Screenings Onderzoek [NELSON]) further strengthens and expands on this evidence. These studies demonstrate the benefit of integrating lung cancer screening into clinical practice, yet lung cancer continues to lead cancer mortality rates in the United States. Fewer than 20% of screen eligible individuals are enrolled in lung cancer screening, leaving millions of qualified individuals without the standard of care and benefit they deserve. This article, part of the American Cancer Society National Lung Cancer Roundtable (ACS NLCRT) strategic plan, examines the impediments to successful adoption, dissemination, and implementation of lung cancer screening. Proposed solutions identified by the ACS NLCRT Implementation Strategies Task Group and work currently underway to address these challenges to improve uptake of lung cancer screening are discussed. PLAIN LANGUAGE SUMMARY: The evidence supporting the benefit of lung cancer screening in adults who previously or currently smoke has led to widespread endorsement and coverage by health plans. Lung cancer screening programs should be designed to promote high uptake rates of screening among eligible adults, and to deliver high-quality screening and follow-up care.

The American Cancer Society National Lung Cancer Roundtable strategic plan: Current challenges and future directions for shared decision making for lung cancer screening.

Shared decision making (SDM) between health care professionals and patients is essential to help patients make well informed choices about lung cancer screening (LCS). Patients who participate in SDM have greater LCS knowledge, reduced decisional conflict, and improved adherence to annual screening compared with patients who do not participate in SDM. SDM tools are acceptable to patients and clinicians. The importance of SDM in LCS is emphasized in recommendations from professional organizations and highlighted as a priority in the 2022 President's Cancer Panel Report. The updated 2022 national coverage determination from the Centers for Medicare & Medicaid Services reaffirms the value of SDM in offering LCS to eligible beneficiaries. The Shared Decision-Making Task Group of the American Cancer Society National Lung Cancer Roundtable undertook a group consensus process to identify priorities for research and implementation related to SDM for LCS and then evaluated current knowledge in these areas. Priority areas included: (1) developing feasible, adaptable SDM training programs for health care professionals; (2) understanding the impact of alternative health system LCS models on SDM practice and outcomes; (3) developing and evaluating new patient decision aids for use with diverse populations and in varied settings; (4) offering conceptual clarity about what constitutes a high-quality decision and developing appropriate quality measures; and (5) studying the use of prediction-augmented screening to support SDM in practice. Gaps in current research in all areas were observed. The authors conclude with a research and implementation agenda to advance the quality and implementation of SDM for persons who might benefit from LCS.

Impact of the COVID-19 pandemic on cancer mortality in Brazil.

BACKGROUND: In the first year of the COVID-19 pandemic, data projections indicated an increase in cancer mortality for the following years due to the overload of health services and the replacement of health priorities. The first studies published with data from mortality records have not confirmed these projections. However, cancer mortality is not an outcome that occurs immediately, and analyses with more extended follow-up periods are necessary. This study aims to analyze the impact of the COVID-19 pandemic on the mortality from all types and the five most common types of cancer in Brazil and investigate the relationship between the density of hospital beds and mortality from COVID-19 in cancer patients in Brazil's Intermediate Geographic Regions (RGIs). METHODS: The Brazilian Mortality Information System provided data on the deaths from trachea, bronchus, and lung, colorectal, stomach, female breast, and prostate cancer and all types of cancer, and from COVID-19 in individuals who had cancer as a contributing cause of death. Predicted rates for 2020-2022 were compared with the observed ones, through a rate ratio (RR). An association analysis, through multivariate linear regression, was carried out between mortality from COVID-19 in cancer patients, the rate of hospital beds per 100,000 inhabitants, and the Human Development Index of the 133 RGIs of Brazil. RESULTS: In 2020, 2021, and 2022, mortality from all cancers in Brazil was lower than expected, with an RR of 0.95, 0.94, and 0.95, respectively, between the observed and predicted rates. Stomach cancer showed the largest difference between observed and expected rates: RR = 0.89 in 2020 and 2021; RR = 0.88 in 2022. Mortality from COVID-19 in cancer patients, which reached its peak in 2021 (6.0/100,000), was negatively associated with the density of hospital beds in the public health system. CONCLUSIONS: The lower-than-expected cancer mortality during 2020-2022 seems to be partly explained by mortality from COVID-19 in cancer patients, which was probably underestimated in Brazil. The findings suggested a protective role of the availability of hospital care concerning deaths due to COVID-19 in this population. More extensive follow-up is needed to understand the impact of the COVID-19 pandemic on cancer mortality.

Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.

Background: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intelligence-developed algorithm might be useful in assisting with the identification of suspected lung cancer. Objectives: This review sought to identify evidence on adjunct artificial intelligence software for analysing chest X-rays for suspected lung cancer, and to develop a conceptual cost-effectiveness model to inform discussion of what would be required to develop a fully executable cost-effectiveness model for future economic evaluation. Data sources: The data sources were MEDLINE All, EMBASE, Cochrane Database of Systematic Reviews, Cochrane CENTRAL, Epistemonikos, ACM Digital Library, World Health Organization International Clinical Trials Registry Platform, clinical experts, Tufts Cost-Effectiveness Analysis Registry, company submissions and clinical experts. Searches were conducted from 25 November 2022 to 18 January 2023. Methods: Rapid evidence synthesis methods were employed. Data from companies were scrutinised. The eligibility criteria were (1) primary care populations referred for chest X-ray due to symptoms suggestive of lung cancer or reasons unrelated to lung cancer; (2) study designs that compared radiology specialist assessing chest X-ray with adjunct artificial intelligence software versus radiology specialists alone and (3) outcomes relating to test accuracy, practical implications of using artificial intelligence software and patient-related outcomes. A conceptual decision-analytic model was developed to inform a potential full cost-effectiveness evaluation of adjunct artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer. Results: None of the studies identified in the searches or submitted by the companies met the inclusion criteria of the review. Contextual information from six studies that did not meet the inclusion criteria provided some evidence that sensitivity for lung cancer detection (but not nodule detection) might be higher when chest X-rays are interpreted by radiology specialists in combination with artificial intelligence software than when they are interpreted by radiology specialists alone. No significant differences were observed for specificity, positive predictive value or number of cancers detected. None of the six studies provided evidence on the clinical effectiveness of adjunct artificial intelligence software. The conceptual model highlighted a paucity of input data along the course of the diagnostic pathway and identified key assumptions required for evidence linkage. Limitations: This review employed rapid evidence synthesis methods. This included only one reviewer conducting all elements of the review, and targeted searches that were conducted in English only. No eligible studies were identified. Conclusions: There is currently no evidence applicable to this review on the use of adjunct artificial intelligence software for the detection of suspected lung cancer on chest X-ray in either people referred from primary care with symptoms of lung cancer or people referred from primary care for other reasons. Future work: Future research is required to understand the accuracy of adjunct artificial intelligence software to detect lung nodules and cancers, as well as its impact on clinical decision-making and patient outcomes. Research generating key input parameters for the conceptual model will enable refinement of the model structure, and conversion to a full working model, to analyse the cost-effectiveness of artificial intelligence software for this indication. Study registration: This study is registered as PROSPERO CRD42023384164. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135755) and is published in full in Health Technology Assessment; Vol. 28, No. 50. See the NIHR Funding and Awards website for further award information.

Lung cancer is one of the most common types of cancer in the United Kingdom. Early diagnosis may improve survival, as lung cancer is often diagnosed late. Chest X-rays can be used to identify features of lung cancer. There can be delays in getting X-rays, and sometimes features of lung cancer are not seen on them. Artificial intelligence software may help by finding features of cancer on chest X-rays and highlighting them. A radiologist will look at the X-rays and information from the software. There is a lack of information about how lung cancer diagnosis could change if artificial intelligence software is used and what the costs may be to the National Health Service. This project looked at the use of artificial intelligence software in the detection of lung cancer in people referred from primary care. Software companies were invited to provide evidence. There were no studies that looked at this topic among people from primary care. We summarised the closest evidence we could find instead. All of this had flaws, so we could not tell if the results were accurate or helpful to this review. It was not clear if artificial intelligence helped to find cancers or improve people's health. We made a theoretical model to discuss the best way to assess if artificial intelligence software might be cost-effective in detecting lung cancer and what evidence would be needed to do this in a fully working model. Costs and alternative pricing models provided by five companies were used to calculate the cost of adding artificial intelligence software to review chest X-rays in people referred from their general practitioner, for the first 5 years, based on one National Health Service trust. Future studies are needed to identify the impact of adjunct artificial intelligence on test accuracy, clinical decision-making and patient outcomes (e.g. mortality and morbidity).