LC Patients Research Articles

EPID-30. THE COST OF HOSPITAL-BASED CARE AMONG CANADIAN PATIENTS WITH MALIGNANT CENTRAL NERVOUS SYSTEM TUMOURS IN COMPARISON TO THOSE WITH LUNG AND COLORECTAL CANCERS IN THE YEAR PRECEDING THEIR CANCER DIAGNOSIS

Abstract BACKGROUND Approximately 12% of the Canadian GDP was spent on healthcare in 2023. While hospital-based care (HC) constitutes a significant portion of this expenditure, the costs may vary depending on the cancer type. We investigate the HC cost of patients with malignant central nervous system tumours (CNS cancer) and compare it to patients with common cancers in Canadian provinces. METHODS We obtained data between 2010 and 2014 from the Canadian Institute for Health Information’s in-patient and ambulatory care datasets. HC cost was estimated using a 12-month look back period prior to diagnosis date for each patient, including cost related to cancer diagnosis and general healthcare. Choosing colorectal (CRC) and lung (LC) cancers to be the common cancers, patients who were 15 years of age or older and had a diagnosis of one of these cancers were included. We used quantile regression to investigate the factors associated with HC cost. RESULTS A total of 4,498 (CNS), 41,028 (CRC) and 29,747 (LC) patients were included from Alberta and Ontario, Canada. Encounter type (in-patient/out-patient), province (AB/ON), and comorbidities (Yes/No) were the top three factors contributing to HC cost. Adjusting for encounter type, comorbidities and age, the HC costs for CNS patients were $0.7k and $2.4k higher than CRC patients at 50th and 90th percentile, respectively, and $1.0k higher than LC patients at 90th percentile in Ontario. While in Alberta, HC costs for CNS patients were $0.2k and $0.8k higher than CRC patients at 50th and 90th percentile, respectively, and $1.0k lower than LC patients at both 50th and 90th percentiles. CONCLUSIONS We compared HC cost among Canadian patients with different cancer types; significant HC cost differences between patients with CNS and common cancer were observed. Further investigations are warranted to understand drivers of the cost differences.

Circulating microRNA-21, microRNA-122, and microRNA-222 as diagnostic biomarkers for hepatitis c virus-related hepatocellular carcinoma

Background and aimMicroRNAs (miRs) are now a well-known subject in various tumor genesis and are studied as early diagnostic biomarker. Many arrays of miRs were incorporated in the pathogenesis of HCV-related hepatocellular carcinomas (HCV-HCC). In this respect, we aimed to evaluate the diagnostic role of circulating miR-21, miR-122, and miR-222 in Egyptian patients with HCV-HCC.Patient and methodsBetween June 2018 and April 2019, a cross-sectional comparative study was designed to evaluate the circulating miR-21, miR-122, and miR-222 by quantitative Real-Time PCR. For analytical purposes, patients were categorized into three groups: chronic HCV group (CHC-group, n = 22), HCV-related liver cirrhosis (LC-group, n = 22), and HCV-related hepatocellular carcinoma (HCV-HCC-group, n = 54).ResultsSerum levels of miR-21 and miR-222 increased with the progressive course from CHC to LC and HCC; p < .001. Serum levels of miR-122 in HCC patients were significantly lower than non-HCC patients (CHC and LC patients, n = 44); p < .001. However, the differences in levels of serum miR-122 between CHC and LC were not statistically significant; P = 0.8.ROC curve analysis showed that the sensitivity and specificity of miR-21 were 61.1% and 95.5%, miR-222 were 71.7% and 93.2%, and miR-122 were 98.2% and 100%. The positive predictive value for miRNA-21, miRNA-122, and miRNA-222 were 13.4%, 93.3%, and 10.5% respectively. The Negative predictive value for miRNA-21, miRNA-122, and miRNA-222 were 94.3%, 97.8%, and 92.7% respectively.ConclusionMiR-21 and miR-222 could be potential markers for advanced liver damage, while miR-122 had the best diagnostic accuracy and could be a promising marker for detection of HCC.

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning

BackgroundLung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains challenging. This study aims to develop a predictive model for progression-free survival (PFS) in LC patients with IO based on clinical features and advanced imaging biomarkers.Materials and methodsA retrospective analysis was conducted on a cohort of 206 LC patients receiving IO treatment. Pre-treatment computed tomography images were used to extract advanced imaging biomarkers, including intratumoral and peritumoral-vasculature radiomics. Clinical features, including age, gene status, hematology, and staging, were also collected. Key radiomic and clinical features for predicting IO outcomes were identified using a two-step feature selection process, including univariate Cox regression and chi-squared test, followed by sequential forward selection. The DeepSurv model was constructed to predict PFS based on clinical and radiomic features. Model performance was evaluated using the area under the time-dependent receiver operating characteristic curve (AUC) and concordance index (C-index).ResultsCombining radiomics of intratumoral heterogeneity and peritumoral-vasculature with clinical features demonstrated a significant enhancement (p < 0.001) in predicting IO response. The proposed DeepSurv model exhibited a prediction performance with AUCs ranging from 0.76 to 0.80 and a C-index of 0.83. Furthermore, the predicted personalized PFS curves revealed a significant difference (p < 0.05) between patients with favorable and unfavorable prognoses.ConclusionsIntegrating intratumoral and peritumoral-vasculature radiomics with clinical features enabled the development of a predictive model for PFS in LC patients with IO. The proposed model’s capability to estimate individualized PFS probability and differentiate the prognosis status held promise to facilitate personalized medicine and improve patient outcomes in LC.

Identifying patterns of Long-COVID diagnosis pathways: a Latent Class Analysis of Welsh clinical data

ObjectivesLong-COVID (LC) diagnosis remains challenging due to its variable, multisystem, episodic symptoms, and lack of uniformity in the critical time points. We aim to classify diagnosis pathways and associated demographic and health determinants for clinically diagnosed LC patients in Wales. ApproachWe created a cohort of LC-diagnosed adults in Wales from 2020 to 2023 using population-scale data within the SAIL Databank. To classify diagnosis pathways, we extracted a set of indicators suggestive of the general diagnosis process within 6-months before the diagnosis, including LC symptoms, clinical investigations, and management. We conducted Latent Class Analysis (LCA) to examine how these indicators cluster, adjusting the best-fit model for various covariates such as COVID-19 infection history and sociodemographic characteristics. ResultsOf the 7,973 identified LC patients, 59% had clinical investigations, 59% had a clinical management record, and 39% had at least one related symptom. Using LCA, we identified 7 distinct patterns of diagnosis pathways, and how background characteristics associated with each. ConclusionDespite existing guidelines, LC diagnosis is complex due to LC’s diverse manifestations and the absence of exclusive symptoms/tests. Late or missed LC diagnosis can have a detrimental effect at individual, community, and national levels. Previous UK studies have indicated low recording rates of LC compared with self-reported surveys. Understanding current diagnosis pathways can shed light on this discrepancy and identify potential confounding factors that delay/impact LC diagnosis. This insight is crucial for standardising diagnosis pathways, enabling earlier and more accurate detection of LC and thereby mitigating its impact.

International perspective of injection laryngoplasty for laryngeal cleft – A survey study

ObjectivesLaryngeal Cleft (LC) is an anatomical defect that can cause swallowing difficulties and subsequent recurrent respiratory symptoms. LC can be treated surgically by performing suture repair or by Injection Laryngoplasty (IL). The indications and efficacy of IL are debated among pediatric otolaryngologists. The aim of this survey study was to review the international perspective on IL for LC. MethodsAn online survey was conducted to assess international opinions on the indications and efficacy of IL for LC patients. An online survey was sent to 250 pediatric otolaryngologists worldwide. The survey included questions on the management of LC, the physicians’ experience with IL, and their use of IL. ResultsSixty two (25 %) pediatric otolaryngologists, from 47 medical centers, completed the survey. Of the respondents, 38 (62 %) perform IL. The most reported indication was as a diagnostic tool. For the respondents who did not perform IL, the reasons most reported were that the effect is temporary and that there is a need for a second surgery after IL. ConclusionAccording to this survey, the perspectives on the use of IL for LC differ among pediatric otolaryngologists, and there is variation in peri-and postoperative standard of care. The respondents' opinions on IL were partly dependent on the intended outcome of its use, i.e., as a permanent treatment or for other indications.

Interferon gene expression declines over time post-COVID infection and in long COVID patients

Background Interferons (IFNs) represent a first-line defense against viruses and other pathogens. It has been shown that an impaired and uncontrolled release of these glycoproteins can result in tissue damage and explain severe progression of coronavirus disease 2019 (COVID-19). However, their potential role in Long-COVID syndrome (LC) remains debateable. Objectives The objective of the present study is to shed further light on the possible role of IFNs (and related genes) gene expression patterns in the progression of COVID-19 and LC patients. Methods We carried out a multi-cohort study by analyzing the IFN gene expression patterns (using different IFN gene signatures) in five cohorts of acute COVID-19 (n = 541 samples) and LC patients (n = 188), and compared them to patterns observed in three autoimmune diseases (systemic lupus erythematous [n = 242], systemic sclerosis [n = 91], and Sjögren’s syndrome [n = 282]). Results The data show that, while the interferon signatures are strongly upregulated in severe COVID-19 patients and autoimmune diseases, it decays with the time from symptoms onset and in LC patients. Differential pathway analysis of IFN-related terms indicates an over activation in autoimmune diseases (IFN-I/II) and severe COVID-19 (IFN-I/II/III), while these pathways are mostly inactivated or downregulated in LC (IFN-I/III). By analyzing six proteomic LC datasets, we did not find evidence of a role of IFNs in this condition. Conclusion Our findings suggest a potential role of cytokine exhaustion mediated by IFN gene expression inactivation as a possible driver of LC.

Integrated omics characterization reveals reduced cancer indicators and elevated inflammatory factors after thermal ablation in non-small cell lung cancer patients

BackgroundThermal ablation is a minimally invasive treatment for non-small cell lung cancer (NSCLC). Aside from causing an immediate direct tumour cell injury, the effects of thermal ablation on the internal microenvironment are unknown. This study aimed to investigate the effects of thermal ablation on the plasma internal environment in patients with NSCLC.Methods128 plasma samples were collected from 48 NSCLC (pre [LC] and after thermal ablation [LC-T]) patients and 32 healthy controls (HCs). Olink proteomics and metabolomics were utilized to construct an integrated landscape of the cancer-related immune and inflammatory responses after ablation.ResultsCompared with HCs, LC patients exhibited 58 differentially expressed proteins (DEPs) and 479 differentially expressed metabolites (DEMs), which might participate in tumour progression and metastasis. Moreover, 75 DEPs were identified among the HC, LC, and LC-T groups. Forty-eight highly expressed DEPs (eg, programmed death-ligand 1 [PD-L1]) in the LC group were found to be downregulated after thermal ablation. These DEPs had significant impacts on pathways such as angiogenesis, immune checkpoint blockade, and pro-tumour chemotaxis. Metabolites involved in tumour cell survival were associated with these proteins at the expression and functional levels. In contrast, 19 elevated proteins (eg, interleukin [IL]-6) were identified after thermal ablation. These proteins were mainly associated with inflammatory response pathways (NF-κB signalling and tumour necrosis factor signalling) and immune cell activation.ConclusionsThermal ablation-induced changes in the host plasma microenvironment contribute to anti-tumour immunity in NSCLC, offering new insights into tumour ablation combined with immunotherapy.Trial registration This study was registered on the Chinese Clinical Trial Registry (https://www.chictr.org.cn/index.html). ID: ChiCTR2300076517. Registration Date: 2023-10-11.

Cardiopulmonary exercise testing in long covid shows the presence of dysautonomia or chronotropic incompetence independent of subjective exercise intolerance and fatigue

BackgroundAfter COVID-19 infection, 10–20% of patients suffer from varying symptoms lasting more than 12 weeks (Long COVID, LC). Exercise intolerance and fatigue are common in LC. The aim was to measure the maximal exercise capacity of the LC patients with these symptoms and to analyze whether this capacity was related to heart rate (HR) responses at rest and during exercise and recovery, to find out possible sympathetic overactivity, dysautonomia or chronotropic incompetence.MethodsCardiopulmonary exercise test was conducted on 101 LC patients, who were admitted to exercise testing. The majority of them (86%) had been treated at home during their acute COVID-19 infection. Peak oxygen uptake (VO2peak), maximal power during the last 4 min of exercise (Wlast4), HRs, and other exercise test variables were compared between those with or without subjective exercise intolerance, fatigue, or both.ResultsThe measurements were performed in mean 12.7 months (SD 5.75) after COVID-19 infection in patients with exercise intolerance (group EI, 19 patients), fatigue (group F, 31 patients), their combination (group EI + F, 37 patients), or neither (group N, 14 patients). Exercise capacity was, in the mean, normal in all symptom groups and did not significantly differ among them. HRs were higher in group EI + F than in group N at maximum exercise (169/min vs. 158/min, p = 0.034) and 10 min after exercise (104/min vs. 87/min, p = 0.028). Independent of symptoms, 12 patients filled the criteria of dysautonomia associated with slightly decreased Wlast4 (73% vs. 91% of sex, age, height, and weight-based reference values p = 0.017) and 13 filled the criteria of chronotropic incompetence with the lowest Wlast4 (63% vs. 93%, p < 0.001), VO2peak (70% vs. 94%, p < 0.001), the lowest increase of systolic blood pressure (50 mmHg vs. 67 mmHg, p = 0.001), and the greatest prevalence of slight ECG-findings (p = 0.017) compared to patients without these features. The highest prevalence of chronotropic incompetence was seen in the group N (p = 0.022).ConclusionsThis study on LC patients with different symptoms showed that cardiopulmonary exercise capacity was in mean normal, with increased sympathetic activity in most patients. However, we identified subgroups with dysautonomia or chronotropic incompetence with a lowered exercise capacity as measured by Wlast4 or VO2peak. Subjective exercise intolerance and fatigue poorly foresaw the level of exercise capacity. The results could be used to plan the rehabilitation from LC and for selection of the patients suitable for it.

Machine learning computational model to predict lung cancer using electronic medical records

BackgroundLung cancer (LC) screening using low-dose computed tomography (CT) is recommended according to standard risk criteria or personalized risk calculators. Machine learning (ML) models that can predict disease risk are an emerging method in medicine for identifying hidden associations that are personally unique. Materials and methodsUsing the tree-based pipeline optimization tool (TPOT), we developed an ML-based model, which is an ensemble of the Random Forest and XGboost models, based on known risk factors for LC, as part of a larger trial for ML prediction using electronic medical records and chest CT. We used data from patients with LC vs. controls (1:2) of patients aged ≥ 35 years. We developed a model for all LC patients as well as for patients with and without a smoking background. We included age, gender, body mass index (BMI), smoking history, socioeconomic status (SES), history of chronic obstructive pulmonary disease (COPD)/emphysema/chronic bronchitis (CB), interstitial lung disease (ILD)/pulmonary fibrosis (PF), and family history of LC. ResultsOf the 4076 patients, 1428 (35 %) were in the LC group and 2648 (65 %) were in the control group. For the entire study population, our model achieved an accuracy of 71.2 %, with a sensitivity of 69 % and a positive predictive value (PPV) of 74 %. Higher accuracy was achieved for the two subgroups. An accuracy of 74.8 % (sensitivity 72 %, PPV 76 %) and 73.0 % (sensitivity 76 %, PPV 72 %) was achieved for the smoking and never-smoking cohorts, respectively. For the entire population and smoker cohort, COPD/emphysema/CB were the most important contributors, followed by BMI and age, while in the never-smoking cohort, BMI, age and SES were the most important contributors. ConclusionKnown risk factors for LC could be used in ML models to modestly predict LC. Further studies are needed to confirm these results in new patients and to improve them.

A COMPARATIVE STUDY BETWEEN OPEN CHOLECYSTECTOMY VERSUS LAPAROSCOPIC CHOLECYSTECTOMY

Objective: This study aims to evaluate the comparative effectiveness of laparoscopic cholecystectomy (LC) versus open cholecystectomy (OC) in terms of surgery duration, blood loss, postoperative discomfort, hospital stay length, cost-effectiveness, and patient satisfaction. It also assesses differences in primary outcomes, such as mortality, complications, and symptom relief, as well as secondary outcomes, including conversion rates, operative time, and recovery. Methods: We conducted a prospective observational study involving 200 patients aged 10-70 with symptomatic gallstones confirmed via ultrasonography at Somani Hospital, Jaipur, from July 2021 to August 2023. Patients were randomly assigned to undergo either lC or OC. We collected data on surgical duration, blood loss, postoperative pain, hospitalization period, and complications, among other variables. Statistical analysis was performed using software tools. Results: Our study involved 200 patients, predominantly female (77%). The average duration of lC was shorter (67.37 min) compared to OC (93.95 min). lC patients had a shorter average hospital stay (2.8 d) compared to OC patients (5.1 d). The conversion rate from lC to OC was 6%, primarily due to anatomical and technical challenges. Complications were significantly lower in lC (17%) compared to OC (28%). Conclusion: lC is more efficient, entails fewer complications, and leads to a quicker recovery and shorter hospital stay compared to OC, supporting its preference in surgical practice for eligible patients with symptomatic gallstone disease. The lower rate of complications and shorter recovery time suggest that lC should be the standard care for cholecystectomy where feasible.

Association of Serum M2BPGi Levels with Nutritional Status (Using CONUT score) in Hepatitis C Virus Related Compensated Liver Cirrhosis Patients

Abstract Background Protein-energy malnutrition (PEM), which is one of the most common complications seen in LC patients and associated with high morbidity and mortality. So, predicting the presence of PEM and providing appropriate nutritional support help improve the prognosis of those patients. Mac-2-binding protein glycosylation isomer (M2BPGi) was recently identified as a serum glycobiomarker for liver fibrosis. However, the relationship between M2BPGi and malnutrition in patients with chronic liver disease (CLD) is unclear. Aim of the Work The aim of this study is to evaluate the role of serum M2BPGi levels as a surrogate marker for malnutrition in HCV related cirrhotic patients, correlated with CONUT score as the nutritional status marker. Patients and Methods This is a Cross-sectional - Analytic study that included patients with chronic HCV infection and normal control group selected from patients attending to Hepatology Outpatient Clinics at Ain Shams University Hospital. This study was carried out from 30 patients (child A) attending to Hepatology Outpatient Clinics at Ain Shams University Hospital and 30 healthy individuals as a control. Results The M2BPGi levels increased with CONUT score. The correlation coefficient between M2BPGi and CONUT score was r = 0.315 (p = 0.05), indicating a positive weak correlation between M2BPGi and CONUT score. The cut-off for M2BPGi to predict CONUT low vs. moderate was 1.43 with a sensitivity 93.33% and specificity 100% when AUC =0.9 and CONUT moderate vs. severe was 1.7 with a sensitivity 91.67% and specificity 100% when AUC =0.9. Conclusion We found that there is correlation between M2BPGi and CONUT score and both can be useful as a marker for malnutrition in HCV related cirrhotic patients cut of point

Analyzing diagnostic and treatment wait times for lung cancer Patients: Key insights from a provincial registry study

BackgroundLung cancer (LC) remains the leading cause of cancer-related mortality globally, necessitating timely diagnosis and treatment to improve patient outcomes. This study aimed to evaluate the timeliness of care for LC patients at a public hospital in Almería, Spain, assess adherence to guidelines, and explore associations between timeliness and survival. MethodsA retrospective cohort study was conducted, reviewing medical records of LC patients diagnosed between 2019 and 2021. Quality indicators, adapted from prevailing guidelines, facilitated the assessment of care timeliness, with a focus on diagnostic and treatment wait times. Cox regression modeling was employed to explore survival associations, adjusting for covariates including age, performance status, stage, histology, and treatment modalities. ResultsOf 539 patients included, most (79.84 %) had initial specialist contact within 7 days, and 82.25 % received diagnosis within 30 days. However, delays were observed in treatment initiation, with surgery experiencing the longest median wait time (78 days). Survival analysis showed no significant difference between shorter and longer diagnostic (HR: 0.87, 95 % CI: 0.62–1.24) or treatment intervals (HR: 1.14, 95 % CI: 0.83–1.58). Multivariate analysis identified age, performance status, stage, histology, and treatment as prognostic factors. ConclusionThis study highlights the importance of timely diagnosis and treatment in improving lung cancer outcomes. Despite achieving diagnostic targets, treatment delays were common, particularly for surgical interventions. These findings underscore the need for enhanced coordination and efficient care pathways to minimize delays, ultimately improving survival rates and quality of life for lung cancer patients. Addressing these issues is crucial for optimizing lung cancer care delivery in the future.

Promoting equity, diversity, and inclusion in surveys: insights from a patient-engaged study to assess long COVID health-care needs in Brazil

Background and ObjectiveLong COVID (LC) refers to persistent symptoms after acute COVID-19 infection, which may persist for months or years. LC affects millions of people globally, with substantial impacts on quality of life, employment, and social participation. Ensuring access to effective, patient-centered care for LC demands evidence, grounded in inclusive representation of those affected by the condition. Yet survey studies frequently under-represent people with the most disabling disease presentations and racially and socioeconomically marginalized groups. We aimed to describe a patient-engaged approach to developing a survey to inform public LC health care and to assess its implementation in terms of enabling participation by diverse LC patients in Brazil. MethodsSurvey development was iterative, achieved through an interdisciplinary collaboration among researchers including people living with LC, and grounded in 3 guiding principles: (1) evidence-based; (2) inclusive, intersectional, and patient-centered understanding of chronic illness and research participation; and (3) sensitivity to the context of health-care access. ResultsThe product of our collaboration was a longitudinal survey using a questionnaire assessing: LC symptoms; their clinical and functional evolution; and impacts on quality of life, household income, health service access, utilization, and out-of-pocket expenses. We illustrate how we operationalized our 3 principles through survey content, instrument design, and administration. Six hundred fifty-one participants with diverse LC symptoms, demography, and socioeconomic status completed the survey. We successfully included participants experiencing disabling symptoms, Black and mixed race participants, and those with lower education and income. ConclusionBy centering patient experience, our novel, principles-based approach succeeded in promoting equity, diversity, and inclusion in LC survey research. These principles guiding patient-engaged collaboration have broad transferability. We encourage survey researchers working on chronic illness and in other contexts of marginalization and inequality to adopt them.

Analysis of clinical characteristics and prognosis of lung cancer patients with CPFE or COPD: a retrospective study

BackgroundLung cancer (LC) commonly occurs in patients with combined pulmonary fibrosis and emphysema (CPFE) and chronic obstructive pulmonary disease (COPD), but comparative research is limited. This study examines clinical characteristics, treatments, and prognosis in LC patients with CPFE or COPD.MethodsThe retrospective study involved 75 lung cancer patients with CPFE and 182 with COPD. It analyzed clinical features, tumor pathology, pulmonary function, laboratory parameters, and treatment responses.ResultsNotable differences were found between the CPFE + LC and COPD + LC groups. Both groups were mostly elderly, male smokers. The CPFE + LC group had higher BMI and more adenocarcinoma and squamous cell carcinoma, while COPD + LC had predominantly squamous cell carcinoma. CPFE + LC tumors were mostly in the lower lobes; COPD + LC’s were in the upper lobes. The CPFE + LC group showed higher tumor metastasis rates, more paraseptal emphysema, and elevated levels of TG, CEA, NSE, and Killer T Cells. In advanced stages (IIIB-IV), the CPFE + LC group receiving first-line treatment had shorter median progression-free survival (PFS) and a higher risk of progression or death than the COPD + LC group, regardless of whether it was non-small cell lung cancer (NSCLC) or small cell lung cancer (SCLC). No significant PFS difference was found within CPFE + LC between chemotherapy and immunotherapy, nor in immune-related adverse events between groups, with interstitial pneumonia being common.ConclusionThis study emphasizes distinct lung cancer characteristics in CPFE or COPD patients, highlighting the need for tailored diagnostic and treatment approaches. It advocates for further research to improve care for this high-risk group.

The clinical, molecular, and therapeutic implications of time from primary diagnosis to brain metastasis in lung and breast cancer patients

AbstractPurposeLung cancer (LC) and breast cancer (BC) are the most common causes of brain metastases (BMs). Time from primary diagnosis to BM (TPDBM) refers to the time interval between initial LC or BC diagnosis and development of BM. This research aims to identify clinical, molecular, and therapeutic risk factors associated with shorter TPDBM.MethodsWe retrospectively reviewed all diagnosed LC and BC patients with BM at Harbin Medical University Cancer Hospital from 2016 to 2020. A total of 570 patients with LC brain metastasis (LCBM) and 173 patients with breast cancer brain metastasis (BCBM) patients who met the inclusion criteria were enrolled for further analysis. BM free survival time curves were generated using Kaplan–Meier analyses. Univariate and multivariate Cox regression analyses were applied to identify risk factors associated with earlier development of BM in LC and BC, respectively.ResultsThe median TPDBM was 5.3 months in LC and 44.4 months in BC. In multivariate analysis, clinical stage IV and M1 stage were independent risk factors for early development of LCBM. LC patients who received chemotherapy, targeted therapy, pulmonary radiotherapy, and pulmonary surgery had longer TPDBM. For BC patients, age ≥ 50 years, Ki67 ≥ 0.3, HER2 positive or triple‐negative breast cancer subtype, advanced N stage, and no mastectomy were correlated with shorter TPDBM.ConclusionsThis single‐institutional study helps identify patients who have a high risk of developing BM early. For these patients, early detection and intervention could have clinical benefits.

A meta-analysis of models for predicting the incidence of brain metastasis in patients with lung cancer.

e13613 Background: Brain metastasis (BM) represents a significant clinical challenge in the management of lung cancer, impacting patient prognosis and treatment decisions. While various predictive models have been developed to assess the risk of BM development, their performance and applicability remain under scrutiny. Understanding the accuracy and reliability of these models is crucial for informing clinical practice and improving patient care. We sought to evaluate the predictive ability of existing models predicting BM incidence in lung cancer patients, providing valuable insights into their clinical utility and areas for further refinement. Methods: Two reviewers conducted a systematic search of numerous databases, including PubMed, EMBASE, Cochrane Library, and CINAHL, and then extracted the relevant information from the eligible studies. For this study, we conducted a meta-analysis using a random-effects model. Pooled estimates were calculated for any combination of outcomes and population when at least two studies had relevant data. Study heterogeneity was assessed using I² statistics. The area under the curve (AUC) of the best model and 95% confidence intervals were set as effect measures. Additionally, funnel plots and results from meta-regression analysis were reported. Meta-analysis was performed with R software ver. 4.3.1, and quality evaluation of evidence was conducted according to the GRADE standard. Results: A total of seven studies with 535,418 participants were eligible. A random-effects model showed that models that could predict the risk of developing BM among lung cancer cases had a pooled AUC of 81% (95% CI: 74% to 87%). However, the studies had significantly higher heterogeneity, with an I2 = 99% (p&lt;0.01). Results from meta-regression analysis, accounting for the year of publication (?=-0.013), sample size (?&lt; 0.00), number of variables (?=-0.015), and latitude (?=0.0024) did not show any statistically significant associations with a p&gt;0.05. Egger’s regression test for publication bias did not indicate small study effects (Bias estimate: 4.91, SE = 6.01, p&lt; 0.44). Conclusions: Our meta-analysis underscores the utility of existing models in predicting the incidence of BM in LC patients, with a pooled AUC of 81%. Further research aimed at refining predictive models and addressing sources of heterogeneity is imperative to enhance clinical decision-making and improve patient outcomes in this population. [Table: see text]

Association of social determinant of health (SDOH) with clinical outcomes in patients with cancer: Opioid use, emergency admission, anxiety, depression, and length of hospital stays.

e23072 Background: As cancer patients are overburdened by disease, treatment, access to care, and other demographic factors, the obstacles become increasingly significant with SDOH. Patients hospitalized in the United States in 2017 for the treatment of prostate (PC), breast (BC), and lung (LC) cancer were evaluated to characterize further and contrast variations between SDOH and clinical outcomes. Methods: We utilized the generalized linear models to assess the association between homelessness and problem-related living alone (PrbLA) and clinical outcomes–– opioid abuse/long-term use, anxiety and depression, and burden of illness (length of stay) while controlling for patients’ characteristics. Results: In the study among PC, there were 425 homeless, 355 PrbLA; BC, 320 homeless and 225 PrbLA; LC, 1345 homeless and 820 PrbLA. In the adjusted analysis, PC homelessness was significantly associated with anxiety and depression (5.15, 95%CI: 3.17-8.35); emergency admission (5.57; 95%CI: 2.63-11.82); opioid abuse (3.75,95%CI: 1.27-11.13) and longer LOS, unadjusted (2.49; 95%CI: 1.58-3.92), adjusted analysis (1.96; 95%CI: 1.03-3.74). These findings were comparable in the BC and LC cohorts. Further in the adjusted analysis, PC patients with PrbLA were associated with higher combined anxiety and depression, adjusted (2.7, 95%CI: 1.64-4.46); emergency admission, adjusted (5.86; 95%CI: 2.66-12.91); opioid long-term use, adjusted (3.74,95%CI: 1.02-6.88) and longer LOS, adjusted analysis (1.44; 95%CI: 1.11-1.88). These findings were comparable in the BC cohort. In the LC cohort, when stratified to females, the PrbLA was associated with longer LOS (1.29; 95%CI: 1.02-1.63). In all cancer cohorts, when compared to Whites, SDOH was associated with poor outcomes––Blacks had a higher burden of illness. And when compared to Whites, Hispanics, Asians, and Others were associated with lesser opioid abuse among all cancer cohorts with homelessness. Conclusions: According to this study, PC, BC, and LC patients with poor SDOH presented with the worst clinical outcomes, including higher opioid abuse, emergency admission, anxiety and depression, and longer LOS in the hospital. The findings of this study highlight a vacuum in the literature, and the recommendations stress the value of social support for cancer patients in achieving a better prognosis and quality of life.

High expression of AlkB homolog 5 suppresses the progression of non-small cell lung cancer by facilitating ferroptosis through m6A demethylation of SLC7A11.

Non-small cell lung cancer (NSCLC) is a prevailing LC characterized by poor outcomes. AlkB homolog 5 (ALKBH5) functions as a tumor suppressor in several cancers. This study delved into the role of ALKBH5 in NSCLC development. TCGA database predicted ALKBH5 expression in NSCLC patients. ALKBH5 levels in NSCLC and human bronchial epithelial cells were determined. pcDNA3.1-ALKBH5/NC, pcDNA3.1-SLC7A11/NC, and ferrostatin-1 were used to explore the interactions among ALKBH5, SLC7A11, and ferroptosis. SLC7A11 mRNA and its protein levels were measured by RT-qPCR and Western blot. Cell viability, apoptosis, migration, and invasion were assessed by CCK-8, flow cytometry, and Transwell. Total N6-methyladenosine (m6A) quantification and its enrichment on SLC7A11 mRNA were determined, followed by the observation of Ki67, ALKBH5 and SLC7A11-positive cell numbers. Glutathione (GSH), lipid reactive oxygen species (lipid-ROS), malondialdehyde (MDA), and iron ion contents were determined. Animal experiments further analyzed the role of ALKBH5 in tumor development and glutathione peroxidase 4 (GPX4) expression. Bioinformatics analysis revealed the lowly-expressed ALKBH5 in LC patients. ALKBH5 was downregulated in NSCLC cells and its upregulation repressed proliferation activity, invasion, and migration, and facilitated apoptosis. ALKBH5 upregulation decreased GSH, increased lipid-ROS, MDA, and iron ion contents, and downregulated SLC7A11 by reducing m6A modification. SLC7A11 upregulation partly annulled the effect of ALKBH5 overexpression on cell ferroptosis and malignant behaviors. In vivo assays elucidated the suppression of ALKBH5 upregulation on tumor development and GPX4 levels. ALKBH5 upregulation downregulates SLC7A11 transcription by decreasing m6A modification, thus promoting NSCLC cell ferroptosis and ultimately repressing NSCLC progression.

Smoking characteristics and years since quitting smoking of US adults diagnosed with lung and bladder cancer: A national health and nutrition examination survey analysis.

Smoking is a recognized risk factor for bladder BC and lung cancer LC. We investigated the enduring risk of BC after smoking cessation using U.S. national survey data. Our analysis focused on comparing characteristics of LC and BC patients, emphasizing smoking status and the latency period from smoking cessation to cancer diagnosis in former smokers. We analyzed data from the National Health and Examination Survey (2003-2016), identifying adults with LC or BC history. Smoking status (never, active, former) and the interval between quitting smoking and cancer diagnosis for former smokers were assessed. We reported descriptive statistics using frequencies and percentages for categorical variables and median with interquartile ranges (IQR) for continuous variables. Among LC patients, 8.9% never smoked, 18.9% active smokers, and 72.2% former smokers. Former smokers had a median interval of 8 years (IQR 2-12) between quitting and LC diagnosis, with 88.3% quitting within 0-19 years before diagnosis. For BC patients, 26.8% never smoked, 22.4% were active smokers, and 50.8% former smokers. Former smokers had a median interval of 21 years (IQR 14-33) between quitting and BC diagnosis, with 49.3% quitting within 0-19 years before diagnosis. BC patients exhibit a prolonged latency period between smoking cessation and cancer diagnosis compared to LC patients. Despite smoking status evaluation in microhematuria, current risk stratification models for urothelial cancer do not incorporate it. Our findings emphasize the significance of long-term post-smoking cessation surveillance and advocate for integrating smoking history into future risk stratification guidelines.

Abstract 6797: CCR5/CCL4 axis in lung cancer clinicopathological significance and its therapeutic application

Abstract Lung cancer (LC) is the most prevalent type of cancer globally and the leading cause of cancer-related deaths. Based on the histology and type of treatments, LC is divided into small-cells and non-small cell lung cancer (NSCLC) carcinomas, which are more aggressive and less responsive to chemotherapy. Since LC is known to be a highly heterogeneous cell population, treatment is challenging. It has been observed that chemokine receptor-ligand interaction is essential for cancer cells homing to distant sites. Most malignancies, including LC, have established disease status indicators concerning elevated levels of CCL4, a structurally unique chemokine, and its receptor (CCR5). Therefore, treatment strategies that inhibit the LC cell's tumor environment may improve patients' quality of life. However, the CCR5/CCL4 interface in LC invasion and metastasis is poorly understood. In this study, we examined the expression and function of the CCR5/CCL4 axis in the development and invasiveness of LC patient's clinical tissues and cell lines. We conducted immunohistochemistry (IHC) dual staining of CCR5/CCL4 antibodies in LC tissues. Our findings demonstrated significantly (p &amp;lt; 0.001) higher expression of CCR5 and CCL4 in advanced-stage malignant tissues than in normal tissues. The in-vitro analysis of the human LC cell lines NCI-H1437, NCI-H1573, and NCI-H1975 revealed CCL4 activation expressing higher CCR5, determined by immunofluorescence, western blots, flow cytometry, 3D-invasion assay, and RT-qPCR methods. Further, a calcium mobilization assay confirmed the direct interaction between CCR5 and CCL4. However, treating with Maraviroc, a small molecule inhibitor of CCR5, to LC cells blocks their ability to proliferate, demonstrating the crucial role that CCR5-CCL4 chemotaxis plays in LC metastasis. Our findings show both the biological and clinical significance of CCR5 and CCL4 expression, which may serve as potential indicators for metastatic LC. Therefore, inhibiting the CCR5/CCL4 interaction may offer a more effective therapeutic approach for managing the progression of LC. Citation Format: Santosh K. Singh, Rajesh Singh. CCR5/CCL4 axis in lung cancer clinicopathological significance and its therapeutic application [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6797.