Advances in screening, surgical techniques, perioperative care, and multimodality treatment have progressively expanded the population of long-term survivors with early-stage non-small cell lung cancer (NSCLC). However, disease-free survival does not necessarily correspond to complete functional recovery after curative-intent treatment. Many patients continue to experience persistent fatigue, dyspnea, reduced physical activity, impaired exercise tolerance, muscle loss, and deterioration in health-related quality of life despite adequate oncologic control. This narrative review discusses functional recovery as a survivorship endpoint in early-stage NSCLC, focusing on recovery trajectories, physiologic vulnerability, frailty, sarcopenia, rehabilitation, symptom burden, and emerging biologic frameworks such as allostatic load. Increasing evidence suggests that survivorship after NSCLC should not be interpreted exclusively according to recurrence or survival metrics, but also according to the ability to recover physiologic reserve, autonomy, and daily functioning after treatment. Functional recovery appears heterogeneous and influenced by multiple interacting factors, including baseline reserve, systemic inflammation, physical inactivity, behavioral adaptation, and cumulative stress burden. Rehabilitation strategies, structured symptom surveillance, and patient-reported outcomes may help identify vulnerable patients and improve long-term survivorship trajectories. Future survivorship models should probably integrate oncologic outcomes with longitudinal functional assessment to better characterize recovery patterns after treatment.

Pulmonary metastases affect up to 30

INTRODUCTION:Low-dose computed tomography (LDCT) screening saves lives but is limited by high false-positive rates, necessitating noninvasive risk stratification. The prospective Bio-Multicentric Italian Lung Detection (BioMILD) trial was the first to validate the combination of a plasma microRNA test (MSC) with LDCT to personalize screening intervals. This study integrates a novel immune signature classifier (ISC), based on peripheral blood mononuclear cell profiling, to complement MSC, maximize information from a single blood draw, and further optimize the management of suspicious lung nodules. METHODS:Plasma and peripheral blood mononuclear cell samples were prospectively collected from 304 heavy smokers enrolled in the BioMILD trial who presented with LDCT-detected suspicious nodules and a 7.5-year median follow-up. MSC and ISC tests were determined by real-time quantitative polymerase chain reaction. Grafting of patient-derived xenograft models, obtained from the same patients, was used as indicator of tumor aggressiveness. RESULTS:ISC was associated with age (p = 0.0323) and Lung-RADS (p = 0.0008) and was significantly higher in patients with cancers diagnosed within 2 years (p = 0.0006). Higher ISC values also correlated with successful patient-derived xenograft engraftment (p = 0.0449). In terms of diagnostic performance, the combined ISC and MSC model achieved 96% sensitivity and 98% negative predictive value (NPV) (95% confidence interval: 0.93-0.99). It represented a significant enhancement than MSC alone (ΔNPV = +0.05; 95% confidence interval: 0.01-0.08) and resulted in a 37% reduction of false positives. CONCLUSION:Integration of immune and molecular markers significantly enhances LDCT screening accuracy. The higher NPV achieved by the combined model allows greater confidence in ruling out malignancy among LDCT-detected nodules, thereby reducing unnecessary follow-up examinations and invasive procedures.

Background: Current guidelines for NSCLC follow-up lack specific recommendations on surveillance duration. This study aims to analyze survival and surveillance data in resected stage I NSCLC. Methods: We retrospectively reviewed 759 pathological stage I NSCLC (9thTNM ed.) patients with no history of lung cancer (LC) undergoing surgery from January 2003 to December 2018. Overall survival (OS), incidence of relapse (IR), and incidence of new primary LC (NP) were analyzed. Long-term effect of follow-up beyond 5 years was assessed by landmark analysis of OS, IR, and NP at 10 years, restricted to individuals alive without relapse or NP at 5 years (5-year event-free survivors, 5y-EFSs). Results: The rates of 10-year OS, 10-year IR, NP incidence, and 5y-EFSs were, respectively, 75%, 18%, 1.1%/year, and 59.1% (449 patients). Carcinoid IA/IB (0-10%) and adenocarcinoma IA/IB without lung nodules (LNs) (8-12%) had a similarly lower risk of relapse (p = 0.5088) compared to adenocarcinoma with LNs (p = 0.0191). Similarly, carcinoid (0-0.2%/year) and adenocarcinoma without LNs (0-0.3%/year) had the same lower incidence of NP (p = 0.8062) compared to patients with LNs (p < 0.0001). The group of 5y-EFSs had a conditional 10-year OS, IR, and NP incidence of 92%, 5%, and 0.8%/year. In 5y-EFSs, 10-year OS was better in carcinoid (100%) and adenocarcinoma (94%, p = 0.0009) patients; 10-year IR was lower in stage IA (4%) vs. IB (10%, p = 0.0444), and NP was lower in patients with no pre-surgery (0.5 vs. 1.5%/year, p = 0.0147) and no post-surgery LNs (0.6 vs. 1.1%/year, p = 0.0202). Conclusions: Based on our results, we propose a tailored surveillance strategy by de-escalating follow-up for low-risk patients while maintaining intensive monitoring for high-risk individuals.

PURPOSE:To retrospectively assess the agreement between human and automated AI-based readings for low-dose computed tomography (LDCT) outcomes according to LungRADS v1.1 in lung cancer screening (LCS); to test the diagnostic performance of both readings. METHODS:We included 4104 baseline LDCTs from the BioMILD trial. Original readings were retrospectively classified into "negative" (LungRADSv1.1 categories 1, 2) and "positive" (categories 3, 4) by a radiologist and analyzed by AI software for category assignment. Diagnosis of lung cancer (LC) at 2 years served as reference standard to assess sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of both human and AI. Agreement between readers was measured by the k-Cohen Index with Fleiss-Cohen weights (Kw) with 95 % CI. RESULTS:Median age of participants was 60 years; 60.8 % were male and 79.2 % current smokers; 68/4104 (1.7 %) were diagnosed with LC; 6/68 (8.8 %) and 7/68 (10.3 %) LDCT were classified as negative by AI and human reading, respectively. The agreement between human and AI readings for negative and positive LDCTs was 83.5 % (Kw 0.47; 95 %CI: 0.43-0.50). Sensitivity and specificity were 91.2 % and 75.7 % for AI, and 89.7 % and 90.0 % for human reading (p-value 0.5637 and < 0.0001). PPV and NPV were 6.0 % and 99.8 % for AI, and 13.1 % and 99.8 % for human reading (p-value < 0.0001 and 0.9351). The expected reduction in LDCT reading workload when using AI as first reader was 74.7 %. CONCLUSION:AI reading showed comparable sensitivity but lower specificity than human reading. High NPV of AI may support its use as a first reader in LCS.

Low-dose computed tomography (LDCT) lung cancer screening can reduce mortality in high-risk individuals, but many individuals with a heavy smoking history may be reluctant to undergo radiologic examinations. A non-invasive blood test might help overcome this barrier. The BioMILD trial evaluated the combination of a plasma microRNA signature classifier (MSC) and LDCT for personalized lung cancer screening in 4,119 individuals who smoke or used to smoke. Based on BioMILD results, we aim to conduct a projection analysis to estimate the number of early lung cancers that could be detected if MSC were used as an initial screening tool for individuals reluctant to undergo LDCT. This model explores the potential of a biomarker-driven approach to address screening hesitation. The analysis focuses on 3,139 volunteers meeting NLST criteria. At baseline, 24.9

Introduction: Coronary artery calcification (CAC) is a well- known cardiovascular risk factor. In the past year, the CAC score has been investigated in lung cancer (LC) screening, suggesting promising results in terms of mortality risk assessment. Nevertheless, its role in patients with LC is still to be investigated. This study aimed to evaluate the per- formance of a fully automated CAC scoring alone and combined with a prognostic index on the basis of periop- erative routine blood tests in predicting 5-year survival of patients with stage I LC. Methods: This study included 536 consecutive patients with stage I LC who underwent preoperative chest computed tomography followed by surgical resection. The CAC score was measured by commercially available, fully automated artificial intelligence software. The primary outcome was the 5-year overall survival rate. Results: A total of 110 patients (20.5%) had a CAC score greater than or equal to 400, 149 (27.8%) between 100 and 399, and 277 (51.7%) had less than 100. Male smokers had the highest CAC values: 32% compared with only 17% of nonsmokers. Females had lower CAC values compared with males both in smokers and nonsmokers: CAC greater than or equal to 400 only for 10% of smoking females and 0% in nonsmoking females. The 5-year survival was 80.3% overall, 84.7% in CAC less than 100, 77.5% in CAC 100 to 399, and 73.5% in CAC greater than or equal to 400 (p 1/4 0.0047). Conclusions: We observed that the CAC score predicted the 5-year overall survival in patients with resected stage I LC, both alone and combined with the modified routine blood test score. These results open new prospects for the prevention of noncancer mortality in patients with early-stage LC. (c) 2025 The Authors. Published by Elsevier Inc. on behalf of the International Association for the Study of Lung Cancer. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).both alone and combined with the modified routine blood test score. These results open new prospects for the prevention of noncancer mortality in patients with early-stage LC. (c) 2025 The Authors. Published by Elsevier Inc. on behalf of the International Association for the Study of Lung Cancer. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Low-dose computed tomography (LDCT)-based lung cancer screening (LCS) seems to have very limited impact on small cell lung cancer (SCLC) outcomes. This study aims at describing frequency and outcomes of SCLC in a large LCS population.Patients diagnosed with SCLC among the total population enrolled in three different trials (n = 7473) were selected for the present analysis. Demographic and clinical data were collected at the baseline and follow-up screening rounds, while the vital status and date of death were obtained through a dedicated national platform. Of the 396 diagnosed LCs, 28 (7.1%) were SCLCs; median survival time from the diagnosis was 1.5 years, and overall mortality was 71.4%. Screen-detected SCLCs were 20/28 (71.4%); 5/20 (25%) were prevalent cancers and 15/20 (75%) incident ones. Five-year mortality among the screen-detected and non-screen detected SCLCs was 70% and 62.5%, respectively.The frequency of SCLC was lower as compared to other trials. Although no significant differences in five-year mortality were observed between screen-detected and non-screen-detected SCLCs, the overall five-year mortality was substantially lower than that reported in non-LCS populations, suggesting that LDCT-based LCS has an impact on SCLC outcome, albeit limited.

Background The management of subsolid nodules (SSNs) in lung cancer screening (LCS) is still a topic of debate, with no current uniform strategy to deal with these lesions at risk of overdiagnosis and overtreatment. The BioMILD LCS trial has implemented a prospective conservative approach for SSNs, managing with annual low-dose computed tomography nonsolid nodules (NSNs) and part-solid nodules (PSNs) with a solid component <5 mm, regardless of the size of the nonsolid component. The present study aims to determine the lung cancer (LC) detection and survival in BioMILD volunteers with SSNs. Materials and methods Eligible participants were 758 out of 4071 (18.6%) BioMILD volunteers without baseline LC and at least one SSN detected at the baseline or further low-dose computed tomography rounds. The outcomes of the study were LC detection and long-term survival. Results A total of 844 NSNs and 241 PSNs were included. LC detection was 3.7% (31 out of 844) in NSNs and 7.1% (17 out of 241) in PSNs, being significantly greater in prevalent than incident nodules (8.4% versus 1.3% in NSNs; 14.1% versus 2.1% in PSNs; p-value for both nodule types p<0.01). Most LCs from SSNs were stage I (42/48, 87.5%), resectable (47/48, 97.9%), and caused no deaths. The 8-year cumulative survival of volunteers with LC derived from SSNs and not derived from SSNs was 93.8% and 74.9%, respectively. Conclusion Conservative management of SSNs in LCS enables timely diagnosis and treatment of LCs arising from SSNs while ensuring the resection of more aggressive LCs detected away from SSNs.

Background:The proper management of suspicious radiologic findings is crucial to optimize the effectiveness of low-dose computed tomography (LDCT) lung cancer screening trials. In the BioMILD study, we evaluated the utility of combining a plasma 24-microRNA signature classifier (MSC) and LDCT to define the individual risk and personalize screening strategies. Here we aim to assess the utility of repeated MSC testing during annual screening rounds in 1024 participants with suspicious LDCT findings. Methods:The primary outcome was two-year lung cancer incidence in relation to MSC test results, reported as relative risk (RR) with 95% confidence interval (CI). Lung cancer incidence and mortality were estimated using extended Cox models for time-dependent covariates, yielding the respective hazard ratios (HR). Clinicaltrials.gov ID: NCT02247453. Findings:With a median follow-up of 8.5 years, the full study set included 1403 indeterminate LDCT (CTind) and 584 positive LDCT (CT+) results. A lung cancer RR increase in MSC+ compared to MSC- participants was observed in both the CTind (RR: 2.5; 95% CI: 1.4-4.32) and CT+ (RR: 2.6; 95% CI: 1.81-3.74) groups and was maintained when considering stage I or resectable tumors only. A 98% negative predictive value in CTind/MSC- and a 30% positive predictive value in CT+/MSC+ lesions were recorded. At seven years' follow-up, MSC+ participants had a cumulative HR of 4.4 (95% CI: 3.0-6.4) for lung cancer incidence and of 8.1 (95% CI: 2.7-24.5) for lung cancer mortality. Interpretation:Our study shows that MSC can be reliably performed during LDCT screening rounds to increase the accuracy of lung cancer risk and mortality prediction and supports its clinical utility in the management of LDCT findings of uncertain malignancy. Funding:Italian Association for Cancer Research; Italian Ministry of Health; Horizon2020; National Cancer Institute (NCI); Gensignia LifeScience.

Background: Stage III lung cancer (LC) represents a heterogeneous group of diseases, and the optimal management is still a matter of debate. To date, only a few studies have assessed the role of multidisciplinary team (MDT) discussion in impacting survival of stage III LC. Hence, we aimed to reported the impact of the implementation of MDT discussion on long-term survival of stage III LC patients. Methods: This is a retrospective, observational, single-centre cohort study evaluating data of consecutive patients with a clinical and pathological diagnosis of stage III LC treated before [2005-2011] and after [2012-2020] the implementation of MDT. The primary outcome was 5-year overall survival (OS). Results: A total of 983 patients were enrolled with stage III LC, 411 (41.8%) pre-MDT and 572 (58.2%) post-MDT. The 5-year OS rates were 25.3% for the pre-MDT cohort and 33.9% for the post-MDT cohort (P=0.0008). Resected patients (n=670), who underwent trimodality therapy achieved a higher 5-year OS in both pre-MDT and post-MDT groups. An increased 5-year OS was observed in patients who underwent systemic therapy, from 28.2% in pre-MDT to 40.2% in post-MDT cohorts. In non-resected patients, there was an increased in 5-year OS in both systemic and chemoradiotherapy groups. Conclusions: The implementation of an MDT increased the 5-year OS in both resected and non-resected stage III LC patients. Implementing MDT might be useful in improving the management of therapy with less invasive local and surgical strategies personalized for each LC patient.

To assess the consistency of automated measurements of coronary artery calcification (CAC) burden and emphysema extent on computed tomography (CT) images acquired with different radiation dose protocols in a lung cancer screening (LCS) population. The patient cohort comprised 361 consecutive screenees who underwent a low-dose CT (LDCT) scan and an ultra-low-dose CT (ULDCT) scan at an incident screening round. Exclusion criteria for CAC measurements were software failure and previous history of CVD, including coronary stenting, whereas for emphysema assessment, software failure only. CT images were retrospectively analyzed by a fully automated AI software for CAC scoring, using three predefined Agatston score categories (0–99, 100–399, and ≥ 400), and emphysema quantification, using the percentage of low attenuation areas (

BACKGROUND AND AIMS:Body composition has been linked with clinical and prognostic outcomes in patients with cancer and cardiovascular diseases. Body composition analysis in lung cancer screening (LCS) is very limited. This study aimed at assessing the association of subcutaneous fat volume (SFV) and subcutaneous fat density (SFD), measured on chest ultra-low dose computed tomography (ultra-LDCT) images by a fully automated artificial intelligence (AI)-based software, with clinical and anthropometric characteristics in a LCS population. METHODS AND RESULTS:Demographic, clinical, and dietary data were obtained from the written questionnaire completed by each participant at the first visit, when anthropometric measurements, blood sample collection and chest ultra-LDCT were performed. Images were analyzed for automated 3D segmentation of subcutaneous fat and muscle. The analysis included 938 volunteers (372 females); men with a smoking history of ≥40 pack-years had higher SFV (p = 0.0009), while former smokers had lower SFD (p = 0.0019). In female participants, SFV and SFD differed significantly according to age. SFV increased with rising BMI, waist circumference, waist-hip ratio, and CRP levels ≥2 mg/L (p < 0.0001), whereas SFD decreased with rising BMI, waist circumference, waist-hip ratio, and CRP levels ≥2 mg/L (p < 0.001) in both sexes. SFV was associated with glycemia and triglycerides levels (p = 0.0067 and p=<0.0001 in males, p = 0.0074 and p < 0.0001 in females, respectively), while SFD with triglycerides levels (p < 0.0001). CONCLUSION:We observed different associations of SFV and SFD with age and smoking history between men and women, whereas the association with anthropometric data, CRP, glycemia and triglycerides levels was similar in the two sexes.

Coronary artery calcification (CAC) is a well-known cardiovascular risk factor and a reliable score to predict non-cancer survival. In the last year, the CAC score has been investigated in lung cancer (LC) screening, showing promising results in terms of mortality risk assessment. Nevertheless, its role in LC patients has still to be investigated. This study aims to evaluate the performance of a fully automated CAC scoring in predicting 5-year survival of patients who underwent surgical resection for stage I LC. This retrospective observational study included 536 consecutive patients with stage I LC who underwent preoperative chest CT with a 128+ slice CT scanner followed by surgical resection, between 2011 and 2022. The CAC score was measured by a commercially available, fully automated artificial intelligence (AI) software. CAC score was categorized into three validated risk categories: <100; 100-399; and ≥400. The primary outcome was the 5-year overall survival rate. A total of 110 (20.5%) patients had a CAC score ≥400, 149 (27.8%) of 100-399, and 277 (51.7%) <100. Male smokers had the highest CAC values: 32% (88/273) ≥400 and 36% (97/273) <100, while only 17% (5/29) of non-smoking males had CAC ≥400. Females had lower CAC values compared to males both in smokers and in non-smokers: only 10% (17/167) ≥400 in smoking females and 0% in non-smoking females. After a median follow-up of 3.7 years, the 5-year survival was 80.3% overall, 84.1% in CAC<100, 78.6% in CAC 100-399, and 73.3% in CAC >=400, with a statistically significant poorer outcome in patients with higher CAC (p=0.0072). We observed that CAC score was a risk factor associated with gender and smoking status and predicted the 5-year overall survival in patients with resected stage I LC. These results open new prospects for prevention of non-cancer mortality in early-stage LC patients.

Introduction: Cigarette smoke accounts for over 90,000 deaths each year in Italy. Tobacco dependence treatment guidelines suggest adopting an integrated pharmacological-behavioral model of intervention. Cytisine is a partial agonist of nicotinic receptors. Trials conducted to date have demonstrated its good efficacy in promoting smoking cessation. The cytisine scheme of treatment consists of 25 days of treatment. A 40-day regimen, with an escalating dose and an extended duration of the treatment, has been in use in many anti-smoking centers in Italy for several years, but to date there are no reports on the use of cytisine with this scheme. Methods: A retrospective, real-life, observational study was conducted between January 2016 and September 2022. The 300 patients who had received at least one dose of study medication were selected. Continuous variables were compared by the Wilcoxon-Mann-Whitney test. Univariate and multivariate logistic regression models were implemented for self-reported seven-day point prevalence for abstinence at three, six and 12 months. Results: The median age of the patients was 59 years, 57% were women. The median smoking exposure was 33.8 pack-years. Self-reported smoking abstinence at three, six and 12 months was 68.7%, 56.3% and 47.3% respectively. 84% completed the cytisine treatment, 31.3% reported adverse events and in 8.3% these led to dropping out of the treatment. Conclusion: Cytisine, administered with a novel therapeutic scheme in the real-life setting of a specialized anti-smoking center, significantly promotes smoking abstinence. However, more studies are needed to assess the tolerability and efficacy of this new regimen.