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The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Small Cell Lung Cancer (SCLC) provide recommended management for patients with SCLC, including diagnosis, primary treatment, surveillance for relapse, and subsequent treatment. This selection for the journal focuses on metastatic (known as extensive-stage) SCLC, which is more common than limited-stage SCLC. Systemic therapy alone can palliate symptoms and prolong survival in most patients with extensive-stage disease. Smoking cessation counseling and intervention should be strongly promoted in patients with SCLC and other high-grade neuroendocrine carcinomas. The "Summary of the Guidelines Updates" section in the SCLC algorithm outlines the most recent revisions for the 2022 update, which are described in greater detail in this revised Discussion text.

BackgroundOlder patients with non-small cell lung cancer (NSCLC) are often not prescribed standard therapy. It is important to know which older patients would be candidates for aggressive therapy based on their prognosis, and to develop a model that can help determine prognosis.MethodsData on older patients (≥70 years) enrolled on 38 NCI cooperative group trials of advanced NSCLC from 1991 to 2011 were analyzed. Multivariable Cox PH model was built with a stepwise selection. We derived a prognostic score using the estimated Cox PH regression coefficient. We then calculated the area under receiver operating characteristic (ROC) curve of survival in the testing set.ResultsThe final analysis included 1467 patients, who were randomly divided into a training (n = 963) and a testing set (n = 504). The prognostic risk score was calculated as: 3 (if male) + 3 (if PS = 1) + 8 (if PS = 2) + 11 (if initial stage = IV) + 4 (if weight loss). Patients were classified into two prognostic groups: good (0-8) and poor (≥9). The median survival in the two groups in the testing set were 13.15 (95% CI, 10.82-15.91) and 8.52 months (95% CI, 7.5-9.63), respectively. The model had area under the 1-year and 2-year ROCs (0.6 and 0.65, respectively) that were higher than existing models.ConclusionsMale gender, poor performance status, distant metastases and recent weight loss predict for poor overall survival (OS) in older patients with advanced NSCLC. This study proposes a simple prognostic model for older adults with advanced NSCLC.

Objective: We aimed to evaluate lung cancer risk in patients with rheumatoid arthritis (RA) and RA‐interstitial lung disease (ILD). Methods: We performed a retrospective, matched cohort study of RA and RA‐ILD within the Veterans Health Administration (VA) between 2000 and 2019. Patients with RA and RA‐ILD were identified with validated administrative‐based algorithms, then matched (up to 1:10) on age, gender, and VA enrollment year to individuals without RA. Lung cancers were identified from a VA oncology database and the National Death Index. Conditional Cox regression models assessed lung cancer risk adjusting for race, ethnicity, smoking status, Agent Orange exposure, and comorbidity burden among matched individuals. Several sensitivity analyses were performed. Results: We matched 72,795 patients with RA with 633,937 patients without RA (mean age 63 years; 88% male). Over 4,481,323 patient‐years, 17,099 incident lung cancers occurred. RA was independently associated with an increased lung cancer risk (adjusted hazard ratio [aHR] 1.58 [95% confidence interval (CI) 1.52–1.64]), which persisted in never smokers (aHR 1.65 [95% CI 1.22–2.24]) and in those with incident RA (aHR 1.54 [95% CI 1.44–1.65]). Compared to non‐RA controls, prevalent RA‐ILD (n = 757) was more strongly associated with lung cancer risk (aHR 3.25 [95% CI 2.13–4.95]) than RA without ILD (aHR 1.57 [95% CI 1.51–1.64]). Analyses of both prevalent and incident RA‐ILD produced similar results (RA‐ILD vs non‐RA aHR 2.88 [95% CI 2.45–3.40]). Conclusion: RA was associated with a >50% increased risk of lung cancer, and those with RA‐ILD represented a particularly high‐risk group with an approximate three‐fold increased risk. Increased lung cancer surveillance in RA, and especially RA‐ILD, may be a useful strategy for reducing the burden posed by the leading cause of cancer death. [ABSTRACT FROM AUTHOR]

Introduction: There are limited data available regarding patient outcomes in those who would have been ineligible to receive therapy based on the original clinical trial eligibility criteria. We decided to conduct a retrospective study to evaluate outcomes based on clinical trial eligibility in patients with metastatic non--small cell lung cancer (NSCLC). Methods: A retrospective chart review of all patients with metastatic NSCLC who received first-line systemic therapy at a single academic institution was performed. Each patient's chart was reviewed to determine if they would have qualified for the phase 3 clinical trial that led to the approval of the specific treatment regimen which they received. Data were analyzed to determine if there was a difference in survival time between those who would have been eligible compared with those who were ineligible for the clinical trial of the treatment regimen administered. Results: There were 170 patients with a diagnosis of metastatic NSCLC who received first-line systemic therapy. Of these, 109 received combined chemotherapy, 25 received immunotherapy, and 36 received targeted therapy. There is a statistically significant difference in the restricted mean survival time between the eligible and ineligible groups in those who received combined chemotherapy (19.9 months vs 13.2 months; P = .03), but not in either the immunotherapy group (22.4 months vs 12.9 months; P = .06) or the targeted therapy group (57.7 months vs 39.0 months; P = .14). Conclusion: These data support less restrictive clinical trial eligibility criteria for those with metastatic NSCLC. This is especially true regarding both targeted therapy and immunotherapy treatment regimens. [ABSTRACT FROM AUTHOR]

Simple Summary: It is important for patients to understand their chances of survival when they are diagnosed with advanced-stage lung cancer. A Positron Emission Tomography (PET) scan is an important type of imaging that shows how cancer is affecting the body's metabolism and energy use. Radiomics is an exciting and growing field of research that looks for hidden patterns in medical images, like PET scans, to find potential signs that can help predict clinical outcomes such as a patient's chances of survival. In our study, we identified robust radiomics features from PET scans that can accurately predict a patient's survival likelihood, and these predictions are more accurate than using traditional clinical features alone. Our study could potentially help both doctors and patients better understand the chances of survival for those with advanced-stage lung cancer in the future. (1) Background: Advanced-stage lung cancer poses significant management challenges. The goal of this study was to identify crucial clinical and PET radiomics features that enable prognostic stratification for predicting outcomes. (2) Methods: PET radiomics features of the primary lung lesions were extracted from 99 patients with stage IVB NSCLC, and the robustness of these PET radiomics features was evaluated against uncertainties stemming from extraction parameters and contour variation. We trained three survival risk models (clinical, radiomics, and a composite) through a penalized Cox model framework. We also created a Balanced Random Forest classification predictive model, using the selected features, to predict 1-year survival. (3) Results: We identified 367 common PET radiomics features that exhibited robustness to perturbations introduced by contour variation and extraction parameters. Our findings indicated that both the radiomics and the composite model outperformed the clinical model in stratifying the risk for survival with statistical significance. In predicting 1-year survival, the radiomics model and the composite model also achieved better predicting accuracies compared to the clinical model. (4) Conclusions: Robust PET radiomics analysis successfully facilitated the stratification of patient risk for survival outcomes and predicted 1-year survival in stage IVB NSCLC. [ABSTRACT FROM AUTHOR]

Background: Radiotherapy plays a fundamental role in the treatment of patients with all stages of non‐small‐cell lung cancer (NSCLC). The emergence of immune checkpoint inhibitors (ICIs) has transformed the standard of care in these patients. The use of ICIs is increasingly utilized in the definitive setting as an adjunct to chemoradiotherapy or surgery and remains a vital component in the treatment of metastatic disease. Despite improvements in patient survival, the use of immunotherapy as monotherapy has shown limited overall response rates with susceptibility to resistance. Radiotherapy has been identified as a viable option to enhance the response rate to ICI and improve outcomes in NSCLC. Methods: We queried the English PubMed database utilizing variably combined search items including "radiation," "chemoradiation," "immune checkpoint," "immunotherapy," "stereotactic body radiotherapy," and "non‐small‐cell lung". We additionally searched various acceptable alternative terms for similar keywords such as "radiotherapy" in place of "radiation." These results were subsequently curated for relevance and impact on current treatment paradigms. Results: In this review, we discuss preclinical and clinical studies relating to combinatorial use of immunotherapy and radiation in NSCLC. These studies are presented in the context of early‐stage, operable stage III, unresectable stage III, and metastatic disease. The majority of the data illustrate promising results regarding the additive or synergistic effects of radiation and immunotherapy with a suggestion that the timing of these treatment modalities is crucial to optimizing outcomes. Conclusion: While there is now evidence regarding the favorable interplay between radiation and immunotherapy in NSCLC, there remain multiple unanswered questions which are expected to be addressed in ongoing clinical trials. [ABSTRACT FROM AUTHOR]

Context Rural-urban disparities have been reported in cancer care, but data are sparse on the effect of geography and location of residence on access to care in thyroid cancer. Objective To identify impact of rural or urban residence and distance from treatment center on thyroid cancer stage at diagnosis. Methods We evaluated 800 adults with differentiated thyroid cancer in the iCaRe2 bioinformatics/biospecimen registry at the Fred and Pamela Buffett Cancer Center. Participants were categorized into early and late stage using AJCC staging, and residence/distance from treating facility was categorized as short (≤ 12.5 miles), intermediate (> 12.5 to < 50 miles) or long (≥ 50 miles). Multivariable logistic regression was used to identify factors associated with late-stage diagnosis. Results Overall, 71% lived in an urban area and 29% lived in a rural area. Distance from home to the treating facility was short for 224 (28%), intermediate for 231 (28.8%), and long for 345 (43.1%). All 224 (100%) short, 226 (97.8%) intermediate, and 120 (34.7%) long distances were for urban patients; in contrast, among rural patients, 5 (2.16%) lived intermediate and 225 (65.2%) lived long distances from treatment (P <.0001). Using eighth edition AJCC staging, the odds ratio of late stage at diagnosis for rural participants ≥ 55 years was 2.56 (95% CI, 1.08-6.14) (P =.03), and for those living ≥ 50 miles was 4.65 (95% CI, 1.28-16.93) (P =.0075). Results were similar using seventh edition AJCC staging. Conclusion Older age at diagnosis, living in rural areas, and residing farther from the treatment center are all independently associated with late stage at diagnosis of thyroid cancer. [ABSTRACT FROM AUTHOR]