Artificial intelligence in cancer imaging: Clinical challenges and applications.

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk.

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

BACKGROUND: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated. METHODS: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways. RESULTS: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified. CONCLUSIONS: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby. PLAIN LANGUAGE SUMMARY: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Genome-wide association meta-analysis identifies pleiotropic risk loci for aerodigestive squamous cell cancers.

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes rel to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

Recurrence Patterns for Regionally Metastatic Melanoma Treated in the Era of Adjuvant Therapy: A Systematic Review and Meta-Analysis.

BACKGROUND: The purpose of this systematic review was to examine the timing and patterns of recurrence for patients with regionally metastatic melanoma on the basis of nodal management and receipt of adjuvant therapy. METHODS: We identified randomized controlled trials and non-randomized studies published between 2010 and 2020 that reported timing and/or patterns of recurrence. We evaluated recurrence-free survival (RFS), location of recurrence, and surveillance strategy on the basis of receipt of adjuvant systemic therapy and nodal management with observation versus completion dissection. We compared differences in patterns of recurrence across studies using RevMan. RFS was evaluated graphically using point estimates and confidence intervals. RESULTS: Among the 19 publications, there was wide variation in study populations, imaging surveillance regimens, and format of recurrence reporting. Patterns of disease recurrence did not differ between adjuvant and placebo/observation groups. A total of 11 studies reported RFS at variable time intervals, which ranged in adjuvant therapy groups (38-88% at 1 year, 29-67% at 2 years, 33-58% at 3 years, and 34-53% at 5 years) and placebo/observation groups (47-63% at 1 year, 39-47% at 2 years, 33-68% at 3 years, and 57% at 5 years). Anti-PD-1 immune therapy and BRAF/MEK inhibitor therapy were superior to placebo at year 1. DISCUSSION: We found that adjuvant treatment improved RFS but did not alter the patterns of disease recurrence compared with patients managed without adjuvant systemic treatment. Future studies should separately report sites of disease recurrence on the basis of specific adjuvant systemic treatment and surveillance practices to better advise patients about their patterns and risk of recurrence.

Qualitative Findings From a Survey on Patient Experiences and Satisfaction with Lung Cancer Screening.

BACKGROUND: To reveal successes and potential limitations of the lung cancer screening program, we conducted a survey that included both quantitative and open-ended questions to measure patient experiences and satisfaction with screening. METHODS: We report on the five open-ended items related to barriers to returning for screening, experience with other cancer prevention screenings, positive and negative experiences, and suggestions for improving future appointments. The open-ended responses were analyzed using constant comparison method and inductive content analysis. RESULTS: Respondents (182 patients, 86% response rate for open-ended questions) provided generally positive comments about their lung cancer screening experience. Negative comments were related to desire for more information about results, long wait times for results, and billing issues. Suggestions for improvements included: scheduling on-line appointments and text or email reminders, lower costs, and responding to uncertainty about eligibility criteria. CONCLUSION: Findings provide insights about patient experiences and satisfaction with lung cancer screening which is important given low uptake. Ongoing patient-centered feedback may improve the lung cancer screening experience and increase follow-up screening rates.

Together-Equitable-Accessible-Meaningful (TEAM) Training to Improve Cancer Care for Sexual and Gender Minorities (SGM): Outcomes from a Pilot Study.

To alleviate health disparities experienced by sexual and gender minority (SGM) patients, cancer care professionals need further education on the needs of SGM cancer patients and their loved ones and caregivers. The Together-Equitable-Accessible-Meaningful (TEAM) Training to Improve Cancer Care for SGM Patients (TEAM SGM) was developed and piloted to address this need. This study reports healthcare professional learner outcomes from the TEAM SGM pilot intervention. The TEAM SGM Training pilot consisted of 2.5 h of content from the original online self-paced TEAM Training plus 12 1-h Zoom sessions on specialized topics in addition to readings and activities. Participants (n = 28), representing seven cancer service organizations from six states in the USA, were recruited through newsletter listservs and social media. All participants (n = 28) completed the pre-test and twenty-two participants completed the post-test. Using five factors confirmed in a separate Confirmatory Factor Analysis, paired t-tests of TEAM SGM participant pre- and post-test data were conducted. Statistically significant improvements were found in four of five factors: Environmental Cues (t(21) = 2.56, p = .018), Knowledge (t(21) = 2.15, p = .043), Clinical Preparedness (t(7) = 3.89, p = .006), Clinical Behaviors (t(21) = 2.48, p = .022). The Attitudes factor was not significantly improved from pre-intervention to post-intervention likely due to strong affirming attitudes toward SGM patients at baseline. TEAM SGM is a feasible, effective training to build capacity in SGM-affirming care for cancer care providers.

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer.

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1ß pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

NCCN Guidelines® Insights: Lung Cancer Screening, Version 1.2022.

The NCCN Guidelines for Lung Cancer Screening recommend criteria for selecting individuals for screening and provide recommendations for evaluation and follow-up of lung nodules found during initial and subsequent screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.

Cancer and lesbian, gay, bisexual, transgender/transsexual, and queer/questioning (LGBTQ) populations.

This article provides an overview of the current literature on seven cancer sites that may disproportionately affect lesbian, gay, bisexual, transgender/transsexual, and queer/questioning (LGBTQ) populations. For each cancer site, the authors present and discuss the descriptive statistics, primary prevention, secondary prevention and preclinical disease, tertiary prevention and late-stage disease, and clinical implications. Finally, an overview of psychosocial factors related to cancer survivorship is offered as well as strategies for improving access to care.

Integrated Biomarkers for the Management of Indeterminate Pulmonary Nodules.

Rationale: Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk prediction model that combined clinical, blood, and imaging biomarkers to improve the noninvasive management of IPNs. Methods: In this prospectively collected, retrospective blinded evaluation study, probability of cancer was calculated for 456 patient nodules using the Mayo Clinic model, and patients were categorized into low-, intermediate-, and high-risk groups. A combined biomarker model (CBM) including clinical variables, serum high sensitivity CYFRA 21-1 level, and a radiomic signature was trained in cohort 1 (n = 170) and validated in cohorts 2-4 (total n = 286). All patients were pooled to recalibrate the model for clinical implementation. The clinical utility of the CBM compared with current clinical care was evaluated in 2 cohorts. Measurements and Main Results: The CBM provided improved diagnostic accuracy over the Mayo Clinic model with an improvement in area under the curve of 0.124 (95% bootstrap confidence interval, 0.091-0.156; P < 2 × 10-16). Applying 10% and 70% risk thresholds resulted in a bias-corrected clinical reclassification index for cases and control subjects of 0.15 and 0.12, respectively. A clinical utility analysis of patient medical records estimated that a CBM-guided strategy would have reduced invasive procedures from 62.9% to 50.6% in the intermediate-risk benign population and shortened the median time to diagnosis of cancer from 60 to 21 days in intermediate-risk cancers. Conclusions: Integration of clinical, blood, and image biomarkers improves noninvasive diagnosis of patients with IPNs, potentially reducing the rate of unnecessary invasive procedures while shortening the time to diagnosis.

Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization.

At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR = 1.28, 95% CI = 1.06-1.55, PMVMR = .011), and an inverse effect on lung adenocarcinoma (ORMVMR = 0.86, 95% CI = 0.77-0.96, PMVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR = 1.19, 95% CI = 1.01-1.40, PUVMR = .036), but this effect disappeared after adjustment of smoking (ORMVMR = 1.02, 95% CI = 0.90-1.16, PMVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.

Radiomics predicts risk of cachexia in advanced NSCLC patients treated with immune checkpoint inhibitors.

BACKGROUND: Approximately 50% of cancer patients eventually develop a syndrome of prolonged weight loss (cachexia), which may contribute to primary resistance to immune checkpoint inhibitors (ICI). This study utilised radiomics analysis of 18F-FDG-PET/CT images to predict risk of cachexia that can be subsequently associated with clinical outcomes among advanced non-small cell lung cancer (NSCLC) patients treated with ICI. METHODS: Baseline (pre-therapy) PET/CT images and clinical data were retrospectively curated from 210 ICI-treated NSCLC patients from two institutions. A radiomics signature was developed to predict the cachexia with PET/CT images, which was further used to predict durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) following ICI. RESULTS: The radiomics signature predicted risk of cachexia with areas under receiver operating characteristics curves (AUCs) ≥ 0.74 in the training, test, and external test cohorts. Further, the radiomics signature could identify patients with DCB from ICI with AUCs≥0.66 in these three cohorts. PFS and OS were significantly shorter among patients with higher radiomics-based cachexia probability in all three cohorts, especially among those potentially immunotherapy sensitive patients with PD-L1-positive status (p < 0.05). CONCLUSIONS: PET/CT radiomics analysis has the potential to predict the probability of developing cachexia before the start of ICI, triggering aggressive monitoring to improve potential to achieve more clinical benefit.

Surveillance of Sentinel Node-Positive Melanoma Patients Who Receive Adjuvant Therapy Without Undergoing Completion Lymph Node Dissection.

INTRODUCTION: Adjuvant therapy trials required completion lymph node dissection (CLND) for sentinel lymph node (SLN)-positive melanoma prior to systemic treatment, but nodal surveillance without CLND is now common. For patients receiving adjuvant therapy without CLND, patterns of recurrence are unknown and the value of regional nodal ultrasound alongside cross-sectional imaging is not well-defined. METHODS: In a retrospective cohort of SLN-positive melanoma patients managed with nodal surveillance from June 2014 to June 2019, we evaluated the association between adjuvant treatment and location of first recurrence (locoregional, nodal, distant, or multisite) using Chi-square tests. We compared methods of recurrence detection and cost by surveillance intensity using Chi-square and Dunn's tests. RESULTS: Among 177 nodal surveillance patients, 66 (37%) received adjuvant therapy. Median follow-up was 24 months, during which 48 patients (27%) recurred. Adjuvant treatment did not alter patterns of initial recurrence (p = 0.76). Adjuvant therapy recipients more often had both nodal ultrasound and cross-sectional imaging surveillance (p < 0.01). Among 13 isolated nodal recurrences, 85% were within the first year and 85% were detected by examination and/or ultrasound. Increasing surveillance intensity was not associated with recurrence detection rates but increased overall cost and cost per detected recurrence. CONCLUSION: Regardless of adjuvant treatment, most nodal recurrences occurred in the first year and were initially detected clinically or by ultrasound. Findings support continued use of examination and nodal basin ultrasound in addition to any planned cross-sectional imaging surveillance.

Harmonized Outcome Measures for Use in Non-Small Cell Lung Cancer Patient Registries and Clinical Practice.

BACKGROUND: Lung cancer is the leading cause of cancer-related death in the United States and globally, and many questions exist about treatment options. Harmonizing data across registries and other data collection efforts would yield a robust data infrastructure to help address many research questions. The purpose of this project was to develop a minimum set of patient and clinician relevant harmonized outcome measures that can be collected in non-small cell lung cancer (NSCLC) patient registries and clinical practice. METHODS: Seventeen lung cancer registries and related efforts were identified and invited to submit outcome measures. Representatives from medical specialty societies, government agencies, health systems, health information technology groups, patient advocacy organizations, and industry formed a stakeholder panel to categorize the measures and harmonize definitions using the Agency for Healthcare Research and Quality's supported Outcome Measures Framework (OMF). RESULTS: The panel reviewed 66 outcome measures and identified a minimum set of 8 broadly relevant measures in the OMF categories of patient survival, clinical response, events of interest, and resource utilization. The panel harmonized definitions for the 8 measures through in-person and virtual meetings. The panel did not reach consensus on 1 specific validated instrument for capturing patient-reported outcomes. The minimum set of harmonized outcome measures is broadly relevant to clinicians and patients and feasible to capture across NSCLC disease stages and treatment pathways. A pilot test of these measures would be useful to document the burden and value of the measures for research and in clinical practice. CONCLUSIONS: By collecting the harmonized measures consistently, registries and other data collection systems could contribute to the development research infrastructure and learning health systems to support new research and improve patient outcomes.

Genome-wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk.

Genome-wide association studies (GWAS) have identified 45 susceptibility loci associated with lung cancer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant genetic polymorphisms in the human genome. INDELs are highly associated with multiple human diseases, including lung cancer. However, limited studies with large-scale samples have been available to systematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large-scale meta-analysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional annotations were performed to further explore the potential function of lung cancer risk INDELs. Conditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci were identified in genome-wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, p = 9.10 × 10-8 ; 4q28.2: rs58404727, Deletion, OR = 1.19, p = 5.25 × 10-7 ; 12p13.31: rs71450133, Deletion, OR = 1.09, p = 8.83 × 10-7 ; and 14q22.3: rs34057993, Deletion, OR = 0.90, p = 7.64 × 10-8 ). The eQTL analysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by regulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, the INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be potentially functional genetic variants for lung cancer risk. Further functional experiments are needed to better understand INDEL mechanisms in carcinogenesis.

Transcriptome-wide association study reveals candidate causal genes for lung cancer.

We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large-scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome-wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never- and ever-smokers). We performed replication analysis using lung data from the Genotype-Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever-smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E-99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E-6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E-5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.

Web-based LGBT cultural competency training intervention for oncologists: Pilot study results.

BACKGROUND: Lesbian, gay, bisexual, and transgender (LGBT) cancer patients experience substantial health disparities, including poorer overall health and lower satisfaction with their cancer care than their heterosexual and cisgender counterparts, which may be due in part to a lack of culturally competent providers. To address these disparities, a web-based LGBT cultural competency training tailored to oncologists was developed by an interdisciplinary team of scientists, LGBT cancer survivors, cultural competency experts, oncologists, a web designer, and an instructional designer. METHODS: Oncologists (n = 44) were recruited from 3 academic cancer centers in Florida. Participants were administered the LGBT cultural competency training Curriculum for Oncologists on LGBT populations to Optimize Relevance and Skills (COLORS) and completed pre- and posttraining measures regarding LGBT-related knowledge, attitudes (including general negative attitudes and health care-related attitudes), and clinical practices. After the training, participants completed training acceptability measures. RESULTS: Of the 44 participants, 33 (75%) completed the COLORS training. Participants were 55% non-Hispanic white, 63% male, and had a mean age of 47 years. Participants demonstrated significant improvements in LGBT-related knowledge (t = -4.9, P < .001), attitudes (Z = -3.0, P = .002; t = -2.5, P = .019), and clinical practices (Z = -3.5, P < .001) after completing the COLORS training (Wilcoxon signed rank tests were used for nonnormally distributed variables). Moreover, training acceptability was high, with 82% of participants rating the training as high quality, and 97% being willing to recommend the training to a colleague. CONCLUSION: The COLORS training is both feasible to administer and acceptable for use with oncologists, and may improve oncologists' LGBT-related knowledge, attitudes, and clinical practices. Larger trials are needed to examine the training's effectiveness in reducing LGBT cancer disparities, as well as its applicability to other types of care providers.

Radiomics of 18F-FDG PET/CT images predicts clinical benefit of advanced NSCLC patients to checkpoint blockade immunotherapy.

INTRODUCTION: Immunotherapy has improved outcomes for patients with non-small cell lung cancer (NSCLC), yet durable clinical benefit (DCB) is experienced in only a fraction of patients. Here, we test the hypothesis that radiomics features from baseline pretreatment 18F-FDG PET/CT scans can predict clinical outcomes of NSCLC patients treated with checkpoint blockade immunotherapy. METHODS: This study included 194 patients with histologically confirmed stage IIIB-IV NSCLC with pretreatment PET/CT images. Radiomics features were extracted from PET, CT, and PET+CT fusion images based on minimum Kullback-Leibler divergence (KLD) criteria. The radiomics features from 99 retrospective patients were used to train a multiparametric radiomics signature (mpRS) to predict DCB using an improved least absolute shrinkage and selection operator (LASSO) method, which was subsequently validated in both retrospective (N = 47) and prospective test cohorts (N = 48). Using these cohorts, the mpRS was also used to predict progression-free survival (PFS) and overall survival (OS) by training nomogram models using multivariable Cox regression analyses with additional clinical characteristics incorporated. RESULTS: The mpRS could predict patients who will receive DCB, with areas under receiver operating characteristic curves (AUCs) of 0.86 (95%CI 0.79-0.94), 0.83 (95%CI 0.71-0.94), and 0.81 (95%CI 0.68-0.92) in the training, retrospective test, and prospective test cohorts, respectively. In the same three cohorts, respectively, nomogram models achieved C-indices of 0.74 (95%CI 0.68-0.80), 0.74 (95%CI 0.66-0.82), and 0.77 (95%CI 0.69-0.84) to predict PFS and C-indices of 0.83 (95%CI 0.77-0.88), 0.83 (95%CI 0.71-0.94), and 0.80 (95%CI 0.69-0.91) to predict OS. CONCLUSION: PET/CT-based signature can be used prior to initiation of immunotherapy to identify NSCLC patients most likely to benefit from immunotherapy. As such, these data may be leveraged to improve more precise and individualized decision support in the treatment of patients with advanced NSCLC.

Novel Prognostic Models for Patients With Penile Carcinoma.

Although penile carcinoma is a rare malignancy, there is still an unmet need to identify prognostic factors associated with poor survival. In this study, we utilized demographic and clinical information to identify the most informative variables associated with overall survival in patients with penile cancer. From a full model including all covariates found to be statistically significant in univariable analyses, we identified a parsimonious reduced model containing tumor site (penis glans: hazard ratio [HR] = 0.48; 95% CI: 0.28-0.85 and penis not otherwise specified: HR = 0.45; 95% CI: 0.25-0.84), undetermined tumor differentiation (HR = 0.48; 95% CI: 0.27-0.86), and TNM stage III/IV (HR = 2.83; 95% CI: 1.68-4.75). When all of the covariates from the full model were subjected to classification and regression tree analysis, we identified 6 novel risk groups. Of particular interest, we found marriage was associated with substantial improvement in survival among men with the same stage and disease site. Specifically, among single/widowed/divorced men with TNM stage 0-II and prepuce/penis corpus/overlapping lesions had worse survival (5-year survival = 18.2%) versus married men (5-year survival = 62.5%). Since marital status is linked to social support, these findings warrant a deeper investigation into the relationships between disease prognosis and social support in patients with penile carcinoma.