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The question of anticoagulant dosing in hospitalized patients with coronavirus disease-2019 (COVID-19) is unresolved, with randomized trials showing mixed results and heterogeneity of treatment effects for in-hospital death.To examine the association between the intensity of anticoagulation and clinical outcomes in hospitalized patients with COVID-19.Retrospective cohort study of patients with COVID-19 and respiratory impairment who were hospitalized between 3/1/2020-12/31/2020 in two Kaiser Permanente regions.We fit propensity score models using categorical regression to estimate the probability of receiving standard prophylactic, intermediate, or full-dose anticoagulation beginning on the day of admission or on the day of first respiratory deterioration. Exposure was defined by the highest dose on the day of admission or within 24 hours after deterioration. The primary outcome was in-hospital death.We included 17,130 patients in the day of admission analysis and 4,924 patients who experienced respiratory deterioration. There were no differences in propensity score-adjusted odds of in-hospital death for patients who received either intermediate (odds ratio [OR]: 1.00, 95% confidence intervals [CI] 0.89-1.12) or full anticoagulation (OR: 1.00, 95% CI: 0.85-1.17) compared with standard prophylaxis beginning on the day of admission. Similarly, there were no differences in in-hospital death for either intermediate (OR: 1.22, 95% CI: 0.82-1.82) or full anticoagulation (OR: 1.50, 95% CI: 0.90-2.51) compared with standard prophylaxis on the day of deterioration.Results of this real-world, comparative effectiveness study showed no differences in in-hospital death among newly admitted or deteriorating patients with COVID-19 who received intermediate-dose or full anticoagulation compared with standard prophylaxis.

The Fleischner Society aims to limit further evaluations of incidentally detected pulmonary nodules when the probability of lung cancer is1% and to pursue further evaluations when the probability of lung cancer is ≥1%. To evaluate the internal consistency of guideline goals and recommendations, the authors evaluated stratum-specific recommendations and 2-year probabilities of lung cancer.A retrospective cohort study (2005-2015) was conducted of individuals enrolled in one of two integrated health systems with solid nodules incidentally detected on CT. The 2017 Fleischner Society guidelines were used to define strata on the basis of smoking status and nodule size and number. Lung cancer diagnoses within 2 years of nodule detection were ascertained using cancer registry data. Confidence interval (CI) inspection was used to determine if stratum-specific probabilities of lung cancer were different than 1%.Among 5,444 individuals with incidentally detected lung nodules (median age, 66 years; 54% women; 57% smoked; median nodule size, 5.5 mm; 55% with multiple nodules), 214 (3.9%; 95% CI, 3.4%-4.5%) were diagnosed with lung cancer within 2 years. For 7 of 12 strata (58%), 2,765 patients (51%), and 194 lung cancer cases (91%), there was alignment between Fleischner Society goals and recommendations. Alignment was indeterminate for 5 strata (42%), 2,679 patients (49%), and 20 lung cancer cases (9%) because CIs for the probability of lung cancer spanned 1%.Fleischner Society guideline goals and recommendations align at least half the time. It is uncertain whether alignment of guideline goals and recommendations occurs more often.

We sought to compare overall survival (OS) by comorbidity burden among patients with stage I/II non-small cell lung cancer (NSCLC) who received thoracoscopic resection. Utilizing data from the National Cancer Database, we conducted a survival analysis among patients aged 50+ with stage I/II NSCLC who received thoracoscopic resection between 2010 and 2017. The comorbidity burden was measured by the Charlson comorbidity index (CCI, 0, 1, 2+). Multivariable Cox proportional hazard models were used to compare overall survival relative to the CCI (CCI of 0 as the referent). Subgroup analyses were conducted considering sex, age groups, days from diagnosis to surgery, facility type, laterality, and type of surgery. For this study, 61,760 patients were included, with a mean age of 69.1 years (SD: 8.5). Notably, 51.2% had a CCI of 0, 31.8% had a CCI of 1, and 17.0% had a CCI of 2+. Most participants were non-Hispanic White (87.5%), and 56.9% were female. We found that an increase in the CCI was associated with a higher risk of all-cause mortality (CCI 1 vs. 0 aHR: 1.24, 95% CI: 1.20–1.28; CCI 2+ vs. 0 aHR: 1.51, 95% CI: 1.45–1.57; p-trend < 0.01). Our subgroup analysis according to sex suggested that the association between CCI and risk of death was stronger in women.

Background The frequency of cancer and accuracy of prediction models have not been studied in large, population-based samples of patients with incidental pulmonary nodules measuring > 8 mm in diameter. Research Questions How does the frequency of cancer vary by size and smoking history among patients with incidental nodules? How accurate are two widely used models for identifying cancer in these patients? Study Design and Methods We assembled a retrospective cohort of individuals with incidental nodules measuring > 8 mm in diameter identified by chest CT imaging between 2006 and 2016. We used a validated natural language processing algorithm to identify nodules and their characteristics by scanning the text of dictated radiology reports. We reported patient and nodule characteristics stratified by the presence or absence of a lung cancer diagnosis within 27 months of nodule identification and estimated the area under the receiver operating characteristic curve (AUC) to compare the accuracy of the Mayo Clinic and Brock models for identifying cancer. Results The sample included 23,780 individuals with a nodule measuring > 8 mm, including 2,356 patients (9.9%) with a lung cancer diagnosis within 27 months of nodule identification. Cancer was diagnosed in 5.4% of never smokers, 12.2% of former smokers, and 17.7% of current smokers. Cancer was diagnosed in 5.7% of patients with nodules measuring 9 to 15 mm, 12.1% of patients with nodules > 15 to 20 mm, and 18.4% of patients with nodules > 20 to 30 mm. In the full sample, the Mayo Clinic model (AUC, 0.747; 95% CI, 0.737-0.757) was more accurate than the Brock model (AUC, 0.713; 95% CI, 0.702-0.724; P Interpretation Almost 10% of patients with an incidental pulmonary nodule measuring > 8 mm in diameter will receive a lung cancer diagnosis. Existing prediction models have only fair accuracy and overestimate the probability of cancer.

Rationale: Most lung cancers are diagnosed at an advanced stage. Presymptomatic identification of high-risk individuals can prompt earlier intervention and improve long-term outcomes. Objectives: T...

Objective Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. Methods A retrospective cohort study of adult visits for suspected COVID-19 between March 1 – April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. Results 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880–0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874–0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759–0.801) and 0.832 (validation, 95% CI 0.794–0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843–0.892) and 0.837 (95% CI 0.774–0.899) respectively. Conclusion Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.

BACKGROUND: Interventions to support patients with complex needs have proliferated in recent years, but the question of how to identify patients with complex needs has received relatively little attention. There are innumerable ways to structure inclusion and exclusion criteria for complex care interventions, and little is known about the implications of choices made in designing patient selection criteria. OBJECTIVE: To provide insights into the design of patient selection criteria for interventions, by implementing criteria sets within a large health plan member population and comparing the characteristics of the resulting complex patient cohorts. DESIGN: Retrospective observational descriptive study. SUBJECTS: Patients identified as having complex needs, within the membership population of Kaiser Permanente Southern California, a large, population-based health plan with more than 4 million members. We characterize five commonly used archetypes of complex needs: high-cost patients, patients with multiple chronic conditions, frail elders, emergency department high-utilizers, and inpatient high-utilizers. MEASURES: We selected an initial set of criteria for identifying patients in each of the archetypical complex populations, based on available administrative data. We then tested multiple variants of each definition. We compared the resulting patient cohorts using univariate and bivariate descriptive statistics. KEY RESULTS: Overall, 32.7% of the 3,112,797 adults in our population-based sample were selected by at least one of the 25 definitions of complexity we tested. Across definitions the total number of patients identified as complex ranged from 622,560 to 1583 and complex patient cohorts varied widely in demographic characteristics, chronic conditions, healthcare utilization, spending, and survival. CONCLUSIONS: Choice of patient population is critical to the design of complex care programs. Exploratory analyses of population criteria can provide useful information for program planning in the setting of limited resources for interventions. Data such as these should be generated as a key step in program design. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-06815-4.

Interventions to support patients with complex needs are proliferating. However, little attention has been paid to methods for identifying complex patients. This study aims to summarize approaches used to define populations with complex needs in practice, by cataloging specific population criteria and organizing them into a taxonomy. The authors conducted a pragmatic review of literature published January 2000-December 2018 using PubMed. Search results were limited to English-language studies of adults that specified a set of objective criteria to identify a population with complex needs. The authors abstracted data from each article on population parameters, and conducted thematic analysis guided by deductive coding. The review identified 70 studies reflecting 90 unique complex population definitions. Complex populations criteria reflected 3 approaches: stratification, segmentation, and targeting. Six domains of population criteria were found within, including age-based criteria (59 populations); income (12); health care costs (45); health care utilization (39); health conditions (35); and subjective criteria (15). Criteria from multiple domains were frequently used in combination, and exact specifications were highly variable within each domain. Overall, 83% of the 90 population definitions included at least 1 cost- or utilization-based criterion. Nearly every study in the review presented a unique approach to identifying patients with complex needs but a limited number of "schools of thought" were found. Variability in definitions and inconsistent terminology are potential sources of ambiguity between stakeholders. Greater specificity and transparency in complex population definition would be a substantial contribution to the emerging field of complex care.

Background Multiple morbidity is the norm in advanced COPD and contributes to high symptom burden and worse outcomes. Research Question Can distinct comorbidity profiles be identified and validated in a community-based sample of patients with COPD from a large integrated health care system using a standard, commonly used diagnostic code-based comorbidity index and downstream 2-year health care use data? Study Design and Methods In this retrospective cohort study, we used latent class analysis (LCA) to identify comorbidity profiles in a population-based sample of 91,453 patients with a COPD diagnosis between 2011 and 2015. We included specific comorbid conditions from the Charlson Comorbidity Index (CCI) and accounted for variation in underlying prevalence of different comorbidities across the three study sites. Sociodemographic, clinical, and health-care use data were obtained from electronic health records (EHRs). Multivariate logistic regression analysis was used to compare rates of acute and postacute care use by class. Results The mean age was 71 ± 11 years, 55% of patients were women, 23% of patients were people of color, and 80% of patients were former or current smokers. LCA identified four distinct comorbidity profiles with progressively higher CCI scores: low morbidity (61%; 1.9 ± 1.4), metabolic renal (21%; 4.7 ± 1.8), cardiovascular (12%; 4.6 ± 1.9), and multimorbidity (7%; 7.5 ± 1.7). In multivariate models, during 2 years of follow-up, a significant, nonoverlapping increase was found in the odds of having any all-cause acute (hospitalizations, observation stays, and ED visits) and postacute care use across the comorbidity profiles. Interpretation Distinct comorbidity profiles can be identified in patients with COPD using standard EHR-based diagnostic codes, and these profiles are associated with subsequent acute and postacute care use. Population-based risk stratification schemes for end-to-end, comprehensive COPD management should consider integrating comorbidity profiles such as those found in this study.

Survivors of ICU hospitalizations often experience severe and debilitating symptoms long after critical illness has resolved. Many patients experience notable psychiatric sequelae such as depression, anxiety, and posttraumatic stress disorder (PTSD) that may persist for months to years after discharge. The COVID-19 pandemic has produced large numbers of critical illness survivors, warranting deeper understanding of psychological morbidity after COVID-19 critical illness. Many patients with critical illness caused by COVID-19 experience substantial post-ICU psychological sequelae mediated by specific pathophysiologic, iatrogenic, and situational risk factors. Existing and novel interventions focused on minimizing psychiatric morbidity need to be further investigated to improve critical care survivorship after COVID-19 illness. This review proposes a framework to conceptualize three domains of risk factors (pathophysiologic, iatrogenic, and situational) associated with psychological morbidity caused by COVID-19 critical illness: (1) direct and indirect effects of the COVID-19 virus in the brain; (2) iatrogenic complications of ICU care that may disproportionately affect patients with COVID-19; and (3) social isolation that may worsen psychological morbidity. In addition, we review current interventions to minimize psychological complications after critical illness.

IntroductionLung cancer is the leading cause of cancer death in the USA and worldwide, and lung cancer screening (LCS) with low-dose CT (LDCT) has the potential to improve lung cancer outcomes. A critical question is whether the ratio of potential benefits to harms found in prior LCS trials applies to an older and potentially sicker population. The Personalised Lung Cancer Screening (PLuS) study will help close this knowledge gap by leveraging real-world data to fully characterise LCS recipients. The principal goal of the PLuS study is to characterise the comorbidity burden of individuals undergoing LCS and quantify the benefits and harms of LCS to enable informed decision-making.Methods and analysisPLuS is a multicentre observational study designed to assemble an LCS cohort from the electronic health records of ~40 000 individuals undergoing annual LCS with LDCT from 2016 to 2022. Data will be integrated into a unified repository to (1) examine the burden of multimorbidity by race/ethnicity, socioeconomic status and age; (2) quantify potential benefits and harms; and (3) use the observational data with validated simulation models in the Cancer Intervention and Surveillance Modeling Network (CISNET) to provide LCS outcomes in the real-world US population. We will fit a multivariable logistic regression model to estimate the adjusted ORs of comorbidity, functional limitations and impaired pulmonary function adjusted for relevant covariates. We will also estimate the cumulative risk of LCS outcomes using discrete-time survival models. To our knowledge, this is the first study to combine observational data and simulation models to estimate the long-term impact of LCS with LDCT.Ethics and disseminationThe study was approved by the Kaiser Permanente Southern California Institutional Review Board and VA Portland Health Care System. The results will be disseminated through publications and presentations at national and international conferences. Safety considerations include protection of patient confidentiality.

BACKGROUND: The Pan-Canadian Early Detection of Lung Cancer (PanCan) risk model and the Lung CT Screening Reporting & Data System (Lung-RADS) estimate cancer probability for screening-detected nodules. The accuracy and agreement of these models require further study. RESEARCH QUESTION: What is the performance of the PanCan model and Lung-RADS to estimate the probability of cancer in screening-detected solid nodules? STUDY DESIGN AND METHODS: We analyzed data for newly identified, solid nodules detected on any screening round in the low-dose CT arm of the National Lung Screening Trial to assign a PanCan risk and Lung-RADS score. We compared PanCan risk with the corresponding Lung-RADS category according to the expected prevalence of cancer and examined accuracy using logistic regression and between-test agreement. We also analyzed baseline screen-detected nodules only, high (defined as ≥ 5% probability of cancer) vs low-risk nodules, “risk-gap” nodules with a 3% to 5% PanCan probability and no equivalent Lung-RADS category, and procedure use by model. RESULTS: Participants with solid nodules (6,956) had a calculable PanCan risk and Lung-RADS score. PanCan accuracy by cancer probabilities < 1%, 1% to 2%, 5% to 15%, and > 15% was similar to corresponding Lung-RADS categories 2, 3, 4A, and 4B for any solid nodule (area under the curve, 0.84 vs 0.84; P = .95) and for nodules identified at baseline (area under the curve, 0.85 vs 0.84; P = .17). When dichotomized by high/low risk, PanCan and Lung-RADS were discordant (P < .001). Participants with risk-gap nodules (n = 543) were distributed across Lung-RADS categories 2 through 4; 41 (8%) had invasive procedures with 23 (4%) having unnecessary invasive procedure use for solid, benign nodules. INTERPRETATION: PanCan and Lung-RADS had similar overall accuracy for assessing cancer in screening-detected, solid lung nodules with evidence of discordance by subgroup. The existence of Lung-RADS category 4 nodules with a ≥ 3% to 5% PanCan risk may result in unnecessary procedures.

Background Lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients, but most of those eligible are not referred for screening, and most eligible smokers are not aware of LCS. Smoking cessation counseling may be an opportune time to educate smokers about LCS. Here we investigate the effect of LCS educational information on LDCT utilization and smoking cessation in LCS-eligible patients receiving smoking cessation counseling. Patients and Methods We randomized 1281 smokers aged 55-80 who underwent smoking cessation services to view a web-based educational video about LCS (n = 1026) or to receive usual care (n = 255). Outcomes included the utilization of chest computed tomographic (CT) scan during 6 months of follow-up, responses to survey questions, and patient-reported abstinence from smoking at 6 months. Results One hundred forty-six participants (14%) watched the video. Overall, 87 participants (8.5%) in the intervention group underwent any chest CT and 37 (3.6%) underwent LDCT compared to 22 (8.6%) and 11 (4.3%) in the control group during the 6-month follow-up period (P = .94 and .59, respectively). Among participants who completed watching the video, 27 (18.5%) underwent any chest CT and 13 (8.9%) underwent LDCT, compared to 22 (8.6%) and 11 (4.3%) in controls during follow-up (P = .0037 and .062, respectively). There was no difference in abstinence from smoking between groups. Conclusion An LCS educational intervention may be effective in improving utilization of LDCT in eligible individuals who currently smoke at the time of smoking cessation counseling. Further research on the effect of LCS education in the context of smoking cessation counseling is needed.

While passive enrollment or "opt-out" recruitment methods facilitate pragmatic clinical trials, they pose unique challenges, and it is unclear how participants feel about them. Here, we describe patient responses to passive enrollment into the Watch the Spot Trial, a pragmatic trial comparing two sets of guidelines for small lung nodule follow-up.For this nested qualitative study, we analyzed participant-initiated calls and emails. We performed a qualitative content analysis, using a team-coding approach to identify reasons that eligible participants contacted the study team. We calculated the proportion of contacts containing each code, and how often each code coincided with study opt-outs and other codes.Of 23,412 eligible participants across seven sites, 1494 (6.4%) contacted the study team, with 1560 total contacts. Among the total contacts, the most common codes (i.e., reasons for contacting the team) were study opt-outs (n = 614, 39.0%), clarification of study procedures (n = 328, 21.0%), and unawareness of the nodule prior to research notification (n = 244, 15.6%). The least common codes were concerns about sharing of protected health information with the study team (n = 22, 1.4%) or outside of the healthcare system (n = 26, 1.7%), and disapproval of the opt-out approach (n = 10, 0.6%); most patients with these concerns opted-out. Nodule unawareness sometimes coincided with anger (n = 24) or distress (n = 15), and questions about nodule care sometimes coincided with distress (n = 20) and questions about follow-up surveys (n = 26).Most participants did not report concerns about passive enrollment. Patient perspectives are an invaluable resource for minimizing risks and inconveniences of future pragmatic trials using this recruitment method.

Highlights • Targeted anti-cytokine agents, tocilizumab and anakinra, used to treat COVID-19 related cytokine storm yield mixed results. • Early identification of cytokine storm using laboratory abnormalities can detect patients prior to mechanical ventilation. • Early identification and treatment of cytokine storm with anakinra and corticosteroids led to improved outcomes compared to initiating tocilizumab shortly after mechanical ventilation. • Early identification and treatment of cytokine storm may be more important than which anti-inflammatory treatment is chosen. • Our results provide additional support for the use of corticosteroid treatment of COVID19 cytokine storm., Objective To examine outcomes among patients who were treated with the targeted anti-cytokine agents, anakinra or tocilizumab, for COVID-19 -related cytokine storm (COVID19-CS). Methods We conducted a retrospective cohort study of all SARS-coV2-RNA-positive patients treated with tocilizumab or anakinra in Kaiser Permanente Southern California. Local experts developed and implemented criteria to define COVID19-CS. All variables were extracted from the electronic health record. Results At tocilizumab initiation (n = 52), 50 (96.2%) were intubated, and only 7 (13.5%) received concomitant corticosteroids. At anakinra initiation (n = 41), 23 (56.1%) were intubated, and all received concomitant corticosteroids. Fewer anakinra-treated patients died (n = 9, 22%) and more were extubated/never intubated (n = 26, 63.4%) compared to tocilizumab-treated patients (n = 24, 46.2% dead, n = 22, 42.3% extubated/never intubated). Patients who died had more severe sepsis and respiratory failure and met COVID-CS laboratory criteria longer (median = 3 days) compared to those extubated/never intubated (median = 1 day). After accounting for differences in disease severity at treatment initiation, this apparent superiority of anakinra over tocilizumab was no longer statistically significant (propensity score-adjusted hazards ratio 0.46, 95% confidence interval 0.18–1.20). Conclusions Prompt identification and treatment of COVID19-CS prior to intubation may be more important than the specific type of anti-inflammatory treatment. Randomized controlled trials of targeted anti-cytokine treatments and corticosteroids should report duration of cytokine storm in addition to clinical severity at randomization.

Background The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. Methods An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. Results Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non–small-cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non–small-cell lung cancer. Conclusions There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.

There may be many predictors of venous thromboembolism (VTE) and bleeding in hospitalized medical patients, but until now, systematic reviews and assessments of the certainty of the evidence have not been published. We conducted a systematic review to identify prognostic factors for VTE and bleeding in hospitalized medical patients and searched Medline and EMBASE from inception through May 2018. We considered studies that identified potential prognostic factors for VTE and bleeding in hospitalized adult medical patients. Reviewers extracted data in duplicate and independently and assessed the certainty of the evidence using the Grading of Recommendations Assessment, Development, and Evaluation approach. Of 69 410 citations, we included 17 studies in our analysis: 14 that reported on VTE, and 3 that reported on bleeding. For VTE, moderate-certainty evidence showed a probable association with older age; elevated C-reactive protein (CRP), D-dimer, and fibrinogen levels; tachycardia; thrombocytosis; leukocytosis; fever; leg edema; lower Barthel Index (BI) score; immobility; paresis; previous history of VTE; thrombophilia; malignancy; critical illness; and infections. For bleeding, moderate-certainty evidence showed a probable association with older age, sex, anemia, obesity, low hemoglobin, gastroduodenal ulcers, rehospitalization, critical illness, thrombocytopenia, blood dyscrasias, hepatic disease, renal failure, antithrombotic medication, and presence of a central venous catheter. Elevated CRP, a lower BI, a history of malignancy, and elevated heart rate are not included in most VTE risk assessment models. This study informs risk prediction in the management of hospitalized medical patients for VTE and bleeding; it also informs guidelines for VTE prevention and future research.

Smoking burdens are greatest among underserved patients. Lung cancer screening (LCS) reduces mortality among individuals at risk for smoking-associated lung cancer. Although LCS programs must offer smoking cessation support, the interventions that best promote cessation among underserved patients in this setting are unknown. This stakeholder-engaged, pragmatic randomized clinical trial will compare the effectiveness of four interventions promoting smoking cessation among underserved patients referred for LCS. By using an additive study design, all four arms provide standard “ask–advise–refer” care. Arm 2 adds free or subsidized pharmacologic cessation aids, arm 3 adds financial incentives up to $600 for cessation, and arm 4 adds a mobile device–delivered episodic future thinking tool to promote attention to long-term health goals. We hypothesize that smoking abstinence rates will be higher with the addition of each intervention when compared with arm 1. We will enroll 3,200 adults with LCS orders at four U.S. health systems. Eligible patients include those who smoke at least one cigarette daily and self-identify as a member of an underserved group (i.e., is Black or Latinx, is a rural resident, completed a high school education or less, and/or has a household income

Background Randomized controlled trials (RCTs) have demonstrated a survival benefit for adjuvant platinum-based chemotherapy after resection of locoregional non-small cell lung cancer (NSCLC). The relative benefits and harms and optimal approach to treatment for NSCLC patients who have major comorbidities (chronic obstructive pulmonary disease [COPD], coronary artery disease [CAD], and congestive heart failure [CHF]) are unclear, however. Methods We used a simulation model to run in-silico comparative trials of adjuvant chemotherapy versus observation in locoregional NSCLC in patients with comorbidities. The model estimated quality-adjusted life years (QALYs) gained by each treatment strategy stratified by age, comorbidity, and stage. The model was parameterized using outcomes and quality-of-life data from RCTs and primary analyses from large cancer databases. Results Adjuvant chemotherapy was associated with clinically significant QALY gains for all patient age/stage combinations with COPD except for patients >80 years old with Stage IB and IIA cancers. For patients with CHF and Stage IB and IIA disease, adjuvant chemotherapy was not advantageous; in contrast, it was associated with QALY gains for more advanced stages for younger patients with CHF. For stages IIB and IIIA NSCLC, most patient groups benefited from adjuvant chemotherapy. However, In general, patients with multiple comorbidities benefited less from adjuvant chemotherapy than those with single comorbidities and women with comorbidities in older age categories benefited more from adjuvant chemotherapy than their male counterparts. Conclusions Older, multimorbid patients may derive QALY gains from adjuvant chemotherapy after NSCLC surgery. These results help extend existing clinical trial data to specific unstudied, high-risk populations and may reduce the uncertainty regarding adjuvant chemotherapy use in these patients.

Small pulmonary nodules are most often managed by surveillance imaging with computed tomography (CT) of the chest, but the optimal frequency and duration of surveillance are unknown. The Watch the Spot Trial is a multicenter, pragmatic, comparative-effectiveness trial with cluster randomization by hospital or health system that compares more- versus less-intensive strategies for active surveillance of small pulmonary nodules. The study plans to enroll approximately 35,200 patients with a small pulmonary nodule that is newly detected on chest CT imaging, either incidentally or by screening. Study protocols for more- and less-intensive surveillance were adapted from published guidelines. The primary outcome is the percentage of cancerous nodules that progress beyond American Joint Committee on Cancer seventh edition stage T1a. Secondary outcomes include patient-reported anxiety and emotional distress, nodule-related health care use, radiation exposure, and adherence with the assigned surveillance protocol. Distinctive aspects of the trial include: 1) the pragmatic integration of study procedures into existing clinical workflow; 2) the use of cluster randomization by hospital or health system; 3) the implementation and evaluation of a system-level intervention for protocol-based care; 4) the use of highly efficient, technology-enabled methods to identify and (passively) enroll participants; 5) reliance on data collected as part of routine clinical care, including data from electronic health records and state cancer registries; 6) linkage with state cancer registries for complete ascertainment of the primary study outcome; and 7) intensive engagement with a diverse group of patient and nonpatient stakeholders in the design and execution of the study.

36 Background: Risk-stratified survivorship care pathways are critical for meeting needs of cancer survivors and the oncology workforce. To support a clinical trial evaluating a survivorship model that transitions low-risk survivors to a primary care physician (PCP)-led survivorship clinic within an integrated healthcare system, we captured data on real-time clinical risk stratification of low-risk patients potentially eligible between 6 and 36 months after treatment cessation. Methods: After oncology stakeholder input, we developed a screening algorithm to identify low-risk breast and colorectal cancer (CRC) survivors from the electronic medical record based on data from pathology, treatment, and utilization records. The algorithm identified patients meeting study eligibility criteria: adult stage 0-IIb breast cancer or stage I-II CRC patients diagnosed with first primary cancer, excluding those with treatments indicative of high-risk or metastatic disease, ongoing ovarian suppression or trastuzumab treatment (breast), neoadjuvant chemotherapy (breast), or enrollment in other cancer clinical trials. Next, the treating oncologist was asked to confirm or deny patient eligibility based on low-risk criteria; if denied, ineligibility reason was requested. Characteristics and proportions of low-risk patients confirmed/denied eligibility and reasons for ineligibility are summarized. Results: 530 patients were identified and evaluated: 488 breast and 42 CRC. Mean age was 61 years (SD: 11.6, range 23-95); 96% female; 22% had stage 0 disease (breast only), 51% stage I, and 28% stage II. By cancer type, 390 breast patients were deemed eligible (80%); 31 CRC patients were eligible (74%). A greater proportion of Asian and Black patients were categorized eligible vs. ineligible (13% vs. 9%, and 25% vs.14%, respectively), and a smaller proportion of Hispanic and White were categorized eligible (26% vs. 33%, and 31% vs. 42%, respectively). Reasons for ineligibility included: suspicious for recurrence (6%), new primary disease (3%), complex case/condition (36%), patient preference (34%), and other/none (22%). “Complex case/condition” included reasons such as intolerance of chemotherapy, patient declined chemotherapy and/or endocrine treatment (breast), co-occurring hematology disorder; “other/none” included reasons such as current pregnancy Lynch syndrome, and no reason. Conclusions: Oncologists confirmed eligibility for 80% of algorithm-identified low-risk patients for referral to the PCP-led survivorship clinic. Of those ineligible, patient preference and complex case/condition were the most common reasons reported for ineligibility. Consensus-based risk algorithms supported by clinician review can quickly and effectively perform case identification of low-risk patients who may be appropriately transitioned to other settings for survivorship care.

BACKGROUND: Current lung cancer risk-based screening approaches use a single risk-threshold, disregard life-expectancy, and ignore past screening findings. We address these limitations with a comprehensive analytical framework, the individualizEd luNG cAncer screeninG dEcision (ENGAGE) tool, that aims to optimize lung cancer screening for U.S. ever-smokers under dynamic risk assessment by incorporating life expectancy and past screening findings over time. METHODS: ENGAGE employs a partially observable Markov decision process framework that integrates published risk prediction and disease progression models, to dynamically assess the trade-off between the expected health benefits and harms associated with screening. ENGAGE evaluates lung cancer risk annually and provides real-time screening eligibility that maximizes the expected quality-adjusted life-years (QALYs) of ever-smokers. We compare ENGAGE against the 2013 U.S. Preventive Services Task Force (USPSTF) lung cancer screening guideline and single-threshold risk-based screening paradigms. RESULTS: Compared to the 2013 USPSTF guidelines, ENGAGE expands screening coverage among ever-smokers (ENGAGE: 78%, USPSTF: 61%) while reducing the number of screening exams per person (ENGAGE:10.43, USPSTF:12.07, P

Rationale: Immune checkpoint inhibitors (ICIs) have revolutionized cancer care but are associated with unique adverse events, including potentially life-threatening pneumonitis. The diagnosis of ICI-pneumonitis is increasing; however, the biological mechanisms, clinical and radiologic features, and the diagnosis and management have not been well defined. Objectives: To summarize evidence, identify knowledge and research gaps, and prioritize topics and propose methods for future research on ICI-pneumonitis. Methods: A multidisciplinary group of international clinical researchers reviewed available data on ICI-pneumonitis to develop and refine research questions pertaining to ICI-pneumonitis. Results: This statement identifies gaps in knowledge and develops potential research questions to further expand knowledge regarding risk, biologic mechanisms, clinical and radiologic presentation, and management of ICI-pneumonitis. Conclusions: Gaps in knowledge of the basic biological mechanisms of ICI-pneumonitis, coupled with a precipitous increase in the use of ICIs alone or combined with other therapies, highlight the importance in triaging research priorities for ICI-pneumonitis.

Background Although lung cancer screening (LCS) with low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients, most of those eligible are not referred for screening. Tobacco cessation counseling may be an opportune time to educate people about LCS, but little is known about the utilization and perceptions of LCS among people undergoing tobacco cessation treatment. Materials and Methods We surveyed 185 current smokers, including 122 smokers between the ages of 55 and 80 years, who were attending a tobacco cessation class in a large integrated health care system regarding lung cancer risk perception and perceived benefits, harms, and barriers to LCS. We analyzed results according to whether participants had already undergone LCS and also whether they had undergone colorectal cancer screening. Results A minority (18.9%) of participants had undergone LCS, and no participant who had not undergone LCS was familiar with LCS. Perceived lung cancer risk was high, and screening was believed to be beneficial. Common barriers included being a current smoker (56.6%), worrying about test results (52.5%), lack of knowledge about the test (50.8%), absence of symptoms of lung cancer (40.2%), costs of the study (35.2%), and worrying about being blamed for having smoked (33.6%). Perceived risk and barriers to LDCT were similar among people who had or had not previously undergone colorectal cancer screening. Conclusions Utilization of LCS was low, and few smokers were aware of LDCT for LCS. A number of patient-related barriers to screening exist among smokers. Tobacco cessation counseling may be an opportune time to provide education regarding LCS with LDCT.

Background Low-dose CT scan reduces lung cancer mortality in high-risk patients fit to undergo surgical resection. Racial disparities in resection of lung cancer in nonscreening populations are well described. We describe surgical resection patterns of patients with early stage non-small cell lung cancer (NSCLC) in the National Lung Screening Trial (NLST) and examine whether racial disparities exist among blacks. Methods We identified all NLST participants with clinical stage I NSCLC. Covariates included demographics, smoking history, comorbidities, tumor characteristics, and timing of cancer detection. Using logistic regression, we assessed resection rates of blacks vs whites. Results Among 752 patients with clinical stage I disease, 692 patients (92%) underwent resection. Unadjusted surgical resection rates for white men, white women, black men, and black women were 92%, 91%, 61%, and 90%, respectively. In adjusted analyses, compared with white men, black men had a 28% lower risk (relative risk, 0.72; 95% CI, 0.50-0.99) of undergoing surgery; however, white women and black women underwent surgery at comparable rates as white men. The odds of undergoing limited resection instead of full resection were 70% greater in white women than white men (OR, 1.69; 95% CI, 1.08-2.65). Conclusions Our study shows that disparities in the surgical treatment of lung cancer persist, even among NLST participants who were considered fit to undergo thoracic surgery. As lung cancer screening disseminates into clinical practice, efforts targeting black men should be prioritized.

Background New cervical cancer screening guidelines recommend primary human papillomavirus (HPV) testing for women age 30–65 years. Healthcare organizations are preparing to de-implement the previous recommended strategies of Pap testing or co-testing (Pap plus HPV test) and substitute primary HPV testing. However, there may be significant challenges to the replacement of this entrenched clinical practice, even with an evidence-based substitution. We sought to identify stakeholder-perceived barriers and facilitators to this substitution within a large healthcare system, Kaiser Permanente Southern California. Methods We conducted semi-structured qualitative interviews with clinician, administrative, and patient stakeholders regarding (a) acceptability and feasibility of the planned substitution; (b) perceptions of barriers and facilitators, with an emphasis on those related to the de-implementation/implementation cycle of substitution; and (c) perceived readiness to change. Our interview guide was informed by the Consolidated Framework for Implementation Research (CFIR). Using a team coding approach, we developed an initial coding structure refined during iterative analysis; the data were subsequently organized thematically into domains, key themes, and sub-themes using thematic analysis, followed by framework analysis informed by CFIR. Results We conducted 23 interviews: 5 patient and 18 clinical/administrative. Clinicians perceived that patients feel more tests equals better care, and clinicians and patients expressed fear of missed cancers (“…it’ll be more challenging convincing the patient that only one test is…good enough to detect cancer.”). Patients perceived practice changes resulting in “less care” are driven by the desire to cut costs. In contrast, clinicians/administrators viewed changing from two tests to one as acceptable and a workflow efficiency (“…It’s very easy and half the work.”). Stakeholder-recommended strategies included focusing on the increased efficacy of primary HPV testing and developing clinician talking points incorporating national guidelines to assuage “cost-cutting” fears. Conclusions Substitution to replace an entrenched clinical practice is complex. Leveraging available facilitators is key to ease the process for clinical and administrative stakeholders—e.g., emphasizing the efficiency of going from two tests to one. Identifying and addressing clinician and patient fears regarding cost-cutting and perceived poorer quality of care is critical for substitution. Multicomponent and multilevel strategies for engagement and education will be required. Trial registration ClinicalTrials.gov, #NCT04371887

The frequency of cancer and accuracy of prediction models have not been studied in large, population-based samples of patients with incidental pulmonary nodules measuring8 mm in diameter.How does the frequency of cancer vary by size and smoking history among patients with incidental nodules? How accurate are two widely used models for identifying cancer in these patients?We assembled a retrospective cohort of individuals with incidental nodules measuring8 mm in diameter identified by chest CT imaging between 2006 and 2016. We used a validated natural language processing algorithm to identify nodules and their characteristics by scanning the text of dictated radiology reports. We reported patient and nodule characteristics stratified by the presence or absence of a lung cancer diagnosis within 27 months of nodule identification and estimated the area under the receiver operating characteristic curve (AUC) to compare the accuracy of the Mayo Clinic and Brock models for identifying cancer.The sample included 23,780 individuals with a nodule measuring8 mm, including 2,356 patients (9.9%) with a lung cancer diagnosis within 27 months of nodule identification. Cancer was diagnosed in 5.4% of never smokers, 12.2% of former smokers, and 17.7% of current smokers. Cancer was diagnosed in 5.7% of patients with nodules measuring 9 to 15 mm, 12.1% of patients with nodules15 to 20 mm, and 18.4% of patients with nodules20 to 30 mm. In the full sample, the Mayo Clinic model (AUC, 0.747; 95% CI, 0.737-0.757) was more accurate than the Brock model (AUC, 0.713; 95% CI, 0.702-0.724; P .0001). When restricted to ever smokers, the Mayo Clinic model was still more accurate. Both models overestimated the probability of cancer.Almost 10% of patients with an incidental pulmonary nodule measuring8 mm in diameter will receive a lung cancer diagnosis. Existing prediction models have only fair accuracy and overestimate the probability of cancer.

Background Previous reports suggest that the use of angiotensin‐converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) may upregulate angiotensin‐converting enzyme 2 receptors and increase severe acute respiratory syndrome coronavirus 2 infectivity. We evaluated the association between ACEI or ARB use and coronavirus disease 2019 (COVID‐19) infection among patients with hypertension. Methods and Results We identified patients with hypertension as of March 1, 2020 (index date) from Kaiser Permanente Southern California. Patients who received ACEIs, ARBs, calcium channel blockers, beta blockers, thiazide diuretics (TD), or no therapy were identified using outpatient pharmacy data covering the index date. Outcome of interest was a positive reverse transcription polymerase chain reaction test for COVID‐19 between March 1 and May 6, 2020. Patient sociodemographic and clinical characteristics were identified within 1 year preindex date. Among 824 650 patients with hypertension, 16 898 (2.0%) were tested for COVID‐19. Of those tested, 1794 (10.6%) had a positive result. Overall, exposure to ACEIs or ARBs was not statistically significantly associated with COVID‐19 infection after propensity score adjustment (odds ratio [OR], 1.06; 95% CI, 0.90–1.25) for ACEIs versus calcium channel blockers/beta blockers/TD; OR, 1.10; 95% CI, 0.91–1.31 for ARBs versus calcium channel blockers/beta blockers/TD). The associations between ACEI use and COVID‐19 infection varied in different age groups ( P ‐interaction=0.03). ACEI use was associated with lower odds of COVID‐19 among those aged ≥85 years (OR, 0.30; 95% CI, 0.12–0.77). Use of no antihypertensive medication was significantly associated with increased odds of COVID‐19 infection compared with calcium channel blockers/beta blockers/TD (OR, 1.32; 95% CI, 1.11–1.56). Conclusions Neither ACEI nor ARB use was associated with increased likelihood of COVID‐19 infection. Decreased odds of COVID‐19 infection among adults ≥85 years using ACEIs warrants further investigation.

Background There is an urgent need for population-based studies on managing patients with pulmonary nodules. Research Question Is it possible to identify pulmonary nodules and associated characteristics using an automated method? Study Design and Methods We revised and refined an existing natural language processing (NLP) algorithm to identify radiology transcripts with pulmonary nodules and greatly expanded its functionality to identify the characteristics of the largest nodule, when present, including size, lobe, laterality, attenuation, calcification, and edge. We compared NLP results with a reference standard of manual transcript review in a random test sample of 200 radiology transcripts. We applied the final automated method to a larger cohort of patients who underwent chest CT scan in an integrated health care system from 2006 to 2016, and described their demographic and clinical characteristics. Results In the test sample, the NLP algorithm had very high sensitivity (98.6%; 95% CI, 95.0%-99.8%) and specificity (100%; 95% CI, 93.9%-100%) for identifying pulmonary nodules. For attenuation, edge, and calcification, the NLP algorithm achieved similar accuracies, and it correctly identified the diameter of the largest nodule in 135 of 141 cases (95.7%; 95% CI, 91.0%-98.4%). In the larger cohort, the NLP found 217,771 reports with nodules among 717,304 chest CT reports (30.4%). From 2006 to 2016, the number of reports with nodules increased by 150%, and the mean size of the largest nodule gradually decreased from 11 to 8.9 mm. Radiologists documented the laterality and lobe (90%-95%) more often than the attenuation, calcification, and edge characteristics (11%-14%). Interpretation The NLP algorithm identified pulmonary nodules and associated characteristics with high accuracy. In our community practice settings, the documentation of nodule characteristics is incomplete. Our results call for better documentation of nodule findings. The NLP algorithm can be used in population-based studies to identify pulmonary nodules, avoiding labor-intensive chart review.