Individuals Eligible for Lung Cancer Screening Less Likely to Receive Screening When Enrolled in Health Plans With Deductibles.

BACKGROUND: In 2015, the Centers for Medicare & Medicaid Services and commercial insurance plans began covering lung cancer screening (LCS) without patient cost-sharing for all plans. We explore the impact of enrolling into a deductible plan on the utilization of LCS services despite having no out-of-pocket cost requirement. METHODS: This retrospective study analyzed data from the Population-based Research to Optimize the Screening Process Lung Consortium. Our cohort included non-Medicare LCS-eligible individuals enrolled in managed care organizations between February 5, 2015, and February 28, 2019. We estimate a series of sequential logistic regression models examining utilization across the sequence of events required for baseline LCS. We report the marginal effects of enrollment into deductible plans compared with enrollment in no-deductible plans. RESULTS: The total effect of deductible plan enrollment was a 1.8 percentage-point (PP) decrease in baseline LCS. Sequential logistic regression results that explore each transition separately indicate deductible plan enrollment was associated with a 4.3 PP decrease in receipt of clinician visit, a 1.7 PP decrease in receipt of LCS order, and a 7.0 PP decrease in receipt of baseline LCS. Reductions persisted across all observable races and ethnicities. CONCLUSIONS: These findings suggest individuals enrolled in deductible plans are more likely to forgo preventive LCS services despite requiring no out-of-pocket costs. This result may indicate that increased cost-sharing is associated with suboptimal choices to forgo recommended LCS. Alternatively, this effect may indicate individuals enrolling into deductible plans prefer less health care utilization. Patient outreach interventions at the health plan level may improve LCS.

Patterns of Medical Care Cost by Service Type for Patients With Recurrent and De Novo Advanced Cancer.

OBJECTIVES: There is limited knowledge about the cost patterns of patients who receive a diagnosis of de novo and recurrent advanced cancers in the United States. METHODS: Data on patients who received a diagnosis of de novo stage IV or recurrent breast, colorectal, or lung cancer between 2000 and 2012 from 3 integrated health systems were used to estimate average annual costs for total, ambulatory, inpatient, medication, and other services during (1) 12 months preceding de novo or recurrent diagnosis (preindex) and (2) diagnosis month through 11 months after (postindex), from the payer perspective. Generalized linear regression models estimated costs adjusting for patient and clinical factors. RESULTS: Patients who developed a recurrence <1 year after their initial cancer diagnosis had significantly higher total costs in the preindex period than those with recurrence ≥1 year after initial diagnosis and those with de novo stage IV disease across all cancers (all P < .05). Patients with de novo stage IV breast and colorectal cancer had significantly higher total costs in the postindex period than patients with cancer recurrent in <1 year and ≥1 year (all P < .05), respectively. Patients in de novo stage IV and those with recurrence in ≥1 year experienced significantly higher postindex costs than the preindex period (all P < .001). CONCLUSIONS: Our findings reveal distinct cost patterns between patients with de novo stage IV, recurrent <1-year, and recurrent ≥1-year cancer, suggesting unique care trajectories that may influence resource use and planning. Future cost studies among patients with advanced cancer should account for de novo versus recurrent diagnoses and timing of recurrence to obtain estimates that accurately reflect these care pattern complexities.

Real-world Clinical Implementation of Lung Cancer Screening-Evaluating Processes to Improve Screening Guidelines-Concordance.

BACKGROUND: Lung cancer screening (LCS) requires complex processes to identify eligible patients, provide appropriate follow-up, and manage findings. It is unclear whether LCS in real-world clinical settings will realize the same benefits as the National Lung Screening Trial (NLST). OBJECTIVE: To evaluate the impact of process modifications on compliance with LCS guidelines during LCS program implementation, and to compare patient characteristics and outcomes with those in NLST. DESIGN: Retrospective cohort study. SETTING: Kaiser Permanente Colorado (KPCO), a non-profit integrated healthcare system. PATIENTS: A total of 3375 patients who underwent a baseline lung cancer screening low-dose computed tomography (S-LDCT) scan between May 2014 and June 2017. MEASUREMENTS: Among those receiving an S-LDCT, proportion who met guidelines-based LCS eligibility criteria before and after LCS process modifications, differences in patient characteristics and outcomes between KPCO LCS patients and the NLST cohort, and factors associated with a positive screen. RESULTS: After modifying LCS eligibility confirmation processes, patients receiving S-LDCT who met guidelines-based LCS eligibility criteria increased from 45.6 to 92.7% (P < 0.001). Prior to changes, patients were older (68 vs. 67 years; P = 0.001), less likely to be current smokers (51.3% vs. 52.5%; P < 0.001), and less likely to have a ≥ 30-pack-year smoking history (50.0% vs. 95.3%; P < 0.001). Compared with NLST participants, KPCO LCS patients were older (67 vs. 60 years; P < 0.001), more likely to currently smoke (52.3% vs. 48.1%; P < 0.001), and more likely to have pulmonary disease. Among those with a positive baseline S-LDCT, the lung cancer detection rate was higher at KPCO (9.4% vs. 3.8%; P < 0.001) and was positively associated with prior pulmonary disease. CONCLUSION: Adherence to LCS guidelines requires eligibility confirmation procedures. Among those with a positive baseline S-LDCT, comorbidity burden and lung cancer detection rates were notably higher than in NLST, suggesting that the study of long-term outcomes in patients undergoing LCS in real-world clinical settings is warranted.

Demographic differences in the utilization of clinical and direct-to-consumer genetic testing.

Genetic testing has increased over the last decade due to growth in the number of clinical and direct-to-consumer (DTC) tests. However, there is uncertainty about how increased DTC genetic testing affects disparities. Between November 2017 and February 2018, a nationwide electronic survey on experiences with genetic testing was conducted among adult Kaiser Permanente members. Logistic regression was used to calculate adjusted odds ratios and 95% confidence intervals comparing receipt of clinical and DTC genetic testing between groups by race and ethnicity. Invitations were sent to 57,331 members, and 10,369 surveys were completed. 22% of respondents had received genetic testing (17% DTC and 5% provider-ordered). Non-Hispanic Whites were more likely than other groups to have clinical genetic testing but were similar to Hispanics and non-Hispanic Blacks in rates of DTC genetic testing. Among those who received any health-related genetic test, 10% reported abnormal results. Of these, non-Hispanic Whites were more likely than other racial/ethnic groups to speak to a medical professional about abnormal results. Results suggest that racial/ethnic disparities in the use of clinical genetic services persist. Additional research is needed to identify lessons learned from DTC genetic testing that may increase equity in the use of clinical genetic services.

Long-Term Patterns of Oral Anticancer Agent Adoption, Duration, and Switching in Patients With CML.

BACKGROUND: Oral tyrosine kinase inhibitors (TKIs) have been the standard of care for chronic myeloid leukemia (CML) since 2001. However, few studies have evaluated changes in the treatment landscape of CML over time. This study assessed the long-term treatment patterns of oral anticancer therapies among patients with CML. METHODS: This retrospective cohort study included patients newly diagnosed with CML between January 1, 2000, and December 31, 2016, from 10 integrated healthcare systems. The proportion of patients treated with 5 FDA-approved oral TKI agents-bosutinib, dasatinib, imatinib, nilotinib, and ponatinib-in the 12 months after diagnosis were measured, overall and by year, between 2000 and 2017. We assessed the use of each oral agent through the fourth-line setting. Multivariable logistic regression estimated the odds of receiving any oral agent, adjusting for sociodemographic and clinical characteristics. RESULTS: Among 853 patients with CML, 81% received an oral agent between 2000 and 2017. Use of non-oral therapies decreased from 100% in 2000 to 5% in 2005, coinciding with imatinib uptake from 65% in 2001 to 98% in 2005. Approximately 28% of patients switched to a second-line agent, 9% switched to a third-line agent, and 2% switched to a fourth-line agent. Adjusted analysis showed that age at diagnosis, year of diagnosis, and comorbidity burden were statistically significantly associated with odds of receiving an oral agent. CONCLUSIONS: A dramatic shift was seen in CML treatments away from traditional, nonoral chemotherapy toward use of novel oral TKIs between 2000 and 2017. As the costs of oral anticancer agents reach new highs, studies assessing the long-term health and financial outcomes among patients with CML are warranted.

The association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) measures of treatment initiation and engagement for alcohol and other drug use disorders.

Background: Medical comorbidity may influence treatment initiation and engagement for alcohol and other drug (AOD) use disorders. We examined the association between medical comorbidity and Healthcare Effectiveness Data and Information Set (HEDIS) treatment initiation and engagement measures.Methods: We used electronic health record and insurance claims data from 7 US health care systems to identify patients with AOD use disorders between October 1, 2014, and August 15, 2015 (N = 86,565). Among patients identified with AOD use disorders in outpatient and emergency department (ED) settings, we examined how Charlson/Deyo comorbidity index scores and medical complications of AOD use were associated with treatment initiation. Among those who initiated treatment in inpatient and outpatient/ED settings, we also examined how comorbidity and AOD use-related medical complications were associated with treatment engagement. Analyses were conducted using generalized estimating equation logistic regression modeling.Results: Among patients identified as having an AOD diagnosis in outpatient and ED settings (n = 69,965), Charlson/Deyo comorbidity index scores of 2 or more were independently associated with reduced likelihood of initiation (risk ratio [RR] = 0.80, 95% confidence interval [CI] = 0.74, 0.86; reference score = 0), whereas prior-year diagnoses of cirrhosis (RR = 1.25, 95% CI = 1.12, 1.35) and pancreatic disease (RR = 1.34, 95% CI = 1.15, 1.56) were associated with greater likelihood of initiation. Among those who were identified in outpatient/ED settings and initiated, higher comorbidity scores were associated with lower likelihood of engagement (score 1: RR = 0.85, 95% CI = 0.76, 0.94; score 2+: RR = 0.61, 95% CI = 0.53, 0.71).Conclusion: Medical comorbidity was associated with lower likelihood of initiating or engaging in AOD treatment, but cirrhosis and pancreatic disease were associated with greater likelihood of initiation. Interventions to improve AOD treatment initiation and engagement for patients with comorbidities are needed, such as integrating medical and AOD treatment.

Risk of Breast Cancer With Long-Term Use of Calcium Channel Blockers or Angiotensin-Converting Enzyme Inhibitors Among Older Women.

Controversy exists about breast cancer risk associated with long-term use of calcium channel blockers (CCBs) or angiotensin-converting enzyme inhibitors (ACEis), respectively. Our objective in this study was to separately evaluate associations between duration of CCB or ACEi use and breast cancer in hypertensive women aged ≥55 years at 3 sites in the Kaiser Permanente health-care system (1997­2012). Exposures included CCB or ACEi use of 1­12 years' duration, determined from pharmacy dispensings. Outcomes included invasive lobular or ductal carcinoma. Statistical methods included discrete-time survival analyses. The cohort included 19,674 (17.9%) CCB users and 90,078 (82.1%) ACEi users. Two percent (n = 397) of CCB users and 1.9% (n = 1,733) of ACEi users developed breast cancer. Compared with 1­<2 years of use, in adjusted analysis, there was no association between CCB use for 2­<12 years and breast cancer: All 95% confidence intervals included 1. Increasing duration of ACEi use was associated with reduced breast cancer risk: Compared with 1­<2 years of use, the adjusted hazard ratio was 0.76 (95% confidence interval: 0.63, 0.92) for 5­<6 years of use and 0.63 (95% confidence interval: 0.43, 0.93) for 9­<10 years of use. We conclude that among older women with hypertension, long-term CCB use does not increase breast cancer risk and long-term treatment with ACEis may confer protection against breast cancer.

Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management.

INTRODUCTION: Recurrent cancer is common, costly, and lethal, yet we know little about it in community-based populations. Electronic health records and tumor registries contain vast amounts of data regarding community-based patients, but usually lack recurrence status. Existing algorithms that use structured data to detect recurrence have limitations. METHODS: We developed algorithms to detect the presence and timing of recurrence after definitive therapy for stages I-III lung and colorectal cancer using 2 data sources that contain a widely available type of structured data (claims or electronic health record encounters) linked to gold-standard recurrence status: Medicare claims linked to the Cancer Care Outcomes Research and Surveillance study, and the Cancer Research Network Virtual Data Warehouse linked to registry data. Twelve potential indicators of recurrence were used to develop separate models for each cancer in each data source. Detection models maximized area under the ROC curve (AUC); timing models minimized average absolute error. Algorithms were compared by cancer type/data source, and contrasted with an existing binary detection rule. RESULTS: Detection model AUCs (>0.92) exceeded existing prediction rules. Timing models yielded absolute prediction errors that were small relative to follow-up time (<15%). Similar covariates were included in all detection and timing algorithms, though differences by cancer type and dataset challenged efforts to create 1 common algorithm for all scenarios. CONCLUSIONS: Valid and reliable detection of recurrence using big data is feasible. These tools will enable extensive, novel research on quality, effectiveness, and outcomes for lung and colorectal cancer patients and those who develop recurrence.

Percentage Up to Date With Chest Computed Tomography Among Those Eligible for Lung Cancer Screening.

INTRODUCTION: Authors aimed to calculate the percentage up-to-date with testing in the context of lung cancer screening across 5 healthcare systems and evaluate differences according to patient and health system characteristics. METHODS: Lung cancer screening‒eligible individuals receiving care within the five systems in the Population-based Research to Optimize the Screening Process Lung consortium from October 1, 2018 to September 30, 2019 were included in analyses. Data collection was completed on June 15, 2021; final analyses were completed on April 1, 2022. Chest computed tomography scans and patient characteristics were obtained through electronic health records and used to calculate the percentage completing a chest computed tomography scan in the previous 12 months (considered up-to-date). The association of patient and healthcare system factors with being up-to-date was evaluated with adjusted prevalence ratios and 95% CIs using log-binomial regression models. RESULTS: There were 29,417 individuals eligible for lung cancer screening as of September 30, 2019; 8,333 (28.3%) were up-to-date with testing. Those aged 65-74 years (prevalence ratio=1.19; CI=1.15, 1.24, versus ages 55-64), those with chronic obstructive pulmonary disease (prevalence ratio=2.05; CI=1.98, 2.13), and those in higher SES census tracts (prevalence ratio=1.22; CI=1.16, 1.30, highest quintile versus lowest) were more likely to be up-to-date. Currently smoking (prevalence ratio=0.91; CI=0.88, 0.95), having a BMI ≥30 kg/m2 (prevalence ratio=0.83; CI=0.77, 0.88), identifying as Native Hawaiian or other Pacific Islander (prevalence ratio=0.79; CI=0.68, 0.92), and having a decentralized lung cancer screening program (prevalence ratio=0.77; CI=0.74, 0.80) were inversely associated with being up-to-date. CONCLUSIONS: The percentage up-to-date with testing among those eligible for lung cancer screening is well below up-to-date estimates for other types of cancer screening, and disparities in lung cancer screening participation remain.

Smoking status and the association between patient-level factors and survival among lung cancer patients.

BACKGROUND: Declines in the prevalence of cigarette smoking, advances in targeted therapies, and implementation of lung cancer screening have changed the clinical landscape for lung cancer. The proportion of lung cancer deaths is increasing in those who have never smoked cigarettes. To better understand contemporary patterns in survival among patients with lung cancer, a comprehensive evaluation of factors associated with survival, including differential associations by smoking status, is needed. METHODS: Patients diagnosed with lung cancer between January 1, 2010, and September 30, 2019, were identified. We estimated all-cause and lung cancer-specific median, 5-year, and multivariable restricted mean survival time (RMST) to identify demographic, socioeconomic, and clinical factors associated with survival, overall and stratified by smoking status (never, former, and current). RESULTS: Analyses included 6813 patients with lung cancer: 13.9% never smoked, 54.2% formerly smoked, and 31.9% currently smoked. All-cause RMST through 5 years for those who never, formerly, and currently smoked was 32.1, 25.9, and 23.3 months, respectively. Lung cancer-specific RMST was 36.3 months, 30.3 months, and 26.0 months, respectively. Across most models, female sex, younger age, higher socioeconomic measures, first-course surgery, histology, and body mass index were positively associated, and higher stage was inversely associated with survival. Relative to White patients, Black patients had increased survival among those who formerly smoked. CONCLUSIONS: We identify actionable factors associated with survival between those who never, formerly, and currently smoked cigarettes. These findings illuminate opportunities to address underlying mechanisms driving lung cancer progression, including use of first-course treatment, and enhanced implementation of tailored smoking cessation interventions for individuals diagnosed with cancer.

Uptake of novel systemic therapy: Real world patterns among adults with advanced non-small cell lung cancer.

INTRODUCTION/BACKGROUND: Systemic treatment for advanced non-small cell lung cancer (NSCLC) is shifting from platinum-based chemotherapy to immunotherapy and targeted therapies associated with improved survival in clinical trials. As new therapies are approved for use, examining variations in use for treating patients in community practice can generate additional evidence as to the magnitude of their benefit. PATIENTS AND METHODS: We identified 1,442 patients diagnosed with de novo stage IV NSCLC between 3/1/2012 and 12/31/2020. Patient characteristics and treatment patterns are described overall and by type of first- and second-line systemic therapy received. Prevalence ratios estimate the association of patient and tumor characteristics with receipt of first-line therapy. RESULTS: Within 180 days of diagnosis, 949 (66%) patients received first-line systemic therapy, increasing from 53% in 2012 to 71% in 2020 (p = 0.0004). The proportion of patients receiving first-line immunotherapy+/-chemotherapy (IMO) increased from 14%-66% (p<0.0001). Overall, 380 (26%) patients received both first- and second-line treatment, varying by year between 16%-36% (p = 0.18). The proportion of patients receiving second-line IMO increased from 13%-37% (p<0.0001). Older age and current smoking status were inversely associated with receipt of first-line therapy. Higher BMI, receipt of radiation, and diagnosis year were positively associated with receipt of first-line therapy. No association was found for race, ethnicity, or socioeconomic status. CONCLUSION: The proportion of advanced NSCLC patients receiving first- and second-line treatment increased over time, particularly for IMO treatments. Additional research is needed to better understand the impact of these therapies on patient outcomes, including short-term, long-term, and financial toxicities. MICROABSTRACT: Systemic treatment for non-small cell lung cancer (NSCLC) is shifting from platinum-based therapies to immunotherapy and targeted therapies. Using de novo stage IV NSCLC patients identified from 4 healthcare systems, we examine trends in systemic therapy. We saw an increase in the portion of patients receiving any systemic therapy and a sharp increase in the proportion of patients receiving immunotherapy.

Development of an Electronic Health Record-Based Algorithm for Predicting Lung Cancer Screening Eligibility in the Population-Based Research to Optimize the Screening Process Lung Research Consortium.

PURPOSE: Lung cancer screening (LCS) guidelines in the United States recommend LCS for those age 50-80 years with at least 20 pack-years smoking history who currently smoke or quit within the last 15 years. We tested the performance of simple smoking-related criteria derived from electronic health record (EHR) data and developed and tested the performance of a multivariable model in predicting LCS eligibility. METHODS: Analyses were completed within the Population-based Research to Optimize the Screening Process Lung Consortium (PROSPR-Lung). In our primary validity analyses, the reference standard LCS eligibility was based on self-reported smoking data collected via survey. Within one PROSPR-Lung health system, we used a training data set and penalized multivariable logistic regression using the Least Absolute Shrinkage and Selection Operator to select EHR-based variables into the prediction model including demographics, smoking history, diagnoses, and prescription medications. A separate test data set assessed model performance. We also conducted external validation analysis in a separate health system and reported AUC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy metrics associated with the Youden Index. RESULTS: There were 14,214 individuals with survey data to assess LCS eligibility in primary analyses. The overall performance for assigning LCS eligibility status as measured by the AUC values at the two health systems was 0.940 and 0.938. At the Youden Index cutoff value, performance metrics were as follows: accuracy, 0.855 and 0.895; sensitivity, 0.886 and 0.920; specificity, 0.896 and 0.850; PPV, 0.357 and 0.444; and NPV, 0.988 and 0.992. CONCLUSION: Our results suggest that health systems can use an EHR-derived multivariable prediction model to aid in the identification of those who may be eligible for LCS.

Application of team science best practices to the project management of a large, multi-site lung cancer screening research consortium.

Research is increasingly conducted through multi-institutional consortia, and best practices for establishing multi-site research collaborations must be employed to ensure efficient, effective, and productive translational research teams. In this manuscript, we describe how the Population-based Research to Optimize the Screening Process Lung Research Center (PROSPR-Lung) utilized evidence-based Science of Team Science (SciTS) best practices to establish the consortium's infrastructure and processes to promote translational research in lung cancer screening. We provide specific, actionable examples of how we: (1) developed and reinforced a shared mission, vision, and goals; (2) maintained a transparent and representative leadership structure; (3) employed strong research support systems; (4) provided efficient and effective data management; (5) promoted interdisciplinary conversations; and (6) built a culture of trust. We offer guidance for managing a multi-site research center and data repository that may be applied to a variety of settings. Finally, we detail specific project management tools and processes used to drive collaboration, efficiency, and scientific productivity.

Characteristics of patients with primary non-adherence to medications for hypertension, diabetes, and lipid disorders.

BACKGROUND: Information comparing characteristics of patients who do and do not pick up their prescriptions is sparse, in part because adherence measured using pharmacy claims databases does not include information on patients who never pick up their first prescription, that is, patients with primary non-adherence. Electronic health record medication order entry enhances the potential to identify patients with primary non-adherence, and in organizations with medication order entry and pharmacy information systems, orders can be linked to dispensings to identify primarily non-adherent patients. OBJECTIVE: This study aims to use database information from an integrated system to compare patient, prescriber, and payment characteristics of patients with primary non-adherence and patients with ongoing dispensings of newly initiated medications for hypertension, diabetes, and/or hyperlipidemia. DESIGN: This is a retrospective observational cohort study. PARTICIPANTS (OR PATIENTS OR SUBJECTS): Participants of this study include patients with a newly initiated order for an antihypertensive, antidiabetic, and/or antihyperlipidemic within an 18-month period. MAIN MEASURES: Proportion of patients with primary non-adherence overall and by therapeutic class subgroup. Multivariable logistic regression modeling was used to investigate characteristics associated with primary non-adherence relative to ongoing dispensings. KEY RESULTS: The proportion of primarily non-adherent patients varied by therapeutic class, including 7% of patients ordered an antihypertensive, 11% ordered an antidiabetic, 13% ordered an antihyperlipidemic, and 5% ordered medications from more than one of these therapeutic classes within the study period. Characteristics of patients with primary non-adherence varied across therapeutic classes, but these characteristics had poor ability to explain or predict primary non-adherence (models c-statistics = 0.61-0.63). CONCLUSIONS: Primary non-adherence varies by therapeutic class. Healthcare delivery systems should pursue linking medication orders with dispensings to identify primarily non-adherent patients. We encourage conduct of research to determine interventions successful at decreasing primary non-adherence, as characteristics available from databases provide little assistance in predicting primary non-adherence.

Community-based Lung Cancer Screening Results in Relation to Patient and Radiologist Characteristics: The PROSPR Consortium.

Rationale: Lung-RADS classification was developed to standardize reporting and management of lung cancer screening using low-dose computed tomographic (LDCT) imaging. Although variation in Lung-RADS distribution between healthcare systems has been reported, it is unclear if this is explained by patient characteristics, radiologist experience with lung cancer screening, or other factors. Objectives: Our objective was to determine if patient or radiologist factors are associated with Lung-RADS score. Methods: In the Population-based Research to Optimize the Screening Process (PROSPR) Lung consortium, we conducted a study of patients who received their first screening LDCT imaging at one of the five healthcare systems in the PROSPR Lung Research Center from May 1, 2014, through December 31, 2017. Data on LDCT scans, patient factors, and radiologist characteristics were obtained via electronic health records. LDCT scan findings were categorized using Lung-RADS (negative [1], benign [2], probably benign [3], or suspicious [4]). We used generalized estimating equations with a multinomial distribution to compare the odds of Lung-RADS 3, and separately Lung-RADS 4, versus Lung-RADS 1 or 2 and estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between Lung-RADS assignment and patient and radiologist characteristics. Results: Analyses included 8,556 patients; 24% were assigned Lung-RADS 1, 60% Lung-RADS 2, 10% Lung-RADS 3, and 5% Lung-RADS 4. Age was positively associated with Lung-RADS 3 (OR, 1.02; 95% CI, 1.01-1.03) and 4 (OR, 1.03; 95% CI, 1.01-1.05); chronic obstructive pulmonary disease (COPD) was positively associated with Lung-RADS 4 (OR, 1.78; 95% CI, 1.45-2.20); obesity was inversely associated with Lung-RADS 3 (OR, 0.70; 95% CI, 0.58-0.84) and 4 (OR, 0.58; 95% CI, 0.45-0.75). There was no association between sex, race, ethnicity, education, or smoking status and Lung-RADS assignment. Radiologist volume of interpreting screening LDCT scans, years in practice, and thoracic specialty were also not associated with Lung-RADS assignment. Conclusions: Healthcare systems that are comprised of patients with an older age distribution or higher levels of COPD will have a greater proportion of screening LDCT scans with Lung-RADS 3 or 4 findings and should plan for additional resources to support appropriate and timely management of noted positive findings.

Stage Migration and Lung Cancer Incidence After Initiation of Low-Dose Computed Tomography Screening.

INTRODUCTION: Despite evidence from clinical trials of favorable shifts in cancer stage and improvements in lung cancer-specific mortality, the effectiveness of lung cancer screening (LCS) in clinical practice has not been clearly revealed. METHODS: We performed a multicenter cohort study of patients diagnosed with a primary lung cancer between January 1, 2014, and September 30, 2019, at one of four U.S. health care systems. The primary outcome variables were cancer stage distribution and annual age-adjusted lung cancer incidence. The primary exposure variable was receipt of at least one low-dose computed tomography for LCS before cancer diagnosis. RESULTS: A total of 3678 individuals were diagnosed with an incident lung cancer during the study period; 404 (11%) of these patients were diagnosed after initiation of LCS. As screening volume increased, the proportion of patients diagnosed with lung cancer after LCS initiation also rose from 0% in the first quartile of 2014 to 20% in the third quartile of 2019. LCS did not result in a significant change in the overall incidence of lung cancer (average annual percentage change [AAPC]: -0.8 [95% confidence interval (CI): -4.7 to 3.2]) between 2014 and 2018. Stage-specific incidence rates increased for stage I cancer (AAPC = 8.0 [95% CI: 0.8-15.7]) and declined for stage IV disease (AAPC = -6.0 [95% CI: -11.2 to -0.5]). CONCLUSIONS: Implementation of LCS at four diverse health care systems has resulted in a favorable shift to a higher incidence of stage I cancer with an associated decline in stage IV disease. Overall lung cancer incidence did not increase, suggesting a limited impact of overdiagnosis.

Importance of including early nonadherence in estimations of medication adherence.

BACKGROUND: Many medication adherence metrics are based on refill rates determined from pharmacy claims databases. However, these methods do not incorporate assessment of nonadherence to new prescriptions when those prescriptions are never dispensed (primary nonadherence), or dispensed only once (early nonpersistence). As a result, published studies may overestimate adherence, but the extent of overestimation posed by not considering patients with primary nonadherence and early nonpersistence has not been assessed. OBJECTIVE: To estimate the magnitude of misestimation in adherence estimates that results from not including patients with primary nonadherence and early nonpersistence. METHODS: We conducted a retrospective cohort study of 15,417 patients enrolled in an integrated health care delivery system who were newly prescribed an antihypertensive, antidiabetic, or antihyperlipidemic medication. We linked prescription orders to medication dispensings. Based on dispensing and refill rates, we stratified patients into primary nonadherent, early nonpersistent, and ongoing dispensings groups. Adherence was estimated using the proportion of days covered (PDC). Standardized observation periods were applied across all groups. RESULTS: A total of 1142 (7.4%) patients were primarily nonadherent, 3356 (21.8%) demonstrated early nonpersistence, and 10,919 (70.8%) patients received ongoing dispensings, with a mean PDC of 84%. Not including primarily nonadherent and early nonpersistent patients in calculations resulted in adherence estimates overestimated by 9-18%. CONCLUSIONS: When medication adherence is estimated from pharmacy claims databases, adherence estimates are substantially inflated because primarily nonadherent and early nonpersistent patients are not included in the estimations. An implication of this incorrect estimation is potential distortion of the true relationship between medication adherence and clinical outcomes.

Evaluation of Population-Level Changes Associated With the 2021 US Preventive Services Task Force Lung Cancer Screening Recommendations in Community-Based Health Care Systems.

Importance: The US Preventive Services Task Force (USPSTF) released updated lung cancer screening recommendations in 2021, lowering the screening age from 55 to 50 years and smoking history from 30 to 20 pack-years. These changes are expected to expand screening access to women and racial and ethnic minority groups. Objective: To estimate the population-level changes associated with the 2021 USPSTF expansion of lung cancer screening eligibility by sex, race and ethnicity, sociodemographic factors, and comorbidities in 5 community-based health care systems. Design, Setting, and Participants: This cohort study analyzed data of patients who received care from any of 5 community-based health care systems (which are members of the Population-based Research to Optimize the Screening Process Lung Consortium, a collaboration that conducts research to better understand how to improve the cancer screening processes in community health care settings) from January 1, 2010, through September 30, 2019. Individuals who had complete smoking history and were engaged with the health care system for 12 or more continuous months were included. Those who had never smoked or who had unknown smoking history were excluded. Exposures: Electronic health record-derived age, sex, race and ethnicity, socioeconomic status (SES), comorbidities, and smoking history. Main Outcomes and Measures: Differences in the proportion of the newly eligible population by age, sex, race and ethnicity, Charlson Comorbidity Index, chronic obstructive pulmonary disease diagnosis, and SES as well as lung cancer diagnoses under the 2013 recommendations vs the expected cases under the 2021 recommendations were evaluated using χ2 tests. Results: As of September 2019, there were 341 163 individuals aged 50 to 80 years who currently or previously smoked. Among these, 34 528 had electronic health record data that captured pack-year and quit-date information and were eligible for lung cancer screening according to the 2013 USPSTF recommendations. The 2021 USPSTF recommendations expanded screening eligibility to 18 533 individuals, representing a 53.7% increase. Compared with the 2013 cohort, the newly eligible 2021 population included 5833 individuals (31.5%) aged 50 to 54 years, a larger proportion of women (52.0% [n = 9631]), and more racial or ethnic minority groups. The relative increases in the proportion of newly eligible individuals were 60.6% for Asian, Native Hawaiian, or Pacific Islander; 67.4% for Hispanic; 69.7% for non-Hispanic Black; and 49.0% for non-Hispanic White groups. The relative increase for women was 13.8% higher than for men (61.2% vs 47.4%), and those with a lower comorbidity burden and lower SES had higher relative increases (eg, 68.7% for a Charlson Comorbidity Index score of 0; 61.1% for lowest SES). The 2021 recommendations were associated with an estimated 30% increase in incident lung cancer diagnoses compared with the 2013 recommendations. Conclusions and Relevance: This cohort study suggests that, in diverse health care systems, adopting the 2021 USPSTF recommendations will increase the number of women, racial and ethnic minority groups, and individuals with lower SES who are eligible for lung cancer screening, thus helping to minimize the barriers to screening access for individuals with high risk for lung cancer.

Identifying and oversampling Hispanics by the Passel-Word surname list for enrollment in a web-based nutritional intervention.

OBJECTIVE: To describe the enrollment rates and characteristics of Hispanics and non-Hispanics from Kaiser Permanente Colorado invited to participate in a web-based intervention promoting increased fruit and vegetable consumption. DESIGN: Hispanics were identified by the Passel-Word Spanish surname list. Characteristics associated with the likelihood of enrollment overall and by ethnicity were examined by logistic regression. RESULTS: A total of 174 (6.1%) probable Hispanics and 340 probable non-Hispanics (11.8%) enrolled. Hispanics were 48% less likely to enroll than non-Hispanics, females were almost four times as likely to enroll as males, and those living in a census tract associated with higher income levels were 41% more likely to enroll than other income groups. Among Hispanics, females were 87% more likely to enroll than males and those living in a census tract associated with higher income levels were 62% more likely to enroll than other income groups. Among non-Hispanics, the odds for enrolling increased 14% for each decade increase of age, females were 43% more likely to enroll than males and those living in a census tract associated with higher income levels were 68% more likely to enroll than those in other income groups. CONCLUSION: Identifying Hispanics through surname for oversampling can be successful in terms of sampling yield and accuracy. However, our results suggest that Hispanics are less likely to enroll in a web-based nutritional intervention. Additional research is needed to identify methods of attracting more Hispanic subjects to these kinds of interventions.

Return of Research-Related Genetic Test Results and Genetic Discrimination Concerns: Facilitators and Barriers of Genetic Research Participation in Diverse Groups.

BACKGROUND: Most genetics studies lack the diversity necessary to ensure that all groups benefit from genetic research. OBJECTIVES: To explore facilitators and barriers to genetic research participation. METHODS: We conducted a survey on genetics in research and healthcare from November 15, 2017 to February 28, 2018 among adult Kaiser Permanente (KP) members who had been invited to participate in the KP biobank (KP Research Bank). We used logistic regression to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) comparing the willingness to participate in genetic research under different return of results scenarios and genetic discrimination concerns between groups, according to their demographic characteristics. RESULTS: A total of 57,331 KP members were invited to participate, and 10,369 completed the survey (18% response rate). Respondents were 65% female, 44% non-Hispanic White (NH White), 22% Asian/Native Hawaiian or other Pacific Islander (Asian/PI), 19% non-Hispanic Black (NH Black), and 16% Hispanic. Respondents willing to participate in genetic research ranged from 22% with no results returned to 87% if health-related genetic results were returned. We also found variation by race/ethnicity; when no results were to be returned, Asian/PIs, Hispanics, and NH Blacks were less likely to want to participate than NH Whites (p < 0.05). However, when results were returned, disparities in the willingness to participate disappeared for NH Blacks and Hispanics. Genetic discrimination concerns were more prevalent in Asian/PIs, Hispanics, and NH Blacks than in NH Whites (p < 0.05). CONCLUSIONS: Policies that prohibit the return of results and do not address genetic discrimination concerns may contribute to a greater underrepresentation of diverse groups in genetic research.