Quantifying the Value of Reduced Health Disparities: Low-Dose Computed Tomography Lung Cancer Screening of High-Risk Individuals Within the United States.

OBJECTIVE: This study aimed to measure the value of increasing lung cancer screening rates for high-risk individuals and its impact on health disparities. METHODS: The model estimated changes in health economic outcomes if low-dose computed tomography screening increased from current to 100% compliance, following clinical guidelines. Current low-dose computed tomography screening rates were estimated by income, education, and race, using 2017-2019 Behavioral Risk Factor Surveillance System data. The model contained a decision tree module to segment the population by screening outcomes and a Markov chain module to estimate cancer progression over time. Model parameters included information on survival, quality of life, and costs related to cancer diagnosis, treatment, and adverse events. Distributional cost-effectiveness analysis estimated the net monetary value from reduced health disparities-measured using quality-adjusted life expectancy-across income, education, and race groups. Outcomes were assessed over 30 years. RESULTS: Lung cancer screening eligibility using US Preventive Services Task Force guidelines was higher for individuals with income <$15 000 (47.2%) and without a high-school education (46.1%) than individuals with income >$50 000 (16.6%) and with a college degree (13.5%), respectively. Increasing lung cancer screening to 100% compliance was cost-effective ($64 654 per quality-adjusted life-year) and produced economic value by up to $560 per person ($182.1 billion for United States overall). Up to 32.2% of the value was due to reductions in health disparities. CONCLUSIONS: Significant value in increasing lung cancer screening rates derived from reducing health disparities. Policy makers and clinicians may not be appropriately prioritizing cancer screening if value from reducing health disparities is unconsidered.

Diagnostic outcomes of robotic-assisted bronchoscopy for pulmonary lesions in a real-world multicenter community setting.

BACKGROUND: Robot-assisted bronchoscopy (RAB) is among the newest bronchoscopic technologies, allowing improved visualization and access for small and hard-to-reach nodules. RAB studies have primarily been conducted at academic centers, limiting the generalizability of results to the broader real-world setting, while variability in diagnostic yield definitions has impaired the validity of cross-study comparisons. The objective of this study was to determine the diagnostic yield and sensitivity for malignancy of RAB in patients with pulmonary lesions in a community setting and explore the impact of different definitions on diagnostic yield estimates. METHODS: Data were collected retrospectively from medical records of patients ≥ 21 years who underwent bronchoscopy with the Monarch® Platform (Auris Health, Inc., Redwood City, CA) for biopsy of pulmonary lesions at three US community hospitals between January 2019 and March 2020. Diagnostic yield was calculated at the index RAB and using 12-month follow-up data. At index, all malignant and benign (specific and non-specific) diagnoses were considered diagnostic. After 12 months, benign non-specific cases were considered diagnostic only when follow-up data corroborated the benign result. An alternative definition at index classified benign non-specific results as non-diagnostic, while an alternative 12-month definition categorized index non-diagnostic cases as diagnostic if no malignancy was diagnosed during follow-up. RESULTS: The study included 264 patients. Median lesion size was 19.3 mm, 58.9% were peripherally located, and 30.1% had a bronchus sign. Samples were obtained via Monarch in 99.6% of patients. Pathology led to a malignant diagnosis in 115 patients (43.6%), a benign diagnosis in 110 (41.7%), and 39 (14.8%) non-diagnostic cases. Index diagnostic yield was 85.2% (95% CI: [80.9%, 89.5%]) and the 12-month diagnostic yield was 79.4% (95% CI: [74.4%, 84.3%]). Alternative definitions resulted in diagnostic yield estimates of 58.7% (95% CI: [52.8%, 64.7%]) at index and 89.0% (95% CI: [85.1%, 92.8%]) at 12 months. Sensitivity for malignancy was 79.3% (95% CI: [72.7%, 85.9%]) and cancer prevalence was 58.0% after 12 months. CONCLUSIONS: RAB demonstrated a high diagnostic yield in the largest study to date, despite representing a real-world community population with a relatively low prevalence of cancer. Alternative definitions had a considerable impact on diagnostic yield estimates.

Limited duration of antiarrhythmic drug use for newly diagnosed atrial fibrillation in a nationwide population under age 65.

INTRODUCTION: Antiarrhythmic drugs (AADs) are commonly used for the treatment of newly diagnosed symptomatic atrial fibrillation (AF), however initial AAD choice, duration of therapy, rates of discontinuation, and factors associated with a durable response to therapy are poorly understood. This study assesses the initial choice and duration of antiarrhythmic drug therapy in the first 2 years after diagnosis of AF in a younger, commercially insured population. METHODS: A large nationally representative sample of patients age 20-64 was studied using the IBM MarketScan Database. Patients who started an AAD within 90 days of AF diagnosis with continuous enrollment for 1-year pre-index diagnosis and 2 years post-index were included. A Cox proportional hazards model was used to determine factors associated with AAD discontinuation. RESULTS: Flecainide was used most frequently (26.8%), followed by amiodarone (22.5%), dronedarone (18.3%), sotalol (15.8%), and propafenone (14.0%), with other AADs used less frequently. Twenty-two percent of patients who started on an AAD underwent ablation within 2 years, with 79% discontinuing the AAD after ablation. Ablation was the strongest predictor of AAD discontinuation (hazard ratio [HR], 1.70; 95% confidence interval [CI]: 1.61-1.80), followed by the male gender (HR, 1.10; CI: 1.02-1.19). Older patients (HR, 0.76; CI: 0.72-0.80; reference age 18-49) and those with comorbidities, including cardiomyopathy (HR, 075; CI: 0.61-0.91), diabetes (HR, 0.83; CI: 0.75-0.91), and hypertension (HR, 0.87; CI: 0.81-0.94) were less likely to discontinue AADs. CONCLUSION: Only 31% of patients remained on the initial AAD at 2 years, with a mean duration of initial therapy 7.6 months before discontinuation.

Real-world outcomes of ventricular tachycardia catheter ablation with versus without intracardiac echocardiography.

INTRODUCTION: By providing real-time monitoring of catheter-tissue interface and for complications, intracardiac echocardiography (ICE) during catheter ablation for ventricular tachycardia (VT) may improve outcomes. To test this hypothesis, we compared 12-month readmission rates (all-cause, cardiovascular [CV]-related, and VT-related), repeat ablation, and complications among patients with VT with structural heart disease undergoing ablation with versus without ICE. METHODS AND RESULTS: Using the 2008-2017 IBM MarketScan Commercial and Medicare Supplemental databases, patients with a history of implantable cardioverter defibrillator/cardiac resynchronization therapy (ICD/CRT-D) who underwent VT ablation with and without ICE use were identified. Propensity matching was performed and regression analysis was used to compare outcomes. After matching, 1324 patients were identified (ICE: 662; non-ICE: 662). The rate of 12-month VT-related readmission (18.13% vs 22.51%; P < .05) and repeat VT ablation (14.35% vs 19.34%; P = .02) postindex discharge were lower among patients in the ICE group compared with the non-ICE group, with a 24% lower risk of 12-month VT-related readmission (odds ratio [OR], 0.76; 95% confidence interval [CI], 0.58-0.99) and a 30% lower risk of repeat ablation (OR, 0.70; 95% CI, 0.52-0.93) vs non-ICE group. The 12-month all-cause (44.56% vs 43.20%; P = .62) and CV-related readmissions (35.20% vs 32.93%; P = 0.38) and complication rates were not significantly different between the two groups. CONCLUSIONS: VT ablation using ICE was associated with a lower likelihood of 12-month VT-related readmission and repeat ablation compared with non-ICE patients.

Trends and predictors of early ablation for Atrial Fibrillation in a Nationwide population under age 65: a retrospective observational study.

BACKGROUND: Catheter ablation (CA) has emerged as an effective treatment for symptomatic atrial fibrillation (AF). However practice patterns and patient factors associated with referral for CA within the first 12 months after diagnosis are poorly characterized. This study examined overall procedural trends and factors predictive of catheter ablation for newly-diagnosed atrial fibrillation in a young, commercially-insured population. METHODS: A large nationally-representative sample of patients age 20 to 64 from years 2010 to 2016 was studied using the IBM MarketScan® Commercial Database. Patients were included with a new diagnosis of AF in the inpatient or outpatient setting with continuous enrollment for at least 1 year pre and post index visit. Patients were excluded if they had prior history of AF or had filled an anti-arrhythmic drug (AAD) in the pre-index period. RESULTS: Early CA increased from 5.0% in 2010 to 10.5% in 2016. Patients were less likely to undergo CA if they were located in the Northeast (OR: 0.80, CI: 0.73-0.88) or North Central (OR: 0.91, CI: 0.83-0.99) regions (compared with the West), had higher CHA2DS2-VASc scores, or had Charlson Comorbidity Index (CCI) score of 3 or greater (OR: 0.61; CI: 0.51-0.72). CONCLUSIONS: CA within 12 months for new-diagnosed AF increased significantly from 2010 to 2016, with most patients still trialed on an AAD prior to CA. Patients are less likely to be referred for early CA if they are located in the Northeast and North Central regions, have more comorbidities, or higher CHA2DS2-VASc scores.

Endovascular Stroke Therapy Trends From 2011 to 2017 Show Significant Improvement in Clinical and Economic Outcomes.

Background and Purpose- The purpose of this study was to evaluate trends in length of stay, discharge status, and costs among patients with acute ischemic stroke who underwent endovascular therapy (ET) between 2011 and 2017. Methods- Using a retrospective observational study design, acute ischemic stroke patients undergoing ET from 2011 to 2017 were identified in the Premier Healthcare Database. The Mann-Kendall trend test was performed to examine clinical and economic outcomes trends. Results- Among the 505 824 acute ischemic stroke patients, 11 811(2.3%) were treated with ET. Patients receiving ET had a significant increase in home discharge and a significant decrease in mortality (17.7% to 29.6%, P<0.01; 21.6% to 12.8%, P<0.01). There was a significant decline in length of stay from 11.7 days to 8.7 days ( P<0.01). Total index admission costs declined ≈17% from 2011 to 2017 ($50 516.5-$42 026.9, P<0.01). Conclusions- Clinical and economic indicators significantly improved for acute ischemic stroke patients undergoing ET from 2011 to 2017.

Using Machine Learning Applied to Real-World Healthcare Data for Predictive Analytics: An Applied Example in Bariatric Surgery.

OBJECTIVES: Laparoscopic metabolic surgery (MxS) can lead to remission of type 2 diabetes (T2D); however, treatment response to MxS can be heterogeneous. Here, we demonstrate an open-source predictive analytics platform that applies machine-learning techniques to a common data model; we develop and validate a predictive model of antihyperglycemic medication cessation (validated proxy for A1c control) in patients with treated T2D who underwent MxS. METHODS: We selected patients meeting the following criteria in 2 large US healthcare claims databases (Truven Health MarketScan Commercial [CCAE]; Optum Clinformatics [Optum]): underwent MxS between January 1, 2007, to October 1, 2013 (first = index); aged ≥18 years; continuous enrollment 180 days pre-index (baseline) to 730 days postindex; baseline T2D diagnosis and treatment. The outcome was no antihyperglycemic medication treatment from 365 to 730 days after MxS. A regularized logistic regression model was trained using the following candidate predictor categories measured at baseline: demographics, conditions, medications, measurements, and procedures. A 75% to 25% split of the CCAE group was used for model training and testing; the Optum group was used for external validation. RESULTS: 13 050 (CCAE) and 3477 (Optum) patients met the study inclusion criteria. Antihyperglycemic medication cessation rates were 72.9% (CCAE) and 70.8% (Optum). The model possessed good internal discriminative accuracy (area under the curve [AUC] = 0.778 [95% CI = 0.761-0.795] in CCAE test set N = 3527) and transportability (external AUC = 0.759 [95% CI = 0.741-0.777] in Optum N = 3477). CONCLUSION: The application of machine learning techniques to real-world healthcare data can yield useful predictive models to assist patient selection. In future practice, establishment of prerequisite technological infrastructure will be needed to implement such models for real-world decision support.

Resource use and clinical outcomes in patients with atrial fibrillation with ablation versus antiarrhythmic drug treatment.

BACKGROUND: The objective of our study was to compare resource use and clinical outcomes among atrial fibrillation (AF) patients who underwent catheter ablation versus antiarrhythmic drug (AAD) treatment. METHODS: A retrospective cohort design using the Clinical Practice Research Data-Hospital Episode Statistics linkage data from England (2008-2013) was used. Patients undergoing catheter ablation treatment for AF were indexed to the date of first procedure. AAD patients with at least two different AAD drugs were indexed to the first fill of the second AAD. Patients were matched using 1:1 propensity matching. Primary endpoints including inpatient and outpatient visits were compared between ablation and AAD cohorts in the 4 months-1 year period after index. Secondary endpoints including heart failure, stroke, cardioversion, mortality, and a composite outcome were compared for the 4 months-3 years post-index period in the two groups. Cox-proportional hazards models were estimated for clinical outcomes comparison. RESULTS: A total of 558 patients were matched in the two groups for resource utilization comparison. The average number of cardiovascular (CV)-related outpatient visits in the 4-12 months post-index period were significantly lower in the ablation group versus the AAD group (1.76 vs 3.57, p < .0001). There was no significant difference in all-cause and CV-related inpatient visits and all-cause outpatient visits among the two groups. For secondary endpoints comparison, 615 matched patients in each group emerged. Ablation patients had 38% lower risk of heart failure (hazard ratio [HR] 0.62, p = 0.0318), 50% lower risk of mortality (HR 0.50, p = 0.0082), and 43% lower risk of experiencing a composite outcome (HR 0.57, p = 0.0009) as compared to AAD treatment cohort. CONCLUSION: AF ablation was associated with significantly lower CV-related outpatient visits, and lower risk of heart failure and mortality versus AAD therapy.

Validation of body mass index (BMI)-related ICD-9-CM and ICD-10-CM administrative diagnosis codes recorded in US claims data.

PURPOSE: To quantify the sensitivity and positive predictive value (PPV) of body mass index (BMI)-related ICD-9-CM and ICD-10-CM diagnosis codes in claims data. METHODS: De-identified electronic health record (EHR) and claims data were obtained from the Optum Integrated Claims-Clinical Database for cross-sections of commercial and Medicare Advantage health plan members age ≥ 20 years in 2013, 2014, and 2016. In each calendar year, health plan members' BMI as coded in the insurance claims data (error-prone measure) was compared with their BMI as recorded in the EHR (gold standard) to estimate the sensitivity and PPV of BMI-related ICD-9-CM and ICD-10-CM diagnosis codes. The unit of analysis was the person-year. RESULTS: The study sample included 746 763 distinct health plan members who contributed 1 116 283 eligible person-years (median age 56 years; 57% female; 65% commercially insured and 35% with Medicare Advantage). BMI-related diagnoses were coded for 14.6%. The sensitivity of BMI-related diagnoses codes for the detection of underweight, normal weight, overweight, and obesity was 10.1%, 3.7%, 6.0%, and 25.2%, and the PPV was 49.0% for underweight, 89.6% for normal weight, 73.4% for overweight, and 92.4% for obesity, respectively. The sensitivity of BMI-related diagnosis codes was higher in the ICD-10-CM era relative to the ICD-9-CM era. CONCLUSIONS: The PPV of BMI-related diagnosis codes for normal weight, overweight, and obesity was high (>70%) but the sensitivity was low (<30%). BMI-related diagnoses were more likely to be coded in patients with class II or III obesity (BMI ≥35 kg/m2 ), and in 2016 relative to 2013 or 2014.

Breast Reconstruction Among Commercially Insured Women With Breast Cancer in the United States.

INTRODUCTION: This study evaluated trends related to breast reconstruction and the factors associated with reconstruction. METHODS: Women with breast cancer aged 19 to 64 years who underwent a mastectomy procedure between July 1, 2011, and September 30, 2014, were identified from the MarketScan Commercial Claims and Encounters Database. The first date of surgical procedure during this period was defined as the index date. Continuous enrollment during the 12-month preindex and postindex period was required, and the patient sample was followed for 12 months postindex. Multivariable regression analysis was used to determine factors associated with having breast reconstruction. RESULTS: Among the 17,502 women undergoing mastectomy during the study period, 73% (n = 12,816) had breast reconstruction, with 66% (n = 11,613) having immediate and 7% (n = 1203) having delayed reconstruction. Overall reconstruction rates increased during the study period from 69.47% in the third quarter of 2011 to 75.72% in the third quarter of 2014. The most common type of immediate reconstruction involved the use of tissue expanders (with or without implant and autologous reconstruction) (~77%), followed by implant reconstruction (9.67%), autologous reconstruction (10.81%), and other reconstruction (2.52%). Acellular dermal matrix was commonly used with immediate tissue expander and immediate implant-based reconstruction, and its use increased during the study period. Demographic and treatment-related factors were found to be associated with reconstruction among women undergoing mastectomy. CONCLUSIONS: In this commercial payor setting, most women undergoing mastectomy had breast reconstruction. Among women undergoing immediate reconstruction, tissue expander use was common. Several factors were shown to be associated with the decision to have breast reconstruction.

Medical costs and hospitalizations among patients with depression treated with adjunctive atypical antipsychotic therapy: an analysis of health insurance claims data.

BACKGROUND: Depression is frequently debilitating. The American Psychiatric Association recommends adjunctive atypical antipsychotics as a treatment option when response to antidepressants is inadequate. OBJECTIVE: To compare medical costs and hospitalizations among patients with depression treated with adjunctive aripiprazole, olanzapine, or quetiapine. METHODS: This retrospective analysis used medical and pharmacy claims data and enrollment information from a large US health plan. Patients were adult members of a commercial health plan who were diagnosed with depression (ie, ICD-9-CM 296.2x, 296.3x, or 311) and who received an antidepressant with adjunctive atypical antipsychotic therapy (aripiprazole, olanzapine, or quetiapine) between January 1, 2004, and January 31, 2010. Patients were continuously enrolled for 6-month pre- and 12-month postaugmentation periods. Those with schizophrenia or bipolar disorder were excluded. Postaugmentation outcomes were total and mental health-related medical costs and hospitalizations. Costs and hospitalizations were modeled with generalized linear models (ie, gamma distribution, log link) and logistic regression, respectively. Regressions controlled for dose, demographics, and general and medical health-related health status. RESULTS: A total of 10,292 patients were identified across atypical antipsychotic cohorts: 3849 used aripiprazole, 1033 used olanzapine, and 5410 used quetiapine. Mean (SD) age was 44.1 (11.6) years and 70.3% were female. Compared with patients in the aripiprazole cohort, those in the olanzapine cohort had higher total medical costs (cost ratio [CR] 1.22, 95% CI 1.07-1.39) and higher mental health-related medical costs (CR 1.33, 95% CI 1.11-1.59), as well as higher odds of any (total) hospitalization (OR 1.58, 95% CI 1.30-1.92) and any mental health-related hospitalization (OR 1.81, 95% CI 1.38-2.38). Similarly, the quetiapine cohort had higher total medical costs (CR 1.27, 95% CI 1.16-1.39) and higher mental health-related medical costs (CR 1.23, 95% CI 1.09-1.39), as well as higher odds of any (total) hospitalization (OR 1.65, 95% CI 1.44-1.90) and any mental health-related hospitalizations (OR 1.78, 95% CI 1.45-2.18), compared with the aripiprazole cohort. CONCLUSIONS: Compared with adjunctive olanzapine or quetiapine, adjunctive aripiprazole was associated with lower mean total and mental health-related medical costs and with lower odds of total and mental health-related hospitalizations in patients with depression.

Machine Learning and Real-World Data to Predict Lung Cancer Risk in Routine Care.

BACKGROUND: This study used machine learning to develop a 3-year lung cancer risk prediction model with large real-world data in a mostly younger population. METHODS: Over 4.7 million individuals, aged 45 to 65 years with no history of any cancer or lung cancer screening, diagnostic, or treatment procedures, with an outpatient visit in 2013 were identified in Optum's de-identified Electronic Health Record (EHR) dataset. A least absolute shrinkage and selection operator model was fit using all available data in the 365 days prior. Temporal validation was assessed with recent data. External validation was assessed with data from Mercy Health Systems EHR and Optum's de-identified Clinformatics Data Mart Database. Racial inequities in model discrimination were assessed with xAUCs. RESULTS: The model AUC was 0.76. Top predictors included age, smoking, race, ethnicity, and diagnosis of chronic obstructive pulmonary disease. The model identified a high-risk group with lung cancer incidence 9 times the average cohort incidence, representing 10% of patients with lung cancer. Model performed well temporally and externally, while performance was reduced for Asians and Hispanics. CONCLUSIONS: A high-dimensional model trained using big data identified a subset of patients with high lung cancer risk. The model demonstrated transportability to EHR and claims data, while underscoring the need to assess racial disparities when using machine learning methods. IMPACT: This internally and externally validated real-world data-based lung cancer prediction model is available on an open-source platform for broad sharing and application. Model integration into an EHR system could minimize physician burden by automating identification of high-risk patients.

The Effect of Definitions and Cancer Prevalence on Diagnostic Yield Estimates of Bronchoscopy: A Simulation-based Analysis.

Rationale: Studies of bronchoscopy have reported diagnostic yield (DY) using different calculation methods, which has hindered comparisons across studies. Objectives: To quantify the effect of the variability of four methods on DY estimates of bronchoscopy. Methods: We performed a simulation-based analysis of patients undergoing bronchoscopy using variations around base case assumptions for cancer prevalence (60%), distribution of nonmalignant findings, and degree of follow-up information at a fixed sensitivity of bronchoscopy for malignancy (80%). We calculated DY, the rate of true positives and true negatives (TNs), using four methods. Method 1 considered malignant and specific benign findings at index bronchoscopy as true positives and TNs, respectively. Method 2 included nonspecific benign findings as TNs. Method 3 considered nonspecific benign findings cases as TNs only if follow-up confirmed benign disease. Method 4 counted all cases with a nonmalignant diagnosis as TNs if follow-up confirmed benign disease. A scenario analysis and probabilistic sensitivity analysis were conducted to demonstrate the effect of parameter estimates on DY. A change in DY of >10% was considered clinically meaningful. Results: Across all pairwise comparisons of the four methods, a DY difference of >10% was observed in 76.7% of cases (45,992 of 60,000 comparisons). Method 4 resulted in DY estimates that were >10% higher than estimates made with other methods in >90% of scenarios. Variation in cancer prevalence had a large effect on DY. Conclusions: Across a wide range of clinical scenarios, the categorization of nonmalignant findings at index bronchoscopy and cancer prevalence had the largest impact on DY. The large variability in DY estimates across the four methods limits the interpretation of bronchoscopy studies and warrants standardization.

A Comparison of Microwave Ablation and Cryoablation for the Treatment of Renal Cell Carcinoma: A Systematic Literature Review and Meta-analysis.

OBJECTIVE: To conduct a systematic review and meta-analysis comparing microwave ablation (MWA) and cryoablation for renal cell carcinoma (RCC). METHODS: The systematic search was performed in MEDLINE, Embase, and Cochrane databases. Studies published in English from January 2006 to February 2022 that assessed adults with primary RCC who received MWA or cryoablation were included. Study arms from RCTs, comparative observational, and single-arm studies were eligible. The outcomes included local tumor recurrence (LTR), overall survival, disease-free survival, overall/major complications, procedure/ablation time, 1- to 3-month primary technique efficacy, and technical success. Single-arm meta-analyses were performed using the random effects model. Sensitivity analyses excluding low-quality studies assessed using the MINORs scale were performed. Univariable and multivariable examined the effects of prognostic factors. RESULTS: Baseline characteristics were similar between groups and mean tumor size for MWA and cryoablation were 2.74 and 2.69 cm. Single-arm meta-analyses were similar for LTR and secondary outcomes between cryoablation and MWA. Ablation time was significantly shorter with MWA than with cryoablation (meta-regression weighted mean difference 24.55 minutes, 95% confidence interval -31.71, -17.38, P < .0001). One-year LTR was significantly lower with MWA than cryoablation (odds ratio 0.33, 95% confidence interval 0.10-0.93, P = .04). There were no significant differences for other outcomes. CONCLUSION: MWA provides significantly improved 1-year LTR and ablation time compared with cryoablation for patients with RCC. Other outcomes appeared similar or favorable for MWA; however, results were not statistically significant. MWA of primary RCC is as safe and effective as cryoablation, which should be confirmed with future comparative studies.

Recurrence-Free Survival in Patients With Surgically Resected Non-Small Cell Lung Cancer: A Systematic Literature Review and Meta-Analysis.

BACKGROUND: Standard treatment for early-stage or locoregionally advanced non-small cell lung cancer (NSCLC) includes surgical resection. Recurrence after surgery is commonly reported, but a summary estimate for postsurgical recurrence-free survival (RFS) in patients with NSCLC is lacking. RESEARCH QUESTION: What is the RFS after surgery in patients with stage I-III NSCLC at different time points, and what factors are associated with RFS? STUDY DESIGN AND METHODS: A systematic search was performed in MEDLINE, EMBASE, and Cochrane databases between January 2011 and June 2021. The primary outcome was RFS at 1, 2, 3, and 5 years postresection. Single-arm, random-effects meta-analyses were done to calculate effect estimates and 95% CIs. Analyses were stratified by stage/substage as per the AJCC Cancer Staging Manual, and RFS was estimated (1) after pooling studies, using seventh or eighth edition staging criteria; and (2) among studies using only the eighth edition. Meta-regressions were performed to assess associations between RFS and patient demographic/clinical characteristics of interest. RESULTS: Data from 471 studies comprising 1,060 surgical study arms were extracted. RFS estimates from 60,695 patients staged with the seventh or eighth edition were analyzed. RFS ranged from 96% at 1 year postresection to 82% at 5 years for stage I, and from 68% at 1 year to 34% at 5 years for stage III. Estimates for patients staged using only eighth edition criteria were slightly higher. Older age, higher percentage of male patients, advancing stage, larger tumor size, and geographic region (North America/Europe vs Asia) were significantly associated with worse RFS. INTERPRETATION: This study presents a comprehensive assessment of reported RFS from published clinical literature, offering estimates at multiple postsurgical time points and by geographic region. Findings can inform treatment decisions, clinical trial design, and future research to improve outcomes among patients with NSCLC.

Patient Preferences for Lung Cancer Interception Therapy.

Importance: Interception therapy requires individuals to undergo treatment to prevent a future medical event, but little is known about preferences of individuals at high risk for lung cancer and whether they would be interested in this type of treatment. Objective: To explore preferences of individuals at high risk for lung cancer for potential interception therapies to reduce this risk. Design, Setting, and Participants: This survey study used a discrete-choice experiment and included hypothetical lung cancer interception treatments with 4 attributes: reduction in lung cancer risk over 3 years, injection site reaction severity, nonfatal serious infection, and death from serious infection. Respondents were assigned to a baseline lung cancer risk of 6%, 10%, or 16% over 3 years. The discrete-choice experiment was administered online (July 13 to September 6, 2022) to US respondents eligible for lung cancer screening according to US Preventive Services Task Force guidelines. Participants included adults aged 50 to 80 years with at least a 20 pack-year smoking history. Statistical analysis was performed from September to December 2022. Main Outcomes and Measures: Attribute-level preference weights were estimated, and conditional relative attribute importance, maximum acceptable risks, and minimum acceptable benefits were calculated. Characteristics of respondents who always selected no treatment were also explored. Results: Of the 803 survey respondents, 495 (61.6%) were female, 138 (17.2%) were African American or Black, 55 (6.8%) were Alaska Native, American Indian, or Native American, 44 (5.5%) were Asian or Native Hawaiian or Other Pacific Islander, 104 (13.0%) were Hispanic, Latin American, or Latinx, and 462 (57.5%) were White, Middle Eastern or North African, or a race or ethnicity not listed; and mean (SD) age was 63.0 (7.5) years. Most respondents were willing to accept interception therapy and viewed reduction in lung cancer risk as the most important attribute. Respondents would accept a greater than or equal to a 12.0 percentage point increase in risk of nonfatal serious infection if lung cancer risk was reduced by at least 20.0 percentage points; and a greater than or equal to 1.2 percentage point increase in risk of fatal serious infection if lung cancer risk was reduced by at least 30.0 percentage points. Respondents would require at least a 15.4 (95% CI, 10.6-20.2) percentage point decrease in lung cancer risk to accept a 12.0 percentage point increase in risk of nonfatal serious infection; and at least a 23.1 (95% CI, 16.4-29.8) percentage point decrease in lung cancer risk to accept a 1.2 percentage point increase in risk of death from serious infection. Respondents who were unwilling to accept interception therapy in any question (129 [16.1%]) were more likely to be older and to currently smoke with no prior cessation attempt, and less likely to have been vaccinated against COVID-19 or examined for skin cancer. Conclusions and Relevance: In this survey study of individuals at high risk of lung cancer, most respondents were willing to consider interception therapy. These results suggest the importance of benefit-risk assessments for future lung cancer interception treatments.

Stereotactic body radiation therapy and thermal ablation for treatment of NSCLC: A systematic literature review and meta-analysis.

RATIONALE: Stereotactic body radiation therapy (SBRT) is the standard of care for inoperable early stage non-small cell lung cancer (NSCLC). Use of image guided thermal ablation (IGTA; including microwave ablation [MWA] and radiofrequency ablation [RFA]) has increased in NSCLC, however there are no studies comparing all three. OBJECTIVE: To compare the efficacy of IGTA (including MWA and RFA) and SBRT for the treatment of NSCLC. METHODS: Published literature databases were systematically searched for studies assessing MWA, RFA, or SBRT. Local tumor progression (LTP), disease-free survival (DFS), and overall survival (OS) were assessed with single-arm pooled analyses and meta-regressions in NSCLC patients and a stage IA subgroup. Study quality was assessed with a modified methodological index for non-randomized studies (MINORS) tool. RESULTS: Forty IGTA study-arms (2,691 patients) and 215 SBRT study-arms (54,789 patients) were identified. LTP was lowest after SBRT at one and two years in single-arm pooled analyses (4% and 9% vs. 11% and 18%) and at one year in meta-regressions when compared to IGTA (OR = 0.2, 95%CI = 0.07-0.63). MWA patients had the highest DFS of all treatments in single-arm pooled analyses. In meta-regressions at two and three-years, DFS was significantly lower for RFA compared to MWA (OR = 0.26, 95%CI = 0.12-0.58; OR = 0.33, 95%CI = 0.16-0.66, respectively). OS was similar across modalities, timepoints, and analyses. Older age, male patients, larger tumors, retrospective studies, and non-Asian study region were also predictors of worse clinical outcomes. In high-quality studies (MINORS score ≥ 7), MWA patients had better clinical outcomes than the overall analysis. Stage IA MWA patients had lower LTP, higher OS, and generally lower DFS, compared to the main analysis of all NSCLC patients. CONCLUSIONS: NSCLC patients had comparable outcomes after SBRT and MWA, which were better than those with RFA.

Detecting Ground Glass Opacity Features in Patients With Lung Cancer: Automated Extraction and Longitudinal Analysis via Deep Learning-Based Natural Language Processing.

BACKGROUND: Ground-glass opacities (GGOs) appearing in computed tomography (CT) scans may indicate potential lung malignancy. Proper management of GGOs based on their features can prevent the development of lung cancer. Electronic health records are rich sources of information on GGO nodules and their granular features, but most of the valuable information is embedded in unstructured clinical notes. OBJECTIVE: We aimed to develop, test, and validate a deep learning-based natural language processing (NLP) tool that automatically extracts GGO features to inform the longitudinal trajectory of GGO status from large-scale radiology notes. METHODS: We developed a bidirectional long short-term memory with a conditional random field-based deep-learning NLP pipeline to extract GGO and granular features of GGO retrospectively from radiology notes of 13,216 lung cancer patients. We evaluated the pipeline with quality assessments and analyzed cohort characterization of the distribution of nodule features longitudinally to assess changes in size and solidity over time. RESULTS: Our NLP pipeline built on the GGO ontology we developed achieved between 95% and 100% precision, 89% and 100% recall, and 92% and 100% F1-scores on different GGO features. We deployed this GGO NLP model to extract and structure comprehensive characteristics of GGOs from 29,496 radiology notes of 4521 lung cancer patients. Longitudinal analysis revealed that size increased in 16.8% (240/1424) of patients, decreased in 14.6% (208/1424), and remained unchanged in 68.5% (976/1424) in their last note compared to the first note. Among 1127 patients who had longitudinal radiology notes of GGO status, 815 (72.3%) were reported to have stable status, and 259 (23%) had increased/progressed status in the subsequent notes. CONCLUSIONS: Our deep learning-based NLP pipeline can automatically extract granular GGO features at scale from electronic health records when this information is documented in radiology notes and help inform the natural history of GGO. This will open the way for a new paradigm in lung cancer prevention and early detection.

Clinical Outcomes in Measurement-based Treatment (Comet): a trial of depression monitoring and feedback to primary care physicians.

BACKGROUND: Despite the availability of effective treatments for depression, many patients under the care of primary care physicians do not achieve remission. Clinical Outcomes in Measurement-based Treatment (COMET) was designed to assess whether communicating patient-reported depression symptom severity to primary care physicians affects patient outcomes at 6 months. METHODS: Nine hundred fifteen patients (intervention: n = 503; control: n = 412) diagnosed with major depressive disorder were enrolled in a prospective trial in which physician practice sites were assigned to either the intervention or control study arm. Only patients who were prescribed an antidepressant by their physician were eligible, but medication type was independent of the study protocol. Intervention-arm physicians received monthly updates on their patients' depression severity, which was determined with the nine-item Patient Health Questionnaire (PHQ-9) administered during telephone interviews. Remission was defined as a PHQ-9 score <5 at 6 months; response was defined as a score reduction ≥50%. RESULTS: Among patients with baseline PHQ-9 score ≥5, 45.0% achieved remission (46.7% intervention versus 42.8% control) and 63.9% responded (67.0% intervention versus 59.7% control) at 6 months. After adjusting for baseline demographic and clinical variables, odds of remission (odds ratio [OR], 1.59 [95% CI, 1.07-2.37]) or response (OR, 2.02 [95% CI, 1.36-3.02]) were significantly greater for the intervention group than for control patients. CONCLUSIONS: This study demonstrated that regular patient symptom monitoring with feedback to physicians improved outcomes of depression treatment in the primary care setting. Determining reasons for the high observed nonremission rates requires further investigation.

Comparison of health-related quality of life among patients using atypical antipsychotics for treatment of depression: results from the National Health and Wellness Survey.

BACKGROUND: Use of atypical antipsychotics (AA) in combination with an antidepressant is recommended as an augmentation strategy for patients with depression. However, there is a paucity of data comparing aripiprazole and other AAs in terms of patient reported outcomes. Therefore, the objective of this study was to examine the levels of HRQoL and health utility scores in patients with depression using aripiprazole compared with patients using olanzapine, quetiapine, risperidone and ziprasidone. METHODS: Data were obtained from the 2009, 2010, and 2011 National Health and Wellness Survey (NHWS), a cross-sectional, internet-based survey that is representative of the adult US population. Only those patients who reported being diagnosed with depression and taking an antidepressant and an atypical antipsychotic for depression were included. Patients taking an atypical antipsychotic for less than 2 months or who reported being diagnosed with bipolar disorder or schizophrenia were excluded. Patients taking aripiprazole were compared with patients taking other atypical antipsychotics. Health-related quality of life (HRQoL) and health utilities were assessed using the Short Form 12-item (SF-12) health survey. Differences between groups were analyzed using General Linear Models (GLM) controlling for demographic and health characteristics. RESULTS: Overall sample size was 426 with 59.9% taking aripiprazole (n=255) and 40.1% (n=171) taking another atypical antipsychotic (olanzapine (n=19), quetiapine (n=127), risperidone (n=14) or ziprasidone (n=11)). Of the SF-12 domains, mean mental component summary (MCS) score (p=.018), bodily pain (p=.047), general health (p=.009) and emotional role limitations (p=.009) were found to be significantly higher in aripiprazole users indicating better HRQoL compared to other atypical antipsychotics. After controlling for demographic and health characteristics, patients taking aripiprazole reported significantly higher mean mental SF-12 component summary (34.10 vs. 31.43, p=.018), bodily pain (55.19 vs. 49.05, p=.047), general health (50.05 vs. 43.07, p=.009), emotional role limitations (49.44 vs. 41.83, p=.009), and SF-6D utility scores (0.59 vs. 0.56, p=.042). CONCLUSIONS: Comparison of patients taking aripiprazole with a cohort of patients using another AA for depression demonstrated that aripiprazole was independently associated with better (both statistically and clinically) HRQoL and health utilities.