[Proactively embracing the challenges of multimorbidity]

With rapid socio-economic development and the acceleration of population aging, the average life span of human beings has increased significantly. Individuals suffering from the co-existence of multiple diseases (multimorbidity) have become a new normal in public health and posed severe challenge to human health. Multimorbidity significantly reduces the quality of life, increases disability and mortality risks, complicates disease treatment and care and increases burden of the healthcare system with higher costs. This commentary discusses the definition of multimorbidity and common public misconceptions, then assesses its profound impact on overall public health, socio-economic development and healthcare system. We also proposes the potential strategies to meet the challenges posed by multimorbidity. The main aim is to raise awareness of multimorbidity, advocate proactive responses to improve public health and build a healthy society through the development of prevention and treatment systems and promote precision prevention and treatment for multimorbidity.

Risk of Gastric Adenocarcinoma in a Multiethnic Population Undergoing Routine Care: An Electronic Health Records Cohort Study

BACKGROUND

Gastric adenocarcinoma (GAC) is often diagnosed at advanced stages and portends a poor prognosis. We hypothesized that electronic health records (EHR) could be leveraged to identify individuals at highest risk for GAC from the population seeking routine care.

METHODS

This was a retrospective cohort study, with endpoint of GAC incidence as ascertained through linkage to an institutional tumor registry. We utilized 2010 to 2020 data from the Palo Alto Medical Foundation, a large multispecialty practice serving Northern California. The analytic cohort comprised individuals ages 40-75 receiving regular ambulatory care. Variables collected included demographic, medical, pharmaceutical, social, and familial data. Electronic phenotyping was based on rule-based methods.

RESULTS

The cohort comprised 316,044 individuals and approximately 2 million person-years (p-y) of observation. 157 incident GACs occurred (incidence 7.9 per 100,000 p-y), of which 102 were non-cardia GACs (incidence 5.1 per 100,000 p-y). In multivariable analysis, male sex [HR: 2.2, 95% confidence interval (CI): 1.6-3.1], older age, Asian race (HR: 2.5, 95% CI: 1.7-3.7), Hispanic ethnicity (HR: 1.9, 95% CI: 1.1-3.3), atrophic gastritis (HR: 4.6, 95% CI: 2.2-9.3), and anemia (HR: 1.9, 95% CI: 1.3-2.6) were associated with GAC risk; use of NSAID was inversely associated (HR: 0.3, 95% CI: 0.2-0.5). Older age, Asian race, Hispanic ethnicity, atrophic gastritis, and anemia were associated with non-cardia GAC.

CONCLUSIONS

Routine EHR data can stratify the general population for GAC risk.

IMPACT

Such methods may help triage populations for targeted screening efforts, such as upper endoscopy.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model

BACKGROUND

Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors.

METHODS

The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines.

RESULTS

Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202).

CONCLUSION

In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance.

PLAIN LANGUAGE SUMMARY

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks

MOTIVATION

Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance.

IMPLEMENTATION

dynamicLM as an R package.

GENERAL FEATURES

The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration.

AVAILABILITY

Available on GitHub [https://github.com/thehanlab/dynamicLM].

Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance

The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.

Objective

To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.

Design, Setting, and Participants

In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.

Exposures

The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.

Outcomes

Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).

Results

Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).

Conclusions

The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.

Second Primary Lung Cancer Among Lung Cancer Survivors Who Never Smoked

Importance

Lung cancer among never-smokers accounts for 25% of all lung cancers in the US; recent therapeutic advances have improved survival among patients with initial primary lung cancer (IPLC), who are now at high risk of developing second primary lung cancer (SPLC). As smoking rates continue to decline in the US, it is critical to examine more closely the epidemiology of lung cancer among patients who never smoked, including their risk for SPLC.

Objective

To estimate and compare the cumulative SPLC incidence among lung cancer survivors who have never smoked vs those who have ever smoked.

Design, Setting, and Participants

This population-based prospective cohort study used data from the Multiethnic Cohort Study (MEC), which enrolled participants between April 18, 1993, and December 31, 1996, with follow-up through July 1, 2017. Eligible individuals for this study were aged 45 to 75 years and had complete smoking data at baseline. These participants were followed up for IPLC and further SPLC development through the Surveillance, Epidemiology, and End Results registry. The data were analyzed from July 1, 2022, to January 31, 2023.

Exposures

Never-smoking vs ever-smoking exposure at MEC enrollment.

Main Outcomes and Measures

The study had 2 primary outcomes: (1) 10-year cumulative incidence of IPLC in the entire study cohort and 10-year cumulative incidence of SPLC among patients with IPLC and (2) standardized incidence ratio (SIR) (calculated as the SPLC incidence divided by the IPLC incidence) by smoking history.

Results

Among 211 414 MEC participants, 7161 (3.96%) developed IPLC over 4 038 007 person-years, and 163 (2.28%) developed SPLC over 16 470 person-years. Of the participants with IPLC, the mean (SD) age at cohort enrollment was 63.6 (7.7) years, 4031 (56.3%) were male, and 3131 (43.7%) were female. The 10-year cumulative IPLC incidence was 2.40% (95% CI, 2.31%-2.49%) among ever-smokers, which was 7 times higher than never-smokers (0.34%; 95% CI, 0.30%-0.37%). However, the 10-year cumulative SPLC incidence following IPLC was as high among never-smokers (2.84%; 95% CI, 1.50%-4.18%) as ever-smokers (2.72%; 95% CI, 2.24%-3.20%), which led to a substantially higher SIR for never-smokers (14.50; 95% CI, 8.73-22.65) vs ever-smokers (3.50; 95% CI, 2.95-4.12).

Conclusions and Relevance

The findings indicate that SPLC risk among lung cancer survivors who never smoked is as high as among those with IPLC who ever-smoked, highlighting the need to identify risk factors for SPLC among patients who never smoked and to develop a targeted surveillance strategy.

Optimizing Lung Cancer Screening With Risk Prediction: Current Challenges and the Emerging Role of Biomarkers

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.Lung cancer screening has been demonstrated to reduce lung cancer mortality, but its benefits must be weighed against the potential harms of unnecessary procedures, false-positive radiological findings, and overdiagnosis. Individuals at highest risk of lung cancer are more likely to maximize benefits while minimizing harm from screening. Although current lung cancer screening guidelines recommended by the US Preventive Services Task Force (USPSTF) only consider age and smoking history for screening eligibility, National Comprehensive Cancer Network and other society guidelines recommend screening on the basis of individualized risk assessment including family history, environmental exposures, and presence of chronic lung disease. Risk prediction models have been developed to integrate various risk factors into an individualized risk prediction score. Previous evidence showed that risk prediction model-based screening eligibility could improve sensitivity for detecting lung cancer cases without reducing specificity. Furthermore, recent advances in lung cancer biomarkers have enhanced the performance of risk prediction in identifying lung cancer cases relative to the USPSTF criteria. These risk prediction models can be used to guide shared decision-making discussions before proceeding with lung cancer screening. This study aims to provide a concise overview of these prediction models and the emerging role of biomarker testing in risk prediction to facilitate conversations with patients. The goal was to assist clinicians in assessing individual patient risk, leading to more informed decision making.

Overall Survival Among Patients With De Novo Stage IV Metastatic and Distant Metastatic Recurrent Non-Small Cell Lung Cancer

Importance

Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains poorly understood by metastatic disease type (ie, de novo stage IV vs distant recurrence).

Objective

To evaluate the association of metastatic disease type on overall survival (OS) among patients with non-small cell lung cancer (NSCLC) and to identify potential mechanisms underlying any survival difference.

Design, Setting, and Participants

Cohort study of a national US population based at a tertiary referral center in the San Francisco Bay Area using participant data from the National Lung Screening Trial (NLST) who were enrolled between 2002 and 2004 and followed up for up to 7 years as the primary cohort and patient data from Stanford Healthcare (SHC) for diagnoses between 2009 and 2019 and followed up for up to 13 years as the validation cohort. Participants from NLST with de novo metastatic or distant recurrent NSCLC diagnoses were included. Data were analyzed from January 2021 to March 2023.

Exposures

De novo stage IV vs distant recurrent metastatic disease.

Main Outcomes and Measures

OS after diagnosis of metastatic disease.

Results

The NLST and SHC cohort consisted of 660 and 180 participants, respectively (411 men [62.3%] vs 109 men [60.6%], 602 White participants [91.2%] vs 111 White participants [61.7%], and mean [SD] age of 66.8 [5.5] vs 71.4 [7.9] years at metastasis, respectively). Patients with distant recurrence showed significantly better OS than patients with de novo metastasis (adjusted hazard ratio [aHR], 0.72; 95% CI, 0.60-0.87; P < .001) in NLST, which was replicated in SHC (aHR, 0.64; 95% CI, 0.43-0.96; P = .03). In SHC, patients with de novo metastasis more frequently progressed to the bone (63 patients with de novo metastasis [52.5%] vs 19 patients with distant recurrence [31.7%]) or pleura (40 patients with de novo metastasis [33.3%] vs 8 patients with distant recurrence [13.3%]) than patients with distant recurrence and were primarily detected through symptoms (102 patients [85.0%]) as compared with posttreatment surveillance (47 patients [78.3%]) in the latter. The main finding remained consistent after further adjusting for metastasis sites and detection methods.

Conclusions and Relevance

In this cohort study, patients with distant recurrent NSCLC had significantly better OS than those with de novo disease, and the latter group was associated with characteristics that may affect overall survival. This finding can help inform future clinical trial designs to ensure a balance for baseline patient characteristics.

Risk of developing glioblastoma following non-CNS primary cancer: a SEER analysis between 2000 and 2018

BACKGROUND

Patients with a prior malignancy are at elevated risk of developing subsequent primary malignancies (SPMs). However, the risk of developing subsequent primary glioblastoma (SPGBM) in patients with a prior cancer history is poorly understood.

METHODS

We used the Surveillance, Epidemiology, and End Results (SEER) database and identified patients diagnosed with non-CNS malignancy between 2000 and 2018. We calculated a modified standardized incidence ratio (M-SIR), defined as the ratio of the incidence of SPGBM among patients with initial non-CNS malignancy to the incidence of GBM in the general population, stratified by sex latency, and initial tumor location.

RESULTS

Of the 5,326,172 patients diagnosed with a primary non-CNS malignancy, 3559 patients developed SPGBM (0.07%). Among patients with SPGBM, 2312 (65.0%) were men, compared to 2,706,933 (50.8%) men in the total primary non-CNS malignancy cohort. The median age at diagnosis of SPGBM was 65 years. The mean latency between a prior non-CNS malignancy and developing a SPGBM was 67.3 months (interquartile range [IQR] 27-100). Overall, patients with a primary non-CNS malignancy had a significantly elevated M-SIR (1.13, 95% CI 1.09-1.16), with a 13% increased incidence of SPGBM when compared to the incidence of developing GBM in the age-matched general population. When stratified by non-CNS tumor location, patients diagnosed with primary melanoma, lymphoma, prostate, breast, renal, or endocrine malignancies had a higher M-SIR (M-SIR ranges: 1.09-2.15). Patients with lung cancers (M-SIR 0.82, 95% CI 0.68-0.99), or stomach cancers (M-SIR 0.47, 95% CI 0.24-0.82) demonstrated a lower M-SIR.

CONCLUSION

Patients with a history of prior non-CNS malignancy are at an overall increased risk of developing SPGBM relative to the incidence of developing GBM in the general population. However, the incidence of SPGBM after prior non-CNS malignancy varies by primary tumor location, with some non-CNS malignancies demonstrating either increased or decreased predisposition for SPGBM depending on tumor origin. These findings merit future investigation into whether these relationships represent treatment effects or a previously unknown shared predisposition for glioblastoma and non-CNS malignancy.

[Abnormal changes of static and dynamic functional connectivity of dopaminergic midbrain in patients with first-episode schizophrenia and their correlations with clinical symptoms]

Objective: To investigate the abnormal changes of static functional connectivity (sFC) and dynamic functional connectivity (dFC) in the dopaminergic midbrain (ventral dorsal tegmental area and bilateral substantia nigra compacta, VTA/SNc) in patients with first-episode schizophrenia(SCH), and their correlation with the Positive and Negative Symptom Scale (PANSS). Methods: The data of 198 first-episode untreated schizophrenia patients and 199 healthy controls (HC) matched by age, sex and years of education who were admitted to the First Affiliated Hospital of Zhengzhou University from January 2019 to May 2022 were prospectively collected. All subjects underwent high resolution structural MRI and resting state functional magnetic resonance imaging (rs-fMRI) scanning. The dopaminergic midbrain (VTA/SNc) was defined as three regions of interest (ROI). The sFC and dFC analyses with VTA/SNc as seeds were performed to produce a whole-brain diagram initially, which subsequently were compared between schizophrenia group and HC group. Finally, the correlation analysis of sFC and dFC values with the PANSS scores were performed, including the positive scale score, negative scale score, general psychopathology scale score, total score and symptom scores. Results: There were 86 males and 112 females in SCH group, and aged (23±9) years. Meanwhile, there were 95 males and 104 females in HC group, and aged (22±5) years. In the SCH group, the positive (P), the negative (N) and the general psychopathology (G) scale scores and the total score (T) of the PANSS scale was 20±7, 21±7, 41±11 and 82±22, respectively. Compared with the HC group, the VTA showed decreased sFC with four clusters including cerebellar vermis 7/9, left putamen, right thalamus and left middle cingulate gyrus in the schizophrenia group (peak center, t=-4.35, -4.81, -4.35 and -4.65; voxel P<0.005; cluster P<0.05), the right SNc showed decreased sFC with four clusters including left cerebellar hemisphere 4/5/8, right putamen, right medial orbitofrontal gyrus and the left putamen in the schizophrenia group (peak center, t=-4.91, -5.15, -4.77 and -5.21; voxel P<0.005; cluster P<0.05), and the left SNc showed decreased sFC with four clusters including the left putamen, right putamen, right medial orbitofrontal gyrus and left middle cingulate gyrus in the schizophrenia group (peak center, t=-5.82, -4.83 and -4.65; voxel P<0.005; cluster P<0.05). Compared with the HC group, the VTA showed decreased dFC with the right inferior parietal gyrus, right angular gyrus and right superior parietal gyrus in schizophrenia group (t=-4.17). In the schizophrenia group, the sFC value of cluster 2 (left putamen) with VTA as seed and cluster 4 (left putamen) with right SNc as seed were positively correlated with the positive scale scores in PANSS (r=0.141, 0.169, both P<0.05). The sFC and dFC values of significant regions were also correlated with hallucination, delusion, suspicion, hostility, communication disorder, passivity/indifference, lack of communication, stereotyped thinking, depression, non-cooperation, lack of judgment and insight, impulse control disorder, active social avoidance (all P<0.05). Conclusion: The static and dynamic functional connectivity (stability) of VTA/SNc to cerebellum, thalamus, striatum, prefrontal lobe and cingulate gyrus in first-episode schizophrenia patients were decreased, which were closely related to the positive and negative symptoms of schizophrenia.

Predictors of spine metastases at initial presentation of pediatric brain tumor patients: a single-institution study

PURPOSE

Given the rarity of disseminated disease at the time of initial evaluation for pediatric brain tumor patients, we sought to identify clinical and radiographic predictors of spinal metastasis (SM) at the time of presentation.

METHODS

We performed a single-institution retrospective chart review of pediatric brain tumor patients who first presented between 2004 and 2018. We extracted information regarding patient demographics, radiographic attributes, and presenting symptoms. Univariate and multivariate logistic regression was used to estimate the association between measured variables and SMs.

RESULTS

We identified 281 patients who met our inclusion criteria, of whom 19 had SM at initial presentation (6.8%). The most common symptoms at presentation were headache (n = 12; 63.2%), nausea/vomiting (n = 16; 84.2%), and gait abnormalities (n = 8; 41.2%). Multivariate models demonstrated that intraventricular and posterior fossa tumors were more frequently associated with SM (OR: 5.28, 95% CI: 1.79-15.59, p = 0.003), with 4th ventricular (OR: 7.42, 95% CI: 1.77-31.11, p = 0.006) and cerebellar parenchymal tumor location (OR: 4.79, 95% CI: 1.17-19.63, p = 0.030) carrying the highest risk for disseminated disease. In addition, evidence of intracranial leptomeningeal enhancement on magnetic resonance imaging (OR: 46.85, 95% CI: 12.31-178.28, p < 0.001) and hydrocephalus (OR: 3.19; 95% CI: 1.06-9.58; p = 0.038) were associated with SM.

CONCLUSIONS

Intraventricular tumors and the presence of intracranial leptomeningeal disease were most frequently associated with disseminated disease at presentation. These findings are consistent with current clinical expectations and offer empirical evidence that heightened suspicion for SM may be prospectively applied to certain subsets of pediatric brain tumor patients at the time of presentation.

Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis

BACKGROUND

In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening.

OBJECTIVE

To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds.

DESIGN

Comparative modeling analysis.

DATA SOURCES

National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator.

TARGET POPULATION

1960 U.S. birth cohort.

TIME HORIZON

45 years.

PERSPECTIVE

U.S. health care sector.

INTERVENTION

Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model.

OUTCOME MEASURES

Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost.

RESULTS OF BASE-CASE ANALYSIS

Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%).

RESULTS OF SENSITIVITY ANALYSES

Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions.

LIMITATION

Risk models were restricted to age, sex, and smoking-related risk predictors.

CONCLUSION

Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration.

PRIMARY FUNDING SOURCE

National Cancer Institute (NCI).

Abstract P055: Risk factors for second primary lung cancer among breast cancer survivors

Introduction: Breast cancer is the most common cancer in women in the U.S. As survival in breast cancer has improved, one of the key clinical problems in breast cancer survivors is the increased risk of second cancers. Over half (55%) of breast cancer survivors die from second cancers, of which lung cancer (i.e., second primary lung cancer [SPLC]) is the most frequent type. While smoking and radiotherapy have been identified as the risk factors for SPLC among breast cancer survivors, other potential factors (e.g., comorbidity, and medication) have been underexamined. In addition, women in general have shown higher susceptibility to smoking-induced lung cancer than men, suggesting the potential involvement of hormonal factors; however, the effect of hormone replacement therapy (HRT) on lung cancer risk has been controversial and has never been examined among breast cancer survivors. We aimed to examine the factors associated with SPLC risk among breast cancer survivors, focusing on the effect of HRT and its interaction with smoking. We also explored the potential of tailored risk-based management of SPLC for breast cancer survivors. Methods: We identified 5,552 patients diagnosed with breast cancer in 1993-2014 from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. SPLC was defined as a newly diagnosed lung cancer after 6 months from the time of breast cancer diagnosis. We applied multivariable cause-specific Cox regression to identify new factors associated with SPLC risk, adjusting for multiple testing using the Bonferroni method (P&lt;0.01). We developed a prediction model to predict a 5-year risk of SPLC among breast cancer survivors that included both ever- and never-smokers and evaluated the predictive accuracy vs. a well-established lung cancer risk model, PLCOm2012, that was developed for a cancer-free population who ever smoked. Results: Of 5,552 patients, 89 (1.6%) developed SPLC over 102,545 person-years. Several factors measured at baseline in PLCO were significantly associated with SPLC risk among breast cancer survivors, including liver comorbidity (Hazard Ratio [HR] 3.28; P&lt;.001), prior history of other cancer (HR 2.02; P=0.01), and regular use of ibuprofen (HR 0.52; P=0.01). In addition, ever-use of HRT was associated with a 51% reduction in SPLC risk (HR 0.49; P=0.001). The effect of active smoking on SPLC risk vs non-active smoking (HR 7.09; P&lt;.001) was validated in PLCO. Notably, the effect of active smoking was intensified among ever-HRT users (HR=10.5; P&lt;.001) vs. never-HRT users (HR 4.1; P&lt;.001), thus showing a significant interaction (Pinteraction=0.003). The prediction model for SPLC risk was validated through bootstrap and demonstrated higher discrimination (AUC 0.83) vs. the PLCOm2012 model (AUC 0.79). Conclusions: In a large prospective cohort of breast cancer survivors, smoking and HRT use showed a significant interaction on SPLC risk. The prediction model for SPLC could identify high-risk survivors for SPLC for tailored surveillance to improve the management of breast cancer survivors.

Citation Format: Eunji Choi, Justin Lee, Julie T. Wu, Heather A. Wakelee, Lidia Schapira, Allison W. Kurian, Summer S. Han. Risk factors for second primary lung cancer among breast cancer survivors. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P055.

Abstract P068: A hybrid modelling approach for abstracting CT imaging indications by integrating natural language processing from radiology reports with structured data from electronic health records

Background: Real-world evidence (RWE) studies for surveillance patterns following lung cancer (LC) diagnosis can inform optimizing recommendations on surveillance and practice. One major obstacle in RWE studies for LC surveillance is the lack of radiologic imaging indication for surveillance vs. other reasons (e.g., symptoms). To enable RWE studies for surveillance to detect second primary lung cancer among LC survivors, we developed a hybrid modelling approach that integrates structured data from electronic health records (EHRs) with natural language processing (NLP) from radiology reports for abstracting computed tomography (CT) imaging indications in LC survivors. Methods: We manually reviewed and abstracted CT imaging indications, i.e., surveillance vs. others (e.g., symptoms and metastatic disease follow-up) to create a gold standard from 200 randomly selected radiology reports among 1,952 LC patients (i) who were diagnosed in 2000-2017 at Stanford Health Care (SHC) and (ii) survived ≧5 years after the diagnosis. We abstracted medically relevant key-phrases using the part-of-speech grammar and PageRank algorithms. Hierarchical clustering identified context-specific key-phrase clusters as follows: “surveillance”, “stable”, “nodule”, “symptom”, and “metastasis”. The text-based radiology reports were vectorized to generate NLP features using phrase occurrence frequencies. The structured variables from EHRs included: (i) diagnosis of lung diseases or chest symptoms in previous 6 months, (ii) ordering provider-type (oncology vs. others [e.g. emergency and internal medicine]), and (iii) time from previous CT (≧6 months). A hybrid model was then fitted using logistic regression including both structured and NLP features and validated using a 10-fold cross-validation. The model’s performance was compared to those solely based on NLP or structured data. Results: The dataset of 200 radiology reports included 141 LC survivors (49% White, 72% adenocarcinoma). The proposed hybrid model showed high discrimination (AUC: 0.92), outperforming those based solely on NLP (AUC: 0.88) or structured data (AUC: 0.87). The proposed model demonstrated higher sensitivity (SN: 0.73) and specificity (SP: 0.96) versus those solely based on NLP (SN: 0.53; SP: 0.96) or structured data (SN: 0.53; SP: 0.90). The hybrid model showed that the following variables were positively associated with a higher likelihood that the given CT imaging indication is “surveillance”: (i) a longer time interval (≧6 months) from the previous CT (odds ratio [OR]: 4.63; p=0.01) and key-phrases of (ii) “nodule” (OR: 1.55; p=0.004) and (iii) “stable” (OR: 1.37; p=0.03). On the other hand, the following were negatively associated with the likelihood of surveillance: the key-phrases of “symptom” (OR: 0.17; p=0.02) and “metastasis” (OR: 0.26; p=0.02). Conclusion: A hybrid modeling approach combining text-based NLP and structured EHRs has the potential for abstracting CT imaging indications for LC surveillance. Future directions include validation using other EHR systems and extension using larger data.

Citation Format: Aparajita Khan, Julie Wu, Eunji Choi, Anna Graber-Naidich, Solomon Henry, Heather A. Wakelee, Allison W. Kurian, Su-Ying Liang, Ann Leung, Curtis Langlotz, Leah M. Backhus, Summer S. Han. A hybrid modelling approach for abstracting CT imaging indications by integrating natural language processing from radiology reports with structured data from electronic health records. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P068.

Predictive Model to Guide Brain Magnetic Resonance Imaging Surveillance in Patients With Metastatic Lung Cancer: Impact on Real-World Outcomes

PURPOSE

Brain metastasis is common in lung cancer, and treatment of brain metastasis can lead to significant morbidity. Although early detection of brain metastasis may improve outcomes, there are no prediction models to identify high-risk patients for brain magnetic resonance imaging (MRI) surveillance. Our goal is to develop a machine learning-based clinicogenomic prediction model to estimate patient-level brain metastasis risk.

METHODS

A penalized regression competing risk model was developed using 330 patients diagnosed with lung cancer between January 2014 and June 2019 and followed through June 2021 at Stanford HealthCare. The main outcome was time from the diagnosis of distant metastatic disease to the development of brain metastasis, death, or censoring.

RESULTS

Among the 330 patients, 84 (25%) developed brain metastasis over 627 person-years, with a 1-year cumulative brain metastasis incidence of 10.2% (95% CI, 6.8 to 13.6). Features selected for model inclusion were histology, cancer stage, age at diagnosis, primary site, and RB1 and ALK alterations. The prediction model yielded high discrimination (area under the curve 0.75). When the cohort was stratified by risk using a 1-year risk threshold of > 14.2% (85th percentile), the high-risk group had increased 1-year cumulative incidence of brain metastasis versus the low-risk group (30.8% v 6.1%, P < .01). Of 48 high-risk patients, 24 developed brain metastasis, and of these, 12 patients had brain metastasis detected more than 7 months after last brain MRI. Patients who missed this 7-month window had larger brain metastases (58% v 33% largest diameter > 10 mm; odds ratio, 2.80, CI, 0.51 to 13) versus those who had MRIs more frequently.

CONCLUSION

The proposed model can identify high-risk patients, who may benefit from more intensive brain MRI surveillance to reduce morbidity of subsequent treatment through early detection.

The Gastric Cancer Registry: A Genomic Translational Resource for Multidisciplinary Research in Gastric Cancer

BACKGROUND

Gastric cancer is a leading cause of cancer morbidity and mortality. Developing information systems which integrate clinical and genomic data may accelerate discoveries to improve cancer prevention, detection, and treatment. To support translational research in gastric cancer, we developed the Gastric Cancer Registry (GCR), a North American repository of clinical and cancer genomics data.

METHODS

Participants self-enrolled online. Entry criteria into the GCR included the following: (i) diagnosis of gastric cancer, (ii) history of gastric cancer in a first- or second-degree relative, or (iii) known germline mutation in the gene CDH1. Participants provided demographic and clinical information through a detailed survey. Some participants provided specimens of saliva and tumor samples. Tumor samples underwent exome sequencing, whole-genome sequencing, and transcriptome sequencing.

RESULTS

From 2011 to 2021, 567 individuals registered and returned the clinical questionnaire. For this cohort 65% had a personal history of gastric cancer, 36% reported a family history of gastric cancer, and 14% had a germline CDH1 mutation. 89 patients with gastric cancer provided tumor samples. For the initial study, 41 tumors were sequenced using next-generation sequencing. The data was analyzed for cancer mutations, copy-number variations, gene expression, microbiome, neoantigens, immune infiltrates, and other features. We developed a searchable, web-based interface (the GCR Genome Explorer) to enable researchers' access to these datasets.

CONCLUSIONS

The GCR is a unique, North American gastric cancer registry which integrates clinical and genomic annotation.

IMPACT

Available for researchers through an open access, web-based explorer, the GCR Genome Explorer will accelerate collaborative gastric cancer research across the United States and world.

Elevated cerebrospinal fluid iron and ferritin associated with early severe ventriculomegaly in preterm posthemorrhagic hydrocephalus

OBJECTIVE

Posthemorrhagic hydrocephalus (PHH) following preterm intraventricular hemorrhage (IVH) is among the most severe sequelae of extreme prematurity and a significant contributor to preterm morbidity and mortality. The authors have previously shown hemoglobin and ferritin to be elevated in the lumbar puncture cerebrospinal fluid (CSF) of neonates with PHH. Herein, they evaluated CSF from serial ventricular taps to determine whether neonates with PHH following severe initial ventriculomegaly had higher initial levels and prolonged clearance of CSF hemoglobin and hemoglobin degradation products compared to those in neonates with PHH following moderate initial ventriculomegaly.

METHODS

In this observational cohort study, CSF samples were obtained from serial ventricular taps in premature neonates with severe IVH and subsequent PHH. CSF hemoglobin, ferritin, total iron, total bilirubin, and total protein were quantified using ELISA. Ventriculomegaly on cranial imaging was assessed using the frontal occipital horn ratio (FOHR) and was categorized as severe (FOHR > 0.6) or moderate (FOHR ≤ 0.6).

RESULTS

Ventricular tap CSF hemoglobin (mean) and ferritin (initial and mean) were higher in neonates with severe versus moderate initial ventriculomegaly. CSF hemoglobin, ferritin, total iron, total bilirubin, and total protein decreased in a nonlinear fashion over the weeks following severe IVH. Significantly higher levels of CSF ferritin and total iron were observed in the early weeks following IVH in neonates with severe initial ventriculomegaly than in those with initial moderate ventriculomegaly.

CONCLUSIONS

Among preterm neonates with PHH following severe IVH, elevated CSF hemoglobin, ferritin, and iron were associated with more severe early ventricular enlargement (FOHR > 0.6 vs ≤ 0.6 at first ventricular tap).

A case-control study of healthcare disparities in sex and gender minority patients with breast cancer

6517

Background: Disparities in the quality of diagnosis and treatment of breast cancer in sex and gender minority (SGM) populations are largely undefined. Only 24% of studies funded by the National Cancer Institute capture data on sexual orientation, while only 10% capture data on gender identity. To address this gap, the National Academies 2020 Report calls for adding sexual orientation and gender identity (SOGI) to ongoing data collection efforts. This case-control study matching SGM patients with breast cancer to cisgender heterosexual controls is the result of linking SOGI data to the Stanford University Healthcare (SHC) Oncoshare breast cancer database, which integrates data from the electronic medical record (EMR) and California Cancer Registry. Methods: An initial database query across the SHC EMR was performed for charts containing SOGI terms in patients with breast cancer seen in SHC Oncology. 686 charts were identified for manual review and after eliminating false positives, the sample was reduced to 92 SGM patients, who were then matched by year of diagnosis, age, stage, ER-status, and HER-2 status to cisgender heterosexual controls within Oncoshare. Additional data on demographics, diagnosis, treatment, and relapse were then manually abstracted from the EMR. Results: The SGM cohort was comprised of 80% lesbians, 13% bisexuals and 6% transgender men. The median age at diagnosis across both groups was 49. SGM patients were 72% white, 4% Asian, 12% Black or Latinx 6% other compared to 63% white, 24% Asian, 6% Black or Latinx, 6% other in the controls (p = 0.0006). Thirteen percent and 32% of SGM patients engaged in risky alcohol and illicit drug use respectively, compared to 3% and 6% of controls (p = 0.028; p < 0.0001). Estrogen exposure risk factors including median age of menarche, first delivery, menopause, and use of exogenous estrogens were balanced between the two groups, but SGM patients had fewer children (median 0 vs 2, p < 0.0001). There was a delay in time to diagnosis from symptom onset in SGM patients versus controls (median 64 days vs 37 days, p = 0.043). There was no difference in surgical approach, use of post-lumpectomy radiation, or use of neoadjuvant chemotherapy for stage III disease. However, SGM patients were less likely to undergo chest reconstruction (55% vs 82%, p = 0.0098) and if ER+, to complete ≥5 years of ER-directed therapy (53% vs 72%, p = 0.048). SGM patients used more alternative medicine (46% vs 29%, p = 0.033) and had a higher rate of documented refusal of recommended oncologic treatments (38% vs 21%, p = 0.0088). Correspondingly, SGM patients experienced a higher recurrence rate (31% vs 14%, p = 0.0124). Conclusions: To our knowledge, this is the first study to examine quality of diagnosis and treatment of breast cancer in SGM patients. Several novel potential healthcare disparities are identified, which should be further evaluated in population-based studies to inform interventions.

The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer

BACKGROUND

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC), but little is known about the survival impact of SPLC diagnosis.

METHODS

We analyzed data from 138 969 patients in the Surveillance, Epidemiology, and End Results (SEER), who were surgically treated for initial primary lung cancer (IPLC) in 1988-2013. Each patient was followed from the date of IPLC diagnosis to SPLC diagnosis (for those with SPLC) and last vital status through 2016. We performed multivariable Cox regression to evaluate the association between overall survival and SPLC diagnosis as a time-varying predictor. To investigate potential effect modification, we tested interaction between SPLC and IPLC stage. Using data from the Multiethnic Cohort Study (MEC) (n = 1540 IPLC patients with surgery), we evaluated the survival impact of SPLC by smoking status. All statistical tests were 2-sided.

RESULTS

A total of 12 115 (8.7%) patients developed SPLC in SEER over 700 421 person-years of follow-up. Compared with patients with single primary lung cancer, those with SPLC had statistically significantly reduced overall survival (hazard ratio [HR] = 2.12, 95% confidence interval [CI] = 2.06 to 2.17; P < .001). The effect of SPLC on reduced survival was more pronounced among patients with early stage IPLC vs advanced-stage IPLC (HR = 2.14, 95% CI = 2.08 to 2.20, vs HR = 1.43, 95% CI = 1.21 to 1.70, respectively; Pinteraction < .001). Analysis using MEC data showed that the effect of SPLC on reduced survival was statistically significantly larger among persons who actively smoked at initial diagnosis vs those who formerly or never smoked (HR = 2.31, 95% CI = 1.48 to 3.61, vs HR = 1.41, 95% CI = 0.98 to 2.03, respectively; Pinteraction = .04).

CONCLUSIONS

SPLC diagnosis is statistically significantly associated with decreased survival in SEER and MEC. Intensive surveillance targeting patients with early stage IPLC and active smoking at IPLC diagnosis may lead to a larger survival benefit.

An integrated risk model stratifying seizure risk following brain tumor resection among seizure-naive patients without antiepileptic prophylaxis

OBJECTIVE

The natural history of seizure risk after brain tumor resection is not well understood. Identifying seizure-naive patients at highest risk for postoperative seizure events remains a clinical need. In this study, the authors sought to develop a predictive modeling strategy for anticipating postcraniotomy seizures after brain tumor resection.

METHODS

The IBM Watson Health MarketScan Claims Database was canvassed for antiepileptic drug (AED)– and seizure-naive patients who underwent brain tumor resection (2007–2016). The primary event of interest was short-term seizure risk (within 90 days postdischarge). The secondary event of interest was long-term seizure risk during the follow-up period. To model early-onset and long-term postdischarge seizure risk, a penalized logistic regression classifier and multivariable Cox regression model, respectively, were built, which integrated patient-, tumor-, and hospitalization-specific features. To compare empirical seizure rates, equally sized cohort tertiles were created and labeled as low risk, medium risk, and high risk.

RESULTS

Of 5470 patients, 983 (18.0%) had a postdischarge-coded seizure event. The integrated binary classification approach for predicting early-onset seizures outperformed models using feature subsets (area under the curve [AUC] = 0.751, hospitalization features only AUC = 0.667, patient features only AUC = 0.603, and tumor features only AUC = 0.694). Held-out validation patient cases that were predicted by the integrated model to have elevated short-term risk more frequently developed seizures within 90 days of discharge (24.1% high risk vs 3.8% low risk, p < 0.001). Compared with those in the low-risk tertile by the long-term seizure risk model, patients in the medium-risk and high-risk tertiles had 2.13 (95% CI 1.45–3.11) and 6.24 (95% CI 4.40–8.84) times higher long-term risk for postdischarge seizures. Only patients predicted as high risk developed status epilepticus within 90 days of discharge (1.7% high risk vs 0% low risk, p = 0.003).

CONCLUSIONS

The authors have presented a risk-stratified model that accurately predicted short- and long-term seizure risk in patients who underwent brain tumor resection, which may be used to stratify future study of postoperative AED prophylaxis in highest-risk patient subpopulations.

Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping

BACKGROUND

Genetic variants within the APOE locus may modulate Alzheimer's disease (AD) risk independently or in conjunction with APOE*2/3/4 genotypes. Identifying such variants and mechanisms would importantly advance our understanding of APOE pathophysiology and provide critical guidance for AD therapies aimed at APOE. The APOE locus however remains relatively poorly understood in AD, owing to multiple challenges that include its complex linkage structure and uncertainty in APOE*2/3/4 genotype quality. Here, we present a novel APOE*2/3/4 filtering approach and showcase its relevance on AD risk association analyses for the rs439401 variant, which is located 1801 base pairs downstream of APOE and has been associated with a potential regulatory effect on APOE.

METHODS

We used thirty-two AD-related cohorts, with genetic data from various high-density single-nucleotide polymorphism microarrays, whole-genome sequencing, and whole-exome sequencing. Study participants were filtered to be ages 60 and older, non-Hispanic, of European ancestry, and diagnosed as cognitively normal or AD (n = 65,701). Primary analyses investigated AD risk in APOE*4/4 carriers. Additional supporting analyses were performed in APOE*3/4 and 3/3 strata. Outcomes were compared under two different APOE*2/3/4 filtering approaches.

RESULTS

Using more conventional APOE*2/3/4 filtering criteria (approach 1), we showed that, when in-phase with APOE*4, rs439401 was variably associated with protective effects on AD case-control status. However, when applying a novel filter that increases the certainty of the APOE*2/3/4 genotypes by applying more stringent criteria for concordance between the provided APOE genotype and imputed APOE genotype (approach 2), we observed that all significant effects were lost.

CONCLUSIONS

We showed that careful consideration of APOE genotype and appropriate sample filtering were crucial to robustly interrogate the role of the APOE locus on AD risk. Our study presents a novel APOE filtering approach and provides important guidelines for research into the APOE locus, as well as for elucidating genetic interaction effects with APOE*2/3/4.

OUP accepted manuscript

Background

Methods

Results

Conclusions

Abstract PO-130: Disparities in risk of second primary lung cancer among lung cancer patients in the United States

Introduction: Lung cancer is the leading cause of cancer death in the U.S. Despite recent survival improvements, racial and socioeconomic disparities still exist in lung cancer incidence and survival. Furthermore, recent studies showed that lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). While racial and socioeconomic disparities have long been examined for lung cancer survival and incidence, little is known about their impacts on SPLC risk among lung cancer survivors. This study evaluated the disparities in SPLC incidence by calculating the standardized incidence ratio (SIR) of the observed SPLC incidence versus the expected incidence of initial primary lung cancer (IPLC) across different socioeconomic, acculturation, and smoking-related factors using county-level data obtained from the Surveillance, Epidemiology, and End Results Program (SEER). Methods: We identified 158,018 patients diagnosed with IPLC between 2000 and 2013 in SEER. SPLC was defined as a newly developed primary lung cancer after 2 years from IPLC diagnosis and was followed through 2018. The SIR was calculated as the ratio of the observed SPLC incidence versus the expected incidence of IPLC in the general population across different factors. Indicators of socioeconomic status, acculturation factors, and smoking prevalence in SEER were derived from county-level data using the American Community Survey and the Behavioral Risk Factor Surveillance System (BRFSS). The quintiles of these indicators were created using the data obtained across all 3,142 valid U.S. counties. We applied the Pearson's chi-squared test to evaluate the difference in SIRs across quintiles of the indicators we created, applying a statistical significance of α &lt; 0.005 after adjusting for multiple testing. Results: Among 158,018 IPLC patients, 10,650 (6.7%) developed SPLC over 626,853 person-years. The incidence of SPLC was 6 times higher than the IPLC incidence in the general population, with an overall SIR of 6.2 (95% Confidence Interval (CI): 6.09-6.32). Notably, the SIR, i.e., the ratio between the SPLC incidence and the IPLC incidence, was significantly higher among individuals who live in counties with the lowest quintile of median family income (&lt;$51,770) versus the highest quintile (&gt;$74,331) (SIR 7.18 versus 6.10, P&lt;1 × 10−6). Furthermore, the ratio between the SPLC versus the IPLC incidence was highest (SIR 8.01, CI: 7.36-8.71) among those who live in counties with the highest quintile of smoking prevalence (&gt;29.6%) versus SIR of 5.77 (CI: 5.63-5.91) with the lowest quintile of smoking prevalence (&lt;20.4%) (P=3.4 × 10−3). Race/ethnicity and acculturation factors, including immigration status, did not achieve statistical significance. Discussion: Significant disparities exist in SPLC incidence among lung cancer survivors who live in areas with a low median family income and high smoking prevalence. Targeted SPLC surveillance for lung cancer survivors from an underserved population would be needed to reduce the existing disparities.

Citation Format: Eunji Choi, Sophia J. Luo, Jacqueline V. Aredo, Joel W. Neal, Leah M. Backhus, Heather A. Wakelee, Summer S. Han. Disparities in risk of second primary lung cancer among lung cancer patients in the United States [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-130.

Association of COVID-19 Vaccination With SARS-CoV-2 Infection in Patients With Cancer: A US Nationwide Veterans Affairs Study

Question

What is the effectiveness of SARS-CoV-2 vaccination in patients with cancer?

Findings

In this cohort study of US Veterans Affairs patients who received systemic therapy for cancer between August 15, 2010, and May 4, 2021, a proxy measure for effectiveness of the vaccine starting 14 days after the second dose was 58%. The measure of effectiveness starting 14 days after the second dose was 85% in patients who had not received systemic therapy within the 6 months prior to vaccination and 76% among those receiving hormonal treatment.

Meaning

Results suggest that SARS-CoV-2 vaccination associated with lower infection rates in patients with cancer, especially in those not receiving current systemic therapy and those receiving hormonal treatment.

Importance

Patients with cancer are at increased risk for severe COVID-19, but it is unknown whether SARS-CoV-2 vaccination is effective for them.

Objective

To determine the association between SARS-CoV-2 vaccination and SARS-CoV-2 infections among a population of Veterans Affairs (VA) patients with cancer.

Design, Setting, and Participants

Retrospective, multicenter, nationwide cohort study of SARS-CoV-2 vaccination and infection among patients in the VA health care system from December 15, 2020, to May 4, 2021. All adults with solid tumors or hematologic cancer who received systemic cancer-directed therapy from August 15, 2010, to May 4, 2021, and were alive and without a documented SARS-CoV-2 positive result as of December 15, 2020, were eligible for inclusion. Each day between December 15, 2020, and May 4, 2021, newly vaccinated patients were matched 1:1 with unvaccinated or not yet vaccinated controls based on age, race and ethnicity, VA facility, rurality of home address, cancer type, and treatment type/timing.

Exposures

Receipt of a SARS-CoV-2 vaccine.

Main Outcomes and Measures

The primary outcome was documented SARS-CoV-2 infection. A proxy for vaccine effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared with unvaccinated controls.

Results

A total of 184 485 patients met eligibility criteria, and 113 796 were vaccinated. Of these, 29 152 vaccinated patients (median [IQR] age, 74.1 [70.2-79.3] years; 95% were men; 71% were non-Hispanic White individuals) were matched 1:1 to unvaccinated or not yet vaccinated controls. As of a median 47 days of follow-up, 436 SARS-CoV-2 infections were detected in the matched cohort (161 infections in vaccinated patients vs 275 in unvaccinated patients). There were 17 COVID-19–related deaths in the vaccinated group vs 27 COVID-19–related deaths in the unvaccinated group. Overall vaccine effectiveness in the matched cohort was 58% (95% CI, 39% to 72%) starting 14 days after the second dose. Patients who received chemotherapy within 3 months prior to the first vaccination dose were estimated to have a vaccine effectiveness of 57% (95% CI, –23% to 90%) starting 14 days after the second dose vs 76% (95% CI, 50% to 91%) for those receiving endocrine therapy and 85% (95% CI, 29% to 100%) for those who had not received systemic therapy for at least 6 months prior.

Conclusions and Relevance

In this cohort study, COVID-19 vaccination was associated with lower SARS-CoV-2 infection rates in patients with cancer. Some immunosuppressed subgroups may remain at early risk for COVID-19 despite vaccination, and consideration should be given to additional risk reduction strategies, such as serologic testing for vaccine response and a third vaccine dose to optimize outcomes.

Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening

IMPORTANCE

The US Preventive Services Task Force (USPSTF) issued its 2021 recommendation on lung cancer screening, which lowered the starting age for screening from 55 to 50 years and the minimum cumulative smoking exposure from 30 to 20 pack-years relative to its 2013 recommendation. Although costs are expected to increase because of the expanded screening eligibility criteria, it is unknown whether the new guidelines for lung cancer screening are cost-effective.

OBJECTIVE

To evaluate the cost-effectiveness of the 2021 USPSTF recommendation for lung cancer screening compared with the 2013 recommendation and to explore the cost-effectiveness of 6 alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years and an ending age for screening of 80 years but varied the starting ages for screening (50 or 55 years) and the number of years since smoking cessation (≤15, ≤20, or ≤25).

DESIGN, SETTING, AND PARTICIPANTS

A comparative cost-effectiveness analysis using 4 independently developed microsimulation models that shared common inputs to assess the population-level health benefits and costs of the 2021 recommended screening strategy and 6 alternative screening strategies compared with the 2013 recommended screening strategy. The models simulated a 1960 US birth cohort. Simulated individuals entered the study at age 45 years and were followed up until death or age 90 years, corresponding to a study period from January 1, 2005, to December 31, 2050.

EXPOSURES

Low-dose computed tomography in lung cancer screening programs with a minimum cumulative smoking exposure of 20 pack-years.

MAIN OUTCOMES AND MEASURES

Incremental cost-effectiveness ratio (ICER) per quality-adjusted life-year (QALY) of the 2021 vs 2013 USPSTF lung cancer screening recommendations as well as 6 alternative screening strategies vs the 2013 USPSTF screening strategy. Strategies with a mean ICER lower than $100 000 per QALY were deemed cost-effective.

RESULTS

The 2021 USPSTF recommendation was estimated to be cost-effective compared with the 2013 recommendation, with a mean ICER of $72 564 (range across 4 models, $59 493-$85 837) per QALY gained. The 2021 recommendation was not cost-effective compared with 6 alternative strategies that used the 20 pack-year criterion. Strategies associated with the most cost-effectiveness included those that expanded screening eligibility to include a greater number of former smokers who had not smoked for a longer duration (ie, ≤20 years and ≤25 years since smoking cessation vs ≤15 years since smoking cessation). In particular, the strategy that screened former smokers who quit within the past 25 years and began screening at age 55 years was associated with screening coverage closest to that of the 2021 USPSTF recommendation yet yielded greater cost-effectiveness, with a mean ICER of $66 533 (range across 4 models, $55 693-$80 539).

CONCLUSIONS AND RELEVANCE

This economic evaluation found that the 2021 USPSTF recommendation for lung cancer screening was cost-effective; however, alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years but included individuals who quit smoking within the past 25 years may be more cost-effective and warrant further evaluation.

Smoking Cessation After Lung Cancer Diagnosis and the Risk of Second Primary Lung Cancer: The Multiethnic Cohort Study

Background

Smoking cessation reduces lung cancer mortality. However, little is known about whether diagnosis of lung cancer impacts changes in smoking behaviors. Furthermore, the effects of smoking cessation on the risk of second primary lung cancer (SPLC) have not been established yet. This study aims to examine smoking behavior changes after initial primary lung cancer (IPLC) diagnosis and estimate the effect of smoking cessation on SPLC risk following IPLC diagnosis.

Methods

The study cohort consisted of 986 participants in the Multiethnic Cohort Study who were free of lung cancer and active smokers at baseline (1993-1996), provided 10-year follow-up smoking data (2003-2008), and were diagnosed with IPLC in 1993-2017. The primary outcome was a change in smoking status from “current” at baseline to “former” at 10-year follow-up (ie, smoking cessation), analyzed using logistic regression. The second outcome was SPLC incidence after smoking cessation, estimated using cause-specific Cox regression. All statistical tests were 2-sided.

Results

Among 986 current smokers at baseline, 51.1% reported smoking cessation at 10-year follow-up. The smoking cessation rate was statistically significantly higher (80.6%) for those diagnosed with IPLC between baseline and 10-year follow-up vs those without IPLC diagnosis (45.4%) during the 10-year period (adjusted odds ratio = 5.12, 95% confidence interval [CI] = 3.38 to 7.98; P < .001). Incidence of SPLC was statistically significantly lower among the 504 participants who reported smoking cessation at follow-up compared with those without smoking cessation (adjusted hazard ratio = 0.31, 95% CI = 0.14 to 0.67; P = .003).

Conclusion

Lung cancer diagnosis has a statistically significant impact on smoking cessation. Quitting smoking after IPLC diagnosis may reduce the risk of developing a subsequent malignancy in the lungs.

Predictive modeling of long-term opioid and benzodiazepine use after intradural tumor resection

BACKGROUND CONTEXT

Despite increased awareness of the ongoing opioid epidemic, opioid and benzodiazepine use remain high after spine surgery. In particular, long-term co-prescription of opioids and benzodiazepines have been linked to high risk of overdose-associated death. Tumor patients represent a unique subset of spine surgery patients and few studies have attempted to develop predictive models to anticipate long-term opioid and benzodiazepine use after spinal tumor resection.

METHODS

The IBM Watson Health MarketScan Database and Medicare Supplement were assessed to identify admissions for intradural tumor resection between 2007 and 2015. Adult patients were required to have at least 6 months of continuous preadmission baseline data and 12 months of continuous postdischarge follow-up. Primary outcomes were long-term opioid and benzodiazepine use, defined as at least 6 prescriptions within 12 months. Secondary outcomes were durations of opioid and benzodiazepine prescribing. Logistic regression models, with and without regularization, were trained on an 80% training sample and validated on the withheld 20%.

RESULTS

A total of 1,942 patients were identified. The majority of tumors were extramedullary (74.8%) and benign (62.5%). A minority of patients received arthrodesis (9.2%) and most patients were discharged to home (79.1%). Factors associated with postdischarge opioid use duration include tumor malignancy (vs benign, B=19.8 prescribed-days/year, 95% confidence interval [CI] 1.1-38.5) and intramedullary compartment (vs extramedullary, B=18.1 prescribed-days/year, 95% CI 3.3-32.9). Pre- and perioperative use of prescribed nonsteroidal anti-inflammatory drugs and gabapentin/pregabalin were associated with shorter and longer duration opioid use, respectively. History of opioid and history of benzodiazepine use were both associated with increased postdischarge opioid and benzodiazepine use. Intramedullary location was associated with longer duration postdischarge benzodiazepine use (B=10.3 prescribed-days/year, 95% CI 1.5-19.1). Among assessed models, elastic net regularization demonstrated best predictive performance in the withheld validation cohort when assessing both long-term opioid use (area under curve [AUC]=0.748) and long-term benzodiazepine use (AUC=0.704). Applying our model to the validation set, patients scored as low-risk demonstrated a 4.8% and 2.4% risk of long-term opioid and benzodiazepine use, respectively, compared to 35.2% and 11.1% of high-risk patients.

CONCLUSIONS

We developed and validated a parsimonious, predictive model to anticipate long-term opioid and benzodiazepine use early after intradural tumor resection, providing physicians opportunities to consider alternative pain management strategies.

A Robust Test for Additive Gene-Environment Interaction Under the Trend Effect of Genotype Using an Empirical Bayes-Type Shrinkage Estimator

Evaluating gene by environment (G × E) interaction under an additive risk model (i.e., additive interaction) has gained wider attention. Recently, statistical tests have been proposed for detecting additive interaction, utilizing an assumption on gene-environment (G-E) independence to boost power, that do not rely on restrictive genetic models such as dominant or recessive models. However, a major limitation of these methods is a sharp increase in type I error when this assumption is violated. Our goal was to develop a robust test for additive G × E interaction under the trend effect of genotype, applying an empirical Bayes-type shrinkage estimator of the relative excess risk due to interaction. The proposed method uses a set of constraints to impose the trend effect of genotype and builds an estimator that data-adaptively shrinks an estimator of relative excess risk due to interaction obtained under a general model for G-E dependence using a retrospective likelihood framework. Numerical study under varying levels of departures from G-E independence shows that the proposed method is robust against the violation of the independence assumption while providing an adequate balance between bias and efficiency compared with existing methods. We applied the proposed method to the genetic data of Alzheimer disease and lung cancer.

Treatment and Monitoring Variability in US Metastatic Breast Cancer Care

PURPOSE

Treatment and monitoring options for patients with metastatic breast cancer (MBC) are increasing, but little is known about variability in care. We sought to improve understanding of MBC care and its correlates by analyzing real-world claims data using a search engine with a novel query language to enable temporal electronic phenotyping.

METHODS

Using the Advanced Cohort Engine, we identified 6,180 women who met criteria for having estrogen receptor-positive, human epidermal growth factor receptor 2-negative MBC from IBM MarketScan US insurance claims (2007-2014). We characterized treatment, monitoring, and hospice usage, along with clinical and nonclinical factors affecting care.

RESULTS

We observed wide variability in treatment modality and monitoring across patients and geography. Most women received first-recorded therapy with endocrine (67%) versus chemotherapy, underwent more computed tomography (CT) (76%) than positron emission tomography-CT, and were monitored using tumor markers (58%). Nearly half (46%) met criteria for aggressive disease, which were associated with receiving chemotherapy first, monitoring primarily with CT, and more frequent imaging. Older age was associated with endocrine therapy first, less frequent imaging, and less use of tumor markers. After controlling for clinical factors, care strategies varied significantly by nonclinical factors (median regional income with first-recorded therapy and imaging type, geographic region with these and with imaging frequency and use of tumor markers; P < .0001).

CONCLUSION

Variability in US MBC care is explained by patient and disease factors and by nonclinical factors such as geographic region, suggesting that treatment decisions are influenced by local practice patterns and/or resources. A search engine designed to express complex electronic phenotypes from longitudinal patient records enables the identification of variability in patient care, helping to define disparities and areas for improvement.

Development and Validation of a Risk Prediction Tool for Second Primary Lung Cancer

Background

With advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. Although mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction model available for clinical use to identify high-risk LC survivors for SPLC.

Methods

Using data from 6325 ever-smokers in the Multiethnic Cohort (MEC) study diagnosed with initial primary lung cancer (IPLC) in 1993-2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model’s clinical utility using decision curve analysis and externally validated it using 2 population-based data—Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST)—that included 2963 and 2844 IPLC (101 and 93 SPLC cases), respectively.

Results

Over 14 063 person-years, 145 (2.3%) ever-smoking IPLC patients developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4 to 3.3) and discrimination (area under the receiver operating characteristics [AUC] = 81.9%, 95% CI = 78.2% to 85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th vs 1st quartile (9.5% vs 0.2%; P < .001). Decision curve analysis indicated that in a wide range of 10-year risk thresholds from 1% to 20%, the model yielded a larger net-benefit vs hypothetical all-screening or no-screening scenarios. External validation using PLCO and NLST showed an AUC of 78.8% (95% CI = 74.6% to 82.9%) and 72.7% (95% CI = 67.7% to 77.7%), respectively.

Conclusions

We developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction model can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision making for SPLC surveillance and screening.

Hemorrhage risk of direct oral anticoagulants in real-world venous thromboembolism patients

INTRODUCTION

Venous thromboembolism (VTE) management increasingly involves anticoagulation with direct oral anticoagulants (DOACs). Few studies have used competing-risks analyses to ascertain the mortality-adjusted hemorrhage and recurrent VTE (rVTE) risk of individual DOACs. Furthermore, hemorrhage risk factors in patients treated with apixaban remain underexplored.

MATERIALS AND METHODS

Patients diagnosed with VTE receiving anticoagulation were identified from the Optum Clinformatics Data Mart (2003-2019). Study endpoints included readmissions for intracranial hemorrhage (ICH), non-intracranial hemorrhage (non-ICH hemorrhage), and rVTE. Coarsened exact matching was used to balance baseline clinical characteristics. Complication incidence was evaluated using a competing-risks framework. We additionally modeled hemorrhage risk in apixaban-treated patients.

RESULTS

Overall, 225,559 patients were included, of whom 34,201 received apixaban and 46,007 received rivaroxaban. Compared to rivaroxaban, apixaban was associated with decreased non-ICH hemorrhage (sHR = 0.560, 95%CI = 0.423-0.741), but not ICH, and rVTE (sHR = 0.802, 95%CI = 0.651-0.988) risk. This was primarily in emergent readmissions (sHR[emergent hemorrhage] = 0.515, 95%CI = 0.372-0.711; sHR[emergent rVTE] = 0.636, 95%CI = 0.488-0.830). Contributors to emergent hemorrhage in apixaban-treated patients include older age (sHR = 1.025, 95%CI = 1.011-1.039), female sex (sHR = 1.662, 95%CI = 1.252-2.207), prior prescription antiplatelet therapy (sHR = 1.591, 95%CI = 1.130-2.241), and complicated hypertension (sHR = 1.936, 95%CI = 1.134-3.307). Patients anticipated to be "high-risk" experienced elevated ICH (sHR = 3.396, 95%CI = 1.375-8.388) and non-ICH hemorrhage (sHR = 3.683, 95%CI = 2.957-4.588) incidence.

CONCLUSIONS

In patients with VTE receiving anticoagulation, apixaban was associated with reduced non-ICH hemorrhage and rVTE risk, compared to rivaroxaban. Risk reduction was restricted to emergent readmissions. We present a risk-stratification approach to predict hemorrhage in patients receiving apixaban, potentially guiding future clinical decision-making.

Radiosurgery as a microsurgical adjunct: outcomes after microsurgical resection of intracranial arteriovenous malformations previously treated with stereotactic radiosurgery

OBJECTIVE

Microsurgical resection of arteriovenous malformations (AVMs) can be aided by staged treatment consisting of stereotactic radiosurgery followed by resection in a delayed fashion. This approach is particularly useful for high Spetzler-Martin (SM) grade lesions because radiosurgery can reduce flow through the AVM, downgrade the SM rating, and induce histopathological changes that additively render the AVM more manageable for resection. The authors present their 28-year experience in managing AVMs with adjunctive radiosurgery followed by resection.

METHODS

The authors retrospectively reviewed records of patients treated for cerebral AVMs at their institution between January 1990 and August 2019. All patients who underwent stereotactic radiosurgery (with or without embolization), followed by resection, were included in the study. Of 1245 patients, 95 met the eligibility criteria. Univariate and multivariate regression analyses were performed to assess relationships between key variables and clinical outcomes.

RESULTS

The majority of lesions treated (53.9%) were high grade (SM grade IV-V), 31.5% were intermediate (SM grade III), and 16.6% were low grade (SM grade I-II). Hemorrhage was the initial presenting sign in half of all patients (49.5%). Complete resection was achieved among 84% of patients, whereas 16% had partial resection, the majority of whom received additional radiosurgery. Modified Rankin Scale (mRS) scores of 0-2 were achieved in 79.8% of patients, and 20.2% had poor (mRS scores 3-6) outcomes. Improved (44.8%) or stable (19%) mRS scores were observed among 63.8% of patients, whereas 36.2% had a decline in mRS scores. This includes 22 patients (23.4%) with AVM hemorrhage and 6 deaths (6.7%) outside the perioperative period but prior to AVM obliteration.

CONCLUSIONS

Stereotactic radiosurgery is a useful adjunct in the presurgical management of cerebral AVMs. Multimodal therapy allowed for high rates of AVM obliteration and acceptable morbidity rates, despite the predominance of high-grade lesions in this series of patients.

Impact of Low-Dose Computed Tomography Screening for Primary Lung Cancer on Subsequent Risk of Brain Metastasis

INTRODUCTION

Brain metastasis (BM) is one of the most common metastases from primary lung cancer (PLC). Recently, the National Lung Screening Trial revealed the efficacy of low-dose computed tomography (LDCT) screening on LC mortality reduction. Nevertheless, it remains unknown if early detection of PLC through LDCT may be potentially beneficial in reducing the risk of subsequent metastases. Our study aimed to investigate the impact of LDCT screening for PLC on the risk of developing BM after PLC diagnosis.

METHODS

We used the National Lung Screening Trial data to identify 1502 participants who were diagnosed with PLC in 2002 to 2009 and have follow-up data for BM. Cause-specific competing risk regression was applied to evaluate an association between BM risk and the mode of PLC detection-that is, LDCT screen-detected versus non-LDCT screen-detected. Subgroup analyses were conducted in patients with early stage PLC and those who underwent surgery for PLC.

RESULTS

Of 1502 participants, 41.4% had PLC detected through LDCT screening versus 58.6% detected through other methods, for example, chest radiograph or incidental detection. Patients whose PLC was detected with LDCT screening had a significantly lower 3-year incidence of BM (6.5%) versus those without (11.9%), with a cause-specific hazard ratio (HR) of 0.53 (p = 0.001), adjusting for age at PLC diagnosis, PLC stage, PLC histology, and smoking status. This significant reduction in BM risk among PLCs detected through LDCT screening persisted in subgroups of participants with early stage PLC (HR = 0.47, p = 0.002) and those who underwent surgery (HR = 0.37, p = 0.001).

CONCLUSIONS

Early detection of PLC using LDCT screening is associated with lower risk of BM after PLC diagnosis on the basis of a large population-based study.

Tobacco Smoking and Risk of Second Primary Lung Cancer

INTRODUCTION

Lung cancer survivors are at high risk of developing a second primary lung cancer (SPLC). However, SPLC risk factors have not been established and the impact of tobacco smoking remains controversial. We examined the risk factors for SPLC across multiple epidemiologic cohorts and evaluated the impact of smoking cessation on reducing SPLC risk.

METHODS

We analyzed data from 7059 participants in the Multiethnic Cohort (MEC) diagnosed with an initial primary lung cancer (IPLC) between 1993 and 2017. Cause-specific proportional hazards models estimated SPLC risk. We conducted validation studies using the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (N = 3423 IPLC cases) and European Prospective Investigation into Cancer and Nutrition (N = 4731 IPLC cases) cohorts and pooled the SPLC risk estimates using random effects meta-analysis.

RESULTS

Overall, 163 MEC cases (2.3%) developed SPLC. Smoking pack-years (hazard ratio [HR] = 1.18 per 10 pack-years, p < 0.001) and smoking intensity (HR = 1.30 per 10 cigarettes per day, p < 0.001) were significantly associated with increased SPLC risk. Individuals who met the 2013 U.S. Preventive Services Task Force's screening criteria at IPLC diagnosis also had an increased SPLC risk (HR = 1.92; p < 0.001). Validation studies with the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial and European Prospective Investigation into Cancer and Nutrition revealed consistent results. Meta-analysis yielded pooled HRs of 1.16 per 10 pack-years (pmeta < 0.001), 1.25 per 10 cigarettes per day (pmeta < 0.001), and 1.99 (pmeta < 0.001) for meeting the U.S. Preventive Services Task Force's criteria. In MEC, smoking cessation after IPLC diagnosis was associated with an 83% reduction in SPLC risk (HR = 0.17; p < 0.001).

CONCLUSIONS

Tobacco smoking is a risk factor for SPLC. Smoking cessation may reduce the risk of SPLC. Additional strategies for SPLC surveillance and screening are warranted.

Disparities of National Lung Cancer Screening Guidelines in the US Population

BACKGROUND

Current US Preventive Services Task Force (USPSTF) lung cancer screening guidelines are based on smoking history and age (55-80 years). These guidelines may miss those at higher risk, even at lower exposures of smoking or younger ages, because of other risk factors such as race, family history, or comorbidity. In this study, we characterized the demographic and clinical profiles of those selected by risk-based screening criteria but were missed by USPSTF guidelines in younger (50-54 years) and older (71-80 years) age groups.

METHODS

We used data from the National Health Interview Survey, the CISNET Smoking History Generator, and results of logistic prediction models to simulate lifetime lung cancer risk-factor data for 100 000 individuals in the 1950-1960 birth cohorts. We calculated age-specific 6-year lung cancer risk for each individual from ages 50 to 90 years using the PLCOm2012 model and evaluated age-specific screening eligibility by USPSTF guidelines and by risk-based criteria (varying thresholds between 1.3% and 2.5%).

RESULTS

In the 1950 birth cohort, 5.4% would have been ineligible for screening by USPSTF criteria in their younger ages but eligible based on risk-based criteria. Similarly, 10.4% of the cohort would be ineligible for screening by USPSTF in older ages. Notably, high proportions of blacks were ineligible for screening by USPSTF criteria at younger (15.6%) and older (14.2%) ages, which were statistically significantly greater than those of whites (4.8% and 10.8%, respectively; P < .001). Similar results were observed with other risk thresholds and for the 1960 cohort.

CONCLUSIONS

Further consideration is needed to incorporate comprehensive risk factors, including race and ethnicity, into lung cancer screening to reduce potential racial disparities.

Comparison of Treatments for Cocaine Use Disorder Among Adults: A Systematic Review and Meta-analysis

IMPORTANCE

In the US and the United Kingdom, cocaine use is the second leading cause of illicit drug overdose death. Psychosocial treatments for cocaine use disorder are limited, and no pharmacotherapy is approved for use in the US or Europe.

OBJECTIVE

To compare treatments for active cocaine use among adults.

DATA SOURCES

PubMed and the Cochrane Database of Systematic Reviews were searched for clinical trials published between December 31, 1995, and December 31, 2017.

STUDY SELECTION

This meta-analysis was registered on Covidence.org (study 8731) on December 31, 2015. Clinical trials were included if they (1) had the term cocaine in the article title; (2) were published between December 31, 1995, and December 31, 2017; (3) were written in English; (4) enrolled outpatients 18 years or older with active cocaine use at baseline; and (5) reported treatment group size, treatment duration, retention rates, and urinalysis results for the presence of cocaine metabolites. A study was excluded if (1) more than 25% of participants were not active cocaine users or more than 80% of participants had negative test results for the presence of cocaine metabolites at baseline and (2) it reported only pooled urinalysis results indicating the presence of multiple substances and did not report the specific proportion of positive test results for cocaine metabolites. Multiple reviewers reached criteria consensus. Of 831 records screened, 157 studies (18.9%) met selection criteria and were included in the analysis.

DATA EXTRACTION AND SYNTHESIS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline. Search results were imported from PubMed XML into Covidence.org then Microsoft Excel. Data extraction was completed in 2 iterations to ensure fidelity. Analyses included a multilevel random-effects model, a multilevel mixed-effects meta-regression model, and sensitivity analyses. Treatments were clustered into 11 categories (psychotherapy, contingency management programs, placebo, opioids, psychostimulants, anticonvulsants, dopamine agonists, antidepressants, antipsychotics, miscellaneous medications, and other therapies). Missing data were imputed using multiple imputation by chained equations. The significance threshold for all analyses was P = .05. Data were analyzed using the metafor and mice packages in R software, version 3.3.2 (R Foundation for Statistical Computing). Data were analyzed from January 1, 2018, to February 28, 2021.

MAIN OUTCOMES AND MEASURES

The primary outcome was the intention-to-treat logarithm of the odds ratio (OR) of having a negative urinalysis result for the presence of cocaine metabolites at the end of each treatment period compared with baseline. The hypothesis, which was formulated after data collection, was that no treatment category would have a significant association with objective reductions in cocaine use.

RESULTS

A total of 157 studies comprising 402 treatment groups and 15 842 participants were included. Excluding other therapies, the largest treatment groups across all studies were psychotherapy (mean [SD] number of participants, 40.04 [36.88]) and contingency management programs (mean [SD] number of participants, 37.51 [25.51]). Only contingency management programs were significantly associated with an increased likelihood of having a negative test result for the presence of cocaine (OR, 2.13; 95% CI, 1.62-2.80), and this association remained significant in all sensitivity analyses.

CONCLUSIONS AND RELEVANCE

In this meta-analysis, contingency management programs were associated with reductions in cocaine use among adults. Research efforts and policies that align with this treatment modality may benefit those who actively use cocaine and attenuate societal burdens.

Coordinated Reset Vibrotactile Stimulation Induces Sustained Cumulative Benefits in Parkinson's Disease

BACKGROUND

Abnormal synchronization of neuronal activity in dopaminergic circuits is related to motor impairment in Parkinson's disease (PD). Vibrotactile coordinated reset (vCR) fingertip stimulation aims to counteract excessive synchronization and induce sustained unlearning of pathologic synaptic connectivity and neuronal synchrony. Here, we report two clinical feasibility studies that examine the effect of regular and noisy vCR stimulation on PD motor symptoms. Additionally, in one clinical study (study 1), we examine cortical beta band power changes in the sensorimotor cortex. Lastly, we compare these clinical results in relation to our computational findings.

METHODS

Study 1 examines six PD patients receiving noisy vCR stimulation and their cortical beta power changes after 3 months of daily therapy. Motor evaluations and at-rest electroencephalographic (EEG) recordings were assessed off medication pre- and post-noisy vCR. Study 2 follows three patients for 6+ months, two of whom received daily regular vCR and one patient from study 1 who received daily noisy vCR. Motor evaluations were taken at baseline, and follow-up visits were done approximately every 3 months. Computationally, in a network of leaky integrate-and-fire (LIF) neurons with spike timing-dependent plasticity, we study the differences between regular and noisy vCR by using a stimulus model that reproduces experimentally observed central neuronal phase locking.

RESULTS

Clinically, in both studies, we observed significantly improved motor ability. EEG recordings observed from study 1 indicated a significant decrease in off-medication cortical sensorimotor high beta power (21-30 Hz) at rest after 3 months of daily noisy vCR therapy. Computationally, vCR and noisy vCR cause comparable parameter-robust long-lasting synaptic decoupling and neuronal desynchronization.

CONCLUSION

In these feasibility studies of eight PD patients, regular vCR and noisy vCR were well tolerated, produced no side effects, and delivered sustained cumulative improvement of motor performance, which is congruent with our computational findings. In study 1, reduction of high beta band power over the sensorimotor cortex may suggest noisy vCR is effectively modulating the beta band at the cortical level, which may play a role in improved motor ability. These encouraging therapeutic results enable us to properly plan a proof-of-concept study.

Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography: Modeling Study for the US Preventive Services Task Force

IMPORTANCE

The US Preventive Services Task Force (USPSTF) is updating its 2013 lung cancer screening guidelines, which recommend annual screening for adults aged 55 through 80 years who have a smoking history of at least 30 pack-years and currently smoke or have quit within the past 15 years.

OBJECTIVE

To inform the USPSTF guidelines by estimating the benefits and harms associated with various low-dose computed tomography (LDCT) screening strategies.

DESIGN, SETTING, AND PARTICIPANTS

Comparative simulation modeling with 4 lung cancer natural history models for individuals from the 1950 and 1960 US birth cohorts who were followed up from aged 45 through 90 years.

EXPOSURES

Screening with varying starting ages, stopping ages, and screening frequency. Eligibility criteria based on age, cumulative pack-years, and years since quitting smoking (risk factor-based) or on age and individual lung cancer risk estimation using risk prediction models with varying eligibility thresholds (risk model-based). A total of 1092 LDCT screening strategies were modeled. Full uptake and adherence were assumed for all scenarios.

MAIN OUTCOMES AND MEASURES

Estimated lung cancer deaths averted and life-years gained (benefits) compared with no screening. Estimated lifetime number of LDCT screenings, false-positive results, biopsies, overdiagnosed cases, and radiation-related lung cancer deaths (harms).

RESULTS

Efficient screening programs estimated to yield the most benefits for a given number of screenings were identified. Most of the efficient risk factor-based strategies started screening at aged 50 or 55 years and stopped at aged 80 years. The 2013 USPSTF-recommended criteria were not among the efficient strategies for the 1960 US birth cohort. Annual strategies with a minimum criterion of 20 pack-years of smoking were efficient and, compared with the 2013 USPSTF-recommended criteria, were estimated to increase screening eligibility (20.6%-23.6% vs 14.1% of the population ever eligible), lung cancer deaths averted (469-558 per 100 000 vs 381 per 100 000), and life-years gained (6018-7596 per 100 000 vs 4882 per 100 000). However, these strategies were estimated to result in more false-positive test results (1.9-2.5 per person screened vs 1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (83-94 per 100 000 vs 69 per 100 000), and radiation-related lung cancer deaths (29.0-42.5 per 100 000 vs 20.6 per 100 000). Risk model-based vs risk factor-based strategies were estimated to be associated with more benefits and fewer radiation-related deaths but more overdiagnosed cases.

CONCLUSIONS AND RELEVANCE

Microsimulation modeling studies suggested that LDCT screening for lung cancer compared with no screening may increase lung cancer deaths averted and life-years gained when optimally targeted and implemented. Screening individuals at aged 50 or 55 years through aged 80 years with 20 pack-years or more of smoking exposure was estimated to result in more benefits than the 2013 USPSTF-recommended criteria and less disparity in screening eligibility by sex and race/ethnicity.

Association of Klotho-VS Heterozygosity With Risk of Alzheimer Disease in Individuals Who Carry APOE4

Importance

Identification of genetic factors that interact with the apolipoprotein e4 (APOE4) allele to reduce risk for Alzheimer disease (AD) would accelerate the search for new AD drug targets. Klotho-VS heterozygosity (KL-VSHET+ status) protects against aging-associated phenotypes and cognitive decline, but whether it protects individuals who carry APOE4 from AD remains unclear.

Objectives

To determine if KL-VSHET+ status is associated with reduced AD risk and β-amyloid (Aβ) pathology in individuals who carry APOE4.

Design, Setting, and Participants

This study combined 25 independent case-control, family-based, and longitudinal AD cohorts that recruited referred and volunteer participants and made data available through public repositories. Analyses were stratified by APOE4 status. Three cohorts were used to evaluate conversion risk, 1 provided longitudinal measures of Aβ CSF and PET, and 3 provided cross-sectional measures of Aβ CSF. Genetic data were available from high-density single-nucleotide variant microarrays. All data were collected between September 2015 and September 2019 and analyzed between April 2019 and December 2019.

Main Outcomes and Measures

The risk of AD was evaluated through logistic regression analyses under a case-control design. The risk of conversion to mild cognitive impairment (MCI) or AD was evaluated through competing risks regression. Associations with Aβ, measured from cerebrospinal fluid (CSF) or brain positron emission tomography (PET), were evaluated using linear regression and mixed-effects modeling.

Results

Of 36 530 eligible participants, 13 782 were excluded for analysis exclusion criteria or refusal to participate. Participants were men and women aged 60 years and older who were non-Hispanic and of Northwestern European ancestry and had been diagnosed as being cognitively normal or having MCI or AD. The sample included 20 928 participants in case-control studies, 3008 in conversion studies, 556 in Aβ CSF regression analyses, and 251 in PET regression analyses. The genotype KL-VSHET+ was associated with reduced risk for AD in individuals carrying APOE4 who were 60 years or older (odds ratio, 0.75 [95% CI, 0.67-0.84]; P = 7.4 × 10-7), and this was more prominent at ages 60 to 80 years (odds ratio, 0.69 [95% CI, 0.61-0.79]; P = 3.6 × 10-8). Additionally, control participants carrying APOE4 with KL-VS heterozygosity were at reduced risk of converting to MCI or AD (hazard ratio, 0.64 [95% CI, 0.44-0.94]; P = .02). Finally, in control participants who carried APOE4 and were aged 60 to 80 years, KL-VS heterozygosity was associated with higher Aβ in CSF (β, 0.06 [95% CI, 0.01-0.10]; P = .03) and lower Aβ on PET scans (β, -0.04 [95% CI, -0.07 to -0.00]; P = .04).

Conclusions and Relevance

The genotype KL-VSHET+ is associated with reduced AD risk and Aβ burden in individuals who are aged 60 to 80 years, cognitively normal, and carrying APOE4. Molecular pathways associated with KL merit exploration for novel AD drug targets. The KL-VS genotype should be considered in conjunction with the APOE genotype to refine AD prediction models used in clinical trial enrichment and personalized genetic counseling.

KL∗VS heterozygosity reduces brain amyloid in asymptomatic at-risk APOE∗4 carriers

KLOTHO∗VS heterozygosity (KL∗VS^HET+) was recently shown to be associated with reduced risk of Alzheimer's disease (AD) in APOE∗4 carriers. Additional studies suggest that KL∗VS^HET+ protects against amyloid burden in cognitively normal older subjects, but sample sizes were too small to draw definitive conclusions. We performed a well-powered meta-analysis across 5 independent studies, comprising 3581 pre-clinical participants ages 60-80, to investigate whether KL∗VS^HET+ reduces the risk of having an amyloid-positive positron emission tomography scan. Analyses were stratified by APOE∗4 status. KL∗VS^HET+ reduced the risk of amyloid positivity in APOE∗4 carriers (odds ratio = 0.67 [0.52-0.88]; p = 3.5 × 10^-3), but not in APOE∗4 non-carriers (odds ratio = 0.94 [0.73-1.21]; p = 0.63). The combination of APOE∗4 and KL∗VS genotypes should help enrich AD clinical trials for pre-symptomatic subjects at increased risk of developing amyloid aggregation and AD. KL-related pathways may help elucidate protective mechanisms against amyloid accumulation and merit exploration for novel AD drug targets. Future investigation of the biological mechanisms by which KL interacts with APOE∗4 and AD are warranted.

A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies

BACKGROUND

Risk-prediction models have been proposed to select individuals for lung cancer screening. However, their long-term effects are uncertain. This study evaluates long-term benefits and harms of risk-based screening compared with current United States Preventive Services Task Force (USPSTF) recommendations.

METHODS

Four independent natural history models were used to perform a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. In total, 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, or Lung Cancer Death Risk Assessment Tool [LCDRAT]), and risk threshold were evaluated for a 1950 US birth cohort. Among the evaluated outcomes were percentage of individuals ever screened, screens required, lung cancer deaths averted, life-years gained, and overdiagnosis.

RESULTS

Risk-based screening strategies requiring similar screens among individuals ages 55-80 years as the USPSTF criteria (corresponding risk thresholds: Bach = 2.8%; PLCOm2012 = 1.7%; LCDRAT = 1.7%) averted considerably more lung cancer deaths (Bach = 693; PLCOm2012 = 698; LCDRAT = 696; USPSTF = 613). However, life-years gained were only modestly higher (Bach = 8660; PLCOm2012 = 8862; LCDRAT = 8631; USPSTF = 8590), and risk-based strategies had more overdiagnosed cases (Bach = 149; PLCOm2012 = 147; LCDRAT = 150; USPSTF = 115). Sensitivity analyses suggest excluding individuals with limited life expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by more than 65.3%.

CONCLUSIONS

Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations do. However, they yield modest additional life-years and increased overdiagnosis because of predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life expectancy for determining optimal individual stopping ages.

A Likelihood Ratio Test for Gene-Environment Interaction Based on the Trend Effect of Genotype Under an Additive Risk Model Using the Gene-Environment Independence Assumption

Several statistical methods have been proposed for testing gene-environment (G-E) interactions under additive risk models using data from genome-wide association studies. However, these approaches have strong assumptions from underlying genetic models, such as dominant or recessive effects that are known to be less robust when the true genetic model is unknown. We aimed to develop a robust trend test employing a likelihood ratio test for detecting G-E interaction under an additive risk model, while incorporating the G-E independence assumption to increase power. We used a constrained likelihood to impose 2 sets of constraints for: 1) the linear trend effect of genotype and 2) the additive joint effects of gene and environment. To incorporate the G-E independence assumption, a retrospective likelihood was used versus a standard prospective likelihood. Numerical investigation suggests that the proposed tests are more powerful than tests assuming dominant, recessive, or general models under various parameter settings and under both likelihoods. Incorporation of the independence assumption enhances efficiency by 2.5-fold. We applied the proposed methods to examine the gene-smoking interaction for lung cancer and gene-apolipoprotein E $\varepsilon$4 interaction for Alzheimer disease, which identified 2 interactions between apolipoprotein E $\varepsilon$4 and loci membrane-spanning 4-domains subfamily A (MS4A) and bridging integrator 1 (BIN1) genes at genome-wide significance that were replicated using independent data.

Treatment Tone Spacing and Acute Effects of Acoustic Coordinated Reset Stimulation in Tinnitus Patients

Acoustic coordinated reset (aCR) therapy for tinnitus aims to desynchronize neuronal populations in the auditory cortex that exhibit pathologically increased coincident firing. The original therapeutic paradigm involves fixed spacing of four low-intensity tones centered around the frequency of a tone matching the tinnitus pitch, f _T , but it is unknown whether these tones are optimally spaced for induction of desynchronization. Computational and animal studies suggest that stimulus amplitude, and relatedly, spatial stimulation profiles, of coordinated reset pulses can have a major impact on the degree of desynchronization achievable. In this study, we transform the tone spacing of aCR into a scale that takes into account the frequency selectivity of the auditory system at each therapeutic tone's center frequency via a measure called the gap index. Higher gap indices are indicative of more loosely spaced aCR tones. The gap index was found to be a significant predictor of symptomatic improvement, with larger gap indices, i.e., more loosely spaced aCR tones, resulting in reduction of tinnitus loudness and annoyance scores in the acute stimulation setting. A notable limitation of this study is the intimate relationship of hearing impairment with the gap index. Particularly, the shape of the audiogram in the vicinity of the tinnitus frequency can have a major impact on tone spacing. However, based on our findings we suggest hypotheses-based experimental protocols that may help to disentangle the impact of hearing loss and tone spacing on clinical outcome, to assess the electrophysiologic correlates of clinical improvement, and to elucidate the effects following chronic rather than acute stimulation.

Basal ganglia cavernous malformations: case series and systematic review of surgical management and long-term outcomes

OBJECTIVE

Reports on basal ganglia cavernous malformations (BGCMs) are rare. Here, the authors report on their experience in resecting these malformations to offer insight into this infrequent disease subtype.

METHODS

The authors retrospectively reviewed a prospectively managed departmental database of all deep-seated cerebral cavernous malformations (CCMs) treated at Stanford between 1987 and 2019 and included for further analysis those with a radiographic diagnosis of BGCM. Moreover, a systematic literature review was undertaken using the PubMed and Web of Science databases.

RESULTS

The departmental database search yielded 331 patients with deep-seated CCMs, 44 of whom had a BGCM (13.3%). Headache was the most common presenting sign (53.5%), followed by seizure (32.6%) and hemiparesis (27.9%). Lesion location involved the caudate nucleus in 21.4% of cases compared to 78.6% of cases within the lentiform nucleus. Caudate BGCMs were larger on presentation and were more likely to present to the ependymal surface (p < 0.001) with intraventricular hemorrhage and hydrocephalus (p = 0.005 and 0.007, respectively). Dizziness and diplopia were also more common with lesions involving the caudate. Because of their anatomical location, caudate BGCMs were preferentially treated via an interhemispheric approach and were less likely to be associated with worsening perioperative deficits than lentiform BGCMs (p = 0.006 and 0.045, respectively). Ten patients (25.6%) were clinically worse in the immediate postoperative period, 4 (10.2%) of whom continued to suffer permanent morbidity at the last follow-up. A long-term good outcome (modified Rankin Scale [mRS] score 0-1) was attained in 74.4% of cases compared to the 69.2% of patients who had presented with an mRS score 0-1. Relative to their presenting mRS score, 89.8% of patients had an improved or unchanged status at the last follow-up. The median postoperative follow-up was 11 months (range 1-252 months). Patient outcomes after resection did not differ among surgical approaches; however, patients presenting with hemiparesis and lesions involving the globus pallidus or posterior limb of the internal capsule were more likely to suffer neurological deficits during the immediate perioperative period. Patients who had undergone awake surgeries were more likely to suffer neurological decline at the early as well as the late follow-up. When adjusting for awake craniotomy as a potential confounder of lesion location, a BGCM involving the posterior limb was predictive of developing early postoperative deficits, but this finding did not persist at the long-term follow-up.

CONCLUSIONS

Surgery is a safe and effective treatment modality for managing BGCMs, with an estimated long-term permanent morbidity rate of around 10%.

Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study

BACKGROUND

The use of artificial intelligence (AI) algorithms for the diagnosis of skin diseases has shown promise in experimental settings but has not been yet tested in real-life conditions.

OBJECTIVE

To assess the diagnostic performance and potential clinical utility of a 174-multiclass AI algorithm in a real-life telemedicine setting.

METHODS

Prospective, diagnostic accuracy study including consecutive patients who submitted images for teledermatology evaluation. The treating dermatologist chose a single image to upload to a web application during teleconsultation. A follow-up reader study including nine healthcare providers (3 dermatologists, 3 dermatology residents and 3 general practitioners) was performed.

RESULTS

A total of 340 cases from 281 patients met study inclusion criteria. The mean (SD) age of patients was 33.7 (17.5) years; 63% (n = 177) were female. Exposure to the AI algorithm results was considered useful in 11.8% of visits (n = 40) and the teledermatologist correctly modified the real-time diagnosis in 0.6% (n = 2) of cases. The overall top-1 accuracy of the algorithm (41.2%) was lower than that of the dermatologists (60.1%), residents (57.8%) and general practitioners (49.3%) (all comparisons P < 0.05, in the reader study). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained, the balanced top-1 accuracy of the algorithm (47.6%) was comparable to the dermatologists (49.7%) and residents (47.7%) but superior to the general practitioners (39.7%; P = 0.049). Algorithm performance was associated with patient skin type and image quality.

CONCLUSIONS

A 174-disease class AI algorithm appears to be a promising tool in the triage and evaluation of lesions with patient-taken photographs via telemedicine.

Utility of a Quantitative Approach Using Diffusion Tensor Imaging for Prognostication Regarding Motor and Functional Outcomes in Patients With Surgically Resected Deep Intracranial Cavernous Malformations

BACKGROUND

Resection of deep intracranial cavernous malformations (CMs) is associated with a higher risk of neurological deterioration and uncertainty regarding clinical outcomes.

OBJECTIVE

To examine diffusion tractography imaging (DTI) data evaluating the corticospinal tract (CST) in relation to motor and functional outcomes in patients with surgically resected deep CMs.

METHODS

Perilesional CST was characterized as disrupted, displaced, or normal. Mean fractional anisotropy (FA) values were obtained for whole ipsilateral CST and in 3 regions: subcortical (proximal), perilesional, and distally. Mean FA values in anatomically equivalent regions in the contralateral CST were obtained. Clinical and radiological data were collected independently. Multivariable regression analysis was used for statistical analysis.

RESULTS

A total of 18 patients [brainstem (15) and thalamus/basal ganglia (3); median follow-up: 270 d] were identified over 2 yr. The CST was identified preoperatively as disrupted (6), displaced (8), and normal (4). Five of 6 patients with disruption had weakness. Higher preoperative mean FA values for distal ipsilateral CST segment were associated with better preoperative lower (P < .001), upper limb (P = .004), postoperative lower (P = .005), and upper limb (P < .001) motor examination. Preoperative mean FA values for distal ipsilateral CST segment (P = .001) and contralateral perilesional CST segment (P < .001) were negatively associated with postoperative modified Rankin scale scores.

CONCLUSION

Lower preoperative mean FA values for overall and defined CST segments corresponded to worse patient pre- and postoperative motor examination and/or functional status. FA value for the distal ipsilateral CST segment has prognostic potential with respect to clinical outcomes.