Real-world use, dose intensity, and adherence to enfortumab vedotin in locally advanced or metastatic urothelial cancer

BACKGROUND

Enfortumab vedotin (EV) monotherapy is approved for the treatment of advanced urothelial cancer as later-line therapy (post-immunotherapy and -platinum-chemotherapy) and as earlier-line therapy (cisplatin-ineligible, at least 1 prior therapy). We examined real-world EV monotherapy use, dose intensity and adherence across 280 US cancer clinics.

METHODS

This postmarketing study used data from a nationwide (United States) deidentified patient-level electronic health record-derived database. Included were patients with advanced urothelial cancer initiating EV on or after December 19, 2019 (date of accelerated approval). We summarized characteristics of EV users using descriptive statistics and computed metrics of EV use, EV dose intensity, and EV treatment adherence.

RESULTS

We identified 416 advanced urothelial cancer patients initiating EV monotherapy. More than half of patients (55.3%) received EV as later-line therapy (3L+), and nearly half (44.7%) received EV as earlier line therapy (1 or 2L). Dosing frequency (mean [SD] 2.4 [0.5] treatments per 28 day cycle) and dose (1.1 [0.2] mg/kg) were lower than label indication guidelines (1.25 mg/kg, Day 1, 8, 15 of a 28 day cycle). Only 58.8% of patients received an average of >2 treatments per 28-day cycle.

CONCLUSIONS

Among patients with advanced urothelial cancer treated with EV monotherapy in contemporary practice, EV dosing frequency, and dosage was lower in clinical practice than recommended in the product labeling. Further research is required to understand clinical factors and outcomes associated with the differences observed.

Comparing survival in trial- versus routine-care advanced urothelial cancer patients on immune checkpoint blockade

PURPOSE

Although recent trials involving first-line immune checkpoint inhibitors have expanded treatment options for patients with advanced urothelial carcinoma (aUC) who are ineligible for standard cisplatin-based chemotherapy, there exists limited evidence for whether trial efficacy translates into real-world effectiveness for patients seen in routine care. This retrospective cohort study compares differences in overall survival (OS) between KEYNOTE-052 trial participants and routine-care patients receiving first-line pembrolizumab monotherapy.

METHODS

A routine-care patient cohort was constructed from the Flatiron Health database using trial eligibility criteria and was weighted to balance EHR and trial patient characteristics using matching-adjusted indirect comparisons.

RESULTS

The routine-care cohort was older, more likely to be female, and more often cisplatin-ineligible due to renal dysfunction. ECOG performance status was comparable between the cohorts. Median OS was 9 months (95% CI 7-16) in the weighted routine-care cohort and 11.3 months (9.7-13.1) in the trial cohort. No significant differences between the Kaplan-Meier OS curves were detected (p = 0.76). Survival probabilities were similar between the weighted routine-care and trial cohorts at 12-, 24-, and 36- months (0.45 vs. 0.47, 0.31 vs. 0.31, 0.26 vs. 0.23, respectively). Notably, routine care patients had modestly lower survival at 3 months compared to trial participants (0.69 vs. 0.83, respectively).

CONCLUSION

Our results provide reassurance that cisplatin-ineligible aUC patients receiving first-line immunotherapy in routine care experience similar benefits to those observed in trial patients.

A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records

Accurate outcome and exposure ascertainment in electronic health record (EHR) data, referred to as EHR phenotyping, relies on the completeness and accuracy of EHR data for each individual. However, some individuals, such as those with a greater comorbidity burden, visit the health care system more frequently and thus have more complete data, compared with others. Ignoring such dependence of exposure and outcome misclassification on visit frequency can bias estimates of associations in EHR analysis. We developed a framework for describing the structure of outcome and exposure misclassification due to informative visit processes in EHR data and assessed the utility of a quantitative bias analysis approach to adjusting for bias induced by informative visit patterns. Using simulations, we found that this method produced unbiased estimates across all informative visit structures, if the phenotype sensitivity and specificity were correctly specified. We applied this method in an example where the association between diabetes and progression-free survival in metastatic breast cancer patients may be subject to informative presence bias. The quantitative bias analysis approach allowed us to evaluate robustness of results to informative presence bias and indicated that findings were unlikely to change across a range of plausible values for phenotype sensitivity and specificity. Researchers using EHR data should carefully consider the informative visit structure reflected in their data and use appropriate approaches such as the quantitative bias analysis approach described here to evaluate robustness of study findings.

Racial Differences in Germline Genetic Testing Completion Among Males With Pancreatic, Breast, or Metastatic Prostate Cancers

BACKGROUND

Germline genetic testing is a vital component of guideline-recommended cancer care for males with pancreatic, breast, or metastatic prostate cancers. We sought to determine whether there were racial disparities in germline genetic testing completion in this population.

PATIENTS AND METHODS

This retrospective cohort study included non-Hispanic White and Black males with incident pancreatic, breast, or metastatic prostate cancers between January 1, 2019, and September 30, 2021. Two nationwide cohorts were examined: (1) commercially insured individuals in an administrative claims database, and (2) Veterans receiving care in the Veterans Health Administration. One-year germline genetic testing rates were estimated by using Kaplan-Meier methods. Cox proportional hazards regression was used to test the association between race and genetic testing completion. Causal mediation analyses were performed to investigate whether socioeconomic variables contributed to associations between race and germline testing.

RESULTS

Our cohort consisted of 7,894 males (5,142 commercially insured; 2,752 Veterans). One-year testing rates were 18.0% (95% CI, 16.8%-19.2%) in commercially insured individuals and 14.2% (95% CI, 11.5%-15.0%) in Veterans. Black race was associated with a lower hazard of testing among commercially insured individuals (adjusted hazard ratio [aHR], 0.73; 95% CI, 0.58-0.91; P=.005) but not among Veterans (aHR, 0.99; 95% CI, 0.75-1.32; P=.960). In commercially insured individuals, income (aHR, 0.90; 95% CI, 0.86-0.96) and net worth (aHR, 0.92; 95% CI, 0.86-0.98) mediated racial disparities, whereas education (aHR, 0.98; 95% CI, 0.94-1.01) did not.

CONCLUSIONS

Overall rates of guideline-recommended genetic testing are low in males with pancreatic, breast, or metastatic prostate cancers. Racial disparities in genetic testing among males exist in a commercially insured population, mediated by net worth and household income; these disparities are not seen in the equal-access Veterans Health Administration. Alleviating financial and access barriers may mitigate racial disparities in genetic testing.

Confidence score: a data-driven measure for inclusive systematic reviews considering unpublished preprints

OBJECTIVES

COVID-19, since its emergence in December 2019, has globally impacted research. Over 360 000 COVID-19-related manuscripts have been published on PubMed and preprint servers like medRxiv and bioRxiv, with preprints comprising about 15% of all manuscripts. Yet, the role and impact of preprints on COVID-19 research and evidence synthesis remain uncertain.

MATERIALS AND METHODS

We propose a novel data-driven method for assigning weights to individual preprints in systematic reviews and meta-analyses. This weight termed the "confidence score" is obtained using the survival cure model, also known as the survival mixture model, which takes into account the time elapsed between posting and publication of a preprint, as well as metadata such as the number of first 2-week citations, sample size, and study type.

RESULTS

Using 146 preprints on COVID-19 therapeutics posted from the beginning of the pandemic through April 30, 2021, we validated the confidence scores, showing an area under the curve of 0.95 (95% CI, 0.92-0.98). Through a use case on the effectiveness of hydroxychloroquine, we demonstrated how these scores can be incorporated practically into meta-analyses to properly weigh preprints.

DISCUSSION

It is important to note that our method does not aim to replace existing measures of study quality but rather serves as a supplementary measure that overcomes some limitations of current approaches.

CONCLUSION

Our proposed confidence score has the potential to improve systematic reviews of evidence related to COVID-19 and other clinical conditions by providing a data-driven approach to including unpublished manuscripts.

Identifying clusters of patient comorbidities associated with obstructive sleep apnea using electronic health records

STUDY OBJECTIVES

The objectives of this study were to understand the relative comorbidity burden of obstructive sleep apnea (OSA), determine whether these relationships were modified by sex or age, and identify patient subtypes defined by common comorbidities.

METHODS

Cases with OSA and noncases (controls) were defined using a validated electronic health record (EHR)-based phenotype and matched for age, sex, and time period of follow-up in the EHR. We compared prevalence of the 20 most common comorbidities between matched cases and controls using conditional logistic regression with and without controlling for body mass index. Latent class analysis was used to identify subtypes of OSA cases defined by combinations of these comorbidities.

RESULTS

In total, 60,586 OSA cases were matched to 60,586 controls (from 1,226,755 total controls). Patients with OSA were more likely to have each of the 20 most common comorbidities compared with controls, with odds ratios ranging from 3.1 to 30.8 in the full matched set and 1.3 to 10.2 after body mass index adjustment. Associations between OSA and these comorbidities were generally stronger in females and patients with younger age at diagnosis. We identified 5 distinct subgroups based on EHR-defined comorbidities: High Comorbidity Burden, Low Comorbidity Burden, Cardiovascular Comorbidities, Inflammatory Conditions and Less Obesity, and Inflammatory Conditions and Obesity.

CONCLUSIONS

Our study demonstrates the power of leveraging the EHR to understand the relative health burden of OSA, as well as heterogeneity in these relationships based on age and sex. In addition to enrichment for comorbidities, we identified 5 novel OSA subtypes defined by combinations of comorbidities in the EHR, which may be informative for understanding disease outcomes and improving prevention and clinical care. Overall, this study adds more evidence that OSA is heterogeneous and requires personalized management.

CITATION

Te TT, Keenan BT, Veatch OJ, Boland MR, Hubbard RA, Pack AI. Identifying clusters of patient comorbidities associated with obstructive sleep apnea using electronic health records. J Clin Sleep Med. 2024;20(4):521-533.

Predicting five-year interval second breast cancer risk in women with prior breast cancer

BACKGROUND

Annual surveillance mammography is recommended for women with a personal history of breast cancer. Risk prediction models that estimate mammography failures such as interval second breast cancers could help to tailor surveillance imaging regimens to women's individual risk profiles.

METHODS

In a cohort of women with a history of breast cancer receiving surveillance mammography in the Breast Cancer Surveillance Consortium in 1996-2019, we used LASSO-penalized regression to estimate the probability of an interval second cancer (invasive cancer or ductal carcinoma in situ) in the one-year following a negative surveillance mammogram. Based on predicted risks from this one-year risk model, we generated cumulative risks of an interval second cancer for the five-year period following each mammogram. Model performance was evaluated using cross-validation in the overall cohort and within race and ethnicity strata.

RESULTS

In 173,290 surveillance mammograms, we observed 496 interval cancers. One-year risk models were well-calibrated (expected/observed ratio = 1.00) with good accuracy (area under the receiver operating characteristic curve = 0.64). Model performance was similar across race and ethnicity groups. The median five-year cumulative risk was 1.20% (interquartile range 0.93-1.63%). Median five-year risks were highest in women who were under age 40 or pre- or peri-menopausal at diagnosis and those with estrogen receptor-negative primary breast cancers.

CONCLUSIONS

Our risk model identified women at high risk of interval second breast cancers who may benefit from additional surveillance imaging modalities. Risk models should be evaluated to determine if risk-guided supplemental surveillance imaging improves early detection and decreases surveillance failures.

Risk of Arterial and Venous Thrombotic Events Among Patients with COVID-19: A Multi-National Collaboration of Regulatory Agencies from Canada, Europe, and United States

Purpose

Few studies have examined how the absolute risk of thromboembolism with COVID-19 has evolved over time across different countries. Researchers from the European Medicines Agency, Health Canada, and the United States (US) Food and Drug Administration established a collaboration to evaluate the absolute risk of arterial (ATE) and venous thromboembolism (VTE) in the 90 days after diagnosis of COVID-19 in the ambulatory (eg, outpatient, emergency department, nursing facility) setting from seven countries across North America (Canada, US) and Europe (England, Germany, Italy, Netherlands, and Spain) within periods before and during COVID-19 vaccine availability.

Patients and Methods

We conducted cohort studies of patients initially diagnosed with COVID-19 in the ambulatory setting from the seven specified countries. Patients were followed for 90 days after COVID-19 diagnosis. The primary outcomes were ATE and VTE over 90 days from diagnosis date. We measured country-level estimates of 90-day absolute risk (with 95% confidence intervals) of ATE and VTE.

Results

The seven cohorts included 1,061,565 patients initially diagnosed with COVID-19 in the ambulatory setting before COVID-19 vaccines were available (through November 2020). The 90-day absolute risk of ATE during this period ranged from 0.11% (0.09-0.13%) in Canada to 1.01% (0.97-1.05%) in the US, and the 90-day absolute risk of VTE ranged from 0.23% (0.21-0.26%) in Canada to 0.84% (0.80-0.89%) in England. The seven cohorts included 3,544,062 patients with COVID-19 during vaccine availability (beginning December 2020). The 90-day absolute risk of ATE during this period ranged from 0.06% (0.06-0.07%) in England to 1.04% (1.01-1.06%) in the US, and the 90-day absolute risk of VTE ranged from 0.25% (0.24-0.26%) in England to 1.02% (0.99-1.04%) in the US.

Conclusion

There was heterogeneity by country in 90-day absolute risk of ATE and VTE after ambulatory COVID-19 diagnosis both before and during COVID-19 vaccine availability.

Data gaps and opportunities for modeling cancer health equity

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change.

Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression

Importance

Predictive models using machine learning techniques have potential to improve early detection and management of Alzheimer disease (AD). However, these models potentially have biases and may perpetuate or exacerbate existing disparities.

Objective

To characterize the algorithmic fairness of longitudinal prediction models for AD progression.

Design, Setting, and Participants

This prognostic study investigated the algorithmic fairness of logistic regression, support vector machines, and recurrent neural networks for predicting progression to mild cognitive impairment (MCI) and AD using data from participants in the Alzheimer Disease Neuroimaging Initiative evaluated at 57 sites in the US and Canada. Participants aged 54 to 91 years who contributed data on at least 2 visits between September 2005 and May 2017 were included. Data were analyzed in October 2022.

Exposures

Fairness was quantified across sex, ethnicity, and race groups. Neuropsychological test scores, anatomical features from T1 magnetic resonance imaging, measures extracted from positron emission tomography, and cerebrospinal fluid biomarkers were included as predictors.

Main Outcomes and Measures

Outcome measures quantified fairness of prediction models (logistic regression [LR], support vector machine [SVM], and recurrent neural network [RNN] models), including equal opportunity, equalized odds, and demographic parity. Specifically, if the model exhibited equal sensitivity for all groups, it aligned with the principle of equal opportunity, indicating fairness in predictive performance.

Results

A total of 1730 participants in the cohort (mean [SD] age, 73.81 [6.92] years; 776 females [44.9%]; 69 Hispanic [4.0%] and 1661 non-Hispanic [96.0%]; 29 Asian [1.7%], 77 Black [4.5%], 1599 White [92.4%], and 25 other race [1.4%]) were included. Sensitivity for predicting progression to MCI and AD was lower for Hispanic participants compared with non-Hispanic participants; the difference (SD) in true positive rate ranged from 20.9% (5.5%) for the RNN model to 27.8% (9.8%) for the SVM model in MCI and 24.1% (5.4%) for the RNN model to 48.2% (17.3%) for the LR model in AD. Sensitivity was similarly lower for Black and Asian participants compared with non-Hispanic White participants; for example, the difference (SD) in AD true positive rate was 14.5% (51.6%) in the LR model, 12.3% (35.1%) in the SVM model, and 28.4% (16.8%) in the RNN model for Black vs White participants, and the difference (SD) in MCI true positive rate was 25.6% (13.1%) in the LR model, 24.3% (13.1%) in the SVM model, and 6.8% (18.7%) in the RNN model for Asian vs White participants. Models generally satisfied metrics of fairness with respect to sex, with no significant differences by group, except for cognitively normal (CN)-MCI and MCI-AD transitions (eg, an absolute increase [SD] in the true positive rate of CN-MCI transitions of 10.3% [27.8%] for the LR model).

Conclusions and Relevance

In this study, models were accurate in aggregate but failed to satisfy fairness metrics. These findings suggest that fairness should be considered in the development and use of machine learning models for AD progression.

Sources of Disparities in Surveillance Mammography Performance and Risk-Guided Recommendations for Supplemental Breast Imaging: A Simulation Study

BACKGROUND

Surveillance mammography is recommended for all women with a history of breast cancer. Risk-guided surveillance incorporating advanced imaging modalities based on individual risk of a second cancer could improve cancer detection. However, personalized surveillance may also amplify disparities.

METHODS

In simulated populations using inputs from the Breast Cancer Surveillance Consortium (BCSC), we investigated race- and ethnicity-based disparities. Disparities were decomposed into those due to primary breast cancer and treatment characteristics, social determinants of health (SDOH) and differential error in second cancer ascertainment by modeling populations with or without variation across race and ethnicity in the distribution of these characteristics. We estimated effects of disparities on mammography performance and supplemental imaging recommendations stratified by race and ethnicity.

RESULTS

In simulated cohorts based on 65,446 BCSC surveillance mammograms, when only cancer characteristics varied by race and ethnicity, mammograms for Black women had lower sensitivity compared with the overall population (64.1% vs. 71.1%). Differences between Black women and the overall population were larger when both cancer characteristics and SDOH varied by race and ethnicity (53.8% vs. 71.1%). Basing supplemental imaging recommendations on high predicted second cancer risk resulted in less frequent recommendations for Hispanic (6.7%) and Asian/Pacific Islander women (6.4%) compared with the overall population (10.0%).

CONCLUSIONS

Variation in cancer characteristics and SDOH led to disparities in surveillance mammography performance and recommendations for supplemental imaging.

IMPACT

Risk-guided surveillance imaging may exacerbate disparities. Decision-makers should consider implications for equity in cancer outcomes resulting from implementing risk-guided screening programs. See related In the Spotlight, p. 1479.

Estimation and evaluation of individualized treatment rules following multiple imputation

An individualized treatment rule (ITR) is a function that inputs patient-level information and outputs a recommended treatment. An important focus of precision medicine is to develop optimal ITRs that maximize a population-level distributional summary. However, guidance for estimating and evaluating optimal ITRs in the presence of missing data is limited. Our work is motivated by the Social Incentives to Encourage Physical Activity and Understand Predictors (STEP UP) study. Participants were randomized to a control or one of three interventions designed to increase physical activity and were given wearable devices to record daily steps as a measure of physical activity. Many participants were missing at least one daily step count during the study period. In the primary analysis of the STEP UP trial, multiple imputation (MI) was used to address missingness in daily step counts. Despite ubiquitous use of MI in practice, it has been given relatively little attention in the context of personalized medicine. We fill this gap by describing two frameworks for estimation and evaluation of an optimal ITR following MI and assessing their performance using simulated data. One framework relies on splitting the data into independent training and testing sets for estimation and evaluation, respectively. The other framework estimates an optimal ITR using the full data and constructs anm $$ m $$ -out-of-n $$ n $$ bootstrap confidence interval to evaluate its performance. Finally, we provide an illustrative analysis to estimate and evaluate an optimal ITR from the STEP UP data with a focus on practical considerations such as choosing the number of imputations.

Temporal Trends and Factors Associated with Receipt of Post-mastectomy Radiation After Neoadjuvant Chemotherapy in Women with cT3 Breast Cancer

INTRODUCTION

Given the potential impact of increasingly effective neoadjuvant chemotherapy (NACT) on post-mastectomy radiotherapy (PMRT) recommendations, we examined temporal trends in post-NACT PMRT for cT3 breast cancer.

METHODS

We identified women ≥ 18 years in the National Cancer Database (NCDB) diagnosed 2004-2019 with cT3N0-1M0 breast cancer treated with chemotherapy and mastectomy. Multivariable logistic regression and Cox proportional hazards models were used to estimate associations between pathologic NACT response [complete response (CR), partial response (PR), or no response (NR); or disease progression (DP)] and PMRT and between PMRT and overall survival (OS), respectively.

RESULTS

We identified 39,901 women (Asian/Pacific Islander 1731, Black 5875, Hispanic 3265, White 27,303). Among cN0 patients with CR, PMRT rates declined from 67% in 2004 to 35% in 2019 but remained unchanged for patients with DP. Relative to NR, CR [odds ratio (OR) 0.36, 95% confidence interval (CI) 0.29-0.46] and PR (OR 0.44, 95% CI 0.36-0.55) in cN0 patients were associated with lower odds of PMRT while DP (OR 1.33, 95% CI 1.05-1.69) was associated with higher odds. Among cN1 patients, PMRT rates decreased from 90% to 73% for CR between 2005 and 2019 and increased from 76% to 82% for DP between 2004 and 2019. Relative to NR, CR (OR 0.78, 95% CI 0.63-0.95) was associated with lower odds of PMRT while DP (OR 1.93, 95% CI 1.58-2.37) was associated with higher odds. PMRT was associated with improved OS among cN1 patients (hazard ratio (HR) 0.77, 95% CI 0.67-0.88).

CONCLUSION

CR was associated with decreased PMRT receipt over time, while temporal trends following PR and DP differed by cN status, suggesting that nodal involvement guided PMRT receipt more than in-breast disease.

Association of Time of Day with Delays in Antimicrobial Initiation among Ward Patients with Hospital-Onset Sepsis

Rationale: Although the mainstay of sepsis treatment is timely initiation of broad-spectrum antimicrobials, treatment delays are common, especially among patients who develop hospital-onset sepsis. The time of day has been associated with suboptimal clinical care in several contexts, but its association with treatment initiation among patients with hospital-onset sepsis is unknown. Objectives: Assess the association of time of day with antimicrobial initiation among ward patients with hospital-onset sepsis. Methods: This retrospective cohort study included ward patients who developed hospital-onset sepsis while admitted to five acute care hospitals in a single health system from July 2017 through December 2019. Hospital-onset sepsis was defined by the Centers for Disease Control and Prevention Adult Sepsis Event criteria. We estimated the association between the hour of day and antimicrobial initiation among patients with hospital-onset sepsis using a discrete-time time-to-event model, accounting for time elapsed from sepsis onset. In a secondary analysis, we fit a quantile regression model to estimate the association between the hour of day of sepsis onset and time to antimicrobial initiation. Results: Among 1,672 patients with hospital-onset sepsis, the probability of antimicrobial initiation at any given hour varied nearly fivefold throughout the day, ranging from 3.0% (95% confidence interval [CI], 1.8-4.1%) at 7 a.m. to 13.9% (95% CI, 11.3-16.5%) at 6 p.m., with nadirs at 7 a.m. and 7 p.m. and progressive decline throughout the night shift (13.4% [95% CI, 10.7-16.0%] at 9 p.m. to 3.2% [95% CI, 2.0-4.0] at 6 a.m.). The standardized predicted median time to antimicrobial initiation was 3.2 hours (interquartile range [IQR], 2.5-3.8 h) for sepsis onset during the day shift (7 a.m.-7 p.m.) and 12.9 hours (IQR, 10.9-14.9 h) during the night shift (7 p.m.-7 a.m.). Conclusions: The probability of antimicrobial initiation among patients with new hospital-onset sepsis declined at shift changes and overnight. Time to antimicrobial initiation for patients with sepsis onset overnight was four times longer than for patients with onset during the day. These findings indicate that time of day is associated with important care processes for ward patients with hospital-onset sepsis. Future work should validate these findings in other settings and elucidate underlying mechanisms to inform quality-enhancing interventions.

ReMiND: Recovery of Missing Neuroimaging using Diffusion Models with Application to Alzheimer's Disease

Objective

Missing data is a significant challenge in medical research. In longitudinal studies of Alzheimer's disease (AD) where structural magnetic resonance imaging (MRI) is collected from individuals at multiple time points, participants may miss a study visit or drop out. Additionally, technical issues such as participant motion in the scanner may result in unusable imaging data at designated visits. Such missing data may hinder the development of high-quality imaging-based biomarkers. Furthermore, when imaging data are unavailable in clinical practice, patients may not benefit from effective application of biomarkers for disease diagnosis and monitoring.

Methods

To address the problem of missing MRI data in studies of AD, we introduced a novel 3D diffusion model specifically designed for imputing missing structural MRI (Recovery of Missing Neuroimaging using Diffusion models (ReMiND)). The model generates a whole-brain image conditional on a single structural MRI observed at a past visit or conditional on one past and one future observed structural MRI relative to the missing observation.

Results

Experimental results show that our method can generate high-quality individual 3D structural MRI with high similarity to ground truth, observed images. Additionally, images generated using ReMiND exhibit relatively lower error rates and more accurately estimated rates of atrophy over time in important anatomical brain regions compared with two alternative imputation approaches: forward filling and image generation using variational autoencoders.

Conclusion

Our 3D diffusion model can impute missing structural MRI data at a single designated visit and outperforms alternative methods for imputing whole-brain images that are missing from longitudinal trajectories.

Lung Cancer Screening Decision Aid Designed for a Primary Care Setting: A Randomized Clinical Trial

Importance

Guidelines recommend shared decision-making prior to initiating lung cancer screening (LCS). However, evidence is lacking on how to best implement shared decision-making in clinical practice.

Objective

To evaluate the impact of an LCS Decision Tool (LCSDecTool) on the quality of decision-making and LCS uptake.

Design, Setting, and Participants

This randomized clinical trial enrolled participants at Veteran Affairs Medical Centers in Philadelphia, Pennsylvania; Milwaukee, Wisconsin; and West Haven, Connecticut, from March 18, 2019, to September 29, 2021, with follow-up through July 18, 2022. Individuals aged 55 to 80 years with a smoking history of at least 30 pack-years who were current smokers or had quit within the past 15 years were eligible to participate. Individuals with LCS within 15 months were excluded. Of 1047 individuals who were sent a recruitment letter or had referred themselves, 140 were enrolled.

Intervention

A web-based patient- and clinician-facing LCS decision support tool vs an attention control intervention.

Main Outcome and Measures

The primary outcome was decisional conflict at 1 month. Secondary outcomes included decisional conflict immediately after intervention and 3 months after intervention, knowledge, decisional regret, and anxiety immediately after intervention and 1 and 3 months after intervention and LCS by 6 months.

Results

Of 140 enrolled participants (median age, 64.0 [IQR, 61.0-69.0] years), 129 (92.1%) were men and 11 (7.9%) were women. Of 137 participants with data available, 75 (53.6%) were African American or Black and 62 (44.3%) were White; 4 participants (2.9%) also reported Hispanic or Latino ethnicity. Mean decisional conflict score at 1 month did not differ between the LCSDecTool and control groups (25.7 [95% CI, 21.4-30.1] vs 29.9 [95% CI, 25.6-34.2], respectively; P = .18). Mean LCS knowledge score was greater in the LCSDecTool group immediately after intervention (7.0 [95% CI, 6.3-7.7] vs 4.9 [95% CI, 4.3-5.5]; P < .001) and remained higher at 1 month (6.3 [95% CI, 5.7-6.8] vs 5.2 [95% CI, 4.5-5.8]; P = .03) and 3 months (6.2 [95% CI, 5.6-6.8] vs 5.1 [95% CI, 4.4-5.8]; P = .01). Uptake of LCS was greater in the LCSDecTool group at 6 months (26 of 69 [37.7%] vs 15 of 71 [21.1%]; P = .04).

Conclusions and Relevance

In this randomized clinical trial of an LCSDecTool compared with attention control, no effect on decisional conflict occurred at 1 month. The LCSDecTool used in the primary care setting did not yield a significant difference in decisional conflict. The intervention led to greater knowledge and LCS uptake. These findings can inform future implementation strategies and research in LCS shared decision-making.

Trial Registration

ClinicalTrials.gov Identifier: NCT02899754.

Inverse Probability of Treatment Weighting and Confounder Missingness in Electronic Health Record-based Analyses: A Comparison of Approaches Using Plasmode Simulation

BACKGROUND

Electronic health record (EHR) data represent a critical resource for comparative effectiveness research, allowing investigators to study intervention effects in real-world settings with large patient samples. However, high levels of missingness in confounder variables is common, challenging the perceived validity of EHR-based investigations.

METHODS

We investigated performance of multiple imputation and propensity score (PS) calibration when conducting inverse probability of treatment weights (IPTW)-based comparative effectiveness research using EHR data with missingness in confounder variables and outcome misclassification. Our motivating example compared effectiveness of immunotherapy versus chemotherapy treatment of advanced bladder cancer with missingness in a key prognostic variable. We captured complexity in EHR data structures using a plasmode simulation approach to spike investigator-defined effects into resamples of a cohort of 4361 patients from a nationwide deidentified EHR-derived database. We characterized statistical properties of IPTW hazard ratio estimates when using multiple imputation or PS calibration missingness approaches.

RESULTS

Multiple imputation and PS calibration performed similarly, maintaining ≤0.05 absolute bias in the marginal hazard ratio even when ≥50% of subjects had missing at random or missing not at random confounder data. Multiple imputation required greater computational resources, taking nearly 40 times as long as PS calibration to complete. Outcome misclassification minimally increased bias of both methods.

CONCLUSION

Our results support multiple imputation and PS calibration approaches to missingness in missing completely at random or missing at random confounder variables in EHR-based IPTW comparative effectiveness analyses, even with missingness ≥50%. PS calibration represents a computationally efficient alternative to multiple imputation.

Linking Ambient NO2 Pollution Measures with Electronic Health Record Data to Study Asthma Exacerbations

Electronic health record (EHR)-derived data can be linked to geospatially distributed socioeconomic and environmental factors to conduct large-scale epidemiologic studies. Ambient NO2 is a known environmental risk factor for asthma. However, health exposure studies often rely on data from geographically sparse regulatory monitors that may not reflect true individual exposure. We contrasted use of interpolated NO2 regulatory monitor data with raw satellite measurements and satellite-derived ground estimates, building on previous work which has computed improved exposure estimates from remotely sensed data. Raw satellite and satellite-derived ground measurements captured spatial variation missed by interpolated ground monitor measurements. Multivariable analyses comparing these three NO2 measurement approaches (interpolated monitor, raw satellite, and satellite-derived) revealed a positive relationship between exposure and asthma exacerbations for both satellite measurements. Exposure-outcome relationships using the interpolated monitor NO2 were inconsistent with known relationships to asthma, suggesting that interpolated monitor data might yield misleading results in small region studies.

Risk of admission to hospital with arterial or venous thromboembolism among patients diagnosed in the ambulatory setting with covid-19 compared with influenza: retrospective cohort study

Objective

To measure the 90 day risk of arterial thromboembolism and venous thromboembolism among patients diagnosed with covid-19 in the ambulatory (ie, outpatient, emergency department, or institutional) setting during periods before and during covid-19 vaccine availability and compare results to patients with ambulatory diagnosed influenza.

Design

Retrospective cohort study.

Setting

Four integrated health systems and two national health insurers in the US Food and Drug Administration's Sentinel System.

Participants

Patients with ambulatory diagnosed covid-19 when vaccines were unavailable in the US (period 1, 1 April-30 November 2020; n=272 065) and when vaccines were available in the US (period 2, 1 December 2020-31 May 2021; n=342 103), and patients with ambulatory diagnosed influenza (1 October 2018-30 April 2019; n=118 618).

Main outcome measures

Arterial thromboembolism (hospital diagnosis of acute myocardial infarction or ischemic stroke) and venous thromboembolism (hospital diagnosis of acute deep venous thrombosis or pulmonary embolism) within 90 days after ambulatory covid-19 or influenza diagnosis. We developed propensity scores to account for differences between the cohorts and used weighted Cox regression to estimate adjusted hazard ratios of outcomes with 95% confidence intervals for covid-19 during periods 1 and 2 versus influenza.

Results

90 day absolute risk of arterial thromboembolism with covid-19 was 1.01% (95% confidence interval 0.97% to 1.05%) during period 1, 1.06% (1.03% to 1.10%) during period 2, and with influenza was 0.45% (0.41% to 0.49%). The risk of arterial thromboembolism was higher for patients with covid-19 during period 1 (adjusted hazard ratio 1.53 (95% confidence interval 1.38 to 1.69)) and period 2 (1.69 (1.53 to 1.86)) than for patients with influenza. 90 day absolute risk of venous thromboembolism with covid-19 was 0.73% (0.70% to 0.77%) during period 1, 0.88% (0.84 to 0.91%) during period 2, and with influenza was 0.18% (0.16% to 0.21%). Risk of venous thromboembolism was higher with covid-19 during period 1 (adjusted hazard ratio 2.86 (2.46 to 3.32)) and period 2 (3.56 (3.08 to 4.12)) than with influenza.

Conclusions

Patients diagnosed with covid-19 in the ambulatory setting had a higher 90 day risk of admission to hospital with arterial thromboembolism and venous thromboembolism both before and after covid-19 vaccine availability compared with patients with influenza.

Outcomes in infants with unprovoked venous thromboembolism: A retrospective cohort study

Background

Although children aged <1 year have a relatively high rate of venous thromboembolism (VTE) compared to older children, most have additional prothrombotic risk factors. Unprovoked VTE is rare, and little is known about this population, particularly the risk of recurrent VTE.

Objectives

We aimed to determine the rate of recurrent VTE in infants with prior unprovoked VTE and evaluate long-term, end-organ outcomes for infants with renal and intracranial vein thrombosis.

Methods

Infants <1 year of age with an unprovoked VTE between 2003 and 2021 at a single institution were included. Time to recurrent event and anticoagulation duration were summarized using the Kaplan-Meier estimator. Neurologic outcomes were summarized with the pediatric stroke outcome measure for infants with cerebral sinovenous, medullary, or cortical vein thrombosis. Kidney outcomes were summarized with estimated glomerular filtration rates for infants with renal vein thrombosis. Anticoagulation was summarized.

Results

Forty infants with intracranial, renal, portal, and extremity VTE met the inclusion criteria and were followed for a median of 4.7 years (IQR, 2.1-8.5). Most VTE events occurred during the first month of life. There was 1 recurrent event in 237 person-years of follow-up (incidence rate, 4 per 1000 [95% CI, 0.6-29.9] person-years). In outpatient follow-up, 40% of infants with intracranial thrombosis met criteria for moderate or severe neurologic outcomes and two-thirds of infants with a prior renal vein thrombosis had abnormal kidney function (estimated glomerular filtration rate < 90 mL/min/1.73 m2).

Conclusion

There is a low rate of recurrent VTE but significant end-organ morbidity in infants with unprovoked VTE.

Variation in second breast cancer risk after primary invasive cancer by time since primary cancer diagnosis and estrogen receptor status

BACKGROUND

In women with previously treated breast cancer, occurrence and timing of second breast cancers have implications for surveillance. The authors examined the timing of second breast cancers by primary cancer estrogen receptor (ER) status in the Breast Cancer Surveillance Consortium.

METHODS

Women who were diagnosed with American Joint Commission on Cancer stage I-III breast cancer were identified within six Breast Cancer Surveillance Consortium registries from 2000 to 2017. Characteristics collected at primary breast cancer diagnosis included demographics, ER status, and treatment. Second breast cancer events included subsequent ipsilateral or contralateral breast cancers diagnosed >6 months after primary diagnosis. The authors examined cumulative incidence and second breast cancer rates by primary cancer ER status during 1-5 versus 6-10 years after diagnosis.

RESULTS

At 10 years, the cumulative second breast cancer incidence was 11.8% (95% confidence interval [CI], 10.7%-13.1%) for women with ER-negative disease and 7.5% (95% CI, 7.0%-8.0%) for those with ER-positive disease. Women with ER-negative cancer had higher second breast cancer rates than those with ER-positive cancer during the first 5 years of follow-up (16.0 per 1000 person-years [PY]; 95% CI, 14.2-17.9 per 1000 PY; vs. 7.8 per 1000 PY; 95% CI, 7.3-8.4 per 1000 PY, respectively). After 5 years, second breast cancer rates were similar for women with ER-negative versus ER-positive breast cancer (12.1 per 1000 PY; 95% CI, 9.9-14.7; vs. 9.3 per 1000 PY; 95% CI, 8.4-10.3 per 1000 PY, respectively).

CONCLUSIONS

ER-negative primary breast cancers are associated with a higher risk of second breast cancers than ER-positive cancers during the first 5 years after diagnosis. Further study is needed to examine the potential benefit of more intensive surveillance targeting these women in the early postdiagnosis period.

Performance of Statistical and Machine Learning Risk Prediction Models for Surveillance Benefits and Failures in Breast Cancer Survivors

BACKGROUND

Machine learning (ML) approaches facilitate risk prediction model development using high-dimensional predictors and higher-order interactions at the cost of model interpretability and transparency. We compared the relative predictive performance of statistical and ML models to guide modeling strategy selection for surveillance mammography outcomes in women with a personal history of breast cancer (PHBC).

METHODS

We cross-validated seven risk prediction models for two surveillance outcomes, failure (breast cancer within 12 months of a negative surveillance mammogram) and benefit (surveillance-detected breast cancer). We included 9,447 mammograms (495 failures, 1,414 benefits, and 7,538 nonevents) from years 1996 to 2017 using a 1:4 matched case-control samples of women with PHBC in the Breast Cancer Surveillance Consortium. We assessed model performance of conventional regression, regularized regressions (LASSO and elastic-net), and ML methods (random forests and gradient boosting machines) by evaluating their calibration and, among well-calibrated models, comparing the area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI).

RESULTS

LASSO and elastic-net consistently provided well-calibrated predicted risks for surveillance failure and benefit. The AUCs of LASSO and elastic-net were both 0.63 (95% CI, 0.60-0.66) for surveillance failure and 0.66 (95% CI, 0.64-0.68) for surveillance benefit, the highest among well-calibrated models.

CONCLUSIONS

For predicting breast cancer surveillance mammography outcomes, regularized regression outperformed other modeling approaches and balanced the trade-off between model flexibility and interpretability.

IMPACT

Regularized regression may be preferred for developing risk prediction models in other contexts with rare outcomes, similar training sample sizes, and low-dimensional features.

Exposure to US Cancer Drugs With Lack of Confirmed Benefit After US Food and Drug Administration Accelerated Approval

This cross-sectional study evaluates patient exposure to oncology drugs withdrawn from the US Food and Drug Administration (FDA) Accelerated Approval program.

Performance of Multiple Imputation Using Modern Machine Learning Methods in Electronic Health Records Data

BACKGROUND

Missing data are common in studies using electronic health records (EHRs)-derived data. Missingness in EHR data is related to healthcare utilization patterns, resulting in complex and potentially missing not at random missingness mechanisms. Prior research has suggested that machine learning-based multiple imputation methods may outperform traditional methods and may perform well even in settings of missing not at random missingness.

METHODS

We used plasmode simulations based on a nationwide EHR-derived de-identified database for patients with metastatic urothelial carcinoma to compare the performance of multiple imputation using chained equations, random forests, and denoising autoencoders in terms of bias and precision of hazard ratio estimates under varying proportions of observations with missing values and missingness mechanisms (missing completely at random, missing at random, and missing not at random).

RESULTS

Multiple imputation by chained equations and random forest methods had low bias and similar standard errors for parameter estimates under missingness completely at random. Under missingness at random, denoising autoencoders had higher bias than multiple imputation by chained equations and random forests. Contrary to results of prior studies of denoising autoencoders, all methods exhibited substantial bias under missingness not at random, with bias increasing in direct proportion to the amount of missing data.

CONCLUSIONS

We found no advantage of denoising autoencoders for multiple imputation in the setting of an epidemiologic study conducted using EHR data. Results suggested that denoising autoencoders may overfit the data leading to poor confounder control. Use of more flexible imputation approaches does not mitigate bias induced by missingness not at random and can produce estimates with spurious precision.

Uptake of maintenance immunotherapy and changes in upstream treatment selection in patients with advanced urothelial cancer (aUC)

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Background: In July 2020, the FDA approved avelumab, an immune checkpoint inhibitor (ICI), for maintenance treatment of aUC that has not progressed with first-line (1L) platinum-containing chemotherapy (chemo). Availability of avelumab may have influenced upstream treatment selection between 1L chemo and 1L ICI (pembrolizumab or atezolizumab). We described avelumab use in real-world practice and determined whether 1L treatment choice changed following its approval. Methods: This cohort study used Flatiron Health’s nationwide de-identified EHR-derived database. Included patients started 1L therapy for aUC in the US before (April 1 2017 to June 30 2020) or after (July 1 2020 to May 31 2022) avelumab approval. We calculated the proportion of patients initiating 1L chemo (carboplatin- or cisplatin-based) or ICI during the pre- and post- avelumab approval periods. Time trends were estimated using multinomial logistic regression for 1L treatment choice regressed on time modeled via a natural cubic spline, allowing for a discontinuity in the time trend at the time of FDA approval. Differences in probabilities of 1L treatment in July 2020 (immediately following approval) compared to June 2020 (immediately prior to approval) were calculated. Maintenance avelumab use was described among patients treated with 1L chemo in the post-approval period, and in a sensitivity analysis, among ‘maintenance eligible’ patients defined as those who were progression-free 28 weeks after 1L chemo start. Results: Among all 1L treatment initiators (n=3,507), the FDA approval of maintenance avelumab was followed by increased use of 1L carboplatin-based chemo (+9.9%; 95% CI 1.1-17.2%) but no significant changes in the use of ICI (-5.8%; 95% CI -15.9-4.4%) or cisplatin-based chemo (-4.2%; 95% CI -12.7-5.2%) (Table). Among patients treated with 1L platinum-chemo (n=485), probability of initiating maintenance avelumab increased over time. In the 22 months after approval, approximately 20.4% (n=99/485) of all 1L chemo-treated patients and 24.3% (n=78/321) of maintenance eligible patients received maintenance avelumab. Conclusions: We found modest uptake of maintenance avelumab for aUC after FDA approval. Potential reasons include limited clinician awareness of maintenance immunotherapy and/or patient preferences against long-term treatment after response to initial chemo. Our finding of higher treatment starts with carboplatin-based chemo in the post-maintenance period suggests increasing preference by clinicians of a strategy that provides patients an opportunity for two effective treatment options. Real-world data can provide important insights on community response to regulatory approvals. [Table: see text]

Cumulative 6-Year Risk of Screen-Detected Ductal Carcinoma In Situ by Screening Frequency

IMPORTANCE

Detection of ductal carcinoma in situ (DCIS) by mammography screening is a controversial outcome with potential benefits and harms. The association of mammography screening interval and woman's risk factors with the likelihood of DCIS detection after multiple screening rounds is poorly understood.

OBJECTIVE

To develop a 6-year risk prediction model for screen-detected DCIS according to mammography screening interval and women's risk factors.

DESIGN, SETTING, AND PARTICIPANTS

This Breast Cancer Surveillance Consortium cohort study assessed women aged 40 to 74 years undergoing mammography screening (digital mammography or digital breast tomosynthesis) from January 1, 2005, to December 31, 2020, at breast imaging facilities within 6 geographically diverse registries of the consortium. Data were analyzed between February and June 2022.

EXPOSURES

Screening interval (annual, biennial, or triennial), age, menopausal status, race and ethnicity, family history of breast cancer, benign breast biopsy history, breast density, body mass index, age at first birth, and false-positive mammography history.

MAIN OUTCOMES AND MEASURES

Screen-detected DCIS defined as a DCIS diagnosis within 12 months after a positive screening mammography result, with no concurrent invasive disease.

RESULTS

A total of 916 931 women (median [IQR] age at baseline, 54 [46-62] years; 12% Asian, 9% Black, 5% Hispanic/Latina, 69% White, 2% other or multiple races, and 4% missing) met the eligibility criteria, with 3757 screen-detected DCIS diagnoses. Screening round-specific risk estimates from multivariable logistic regression were well calibrated (expected-observed ratio, 1.00; 95% CI, 0.97-1.03) with a cross-validated area under the receiver operating characteristic curve of 0.639 (95% CI, 0.630-0.648). Cumulative 6-year risk of screen-detected DCIS estimated from screening round-specific risk estimates, accounting for competing risks of death and invasive cancer, varied widely by all included risk factors. Cumulative 6-year screen-detected DCIS risk increased with age and shorter screening interval. Among women aged 40 to 49 years, the mean 6-year screen-detected DCIS risk was 0.30% (IQR, 0.21%-0.37%) for annual screening, 0.21% (IQR, 0.14%-0.26%) for biennial screening, and 0.17% (IQR, 0.12%-0.22%) for triennial screening. Among women aged 70 to 74 years, the mean cumulative risks were 0.58% (IQR, 0.41%-0.69%) after 6 annual screens, 0.40% (IQR, 0.28%-0.48%) for 3 biennial screens, and 0.33% (IQR, 0.23%-0.39%) after 2 triennial screens.

CONCLUSIONS AND RELEVANCE

In this cohort study, 6-year screen-detected DCIS risk was higher with annual screening compared with biennial or triennial screening intervals. Estimates from the prediction model, along with risk estimates of other screening benefits and harms, could help inform policy makers' discussions of screening strategies.

High rate of recurrent venous thromboembolism in children and adolescents with unprovoked venous thromboembolism

BACKGROUND

Unprovoked venous thromboembolism (VTE) is rare in pediatrics. Current recommendations for anticoagulation duration after unprovoked VTE differ for pediatric and adult populations.

OBJECTIVES

This single-center, retrospective cohort study aimed to determine the incidence rate of recurrent VTE in children and adolescents with unprovoked VTE, evaluate the potential risk factors for recurrence, and describe the anticoagulation regimens and bleeding in this population.

METHODS

Children with an index, unprovoked VTE at the age of 1 to <21 years between 2003 and 2021 were included. The time to recurrent VTE and anticoagulation duration were summarized using Kaplan-Meier estimators. Clinical covariates were assessed for association with recurrence using stratified Kaplan-Meier curves and univariate Cox proportional hazards regression.

RESULTS

Eighty-five children met the inclusion criteria, and there were 26 recurrent events in 250 person-years of follow-up (incidence rate = 104 [95% CI, 71-153] per 1000 person-years). An age of ≥12 years at index VTE (hazard ratio [HR], 7.56; 95% CI, 1.60-35.83) and inherited thrombophilia (HR, 2.28; 95% CI, 1.05-4.95) were significantly associated with recurrent VTE. Female sex had a nonstatistically significant decreased hazard of recurrence (HR, 0.56; 95% CI, 0.25-1.27). Duration of anticoagulation was variable, with a median duration of 274 days (IQR, 101-2357) for outpatient therapeutic anticoagulation. Twelve of the 26 (46%) recurrent events occurred while anticoagulation was prescribed.

CONCLUSION

The incidence rate of recurrent VTE in pediatric patients with a prior unprovoked VTE is high, particularly for adolescents and those with inherited thrombophilia. Therefore, future research should focus on the efficacy of prolonged anticoagulation for this population.

Augmenting control arms with real-world data for cancer trials: Hybrid control arm methods and considerations

Background

Hybrid controlled trials with real-world data (RWD), where the control arm is composed of both trial and real-world patients, could facilitate research when the feasibility of randomized controlled trials (RCTs) is challenging and single-arm trials would provide insufficient information.

Methods

We propose a frequentist two-step borrowing method to construct hybrid control arms. We use parameters informed by a completed randomized trial in metastatic triple-negative breast cancer to simulate the operating characteristics of dynamic and static borrowing methods, highlighting key trade-offs and analytic decisions in the design of hybrid studies.

Results

Simulated data were generated under varying residual-bias assumptions (no bias: HR_RWD = 1) and experimental treatment effects (target trial scenario: HR_Exp = 0.78). Under the target scenario with no residual bias, all borrowing methods achieved the desired 88% power, an improvement over the reference model (74% power) that does not borrow information externally. The effective number of external events tended to decrease with higher bias between RWD and RCT (i.e. HR_RWD away from 1), and with weaker experimental treatment effects (i.e. HR_Exp closer to 1). All dynamic borrowing methods illustrated (but not the static power prior) cap the maximum Type 1 error over the residual-bias range considered. Our two-step model achieved comparable results for power, type 1 error, and effective number of external events borrowed compared to other borrowing methodologies.

Conclusion

By pairing high-quality external data with rigorous simulations, researchers have the potential to design hybrid controlled trials that better meet the needs of patients and drug development.

Patient and tumour characteristics of screening-age adults diagnosed with screen-detected versus symptomatic colon cancer

AIM

International studies have shown that most colon cancers are diagnosed among people with symptoms, but research is limited in the United States. Here, we conducted a retrospective study of adults aged 50-85 years diagnosed with stage I-IIIA colon cancer between 1995 and 2014 in two US healthcare systems.

METHODS

Mode of detection (screening or symptomatic) was ascertained from medical records. We estimated unadjusted odds ratios (OR) and 95% confidence intervals (CI) comparing detection mode by patient factors at diagnosis (year, age, sex, race, smoking status, body mass index [BMI], Charlson score), prediagnostic primary care utilization, and tumour characteristics (stage, location).

RESULTS

Of 1,675 people with colon cancer, 38.4% were screen-detected, while 61.6% were diagnosed following symptomatic presentation. Screen-detected cancer was more common among those diagnosed between 2010 and 2014 versus 1995-1999 (OR 1.65, 95% CI: 1.19-2.28), and those with a BMI of 25-<30 kg/m² (OR 1.54, 95% CI: 1.21-1.98) or ≥30 kg/m² (OR 1.52, 95% CI: 1.18-1.96) versus <25 kg/m² . Screen-detected cancer was less common among people aged 76-85 (OR 0.50, 95% CI: 0.39-0.65) versus 50-64, those with comorbidity scores >0 (OR 0.71, 95% CI: 0.56-0.91 for score = 1, OR 0.34, 95% CI: 0.26-0.45 for score = 2+), and those with 2+ prediagnostic primary care visits (OR 0.53, 95% CI: 0.37-0.76) versus 0 visits. The odds of screen detection were lower among patients diagnosed with stage IIA (OR 0.33, 95% CI = 0.27-0.41) or IIB (OR 0.12, 95% CI: 0.06-0.24) cancers versus stage I.

CONCLUSIONS

Most colon cancers among screen-eligible adults were diagnosed following symptomatic presentation. Even with increasing screening rates over time, research is needed to better understand why specific groups are more likely to be diagnosed when symptomatic and identify opportunities for interventions.

Very high PD-L1 expression as a prognostic indicator of overall survival among patients with advanced non-small cell lung cancer receiving anti-PD-(L)1 monotherapies in routine practice

PURPOSE

Programmed death or ligand-1 (PD-(L)1) pathway inhibitors confer improved survival as the first-line treatment for advanced non-small cell lung cancer (aNSCLC) in patients with PD-L1 expression (PD-L1 + e ≥ 50%) compared to platinum-doublet chemotherapy and have become a standard therapy. Some recent evidence suggests that among aNSCLC patients with PD-L1 + e of ≥50% receiving pembrolizumab monotherapy, very high levels of PD-L1 + e (≥90%) may be associated with better outcomes. We sought to assess whether very high PD-L1 + e (≥90%) compared to high PD-L1 + e (50%-89%) is associated with an overall survival benefit in aNSCLC patients receiving anti-PD-(L)1 monotherapies.

METHODS

We conducted a single-site retrospective cohort study of aNSCLC patients who initiated PD-(L)1 inhibitor monotherapy as the first-line treatment from October 24, 2016, to August 25, 2021, and had a PD-L1 + e ≥ 50%. The primary outcome was overall survival, measured from the start of the first-line PD-(L)1 inhibitor monotherapy (index date) to date of death or last confirmed activity prior to the cohort exit date. Propensity score-based inverse probability weighting (IPW) was used to control for confounding in Kaplan-Meier curves and Cox proportional hazard regression analysis.

RESULTS

One hundred sixty-six patients with aNSCLC receiving PD-(L)1 inhibitor monotherapy met inclusion criteria. 54% were female, 90% received pembrolizumab, median age was 68 years, 70% had non-squamous cell carcinoma, 94% had a history of smoking, 29% had a KRAS mutation, and 37% had very high PD-L1 + e. Unweighted covariates at cohort entry were similar between groups (absolute standardized mean differences [SMDs] <0.1) except for race (SMD = 0.2); age at therapy initiation (SMD = 0.13); smoking status (SMD = 0.13), and BRAF mutation status (SMD = 0.11). After weighting, baseline covariates were well balanced (all absolute SMDs <0.1). In the weighted analysis, having a very high PD-L1 + e was associated with lower mortality (weighted hazard ratio 0.57, 95% CI 0.36-0.90) and longer median survival: 3.85 versus 1.49 years.

CONCLUSIONS

Very high PD-L1 + e (≥90%) was associated with an overall survival benefit over high PD-L1 + e (50%-89%) in patients receiving the first-line PD-(L)1 inhibitor monotherapy in a model controlling for potential confounders. These findings should be confirmed in a larger real-world data set.

Mammographic follow-up before and during the COVID-19 pandemic

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Background: Mammography adapted during the COVID-19 pandemic to accommodate social-distancing guidelines and minimize risk of exposure, but it is unclear how these accommodations potentially provoked existing inefficiencies or illuminated opportunities to redress them. The goal of this study was to compare rates of (1) diagnostic follow-up after a BIRADS 0 (i.e., incomplete) screening mammogram and (2) biopsy following a BIRADS 4 or 5 (i.e., biopsy recommended) diagnostic mammogram before and after onset of the pandemic. Methods: We included women ≥18y who underwent a BIRADS 0 screening mammogram and/or BIRADS 4-5 diagnostic mammogram at our institution from 3/15/19-3/15/21. Given seasonal variation in care receipt, pre-COVID (3/15/2019-3/15/20) and COVID (3/15/20-3/15/21) time periods were compared at a quarterly level. Case-mix adjusted associations between time-to-follow-up and COVID vs pre-COVID quarters (Q1-4) were estimated using multivariate Cox proportional hazards models. Results: We identified 17,918 women (Asian: 985, Black: 4054, Hispanic: 840, White: 11,302) who received a total of 14,388 BIRADS 0 screening and 6410 BIRADS 4 or 5 diagnostic mammograms. There were far fewer diagnostic mammograms in COVID Q1 vs pre-COVID Q1 (Table), and they were more likely to be followed up with biopsy (HR 1.21 [95% CI 1.03-1.44], p = 0.023). COVID Q3 (HR 0.92 [95% CI 0.86-0.98], p = 0.002) and Q4 (HR 0.88 [95% CI 0.83-0.95], p < 0.001) screens were less likely to be followed up with diagnostic mammograms but volumes were higher vs the respective pre-COVID quarters (Table). However, COVID Q3 patients with BIRADS 4 or 5 mammograms were 18% more likely to undergo biopsy than their pre-COVID Q3 counterparts (HR 1.18 [95% CI 1.07-1.31], p < 0.0001, Table) despite higher COVID volumes. Conclusions: Early in the pandemic, patients were more likely to receive mammographic follow-up, potentially due to lower patient volumes and enforced strategies for more efficient, less time-intensive care delivery. These gains were lost with regards to diagnostic follow-up for screening mammograms but maintained with regards to performing biopsies. As volumes return to or surpass pre-pandemic levels, health systems must work to identify and preserve operational efficiencies gained during the early pandemic.[Table: see text]

Association of Unit Census with Delays in Antimicrobial Initiation among Ward Patients with Hospital-acquired Sepsis

Rationale: Patients with hospital-acquired sepsis (HAS) experience higher mortality and delayed care compared with those with community-acquired sepsis. Capacity strain, the extent to which demand for hospital resources exceeds availability, thus impacting patient care, is a possible mechanism underlying antimicrobial delays for HAS but has not been studied. Objectives: Assess the association of ward census with the timing of antimicrobial initiation among ward patients with HAS. Methods: This retrospective cohort study included adult patients hospitalized at five acute care hospitals between July 2017 and December 2019 who developed ward-onset HAS, distinguished from community-acquired sepsis by onset after 48 hours of hospitalization. The primary exposure was ward census, measured as the number of patients present in each ward at each hour, standardized by quarter and year. The primary outcome was time from sepsis onset to antimicrobial initiation. We used quantile regression to assess the association between ward census at sepsis onset and time to antimicrobial initiation among patients with HAS defined by Centers for Disease Control and Prevention Adult Sepsis Event criteria. We adjusted for hospital, year, quarter, age, sex, race, ethnicity, severity of illness, admission diagnosis, and service type. Results: A total of 1,672 hospitalizations included at least one ward-onset HAS episode. Median time to antimicrobial initiation after HAS onset was 4.1 hours (interquartile range, 0.4-22.3). Marginal adjusted time to antimicrobial initiation ranged from 3.6 hours (95% confidence interval [CI], 2.4-4.8 h) to 6.8 hours (95% CI, 5.3-8.4 h) at census levels 2 standard deviations (SDs) below and above the ward-specific mean, respectively. Each 1-SD increase in ward census at sepsis onset, representing a median of 2.4 patients, was associated with an increase in time to antimicrobial initiation of 0.80 hours (95% CI, 0.32-1.29 h). In sensitivity analyses, results were consistent across severity of illness and electronic health record-based sepsis definitions. Conclusions: Time to antimicrobial initiation increased with increasing census among ward patients with HAS. These findings suggest that delays in care for HAS may be related to ward capacity strain as measured by census. Additional work is needed to validate these findings and identify potential mechanisms operating through clinician behavior and care delivery processes.

Association of COVID-19 vs Influenza With Risk of Arterial and Venous Thrombotic Events Among Hospitalized Patients

IMPORTANCE

The incidence of arterial thromboembolism and venous thromboembolism in persons with COVID-19 remains unclear.

OBJECTIVE

To measure the 90-day risk of arterial thromboembolism and venous thromboembolism in patients hospitalized with COVID-19 before or during COVID-19 vaccine availability vs patients hospitalized with influenza.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study of 41 443 patients hospitalized with COVID-19 before vaccine availability (April-November 2020), 44 194 patients hospitalized with COVID-19 during vaccine availability (December 2020-May 2021), and 8269 patients hospitalized with influenza (October 2018-April 2019) in the US Food and Drug Administration Sentinel System (data from 2 national health insurers and 4 regional integrated health systems).

EXPOSURES

COVID-19 or influenza (identified by hospital diagnosis or nucleic acid test).

MAIN OUTCOMES AND MEASURES

Hospital diagnosis of arterial thromboembolism (acute myocardial infarction or ischemic stroke) and venous thromboembolism (deep vein thrombosis or pulmonary embolism) within 90 days. Outcomes were ascertained through July 2019 for patients with influenza and through August 2021 for patients with COVID-19. Propensity scores with fine stratification were developed to account for differences between the influenza and COVID-19 cohorts. Weighted Cox regression was used to estimate the adjusted hazard ratios (HRs) for outcomes during each COVID-19 vaccine availability period vs the influenza period.

RESULTS

A total of 85 637 patients with COVID-19 (mean age, 72 [SD, 13.0] years; 50.5% were male) and 8269 with influenza (mean age, 72 [SD, 13.3] years; 45.0% were male) were included. The 90-day absolute risk of arterial thromboembolism was 14.4% (95% CI, 13.6%-15.2%) in patients with influenza vs 15.8% (95% CI, 15.5%-16.2%) in patients with COVID-19 before vaccine availability (risk difference, 1.4% [95% CI, 1.0%-2.3%]) and 16.3% (95% CI, 16.0%-16.6%) in patients with COVID-19 during vaccine availability (risk difference, 1.9% [95% CI, 1.1%-2.7%]). Compared with patients with influenza, the risk of arterial thromboembolism was not significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.04 [95% CI, 0.97-1.11]) or during vaccine availability (adjusted HR, 1.07 [95% CI, 1.00-1.14]). The 90-day absolute risk of venous thromboembolism was 5.3% (95% CI, 4.9%-5.8%) in patients with influenza vs 9.5% (95% CI, 9.2%-9.7%) in patients with COVID-19 before vaccine availability (risk difference, 4.1% [95% CI, 3.6%-4.7%]) and 10.9% (95% CI, 10.6%-11.1%) in patients with COVID-19 during vaccine availability (risk difference, 5.5% [95% CI, 5.0%-6.1%]). Compared with patients with influenza, the risk of venous thromboembolism was significantly higher among patients with COVID-19 before vaccine availability (adjusted HR, 1.60 [95% CI, 1.43-1.79]) and during vaccine availability (adjusted HR, 1.89 [95% CI, 1.68-2.12]).

CONCLUSIONS AND RELEVANCE

Based on data from a US public health surveillance system, hospitalization with COVID-19 before and during vaccine availability, vs hospitalization with influenza in 2018-2019, was significantly associated with a higher risk of venous thromboembolism within 90 days, but there was no significant difference in the risk of arterial thromboembolism within 90 days.

Association Between Up-front Surgery and Risk of Stroke in US Veterans With Oropharyngeal Carcinoma

Importance

Cardiovascular events are an important cause of morbidity in patients with oropharyngeal squamous cell carcinoma (OPSCC). Radiation and chemotherapy have been associated with increased risk of stroke; up-front surgery allows the opportunity for (chemo)radiotherapy de-escalation.

Objective

To evaluate whether up-front surgery was associated with decreased stroke risk compared to nonsurgical treatment for OPSCC.

Design, Setting, and Participants

This cohort study was conducted at the US Veterans Health Administration and examined US veterans diagnosed with nonmetastatic OPSCC from 2000 to 2020. Data cutoff was September 17, 2021, and data analysis was performed from October 2021 to February 2022.

Exposures

Up-front surgical treatment or definitive (chemo)radiotherapy as captured in cancer registry.

Main Outcomes and Measures

Cumulative incidence of stroke, accounting for death as a competing risk; and association between up-front surgery and stroke risk. After generating propensity scores for the probability of receiving surgical treatment and using inverse probability weighting (IPW) to construct balanced pseudo-populations, Cox regression was used to estimate a cause-specific hazard ratio (csHR) of stroke associated with surgical vs nonsurgical treatment.

Results

Of 10 436 patients, median (IQR) age was 61 (56-67) years; 10 329 (99%) were male; 1319 (13%) were Black, and 7823 (75%) were White; 2717 received up-front surgery, and 7719 received nonsurgical therapy with definitive (chemo)radiotherapy. The 10-year cumulative incidence of stroke was 12.5% (95% CI, 11.8%-13.3%) and death was 57.3% (95% CI, 56.2%-58.4%). Surgical patients who also received (chemo)radiotherapy had shorter radiation and chemotherapy courses than nonsurgical patients. After propensity score and IPW, the csHR of stroke for surgical treatment was 0.77 (95% CI, 0.66-0.91). This association was consistent across subgroups defined by age and baseline cardiovascular risk factors.

Conclusions and Relevance

In this cohort study, up-front surgical treatment was associated with a 23% reduced risk of stroke compared with definitive (chemo)radiotherapy. These findings present an important additional risk-benefit consideration to factor into treatment decisions and patient counseling and should motivate future studies to examine cardiovascular events in this high-risk population.

Impact of label restriction on checkpoint-inhibitor use in bladder cancer and changes in mortality

In 2018, the US Food and Drug Administration (FDA) limited the indication for immune checkpoint inhibitors (ICI) in metastatic bladder cancer to patients with programmed cell death protein ligand-1 (PD-L1)–positive tumors. The impact of the label change on survival outcomes remains unknown. We conducted a controlled interrupted time series analysis using a nationwide electronic health record–derived oncology dataset. We used Cox regression to compare mortality in the post- vs prelabel change periods among affected (initiators of ICI or carboplatin-based chemotherapy) vs unaffected (initiators of cisplatin-based chemotherapy) patients. The use of ICI, carboplatin, and cisplatin was similar pre- and postlabel change, but PD-L1 testing increased postlabel change. In adjusted models, survival did not differ after the FDA label change policy compared with prior to the label change in any of the groups. The FDA label restriction on immunotherapy was associated with increased PD-L1 testing but not with changes in treatment patterns or mortality among patients with metastatic bladder cancer.

Abstract 6350: Very high PD-L1 expression as a prognostic indicator of overall survival amongst advanced non-small cell lung cancer patients receiving anti PD-(L)1 monotherapies in the first line setting: An IPW weighted health system analysis

Background Programmed death or ligand-1 (PD-(L)1) pathway inhibitors, a type of immunotherapy (IO), have become a standard anti-tumor strategy for advanced non-small cell lung cancer (aNSCLC) resulting in improved survival compared to platinum-doublet chemotherapy in PD-L1 expression (PD-L1+e ≥50%) in the 1L treatment setting. Limited evidence to suggest that amongst aNSCLC patients with PD-L1+e of 50%-100%, very high levels of PD-L1e (≥90%) would have any additional prognostic value leading to improved outcomes. Identifying additional PDL1+e cutoffs in aNSCLC with PDL1+e of 50%-100% would help treatment selection in routine practice as well as future IO clinical trials design ensuring trial groups are evenly balanced based on PD-L1+e levels. Objective To assess very high PD-L1+e (≥90%) as a prognostic indicator of overall survival in aNSCLC patients with PDL1+e ≥50% receiving anti PD-(L)1 monotherapies, using a single university EMR based health database. Methods Cohort study of aNSCLC patients, who initiated IO monotherapy in the 1L treatment setting from October 2016, to August 2021, and had a PDL1+e ≥ 50%. This study was conducted in the University of Pennsylvania Health System. Patients with incomplete treatment data or those harboring sensitizing alterations in EGFR, ALK, or ROS1 genes were excluded. The primary outcome was overall survival, measured from the start of 1L IO monotherapy (index date) to date of death or last confirmed activity. Propensity score-based inverse probability weighting (IPW) was used to address confounding in KM curves and Cox hazard regression. Baseline characteristics included age at therapy initiation, race, gender, smoking status, tumor histology, presence of KRAS or BRAF mutation, and ECOG PS. Results 196 aNSCLC receiving IO monotherapy met the inclusion criteria; n=30 had missing ECOG PS. 53% of the cohort were female, the median age at therapy initiation was 68 years, 72% had non-squamous cell carcinoma with 92% having a history of smoking, 28% had a KRAS mutation, and 37% had very high PDL1+e. Covariates were well balanced between groups after IPW weighting (all │standardized differences│&lt;0.1). 92% received Pembrolizumab IO monotherapy. Median overall survival was 3.85 years (v high -PDL1+e) vs 1.52 years (high -PDL1+e), respectively. In the complete case analysis (n=166), having a very high PDL1+e (HR 0.57, 95% CI 0.36-0.90) was associated with lower mortality. Study limitations include the potential for unmeasured confounding and potentially limited generalizability. Conclusion Patients with aNSCLC having very high PDL1+e (≥90%) receiving IO monotherapy appear to have improved survival in the 1L setting. These findings should be confirmed in a larger real-world data set.

Citation Format: Mohsin Shah, Rebecca A. Hubbard, Ronac Mamtani, Sean Hennessy. Very high PD-L1 expression as a prognostic indicator of overall survival amongst advanced non-small cell lung cancer patients receiving anti PD-(L)1 monotherapies in the first line setting: An IPW weighted health system analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6350.

Association between up-front surgery and risk of stroke in U.S. veterans with oropharyngeal squamous cell carcinoma

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Background: Cardiovascular disease and stroke are important causes of long-term morbidity and mortality in patients with oropharyngeal squamous cell carcinoma (OPSCC). Cancer treatments including radiotherapy to the neck and chemotherapy have been associated with increased risk of stroke. In the era of treatment de-intensification for OPSCC, up-front surgical treatment has been proposed as one strategy that allows for de-escalation or avoidance of (chemo)radiotherapy. We sought to quantify the cumulative incidence of stroke in patients treated for non-metastatic OPSCC, and then evaluate whether patients receiving up-front surgery for OPSCC have decreased risk of stroke compared to those undergoing non-surgical treatment. Methods: We identified a cohort of 10,436 United States veterans diagnosed with non-metastatic OPSCC from 2000-2020, of whom 2,717 received up-front surgery (with or without perioperative radiotherapy or chemoradiotherapy) and 7,719 received non-surgical therapy (definitive radiotherapy or chemoradiotherapy). We estimated the cumulative incidence of stroke in this population, accounting for death as a competing risk. To assess the association between up-front surgery and risk of stroke, we generated a propensity score for the probability of receiving surgical treatment and used inverse probability weighting to construct pseudo-populations balanced on all potential confounders. Cox regression models of the inverse probability weighted population were used to estimate the cause-specific hazard ratio of stroke associated with surgical vs non-surgical treatment. Results: The 10-year cumulative incidence of stroke was 12.5% (95% CI 11.8-13.23) and death was 57.3% (95% CI 56.2-58.4). Up-front surgical patients who underwent perioperative (chemo)radiotherapy had shorter radiation and chemotherapy courses compared to non-surgical patients, suggestive of lower treatment intensity. Propensity score generation and inverse probability weighting yielded good overlap and covariate balance between surgical and non-surgical treatment groups. The inverse probability weighted cause-specific hazard ratio of stroke associated with up-front surgical treatment was 0.77 (95% CI 0.66-0.91, p = 0.002). This association was consistent across subgroups defined by age ( > /≤65 years) and baseline cardiovascular risk factors (hypertension, hyperlipidemia, diabetes). Conclusions: In over 10,000 US veterans with OPSCC, cumulative incidence of stroke was 12.5% at 10 years. Up-front surgical treatment was associated with a 23% reduced risk of stroke compared to definitive (chemo)radiotherapy. These findings present an important additional risk-benefit consideration to factor into treatment decisions and patient counseling, and should motivate future studies to examine cardiovascular events in this high-risk population.

Racial disparities in diagnostic follow-up following BIRADS 0 mammogram

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Background: Delays in follow-up after abnormal mammograms can lead to worse outcomes and may contribute to health disparities. BIRADS 0 mammograms necessitate additional diagnostic imaging, and BIRADS 4 or 5 mammograms should be followed by biopsy. The goal of this study was to investigate racial disparities in rates and timeliness of (1) diagnostic follow-up after a BIRADS 0 screening mammogram and (2) biopsy following a subsequent BIRADS 4 or 5 diagnostic mammogram. Methods: We included women ≥18 years old who underwent a screening mammogram at the Hospital of the University of Pennsylvania with an assessment of BIRADS 0 between September 2010 and February 2018. The distributions of time from screening to diagnostic mammogram and from BIRADS 4 or 5 diagnostic mammogram to biopsy were estimated using the Kaplan Meier method. Follow-up was censored at 365 days. Case-mix adjusted Cox proportional hazards models were used to estimate the association between race/ethnicity and time to diagnostic mammogram and biopsy. Results: We identified 6299 women (Asian/PI=257, Black=3223, Hispanic=124, White=2420, Other/Unknown=275) with 6880 BIRADS 0 screening mammograms during the study period. Following these BIRADS 0 mammograms, the overall rate of diagnostic mammograms within 365 days was 87.3% (n=6006 mammograms), with a rate of 90.6% (2432) for White women and 85.3% (2971) for Black women. For the 1151 BIRADS 4-5 diagnostic mammograms in the cohort, the overall rate of follow-up biopsies within 365 days was 91.8% (n=1057 biopsies), with a rate of 93.8% (396) for White women and 91.1% (575) for Black women. Compared to mammograms obtained by White women, those obtained by Black women were less likely to be followed up with a diagnostic mammogram (HR 0.71, 95% CI 0.63-0.80, p<0.001) and biopsy (HR 0.74, 95% CI 0.55-0.98, p=0.037) when indicated (Table). Almost 1/4 (24.2%, 95% CI 23.1-25.9%) of BIRADS 0 screening mammograms among Black women were not followed by diagnostic imaging within 30 days as compared to 14.6% among White women (95% CI 13.3-16.0%, p<0.001). 23.6% (95% CI 20.5-27.2%) of BIRADS 4-5 diagnostic mammograms among Black women were not followed up with biopsy within 30 days vs 18.7% for White women (95% CI 15.4-22.8%, p=0.61) (Table). These disparities persisted at 90 days. Conclusions: Racial disparities exist in rates of follow-up after BIRADS 0 mammograms. The additive effects of delays at each diagnostic step put Black women at disproportionately greater risk for worse outcomes. [Table: see text]

Does Living near Trees and Other Vegetation Affect the Contemporaneous Odds of Asthma Exacerbation among Pediatric Asthma Patients?

Vegetation may influence asthma exacerbation through effects on aeroallergens, localized climates, air pollution, or children's behaviors and stress levels. We investigated the association between residential vegetation and asthma exacerbation by conducting a matched case-control study based on electronic health records of asthma patients, from the Children's Hospital of Philadelphia (CHOP). Our study included 17,639 exacerbation case events and 34,681 controls selected from non-exacerbation clinical visits for asthma, matched to cases by age, sex, race/ethnicity, public payment source, and residential proximity to the CHOP main campus ED and hospital. Overall greenness, tree canopy, grass/shrub cover, and impervious surface were assessed near children's homes (250 m) using satellite imagery and high-resolution landcover data. We used generalized estimating equations to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between each vegetation/landcover measure and asthma exacerbation, with adjustment for seasonal and sociodemographic factors-for all cases, and for cases defined by diagnosis setting and exacerbation frequency. Lower odds of asthma exacerbation were observed in association with greater levels of tree canopy near the home, but only for children who experienced multiple exacerbations in a year (OR = 0.94 per 10.2% greater tree canopy coverage, 95% CI = 0.90-0.99). Our findings suggest possible protection for asthma patients from tree canopy, but differing results by case frequency suggest that potential benefits may be specific to certain subpopulations of asthmatic children.

Neighborhood Characteristics and COVID-19 Incidence and Mortality in Southeastern Pennsylvania

The COVID-19 pandemic has differentially impacted people according to their race/ethnicity, socioeconomic status, and preexisting conditions. Public health surveillance efforts, especially those occurring early in the pandemic, did not gather nor report adequate individual-level demographic information to identify these differences, and thus, neighborhood-level characteristics were used to note striking disparities in the US. We sought to determine whether risk factors associated with COVID-19 incidence and mortality in five Southeastern Pennsylvania counties could be better understood by using neighborhood-level demographic data augmented with health, socioeconomic, and environmental characteristics derived from publicly available sources. Although we found that education level and age of residents were the most salient predictors of COVID-19 incidence and mortality, respectively, neighborhoods exhibited a high degree of segregation with multiple correlated factors, which limits the ability of neighborhood-level analysis to identify actionable factors underlying COVID-19 disparities.

Impact of the COVID-19 Pandemic on Treatment Patterns for Patients With Metastatic Solid Cancer in the United States

BACKGROUND

The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer.

METHODS

We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14 136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at approximately 280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy.

RESULTS

The adjusted probability of treatment within 30 days of diagnosis was similar across periods (January-March 2019 = 41.7%, 95% confidence interval [CI] = 32.2% to 51.1%; April-July 2019 = 42.6%, 95% CI = 32.4% to 52.7%; January-March 2020 = 44.5%, 95% CI = 30.4% to 58.6%; April-July 2020 = 46.8%, 95% CI= 34.6% to 59.0%; adjusted percentage-point difference-in-differences = 1.4%, 95% CI = -2.7% to 5.5%). Among 5962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences = 1.6%, 95% CI = -2.6% to 5.8%). There was no meaningful effect modification by cancer type, race, or age.

CONCLUSIONS

Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not affect TTI or treatment selection for patients with metastatic solid cancers.

Associations between high ambient temperatures and asthma exacerbation among children in Philadelphia, PA: a time series analysis

OBJECTIVES

High ambient temperatures may contribute to acute asthma exacerbation, a leading cause of morbidity in children. We quantified associations between hot-season ambient temperatures and asthma exacerbation in children ages 0-18 years in Philadelphia, PA.

METHODS

We created a time series of daily counts of clinical encounters for asthma exacerbation at the Children's Hospital of Philadelphia linked with daily meteorological data, June-August of 2011-2016. We estimated associations between mean daily temperature (up to a 5-day lag) and asthma exacerbation using generalised quasi-Poisson distributed models, adjusted for seasonal and long-term trends, day of the week, mean relative humidity,and US holiday. In secondary analyses, we ran models with adjustment for aeroallergens, air pollutants and respiratory virus counts. We quantified overall associations, and estimates stratified by encounter location (outpatient, emergency department, inpatient), sociodemographics and comorbidities.

RESULTS

The analysis included 7637 asthma exacerbation events. High mean daily temperatures that occurred 5 days before the index date were associated with higher rates of exacerbation (rate ratio (RR) comparing 33°C-13.1°C days: 1.37, 95% CI 1.04 to 1.82). Associations were most substantial for children ages 2 to <5 years and for Hispanic and non-Hispanic black children. Adjustment for air pollutants, aeroallergens and respiratory virus counts did not substantially change RR estimates.

CONCLUSIONS

This research contributes to evidence that ambient heat is associated with higher rates of asthma exacerbation in children. Further work is needed to explore the mechanisms underlying these associations.

Cumulative Probability of False-Positive Results After 10 Years of Screening With Digital Breast Tomosynthesis vs Digital Mammography

Importance

Breast cancer screening with digital breast tomosynthesis may decrease false-positive results compared with digital mammography.

Objective

To estimate the probability of receiving at least 1 false-positive result after 10 years of screening with digital breast tomosynthesis vs digital mammography in the US.

Design, Setting, and Participants

An observational comparative effectiveness study with data collected prospectively for screening examinations was performed between January 1, 2005, and December 31, 2018, at 126 radiology facilities in the Breast Cancer Surveillance Consortium. Analysis included 903 495 individuals aged 40 to 79 years. Data analysis was conducted from February 9 to September 7, 2021.

Exposures

Screening modality, screening interval, age, and Breast Imaging Reporting and Data System breast density.

Main Outcomes and Measures

Cumulative risk of at least 1 false-positive recall for further imaging, short-interval follow-up recommendation, and biopsy recommendation after 10 years of annual or biennial screening with digital breast tomosynthesis vs digital mammography, accounting for competing risks of breast cancer diagnosis and death.

Results

In this study of 903 495 women, 2 969 055 nonbaseline screening examinations were performed with interpretation by 699 radiologists. Mean (SD) age of the women at the time of the screening examinations was 57.6 (9.9) years, and 58% of the examinations were in individuals younger than 60 years and 46% were performed in women with dense breasts. A total of 15% of examinations used tomosynthesis. For annual screening, the 10-year cumulative probability of at least 1 false-positive result was significantly lower with tomosynthesis vs digital mammography for all outcomes: 49.6% vs 56.3% (difference, -6.7; 95% CI, -7.4 to -6.1) for recall, 16.6% vs 17.8% (difference, -1.1; 95% CI, -1.7 to -0.6) for short-interval follow-up recommendation, and 11.2% vs 11.7% (difference, -0.5; 95% CI, -1.0 to -0.1) for biopsy recommendation. For biennial screening, the cumulative probability of a false-positive recall was significantly lower for tomosynthesis vs digital mammography (35.7% vs 38.1%; difference, -2.4; 95% CI, -3.4 to -1.5), but cumulative probabilities did not differ significantly by modality for short-interval follow-up recommendation (10.3% vs 10.5%; difference, -0.1; 95% CI, -0.7 to 0.5) or biopsy recommendation (6.6% vs 6.7%; difference, -0.1; 95% CI, -0.5 to 0.4). Decreases in cumulative probabilities of false-positive results with tomosynthesis vs digital mammography were largest for annual screening in women with nondense breasts (differences for recall, -6.5 to -12.8; short-interval follow-up, 0.1 to -5.2; and biopsy recommendation, -0.5 to -3.1). Regardless of modality, cumulative probabilities of false-positive results were substantially lower for biennial vs annual screening (overall recall, 35.7 to 38.1 vs 49.6 to 56.3; short-interval follow-up, 10.3 to 10.5 vs 16.6 to 17.8; and biopsy recommendation, 6.6 to 6.7 vs 11.2 to 11.7); older vs younger age groups (eg, among annual screening in women ages 70-79 vs 40-49, recall, 39.8 to 47.0 vs 60.8 to 68.0; short-interval follow-up, 13.3 to 14.2 vs 20.7 to 20.9; and biopsy recommendation, 9.1 to 9.3 vs 13.2 to 13.4); and women with entirely fatty vs extremely dense breasts (eg, among annual screening in women aged 50-59 years, recall, 29.1 to 36.3 vs 58.8 to 60.4; short-interval follow-up, 8.9 to 11.6 vs 19.5 to 19.8; and biopsy recommendation, 4.9 to 8.0 vs 15.1 to 15.3).

Conclusions and Relevance

In this comparative effectiveness study, 10-year cumulative probabilities of false-positive results were lower on digital breast tomosynthesis vs digital mammography. Biennial screening interval, older age, and nondense breasts were associated with larger reductions in false-positive probabilities than screening modality.

Comparative risk of serious hypoglycemia among persons dispensed a fluoroquinolone versus a non-fluoroquinolone antibiotic

AIM

Fluoroquinolone antibiotics have been implicated in cases of metabolic adverse events. This study investigated the causal association between fluoroquinolones and serious hypoglycemia in those with and without diabetes.

METHODS

We conducted a propensity score-matched cohort study using Optum claims data. We included adults dispensed an oral fluoroquinolone or comparator antibiotic between January 2000 and September 2015 for specific infections of interest. The outcome was serious hypoglycemia, defined using a validated algorithm. Conditional logistic regression was used to estimate odds ratios (ORs) in diabetes and non-diabetes cohorts after matching on propensity scores fitted using confounding variables of interest.

RESULTS

Our cohort contained 119,112 individuals with diabetes and 917,867 individuals without diabetes exposed to a fluoroquinolone, matched 1:1 with a comparator. Matching produced balance (standardized mean difference < 0.1) on all variables included in the propensity score. The OR for the association between fluoroquinolones and serious hypoglycemia was 1.28 (95% confidence interval [CI]: 1.04-1.57) in the entire cohort, 1.30 (95% CI: 1.05-1.62) in individuals with diabetes, and 1.06 (95% CI: 0.53-2.13) in individuals without diabetes.

CONCLUSION

Fluoroquinolone users are at an increased risk of serious hypoglycemia relative to comparator antibiotic users. This association was evident only among persons diagnosed with diabetes.

Impact of FDA label change on immunotherapy for metastatic urothelial cancer (mUC) and subsequent changes in mortality

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Background: In May 2017, atezolizumab and pembrolizumab (IO) received accelerated approval for first-line treatment of cisplatin-ineligible patients with mUC, irrespective of PDL1 test status. In June 2018, the FDA and EMA restricted IO to cisplatin-ineligible patients with PDL1 positive tumors based on early review of data from confirmatory trials which suggested decreased overall survival in patients with PDL1 negative tumors treated with IO. We assessed the impact of the FDA label change on clinical outcomes of mUC patients in routine care. Methods: We conducted a controlled interrupted time series analysis using the US Flatiron Health electronic health record-derived de-identified database. The study sample included patients from 280 cancer clinics nationwide diagnosed with mUC and compared patients potentially impacted by the label change (cisplatin ineligible patients initiating first-line IO or carboplatin-based chemotherapy) to a comparator group who would have been unaffected by the label change (patients initiating first-line cisplatin-based chemotherapy) from 01 April 2017 to 17 May 2018 (pre-label change) and 20 June 2018 to 01 March 2020 (post-label change), excluding a 30-day wash out period encompassing the time-period between the initial FDA safety alert (18 May 2018) and the official FDA label change (19 June 2018). We used Cox regression to estimate adjusted pre-/post-label change related mortality differences in patients receiving carboplatin-chemotherapy or IO, accounting for secular changes in survival through comparison with the cisplatin comparator group. Results: The study included 829 patients with mUC initiating treatment in the pre-label change period (582 IO or carboplatin, 247 cisplatin) and 1,184 patients in the post-label change period (849 IO or carboplatin, 336 cisplatin), respectively. The use of IO, carboplatin, and cisplatin was similar across time-periods (pre-label change: 44.4%, 25.8%, and 29.8%; post-label change: 48%, 23.6%, 28.4%); while PD-L1 testing increased (6.6% to 28.1%). In adjusted models, there were no differences in survival in any of the groups following the FDA label change policy (table). Conclusions: The U.S. FDA label restriction on first-line immunotherapy was associated with increased PD-L1 testing but was not associated with changes in treatment patterns or improved mortality among patients with mUC.[Table: see text]

Angiotensin Converting Enzyme-Inhibitors and Incidence of Non-infectious Uveitis in a Large Healthcare Claims Database

PURPOSE

To determine if angiotensin converting enzyme-inhibitors (ACE-I) alter the incidence of non-infectious uveitis (NIU).

METHODS

Patients in a large healthcare claims database who initiated ACE-I (n = 695,557) were compared to patients who initiated angiotensin receptor blockers (ARB, n = 354,295). A second comparison was also made between patients who initiated ACE-I (n = 505,958) and those who initiated beta-blockers (BB, n = 538,109). The primary outcome was incident NIU defined as a first diagnosis code for NIU followed by a second instance of a NIU code within 120 days. For the secondary outcome, a corticosteroid prescription or code for an ocular corticosteroid injection within 120 days of the NIU diagnosis code was used instead of the second NIU diagnosis code. Data were analyzed using Cox regression modeling with inverse probability of treatment weighting (IPTW). Sub-analyses were performed by anatomic subtype.

RESULTS

When comparing ACE-I to ARB initiators, the hazard ratio (HR) for incident NIU was not significantly different for the primary outcome [HR = 0.95, 95% Confidence Interval (CI): 0.85-1.07, P = .41] or secondary outcome [HR = 0.96, 95% CI: 0.86-1.07, P = .44]. Similarly, in the ACE-I and BB initiators comparison, the HR for incident NIU was not significantly different comparing ACE-I and BB initiators for either outcome definition or any of the NIU anatomical subtypes.

CONCLUSION

Our results suggest there is no evidence that ACE-I have a protective effect on NIU.