Citations

11176 Background: Progression-free survival (PFS) is frequently measured in oncology clinical trials. In analyses outside of the trial setting, various strategies have been utilized to assess real-world PFS (rwPFS), including manual abstraction of clinical records, natural language processing (NLP) of oncology notes and radiology reports, and longitudinal analyses of radiologic images. Here we develop and validate a new semi-automated workflow that combines NLP of clinical notes with structured electronic health record data to facilitate the evaluation of rwPFS in patients with metastatic breast cancer (mBC). Methods: This study analyzes de-identified EHR data using nference nSights. The data is extracted following privacy-preserving protocols and is HIPAA compliant. The overall cohort included 316 patients with HR-positive, HER2-negative mBC who initiated Palbociclib and Letrozole combination therapy between January 1, 2015 and December 31, 2021. We developed and implemented an ensemble of deep-learning NLP frameworks to capture progression events from unstructured clinical notes and radiology reports. A change in the line of therapy, as determined by structured drug order/administration records, was also considered a progression event. We used manually curated “ground-truth” datasets to evaluate the performance of the progression-event capture workflow at the levels of both sentences (N = 1000) and patients (N = 100) by calculating sensitivity, specificity, precision, accuracy, and F1 scores. Progression events and censoring events (death, loss to follow-up, end of study period) were considered to compute rwPFS. Results: At the sentence level, progression events were captured from clinical notes and radiology reports with a sensitivity of 99.8%, specificity of 96.7%, and accuracy of 98.2% (Table). At the patient level, initial progression was correctly captured within a window of +/-30 days with a sensitivity of 92.5%, specificity of 83.0%, and accuracy of 88.0% (Table). In a sample of 100 patients, the median rwPFS was determined to be 25 months (95% CI; 15-35 months) by manual curation and 22 months (95% CI; 15-35 months) by the semi-automated workflow. In the overall cohort, median rwPFS was 20 months (95% CI; 18-25 months). Conclusions: An ensemble of NLP algorithms extracted progression events from clinical notes and radiology reports with high accuracy. A semi-automated workflow enabled rapid and accurate determination of rwPFS in mBC patients receiving a combination chemotherapy regimen. Further evaluation of this workflow to estimate rwPFS in other cancers and therapeutic settings is warranted. [Table: see text]

Background: Early diagnosis of heart failure with reduced ejection fraction (HFrEF) can lead to reduced healthcare costs and improved outcomes. In this study, we evaluated the economic effectiveness of an AI algorithm for detecting low ejection fraction using 12-lead ECG data. Aims: The primary aim was to estimate the health economic impact of the AI-ECG algorithm intervention to detect low ejection fraction. Methods: The study population consisted of 113,719 individuals without a prior history of HFrEF who visited a multistate health system between 2010-2018 with 12-lead ECG data and an echocardiogram within 1 year. The AI-ECG algorithm was run retrospectively, and projected costs were estimated assuming each patient incurred the average cost based on their age group and AI-detected heart failure stage. Hospitalization costs were estimated using Medicare reimbursement rates, and economic benefits from increased survival were estimated using a willingness to pay of $50,000 per quality-adjusted life year (QALY) gained. Results: At the optimal model threshold, the total cost savings per patient (including benefits from QALYs gained) for the AI-ECG algorithm vs. standard-of-care on the overall study population were projected to be $79.11 (95% CI: [$53.77, $104.44]) and $124.93 (95% CI: [$83.99, $165.88]) for the 2 and 4 year periods, respectively. For patients over 50 years old, the projected total cost savings were $85.56 (95% CI: [$56.35, $114.78]) and $135.28 (95% CI: [$88.18, $182.38]) per patient for the 2 and 4 year periods, respectively. See Figure. Conclusions: The AI-ECG algorithm to detect low ejection fraction is a cost-effective early screening tool for HFrEF.

Abstract Case reports of patients infected with COVID-19 and influenza virus (“flurona”) have raised questions around the prevalence and severity of coinfection. Using data from HHS Protect Public Data Hub, NCBI Virus, and CDC FluView, we analyzed trends in SARS-CoV-2 and influenza hospitalized coinfection cases and strain prevalences. We also characterized coinfection cases across the Mayo Clinic Enterprise from January 2020 to April 2022. We compared expected and observed coinfection case counts across different waves of the pandemic and assessed symptoms and outcomes of coinfection and COVID-19 monoinfection cases after propensity score matching on clinically relevant baseline characteristics. From both the Mayo Clinic and nationwide datasets, the observed coinfection rate for SARS-CoV-2 and influenza has been higher during the Omicron era (2021 December 14 to 2022 April 2) compared to previous waves, but no higher than expected assuming infection rates are independent. At the Mayo Clinic, only 120 coinfection cases were observed among 197,364 SARS-CoV-2 cases. Coinfected patients were relatively young (mean age: 26.7 years) and had fewer serious comorbidities compared to monoinfected patients. While there were no significant differences in 30-day hospitalization, ICU admission, or mortality rates between coinfected and matched COVID-19 monoinfection cases, coinfection cases reported higher rates of symptoms including congestion, cough, fever/chills, headache, myalgia/arthralgia, pharyngitis, and rhinitis. While most coinfection cases observed at the Mayo Clinic occurred among relatively healthy individuals, further observation is needed to assess outcomes among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status.

Abstract COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection after full vaccination with BNT162b2 against polymerase chain reaction (PCR)-confirmed symptomatic SARS-CoV-2 infection, in a national medical practice from January 2021 through January 2022. We fit conditional logistic regression (CLR) models stratified on residential county and calendar time of testing to assess the association between time elapsed since vaccination and the odds of symptomatic infection or non-COVID-19 hospitalization (negative control), adjusted for several covariates. There were 5,985 symptomatic individuals with a positive test after full vaccination with BNT162b2 (cases) and 32,728 negative tests contributed by 27,753 symptomatic individuals after full vaccination (controls). The adjusted odds of symptomatic infection were higher 250 days after full vaccination versus at the date of full vaccination (Odds Ratio [OR]: 3.62, 95% CI: 2.52 to 5.20). The odds of infection were still lower 285 days after the first BNT162b2 dose as compared to 4 days after the first dose (OR: 0.50, 95% CI: 0.37 to 0.67), when immune protection approximates the unvaccinated status. Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. The odds of non-COVID-19 associated hospitalization (negative control) decreased with time since vaccination, suggesting a possible underestimation of waning protection by this approach due to confounding factors. In summary, BNT162b2 strongly protected against symptomatic SARS-CoV-2 infection for at least 8 months after full vaccination, but the degree of protection waned significantly over this period.

Abstract COVID-19 vaccines are effective, but breakthrough infections have been increasingly reported. We conducted a test-negative case-control study to assess the durability of protection against symptomatic infection after vaccination with mRNA-1273. We fit conditional logistic regression (CLR) models stratified on residential county and calendar date of SARS-CoV-2 PCR testing to assess the association between the time elapsed since vaccination and the odds of symptomatic infection, adjusted for several covariates. There were 2,364 symptomatic individuals who had a positive SARS-CoV-2 PCR test after full vaccination with mRNA-1273 (“cases”) and 12,949 symptomatic individuals who contributed 15,087 negative tests after full vaccination (“controls”). The odds of symptomatic infection were significantly higher 250 days after full vaccination compared to the date of full vaccination (Odds Ratio [OR]: 2.47, 95% confidence interval [CI]: 1.19–5.13). The odds of non-COVID-19 associated hospitalization and non-COVID-19 pneumonia (negative control outcomes) remained relatively stable over the same time interval (Day 250 ORNon-COVID Hospitalization: 0.68, 95% CI: 0.47–1.0; Day 250 ORNon-COVID Pneumonia: 1.11, 95% CI: 0.24–5.2). The odds of symptomatic infection remained significantly lower almost 300 days after the first mRNA-1273 dose as compared to 4 days after the first dose, when immune protection approximates the unvaccinated state (OR: 0.26, 95% CI: 0.17–0.39). Low rates of COVID-19 associated hospitalization or death in this cohort precluded analyses of these severe outcomes. In summary, mRNA-1273 robustly protected against symptomatic SARS-CoV-2 infection at least 8 months after full vaccination, but the degree of protection waned over this time period.

Abstract As of 2021 November 29, booster vaccination against SARS-CoV-2 infection has been recommended for all individuals aged 18 years and older in the United States. A key reason for this recommendation is the expectation that a booster vaccine dose can alleviate observed waning of vaccine effectiveness (VE). Although initial reports of booster effectiveness have been positive, the level of protection from booster vaccination is unclear. We conducted two studies to assess the impact of booster vaccination, with BNT162b2 or mRNA-1273, on the incidence of SARS-CoV-2 infection between August and December 2021. We first compared SARS-CoV-2 infection incidence in cohorts of 3-dose vaccine recipients to incidence in matched cohorts of 2-dose vaccine recipients (cohort size = 24,539 for BNT162b2 and 14,004 for mRNA-1273). Additionally, we applied a test-negative study design to compare the level of protection against symptomatic infection in 3-dose recipients to that observed in recent 2-dose primary vaccine series recipients. The 3-dose recipients experienced a significantly lower incidence rate of SARS-CoV-2 infection than the matched 2-dose cohorts (BNT162b2 Incidence Rate Ratio: 0.11, 95% CI: 0.09 to 0.13 and mRNA-1273 IRR: 0.11, 95% CI: 0.08 to 0.15). Results from the test-negative study showed the third vaccine dose mitigated waning of VE, with the risk of symptomatic infection in 3-dose recipients being comparable to that observed 7 to 73 days after the primary vaccine series. These results show that 3-dose vaccine regimens with BNT162b2 or mRNA-1273 are effective at reducing SARS-CoV-2 infection and support the widespread administration of booster vaccine doses.

Abstract The raging COVID-19 pandemic in India and reports of “vaccine breakthrough infections” globally have raised alarm mandating the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed over 1.3 million SARS-CoV-2 genomes from 178 countries and performed whole-genome viral sequencing from 53 COVID-19 patients, including 20 vaccine breakthrough infections. We identified 116 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a three-month window. Deletions in the Spike protein N-terminal domain (NTD) are highly enriched for these ‘surge-associated mutations’ (Odds Ratio = 18.2, 95% CI: 7.53-48.7; p=1.465x10-18). In the recent COVID-19 surge in India, an NTD deletion (ΔF157/R158) increased over 10-fold in prevalence from February 2021 (1.1%) to April 2021 (15%). During the recent surge in Chile, an NTD deletion (Δ246-253) increased rapidly over 30-fold in prevalence from January 2021 (0.86%) to April 2021 (33%). Strikingly, these simultaneously emerging deletions associated with surges in different parts of the world both occur at an antigenic supersite that is targeted by neutralizing antibodies. Finally, we generated clinically annotated SARS-CoV-2 whole genome sequences and identified deletions within this NTD antigenic supersite in a patient with vaccine breakthrough infection (Δ156-164) and other deletions from unvaccinated severe COVID-19 patients that could represent emerging deletion-prone regions. Overall, the expanding repertoire of Spike protein deletions throughout the pandemic and their association with case surges and vaccine breakthrough infections point to antigenic minimalism as an emerging evolutionary strategy for SARS-CoV-2 to evade immune responses. This study highlights the urgent need to sequence SARS-CoV-2 genomes at a larger scale globally and to mandate a public health policy for transparent reporting of relevant clinical annotations (e.g. vaccination status) in order to aid the development of comprehensive therapeutic strategies.