Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development.

Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.

Interstitial lung abnormalities after hospitalization for COVID-19 in patients with cancer: A prospective cohort study.

INTRODUCTION: Survivors of SARS-CoV-2 pneumonia often develop persistent respiratory symptom and interstitial lung abnormalities (ILAs) after infection. Risk factors for ILA development and duration of ILA persistence after SARS-CoV-2 infection are not well described in immunocompromised hosts, such as cancer patients. METHODS: We conducted a prospective cohort study of 95 patients at a major cancer center and 45 patients at a tertiary referral center. We collected clinical and radiographic data during the index hospitalization for COVID-19 pneumonia and measured pneumonia severity using a semi-quantitative radiographic score, the Radiologic Severity Index (RSI). Patients were evaluated in post-COVID-19 clinics at 3 and 6 months after discharge and underwent comprehensive pulmonary evaluations (symptom assessment, chest computed tomography, pulmonary function tests, 6-min walk test). The association of clinical and radiological factors with ILAs at 3 and 6 months post-discharge was measured using univariable and multivariable logistic regression. RESULTS: Sixty-six (70%) patients of cancer cohort had ILAs at 3 months, of whom 39 had persistent respiratory symptoms. Twenty-four (26%) patients had persistent ILA at 6 months after hospital discharge. In adjusted models, higher peak RSI at admission was associated with ILAs at 3 (OR 1.5 per 5-point increase, 95% CI 1.1-1.9) and 6 months (OR 1.3 per 5-point increase, 95% CI 1.1-1.6) post-discharge. Fibrotic ILAs (reticulation, traction bronchiectasis, and architectural distortion) were more common at 6 months post-discharge. CONCLUSIONS: Post-COVID-19 ILAs are common in cancer patients 3 months after hospital discharge, and peak RSI and older age are strong predictors of persistent ILAs.

Multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring.

We propose a reinforcement learning method for estimating an optimal dynamic treatment regime for survival outcomes with dependent censoring. The estimator allows the failure time to be conditionally independent of censoring and dependent on the treatment decision times, supports a flexible number of treatment arms and treatment stages, and can maximize either the mean survival time or the survival probability at a certain time-point. The estimator is constructed using generalized random survival forests and can have polynomial rates of convergence. Simulations and analysis of the Atherosclerosis Risk in Communities study data suggest that the new estimator brings higher expected outcomes than existing methods in various settings.

Estimation of the odds ratio in a proportional odds model with censored time-lagged outcome in a randomized clinical trial.

In many randomized clinical trials of therapeutics for COVID-19, the primary outcome is an ordinal categorical variable, and interest focuses on the odds ratio (OR; active agent vs control) under the assumption of a proportional odds model. Although at the final analysis the outcome will be determined for all subjects, at an interim analysis, the status of some participants may not yet be determined, for example, because ascertainment of the outcome may not be possible until some prespecified follow-up time. Accordingly, the outcome from these subjects can be viewed as censored. A valid interim analysis can be based on data only from those subjects with full follow-up; however, this approach is inefficient, as it does not exploit additional information that may be available on those for whom the outcome is not yet available at the time of the interim analysis. Appealing to the theory of semiparametrics, we propose an estimator for the OR in a proportional odds model with censored, time-lagged categorical outcome that incorporates additional baseline and time-dependent covariate information and demonstrate that it can result in considerable gains in efficiency relative to simpler approaches. A byproduct of the approach is a covariate-adjusted estimator for the OR based on the full data that would be available at a final analysis.

Mitigating Burnout: Transition to a Condensed Workweek for Advanced Practice Providers in Infectious Diseases.

Burnout among health-care workers is highly prevalent and profoundly impacts the quality of patient care. In addition to affecting patient safety, burnout results in higher staff turnover, revenue deficits due to decreased productivity, financial risk, and diminished organization viability because of the impact on quality of care, patient satisfaction, and safety. Culmination of external and internal stressors in health-care worker populations is associated with a higher probability of burnout and workers who reported perceived low workplace flexibility. In addition, workplace flexibility is associated with reduced odds of experiencing burnout. Workplace flexibility plays a critical role in potentially reducing the occurrence of burnout in the health-care worker population. Individually focused solutions are important to mitigate burnout, however, comprehensive organizational change ensures durable and sustainable solutions. There is a correlation between a positive employee outlook and reduced stress when there is a perceived level of control over one's work schedule. The goal of this article is to showcase the process of a successful implementation of a condensed work schedule for an advanced practice provider workforce in infectious diseases in response to burnout and workload shifts. This chronicles the steps of design, rationale, procuring buy-in by stakeholders, and operational implementation of the new schedules. Advanced practice provider satisfaction and burnout were measured by periodic surveys at timepoints along the way.

Phylogeny-guided microbiome OTU-specific association test (POST).

BACKGROUND: The relationship between host conditions and microbiome profiles, typically characterized by operational taxonomic units (OTUs), contains important information about the microbial role in human health. Traditional association testing frameworks are challenged by the high dimensionality and sparsity of typical microbiome profiles. Phylogenetic information is often incorporated to address these challenges with the assumption that evolutionarily similar taxa tend to behave similarly. However, this assumption may not always be valid due to the complex effects of microbes, and phylogenetic information should be incorporated in a data-supervised fashion. RESULTS: In this work, we propose a local collapsing test called phylogeny-guided microbiome OTU-specific association test (POST). In POST, whether or not to borrow information and how much information to borrow from the neighboring OTUs in the phylogenetic tree are supervised by phylogenetic distance and the outcome-OTU association. POST is constructed under the kernel machine framework to accommodate complex OTU effects and extends kernel machine microbiome tests from community level to OTU level. Using simulation studies, we show that when the phylogenetic tree is informative, POST has better performance than existing OTU-level association tests. When the phylogenetic tree is not informative, POST achieves similar performance as existing methods. Finally, in real data applications on bacterial vaginosis and on preterm birth, we find that POST can identify similar or more outcome-associated OTUs that are of biological relevance compared to existing methods. CONCLUSIONS: Using POST, we show that adaptively leveraging the phylogenetic information can enhance the selection performance of associated microbiome features by improving the overall true-positive and false-positive detection. We developed a user friendly R package POSTm which is freely available on CRAN ( https://CRAN.R-project.org/package=POSTm ). Video Abstract.

Effectiveness of Covid-19 Vaccines over a 9-Month Period in North Carolina.

BACKGROUND: The duration of protection afforded by coronavirus disease 2019 (Covid-19) vaccines in the United States is unclear. Whether the increase in postvaccination infections during the summer of 2021 was caused by declining immunity over time, the emergence of the B.1.617.2 (delta) variant, or both is unknown. METHODS: We extracted data regarding Covid-19-related vaccination and outcomes during a 9-month period (December 11, 2020, to September 8, 2021) for approximately 10.6 million North Carolina residents by linking data from the North Carolina Covid-19 Surveillance System and the Covid-19 Vaccine Management System. We used a Cox regression model to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and Ad26.COV2.S (Johnson & Johnson-Janssen) vaccines in reducing the current risks of Covid-19, hospitalization, and death, as a function of time elapsed since vaccination. RESULTS: For the two-dose regimens of messenger RNA (mRNA) vaccines BNT162b2 (30 µg per dose) and mRNA-1273 (100 µg per dose), vaccine effectiveness against Covid-19 was 94.5% (95% confidence interval [CI], 94.1 to 94.9) and 95.9% (95% CI, 95.5 to 96.2), respectively, at 2 months after the first dose and decreased to 66.6% (95% CI, 65.2 to 67.8) and 80.3% (95% CI, 79.3 to 81.2), respectively, at 7 months. Among early recipients of BNT162b2 and mRNA-1273, effectiveness decreased by approximately 15 and 10 percentage points, respectively, from mid-June to mid-July, when the delta variant became dominant. For the one-dose regimen of Ad26.COV2.S (5 × 1010 viral particles), effectiveness against Covid-19 was 74.8% (95% CI, 72.5 to 76.9) at 1 month and decreased to 59.4% (95% CI, 57.2 to 61.5) at 5 months. All three vaccines maintained better effectiveness in preventing hospitalization and death than in preventing infection over time, although the two mRNA vaccines provided higher levels of protection than Ad26.COV2.S. CONCLUSIONS: All three Covid-19 vaccines had durable effectiveness in reducing the risks of hospitalization and death. Waning protection against infection over time was due to both declining immunity and the emergence of the delta variant. (Funded by a Dennis Gillings Distinguished Professorship and the National Institutes of Health.).

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level.

Phase II trial of bortezomib alone or in combination with irinotecan in patients with adenocarcinoma of the gastroesophageal junction or stomach.

PURPOSE: To determine the effectiveness of bortezomib plus irinotecan and bortezomib alone in patients with advanced gastroesophageal junction (GEJ) and gastric adenocarcinoma. We also sought to explore the effect of these therapeutics on tumor and normal gene expression in vivo. METHODS: Forty-one patients with advanced GEJ (89 %) or gastric (11 %) adenocarcinoma received bortezomib (1.3 mg/m(2) days 1, 4, 8, 11) plus irinotecan (125 mg/m(2) days 1, 8) every 21 days as first line therapy (N = 29), or bortezomib alone as second line therapy (N = 12). The trial was designed to detect a 40 % response rate for the combination, and 20 % response rate for bortezomib alone. Affymetrix HU133A gene chip arrays were used for gene expression studies. RESULTS: Objective response occurred in 3 of 29 patients (10 %, 95 % confidence intervals [CI] 2 %, 27 %) treated with bortezomib plus irinotecan, and in 1 of 12 patients (8 %, 95 % CI 0 %, 39 %) with bortezomib alone. Due to the limited number of responders, there were no significant correlations with response found in the gene expression profiles of 12 patients whose tumors were sampled before and 24 h after therapy with bortezomib alone (N = 2) or the combination (N = 10). CONCLUSIONS: We conclude that bortezomib is not effective for the treatment of advanced adenocarcinoma of the GEJ or stomach, whether used alone or in combination with irinotecan, in an unselected patient population.

Manual removal of the placenta and postcesarean endometritis.

OBJECTIVE: To determine if manual vs. spontaneous delivery of the placenta at cesarean section affects the rate of postoperative endometritis and amount of blood loss. STUDY DESIGN: A prospective, randomized study was carried out on patients who had cesarean delivery assigned either to spontaneous delivery of the placenta (group 1) or manual removal (group 2). We excluded patients undergoing emergency cesareans and those with possible placenta accreta or evidence of preexisting infection. Outcome measures (frequency of endometritis and quantitative decrease in hemoglobin) were compared for the two groups. RESULTS: Study criteria were met for 375 subjects: 177 in group 1 and 198 in group 2. Endometritis was diagnosed in 1.7% of the former and 2.5% of the latter. The change in hemoglobin, reflecting operative blood loss, was similar in both groups (-1.81 and -1.72 g/dL, respectively). CONCLUSION: We found no significant difference in either postoperative endometritis or blood loss regardless of the means used to effect delivery of the placenta. The frequency of febrile morbidity in our study cases was considerably lower than heretofore reported.