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Understanding the variables that affect the anaerobic potentially mineralizable N (PMNan) test should lead to a standard procedure of sample collection and incubation length, improving PMNan as a tool in corn (Zea mays L.) N management. We evaluated the effect of soil sample timing (preplant and V5 corn development stage [V5]), N fertilization (0 and 180 kg ha−1) and incubation length (7, 14, and 28 d) on PMNan (0–30 cm) across a range of soil properties and weather conditions. Soil sample timing, N fertilization, and incubation length affected PMNan differently based on soil and weather conditions. Preplant vs. V5 PMNan tended to be greater at sites that received < 183 mm of precipitation or < 359 growing degree-days (GDD) between preplant and V5, or had soil C/N ratios > 9.7:1; otherwise, V5 PMNan tended to be greater than preplant PMNan. The PMNan tended to be greater in unfertilized vs. fertilized soil in sites with clay content > 9.5%, total C < 24.2 g kg−1, soil organic matter (SOM) < 3.9 g kg−1, or C to N ratios < 11.0:1; otherwise, PMNan tended to be greater in fertilized vs. unfertilized soil. Longer incubation lengths increased PMNan at all sites regardless of sampling methods. Since PMNan is sensitive to many factors (sample timing, N fertilization, incubation length, soil properties, and weather conditions), it is important to follow a consistent protocol to compare PMNan among sites and potentially use PMNan to improve corn N management. [ABSTRACT FROM AUTHOR]

Crop growth and yield can be efficiently monitored using canopy reflectance. However, the spatial resolution of freely available remote sensing data is too coarse to fully understand the spatial dynamics of crop status. The objective of this study was to downscale Landsat 7 (L7) reflectance from the native resolution of 30 × 30 m to that typical of yield maps (ca. 5 × 5 m) over two fields in northeastern Colorado, USA. The fields were cultivated with winter wheat ( Triticum aestivum L.) in the 2002-2003 growing season. Geospatial yield measurements were available (1 per ca. 20 m). Geophysical (apparent soil electrical conductivity and bare-soil imagery) and terrain (micro-elevation) data were acquired (resolution <5 × 5 m) to characterize soil spatial variability. Geographically-weighted regressions were established to study the relationships between L7 reflectance and the geophysical and terrain data at the 30 × 30 m scale. Geophysical and terrain sensors could describe a large portion of the L7 reflectance spatial variability (0.83 < R < 0.94). Maps for regression parameters and intercept were obtained at 30 × 30 m and used to estimate the L7 reflectance at 5 × 5 m resolution. To independently assess the quality of the downscaling procedure, yield maps were used. In both fields, the 5 × 5 m estimated reflectance showed stronger correlations (average increase in explained variance = 3.2 %) with yield than at the 30 × 30 m resolution. Land resource managers, producers, agriculture consultants, extension specialists and Natural Resource Conservation Service field staff would be the beneficiaries of downscaled L7 reflectance data. [ABSTRACT FROM AUTHOR]

Abstract: The seasonal patterns of green leaf area index (GLAI) can be used to assess crop physiological and phenological status, to assess yield potential, and to incorporate in crop simulation models. This study focused on examining the potential capabilities and limitations of satellite data retrieved from the moderate resolution imaging spectroradiometer (MODIS) 8- and 16-day composite products to quantitatively estimate GLAI over maize (Zea mays L.) fields. Results, based on the nine years of data used in this study, indicated a wide variability of temporal resolution obtained from MODIS 8- and 16-day composite periods and highlighted the importance of information about day of MODIS products pixel composite for monitoring agricultural crops. Due to high maize GLAI temporal variability, the inclusion of day of pixel composite is necessary to decrease substantial uncertainties in estimating GLAI. Results also indicated that maize GLAI can be accurately retrieved from the 250-m resolution MODIS products (MOD13Q1 and MOD09Q1) by a wide dynamic range vegetation index with root mean square error (RMSE) below 0.60m2 m−2 or by the enhanced vegetation index with RMSE below 0.70m2 m−2. [Copyright &y& Elsevier]

Accurate nitrogen (N) diagnosis early in the growing season across diverse soil, weather, and management conditions is challenging. Strategies using multi-source data are hypothesized to perform significantly better than approaches using crop sensing information alone. The objective of this study was to evaluate, across diverse environments, the potential for integrating genetic (e.g., comparative relative maturity and growing degree units to key developmental growth stages), environmental (e.g., soil and weather), and management (e.g., seeding rate, irrigation, previous crop, and preplant N rate) information with active canopy sensor data for improved corn N nutrition index (NNI) prediction using machine learning methods. Thirteen site-year corn (Zea mays L.) N rate experiments involving eight N treatments conducted in four US Midwest states in 2015 and 2016 were used for this study. A proximal RapidSCAN CS-45 active canopy sensor was used to collect corn canopy reflectance data around the V9 developmental growth stage. The utility of vegetation indices and ancillary data for predicting corn aboveground biomass, plant N concentration, plant N uptake, and NNI was evaluated using singular variable regression and machine learning methods. The results indicated that when the genetic, environmental, and management data were used together with the active canopy sensor data, corn N status indicators could be more reliably predicted either using support vector regression (R2 = 0.74–0.90 for prediction) or random forest regression models (R2 = 0.84–0.93 for prediction), as compared with using the best-performing single vegetation index or using a normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) together (R2 < 0.30). The N diagnostic accuracy based on the NNI was 87% using the data fusion approach with random forest regression (kappa statistic = 0.75), which was better than the result of a support vector regression model using the same inputs. The NDRE index was consistently ranked as the most important variable for predicting all the four corn N status indicators, followed by the preplant N rate. It is concluded that incorporating genetic, environmental, and management information with canopy sensing data can significantly improve in-season corn N status prediction and diagnosis across diverse soil and weather conditions. [ABSTRACT FROM AUTHOR]

• Incorporating soil and weather information improves nitrogen recommendation tools. • Extent of improvement of recommendation tools depended on tool type. • Random forest algorithm best improves recommendation tools. • Decision tree most helpful at identifying and interpreting important variables. Nitrogen (N) fertilizer recommendation tools could be improved for estimating corn (Zea mays L.) N needs by incorporating site-specific soil and weather information. However, an evaluation of analytical methods is needed to determine the success of incorporating this information. The objectives of this research were to evaluate statistical and machine learning (ML) algorithms for utilizing soil and weather information for improving corn N recommendation tools. Eight algorithms [stepwise, ridge regression, least absolute shrinkage and selection operator (Lasso), elastic net regression, principal component regression (PCR), partial least squares regression (PLSR), decision tree, and random forest] were evaluated using a dataset containing measured soil and weather variables from a regional database. The performance was evaluated based on how well these algorithms predicted corn economically optimal N rates (EONR) from 49 sites in the U.S. Midwest. Multiple algorithm modeling scenarios were examined with and without adjustment for multicollinearity and inclusion of two-way interaction terms to identify the soil and weather variables that could improve three dissimilar N recommendation tools. Results showed the out-of-sample root-mean-square error (RMSE) for the decision tree and some random forest modeling scenarios were better than the stepwise or ridge regression, but not significantly different than any other algorithm. The best ML algorithm for adjusting N recommendation tools was the random forest approach (r2 increased between 0.72 and 0.84 and the RMSE decreased between 41 and 94 kg N ha−1). However, the ML algorithm that best adjusted tools while using a minimal amount of variables was the decision tree. This method was simple, needing only one or two variables (regardless of modeling scenario) and provided moderate improvement as r2 values increased between 0.15 and 0.51 and RMSE decreased between 16 and 66 kg N ha−1. Using ML algorithms to adjust N recommendation tools with soil and weather information shows promising results for better N management in the U.S. Midwest. [ABSTRACT FROM AUTHOR]

Background: The study determined the proportion of patients with pancreatic adenocarcinoma (PDAC) who had margin-positive disease and no other adverse pathologic findings (APF) using institutional and administrative datasets., Methods: Patients with clinical stage I or II PDAC in the National Cancer Database (NCDB 2010-2020) and those who underwent pancreatectomy at the authors' institution (2010-2021) were identified. Isolated margin positivity (IMP) was defined as a positive surgical margin with no APF (negative nodes, no lymphovascular/perineural invasion)., Results: The study included 225 patients from the authors' institution and 23,598 patients from the NCDB. The margin-positive rates were 21.8% and 20.3%, and the IMP rates were 0.4% and 0.5%, respectively. In the institutional cohort, 68.4% of the patients had recurrence, and most of the patients (65.6%) had distant recurrences. The median recurrence-free survival (RFS) was 63.3 months for no APF, not reached for IMP, 14.8 months for negative margins & 1 APF, 20.3 months for positive margins & 2 APFs, and 12.9 months with all APF positive. The patients in the NCDB with IMP had a lower median OS than the patients with no APF (20.5 vs 390 months), but a higher median OS than those with margin positivity plus 1 APF (20.5 vs 18.0 months) or all those with APF positivity (20.5 vs 15.4 months). Based on institutional rates of IMP, any margin positivity, neck margin positivity (NMP), and no APF, the fraction of patients who might benefit from neck margin revision was 1 in 100,000, and those likely to benefit from any margin revision was 1 in 18,500. In the NCDB, those estimated to derive potential benefit from margin revision was 1 in 25,000., Conclusions: Isolated margin positivity in resected PDAC is rare, and most patients experience distant recurrence. Revision of IMP appears unlikely to confer benefit to most patients., (© 2024. The Author(s).)

Background: Cardiovascular disease and cancer share a common risk factor: chronic stress/allostatic load (AL). A 1-point increase in AL is linked to up to a 30% higher risk of major cardiac events (MACE) in patients with prostate cancer. However, AL's role in MACE in breast cancer, lung cancer, or colorectal cancer remains unknown., Methods and Results: Patients ≥18 years of age diagnosed with the mentioned 3 cancers of interest (2010-2019) and followed up at a large, hybrid academic-community practice were included in this retrospective cohort study. AL was modeled as an ordinal measure (0-11). Adjusted Fine-Gray competing risks regressions estimated the impact of AL precancer diagnosis on 2-year MACE (a composite of heart failure, ischemic stroke, acute coronary syndrome, and atrial fibrillation). The effect of AL changes over time on MACE was calculated via piecewise Cox regression (before, and 2 months, 6 months, and 1 year after cancer diagnosis). Among 16 467 patients, 50.5% had breast cancer, 27.9% had lung cancer, and 21.4% had colorectal cancer. A 1-point elevation in AL before breast cancer diagnosis corresponded to a 10% heightened associated risk of MACE (adjusted hazard ratio, 1.10 [95% CI, 1.06-1.13]). Similar findings were noted in lung cancer (adjusted hazard ratio, 1.16 [95% CI, 1.12-1.20]) and colorectal cancer (adjusted hazard ratio, 1.13 [95% CI, 1.08-1.19]). When considering AL as a time-varying exposure, the peak associated MACE risk occurred with a 1-point AL rise between 6 and 12 months post- breast cancer, lung cancer, and colorectal cancer diagnosis., Conclusions: AL warrants investigation as a potential marker in these patients to identify those at elevated cardiovascular risk and intervene accordingly.

Objective: To assess the frequency of occult metastases (OM) in patients with resected pancreatic ductal adenocarcinoma (PDAC) or ampullary adenocarcinoma (AA) discovered on detailed pathologic examination on lymph nodes (LNs) previously considered negative by conventional analysis and to examine the association between OM and overall survival (OS)., Background: Poor prognosis of patients with no pathologic evidence of LN metastases may be due to OM that is not detected on conventional LN analysis., Methods: Patients with LN-negative resected PDAC or AA (2010-2020) were identified from our institutional database. Original hematoxylin and eosin ( H and E ) slides were reanalyzed. In addition, selected LN were analyzed by H and E (3 sections/LN) and pan-cytokeratin (AE1-AE3/PCK26) immunohistochemistry., Results: A total of 598 LNs from 74 LN-negative patients were reexamined. Nineteen patients (25.7%) had OM; 9 (47.4%) were found with immunohistochemistry but not on H and E . The number of positive LNs ranged from 1 to 3. No clinicodemographic, pathologic, or treatment-related factors were associated with OM. On conventional LN analysis, 3/19 patients (15.8%) had stage IA, 9/34 (26.5%) had stage IB, and 7/19 (36.8%) had stage IIA. On detailed LN analysis, 11/19 patients (57.9%) were upstaged to IIB, whereas 8/19 (42.1%) had isolated tumor cells only (N0i+). OM was associated with shorter OS (median OS: 22.3 vs 50.5 months; hazard ratio=3.95, 95% CI: 1.58-9.86)., Conclusions: There is a 26% discordance rate between conventional and detailed LN pathologic analysis in resected PDAC and AA. The presence of OM is associated with shorter OS., Competing Interests: The authors report no conflicts of interest., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Racial disparities have been reported for breast cancer and cardiovascular disease (CVD) outcomes. The determinants of racial disparities in CVD outcomes are not yet fully understood. We aimed to examine the impact of individual and neighborhood-level social determinants of health (SDOH) on the racial disparities in major adverse cardiovascular events (MACE; consisting of heart failure, acute coronary syndrome, atrial fibrillation, and ischemic stroke) among female patients with breast cancer., Methods: This 10-year longitudinal retrospective study was based on a cancer informatics platform with electronic medical record supplementation. We included women aged ≥18 years diagnosed with breast cancer. SDOH were obtained from LexisNexis, and consisted of the domains of social and community context, neighborhood and built environment, education access and quality, and economic stability. Race-agnostic (overall data with race as a feature) and race-specific machine learning models were developed to account for and rank the SDOH impact in 2-year MACE., Results: We included 4,309 patients (765 non-Hispanic Black [NHB]; 3,321 non-Hispanic white). In the race-agnostic model (C-index, 0.79; 95% CI, 0.78-0.80), the 5 most important adverse SDOH variables were neighborhood median household income (SHapley Additive exPlanations [SHAP] score [SS], 0.07), neighborhood crime index (SS = 0.06), number of transportation properties in the household (SS = 0.05), neighborhood burglary index (SS = 0.04), and neighborhood median home values (SS = 0.03). Race was not significantly associated with MACE when adverse SDOH were included as covariates (adjusted subdistribution hazard ratio, 1.22; 95% CI, 0.91-1.64). NHB patients were more likely to have unfavorable SDOH conditions for 8 of the 10 most important SDOH variables for the MACE prediction., Conclusions: Neighborhood and built environment variables are the most important SDOH predictors for 2-year MACE, and NHB patients were more likely to have unfavorable SDOH conditions. This finding reinforces that race is a social construct.

Background: Cardiovascular disease (CVD) is the leading cause of death in men with prostate cancer (PC). Accumulated stress plays an important role in CVD development. The cumulative burden of chronic stress and life events can be measured using allostatic load (AL)., Methods: The initial cohort included males aged 18 years and older diagnosed with PC (2005-2019). AL was modeled as an ordinal variable (0-11). Fine-Gray competing risk regressions measured the impact of precancer diagnosis AL and postdiagnosis AL in 2-year major cardiac events (MACE). The effect of AL changes over time on MACE development was calculated via piecewise Cox regression (before, and 2 months, 6 months, and 1 year after PC diagnosis)., Results: We included 5261 PC patients of which 6.6% had a 2-year MACE. For every 1-point increase in AL before and within 60 days after PC diagnosis, the risk of MACE increased 25% (adjusted hazard ratio [aHR] =1.25, 95% confidence interval [CI] = 1.18 to 1.33) and 27% (aHR = 1.27, 95% CI = 1.20 to 1.35), respectively. Using AL as a time-varying exposure, the risk of MACE increased 19% (aHR = 1.19, 95% CI = 1.11 to 1.27), 22% (aHR = 1.22, 95% CI = 1.14 to 1.33), 28% (aHR = 1.28, 95% CI = 1.23 to 1.33), and 31% (aHR = 1.31, 95% CI = 1.27 to 1.35) for every 1-point increase in AL before, 2 months after, 6 months after, and 1 year after PC diagnosis, respectively., Conclusion: AL and its changes over time are associated with MACE in PC patients, suggesting a role of a biological measure of stress as a marker of CVD risk among men with PC., (© The Author(s) 2023. Published by Oxford University Press.)

The main objective of this work was to perform a comprehensive analysis and provide a race-stratified epidemiological report accounting for differences in treatment patterns and treatment related adverse events in Non-Hispanic women with breast cancer (BC). The cohort included women ≥ 18 years diagnosed with in-situ, early-stage, and late-stage BC (2005-2022). Treatment patterns included: surgery, breast radiation, chemotherapy, endocrine therapy, or biologic therapy. Treatment related adverse events were: chemotherapy complications, cardiovascular toxicities, immune-related adverse events, psychological affectations, or cognitive decline/dementia. The influence of race on the outcomes was measured via Cox proportional-hazards models. We included 17,454 patients (82% non-Hispanic Whites [NHW]). Most of the patients had a Charlson Comorbidity Score between 1 and 2 (68%), and TNM stage I (44.5%). Surgery was performed in 51.5% of the cases, while 30.6% received radiotherapy, 26.4% received chemotherapy, 3.1% received immunotherapy, and 41.2% received endocrine therapy. Non-Hispanic Blacks (NHB) had a lower probability of undergoing breast cancer surgery (aHR = 0.92, 95% CI 0.87-0.97) and of being prescribed endocrine therapy (aHR = 0.83, 95% CI 0.79-0.89), but a higher probability of receiving adjuvant radiotherapy (aHR = 1.40, 95% CI 1.29-1.52). Moreover, NHBs had lower risk of being diagnosed with psychological issues (aHR = 0.71, 95% CI 0.63-0.80) but a higher risk for cognitive decline/dementia (aHR = 1.30, 95% CI 1.08-1.56). In conclusion, NHB women diagnosed with BC were less likely than NHW to undergo curative intent surgery or receive endocrine therapy, and had a higher risk of cognitive decline/dementia after cancer treatment. Public policy measures are urgently needed which equalize access to quality healthcare for all patients and that promote a learning healthcare system which can improve cancer outcomes., (© 2023. The Author(s).)

Introduction: Autoimmune disease has both a predisposing and a protective effect toward malignancy. Though studies have investigated the risk of malignancy in patients with autoimmune disease, there is limited research on how autoimmunity affects survival., Methods: This study compared survival in patients with lung cancer with and without autoimmune disease. Patients with lung cancer were culled from the Surveillance, Epidemiology, and End Results Medicare databases (2007-2014), and autoimmune diseases were identified using diagnosis codes., Results: The overall prevalence of investigated autoimmune diseases among the 112,445 patients was 22.7%. Overall survival (OS) ( p < 0.0001) was longer and cancer-specific mortality (CSM) ( p < 0.0001) reduced among patients with autoimmune disease. Median OS was 5 months higher. Improved OS and CSM were also apparent in disease stages 1, 3, and 4 in the NSCLC and SCLC subgroups ( p < 0.0001) and across most specific autoimmune diseases. After adjusting for the effects of age, sex, race, disease stage, and chronic kidney disease, autoimmune disease was still predictive of higher OS (hazard ratio = 1.23, 95% confidence interval: 1.21-1.25, p < 0.0001) and reduced CSM (hazard ratio = 1.16, 95% confidence interval: 1.14-1.18, p < 0.0001)., Conclusions: The prevalence of rheumatoid arthritis, inflammatory bowel disease, and systemic lupus erythematous was highly enriched compared with the general population. The improvement in OS and CSM was larger in NSCLC than in SCLC, suggesting a larger role for the immune system in NSCLC. Alternate explanations for the improved survival include lead time bias, better access to health care, and a survival or autoimmunity-inducing genetic factor., (© 2022 The Authors.)

Background: Objective measures of post-pancreatectomy weight change for pancreatic ductal adenocarcinoma (PDAC) have not been extensively studied for long-term outcomes. We used weight measurements in our institutional medical record to analyze trends in post-pancreatectomy weight and determine the association with disease status., Methods: Pancreatectomies for PDAC (n = 315) and benign indications (n = 111) were identified. Preoperative baseline, minimum postoperative (Min #1), and subsequent postoperative maximum (Max) weights were abstracted. Multivariable Cox hazards regression was conducted to analyze the association between weight change and survival., Results: Median weight loss postoperatively in each group was > 20 lbs. PDAC patients gained 10 lbs after Min #1 compared to 15 lbs in the benign cohort (p < 0.001). Few patients returned to their preoperative weight (29.8% PDAC vs. 40.5% benign, p = 0.04). Patients with early PDAC recurrence (< 13 months) lost more weight (18.0% vs. 13.3% vs. 10.9%, p < 0.001) and gained less weight (2.1% vs. 12.0% vs. 7.9%, p < 0.001) compared with those with late cancer recurrence (≥ 13 months) or no evidence of active disease, respectively. PDAC patients lost 11.2 lbs in the year preceding recurrence diagnosis. Weight loss was not associated with survival; however, weight gain was associated with improved survival., Conclusions: Resections for PDAC are complicated by a similar degree of weight loss as patients with benign disease, and there is no association with survival. However, failure to gain weight is especially ominous. Weight loss after weight recovery foreshadows disease recurrence. These data suggest that rigorous weight tracking is an untapped surveillance strategy in patients with PDAC., (© 2022. Society of Surgical Oncology.)

Background: Weight changes during neoadjuvant chemotherapy (NAC) for pancreatic cancer (PDAC) are not well studied. We hypothesized that weight loss may predict poor outcomes., Methods: Weight change from NAC initiation to pancreatectomy was grouped: gain (≥5%), stable, and loss (≥5%). Pathologic, postoperative, and survival outcomes were compared., Results: 95 patients were included: 31.6% lost weight, 58.9% maintained weight, and 9.5% gained weight. There were no differences in chemotherapeutic regimens. Median recurrence-free survival (RFS) and overall survival (OS) were similar between patients with stable weight and those who lost weight (RFS: 9.6vs14.0months; OS: 25.8vs26.7months). Among those who gained weight, RFS (29.5months) and OS (38.4months) were greater relative to the other weight categories. On multivariable regression, weight gain was associated with improved RFS compared to loss (HR = 0.16)., Conclusion: Most patients maintain or lose weight during NAC, and weight loss does not predict poor outcomes. Weight gain may predict improved RFS., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Pancreatic ductal adenocarcinoma (PDAC) has the worst survival of common cancers, partly because there are no reliable early detection tests. Unintentional weight loss (≥ 5% decrease from baseline) has been linked to PDAC, but the frequency and severity of weight loss using objective measures, and its relationship to prognosis, have not been well characterized., Methods: We identified 390 patients with PDAC (all stages) and two or more prediagnosis weights in the electronic medical record. Percentage weight loss in the 365 and 180 days preceding diagnosis was calculated. Results were compared with raw weights of age- and sex-matched non-cancer controls (n = 780). Odds ratios for PDAC were calculated using conditional logistic regression. Cox proportional hazards models were used for survival., Results: Within 1 year of diagnosis, more PDAC patients lost ≥ 5% weight relative to controls (74.9% vs. 11.2%; p < 0.001), with a median weight loss of 14.2 versus 2.9 lbs. The odds ratio for PDAC comparing weight loss within 1 year of 5 to < 10% was 10.30 (p < 0.001) and 77.82 for ≥ 10% (p < 0.001), compared with stable weight. Weight loss prior to diagnosis was also associated with early-stage PDAC. PDAC cases with ≥ 10% prediagnosis weight loss had worse survival compared with stable weights (hazard ratio [HR] 1.60; p = 0.01). Greater prediagnosis weight loss was associated with poor survival after pancreatectomy (5 to < 10% vs. < 5%, HR 2.40, p = 0.03; ≥ 10% vs. < 5%, HR 2.59, p = 0.03)., Conclusions: Diagnosis of PDAC is preceded by unintentional weight loss in the majority of patients, even at an early stage. Greater prediagnosis weight loss severity is also associated with poor postoperative survival., (© 2021. Society of Surgical Oncology.)

Objectives: COVID-19 created unexpected delays in oncologic treatment. This study sought to assess the volume of missed cancer-related services due to the pandemic. Methods: This case-controlled trial evaluated more than 345,000 oncologic clinic, lab, and radiation appointments from January 1, 2019, through December 31, 2020, and surgery appointments from January 1, 2019, through October 31, 2020. All patients at the Seidman Cancer Center with a cancer diagnosis based on a comprehensive list of 2178 International Classification of Diseases, Ninth Edition (ICD-9) and ICD-10 codes were included in the analysis. Subgroup analyses based on age, race, and sex were also performed. Results: Clinic, lab, and surgical visit cancellations increased by 4.20% (P <.001), 4.84% (P <.001), and 5.22% (P <.001), respectively. In the first 10 months of 2020, there were 703 (9.2%) fewer surgeries compared with the same time period in 2019. The following cancellation rates peaked in March 2020: clinic visits (26.53%), labs (43.66%), surgery (34.00%). Radiation oncology (12.53%) cancellations peaked in April 2020. Prior to the emergence of COVID-19, the group aged 0 to 39 years had the highest clinic cancellation rate (17.85%) compared with patients aged 40 to 64 years (15.95%) and 65 years and older (14.52%; P <.001). Men cancelled (15.63%) significantly more often than women (14.93%; P <.001) in 2019. This reversed during the pandemic: Women (19.56%) cancelled more frequently than men (19.20%; P <.036). Conclusions: There was a large increase in cancelled oncologic care in 2020, which has implications for delayed diagnosis and treatment. This was especially true for patients older than 65 years and for women. These delays could result in patients presenting with more advanced disease, complicating morbidities, and ultimately worse long-term outcomes.

Purpose: Human papilloma virus-positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC), diagnosed with p16 immunohistochemistry, is associated with favorable prognosis; however, this connection was established using European American (EA)-skewed populations. The impact of p16/human papillomavirus status on outcomes in African American (AA) OPSCC patients remains to be settled. In this study, we determine the association between cancer disparity and p16 status in an OPSCC cohort controlling for time to treatment initiation (TTI), a surrogate for medical care access., Materials and Methods: We analyzed data from all patients diagnosed with OPSCC (N = 440) between 2010 and 2017, who received treatment at our academic medical center. Associations between age, disease stage, sex, p16 status, race, TTI, and overall survival (OS) were investigated., Results: TTI was similar between AA and EA OPSCC patients in our p16+ ( P = .291) or p16- ( P = .715) cohorts. Among p16+ OPSCC patients, the median OS was > 8.65 years for EA patients compared with 5.038 years (95% CI, 2.019 to 5.30; P = .003, log-rank) for AA patients. For p16- patients, the median OS was 5.74 years (95% CI, 3.32 to 6.99) for EA patients and 1.85 years (95% CI, 0.978 to 4.50; P = .03, log-rank) for AA patients. Multivariate Cox regression analysis showed that race was an independent prognostic biomarker and the most impactful co-variate for OS (hazard ratio, 0.40; 95% CI, 0.00 to 0.69; P = .001)., Conclusion: Our work showed that AAs with p16+ OPSCC have surprisingly poor clinical outcomes and are thus poor candidates for treatment de-escalation regimens. Caution should be exercised when extending clinical guidelines based on EA-majority studies to non-EA populations., Competing Interests: Rod RezaeeHonoraria: Zimmer BiometSpeakers' Bureau: Zimmer BiometPatents, Royalties, Other Intellectual Property: Zimmer/Biomet trauma fixation deviceTravel, Accommodations, Expenses: Zimmer BioMet Quintin PanResearch Funding: Bristol Myers Squibb FoundationPatents, Royalties, Other Intellectual Property: I have patents on p53 reactivation therapeutics for HPV+ HNSCCNo other potential conflicts of interest were reported.

A nitrifying biofilm was grown in a laboratory-scale membrane aerated bioreactor (MABR) to calibrate and test a one-dimensional biofilm model incorporating chemical equilibria to calculate local pH values. A previously developed model (Shanahan and Semmens, 2004) based upon AQUASIM was modified to incorporate the impact of local pH changes within the biofilm on the kinetics of nitrification. Shielded microelectrodes were used to measure the concentration profiles of dissolved oxygen, ammonium, nitrate, and pH within the biofilm and the overlying boundary layer under actual operating conditions. Operating conditions were varied to assess the impact of bicarbonate loading (alkalinity), ammonium loading, and intra-membrane oxygen partial pressure on biofilm performance. Nitrification performance improved with increased ammonium and bicarbonate loadings over the range of operating conditions tested, but declined when the intra-membrane oxygen partial pressure was increased. Minor discrepancies between the measured and predicted concentration profiles within the biofilm were attributed to changes in biofilm density and vertical heterogeneities in biofilm structure not accounted for by the model. Nevertheless, predicted concentration profiles within the biofilm agreed well with experimental results over the range of conditions studied and highlight the fact that pH changes in the biofilm are significant especially in low alkalinity waters. The influent pH and buffer capacity of a wastewater may therefore have a significant impact on the performance of a membrane-aerated bioreactor with respect to nitrification, and nitrogen removal., (Copyright © 2015 Elsevier Ltd. All rights reserved.)