COVID-19 impacts on residential occupancy schedules and activities in U.S. Homes in 2020 using ATUS.

Many aspects of the daily lives of those living in the United States were substantially impacted by the COVID-19 pandemic in the year 2020. A broad diversity of measures was implemented to curb the spread of the virus, many of which included adjustments to where and how people worked, went to school, and otherwise conducted their daily lives compared to pre-pandemic times. This has impacted how residential buildings are used, how much time people spend in their homes, and as a result, how much energy these buildings consume. The main objective of this study is to analyze, at a national scale, the differences in the occupancy schedules and activities conducted in homes in the U.S., as compared to pre-pandemic. 15 years of American Time Use Survey and Current Population Survey data, from 2006 to 2020, was used in this study to analyze the occupancy schedules for both pandemic (2020) and pre-pandemic (2006-2019) times. These impacts were also analyzed with respect to variables including, weekday/weekend, month of the year, age of the occupants, household income, and household size. The impact of the pandemic on occupant schedules were most substantial in the initial months, whereas as the months progressed, these occupancy profiles slowly changed. Across 2020, people spent, on average, 8 % more time (1.9 h) in their home on weekdays, and 3-6 % (1.2 h) on weekend days. The percentage of time spent for different activities and locations within homes were also studied. For 1-member households, their time spent at home decreased whereas for 2-, 3-, and 4- member households, they spent more time at home. Overall, people spent around 45% more time doing office- and work-related activities at home compared to pre-pandemic, which is likely due to increased remote working and schooling. This research helps to improve the understanding of the occupancy presence and absence profiles in U.S. residential buildings due to the pandemic and provides new insights as to modified profiles for researchers, building designers, and policy makers.

Predicting daily PM2.5 concentrations in Texas using high-resolution satellite aerosol optical depth.

BACKGROUND AND OBJECTIVE: The regulatory monitoring data of particulate matter with an aerodynamic diameter <2.5µm (PM2.5) in Texas have limited spatial and temporal coverage. The purpose of this study is to estimate the ground-level PM2.5 concentrations on a daily basis using satellite-retrieved Aerosol Optical Depth (AOD) in the state of Texas. METHODS: We obtained the AOD values at 1-km resolution generated through the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm based on the images retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellites. We then developed mixed-effects models based on AODs, land use features, geographic characteristics, and weather conditions, and the day-specific as well as site-specific random effects to estimate the PM2.5 concentrations (µg/m3) in the state of Texas during the period 2008-2013. The mixed-effects models' performance was evaluated using the coefficient of determination (R2) and square root of the mean squared prediction error (RMSPE) from ten-fold cross-validation, which randomly selected 90% of the observations for training purpose and 10% of the observations for assessing the models' true prediction ability. RESULTS: Mixed-effects regression models showed good prediction performance (R2 values from 10-fold cross validation: 0.63-0.69). The model performance varied by regions and study years, and the East region of Texas, and year of 2009 presented relatively higher prediction precision (R2: 0.62 for the East region; R2: 0.69 for the year of 2009). The PM2.5 concentrations generated through our developed models at 1-km grid cells in the state of Texas showed a decreasing trend from 2008 to 2013 and a higher reduction of predicted PM2.5 in more polluted areas. CONCLUSIONS: Our findings suggest that mixed-effects regression models developed based on MAIAC AOD are a feasible approach to predict ground-level PM2.5 in Texas. Predicted PM2.5 concentrations at the 1-km resolution on a daily basis can be used for epidemiological studies to investigate short- and long-term health impact of PM2.5 in Texas.

Costs of Cancer Care for Elderly Patients with Neuroendocrine Tumors.

BACKGROUND: The incidence and prevalence of neuroendocrine tumors (NETs) have been steadily rising. NETs can arise in various parts of the body and have distinct pathogenesis, clinical manifestations, treatment, and survival compared to other neoplasms. The magnitude of the economic burden of NETs is largely unknown. This study aimed to estimate the cost of illness for NETs among elderly patients based on a large amount of observational data. METHODS: We estimated the direct medical costs by phase of care using the Surveillance, Epidemiology, and End Results-Medicare data, including claims from January 1, 2002 through to December 31, 2012. Patients' care was categorized into three phases: initial phase (first year after diagnosis), terminal phase (last year of life), and continuing phase (the period between). We estimated the cost of illness by calculating the difference in medical costs between NET patients and a matched sample from a non-cancer control group. RESULTS: Our study sample included 8409 elderly NET patients in the initial phase, 9218 patients in the continuing phase, and 7897 in the terminal phase. The mean cost of care for the initial phase was $46,462 in 2016 US dollars; mean cost of care for the terminal phase with a cancer-related death was $122,702; while the mean cost of care for the continuing phase was $10,457. The mean 5-year cost was $87,079. CONCLUSIONS: This population-based study showed that NET patients had substantial continuing phase costs and 5-year costs. Among elderly NET patients, those with pancreas as the primary cancer site had the highest costs.

A Bayesian basket trial design using a calibrated Bayesian hierarchical model.

BACKGROUND: The basket trial evaluates the treatment effect of a targeted therapy in patients with the same genetic or molecular aberration, regardless of their cancer types. Bayesian hierarchical modeling has been proposed to adaptively borrow information across cancer types to improve the statistical power of basket trials. Although conceptually attractive, research has shown that Bayesian hierarchical models cannot appropriately determine the degree of information borrowing and may lead to substantially inflated type I error rates. METHODS: We propose a novel calibrated Bayesian hierarchical model approach to evaluate the treatment effect in basket trials. In our approach, the shrinkage parameter that controls information borrowing is not regarded as an unknown parameter. Instead, it is defined as a function of a similarity measure of the treatment effect across tumor subgroups. The key is that the function is calibrated using simulation such that information is strongly borrowed across subgroups if their treatment effects are similar and barely borrowed if the treatment effects are heterogeneous. RESULTS: The simulation study shows that our method has substantially better controlled type I error rates than the Bayesian hierarchical model. In some scenarios, for example, when the true response rate is between the null and alternative, the type I error rate of the proposed method can be inflated from 10% up to 20%, but is still better than that of the Bayesian hierarchical model. LIMITATION: The proposed design assumes a binary endpoint. Extension of the proposed design to ordinal and time-to-event endpoints is worthy of further investigation. CONCLUSION: The calibrated Bayesian hierarchical model provides a practical approach to design basket trials with more flexibility and better controlled type I error rates than the Bayesian hierarchical model. The software for implementing the proposed design is available at http://odin.mdacc.tmc.edu/~yyuan/index_code.html.

Cancer and All-cause Mortality in Bladder Cancer Patients Undergoing Radical Cystectomy: Development and Validation of a Nomogram for Treatment Decision-making.

OBJECTIVE: To develop and validate a nomogram assessing cancer and all-cause mortality following radical cystectomy. Given concerns regarding the morbidity associated with surgery, there is a need for incorporation of cancer-specific and competing risks into patient counseling and recommendations. MATERIALS AND METHODS: A total of 5325 and 1257 diagnosed with clinical stage T2-T4a muscle-invasive bladder cancer from January 1, 2006 to December 31, 2011 from Surveillance, Epidemiology, and End Results-Medicare and Texas Cancer Registry-Medicare linked data, respectively. Cox proportional hazards models were used and a nomogram was developed to predict 3- and 5-year overall and cancer-specific survival with external validation. RESULTS: Patients who underwent radical cystectomy were mostly younger, male, married, non-Hispanic white and had fewer comorbidities than those who did not undergo radical cystectomy (P < .001). Married patients, in comparison with their unmarried counterparts, had both improved overall (hazard ratio 0.76; 95% confidence interval 0.70-0.83, P < .001) and cancer-specific (hazard ratio 0.76; 95% confidence interval 0.68-0.85, P < .001) survival. A nomogram developed using Surveillance, Epidemiology, and End Results-Medicare data, predicted 3- and 5-year overall and cancer-specific survival rates with concordance indices of 0.65 and 0.66 in the validated Texas Cancer Registry-Medicare cohort, respectively. CONCLUSION: Older, unmarried patients with increased comorbidities are less likely to undergo radical cystectomy. We developed and validated a generalizable instrument that has been converted into an online tool (Radical Cystectomy Survival Calculator), to provide a benefit-risk assessment for patients considering radical cystectomy.

Increased Utilization of Positron Emission Tomography/Computed Tomography (PET/CT) Imaging and Its Economic Impact for Patients Diagnosed With Bladder Cancer.

BACKGROUND: The purpose of this study was to examine temporal nationwide utilization patterns and predictors for use of positron emission tomography/computed tomography (PET/CT) in comparison with magnetic resonance imaging (MRI) and computed tomography (CT) among patients diagnosed with bladder cancer. MATERIALS AND METHODS: A total of 36,855 patients aged 66 years or older diagnosed with clinical stage TI-IV, N0M0 bladder cancer from 2004 to 2011 were analyzed. We used multivariable logistic regression analyses to discern factors associated with receipt of imaging within 12 months from diagnosis. The Cochran-Armitage test for trend was used to determine changes in the proportion of patients receiving imaging after cancer diagnosis. RESULTS: Independent of clinical stage, there was marked increase in use of PET/CT throughout the study period (2011 vs. 2004: odds ratio, 17.55; 95% confidence interval, 10.14-30.38; P < .001). Although use of CT imaging remained stable during the study period, there was significantly decreased utilization of MRI (odds ratio, 0.60; 95% confidence interval, 0.49-0.75; P < .001) in 2011 versus 2004. The mean incremental cost of PET/CT versus CT and MRI was $1040 and $612 (in 2016 dollars), respectively. Extrapolating these findings to the patients with bladder cancer in the United States results in excess spending of $11.6 million for PET/CT imaging. CONCLUSION: We identified rapid adoption of PET/CT imaging independent of clinical stage, resulting in excess national spending of $11.6 million for this imaging modality alone. Further value-based research discerning the clinical versus economic benefits of advanced imaging among patients with bladder cancer are needed.

Carcinoid Syndrome and Costs of Care During the First Year After Diagnosis of Neuroendocrine Tumors Among Elderly Patients.

BACKGROUND: Neuroendocrine tumors (NETs) can secrete hormonal peptides that lead to additional symptom burdens. However, it is largely unknown whether and to what extent the additional symptom burdens translate into higher costs of care. This study aimed to examine the cost pattern of elderly NET patients during the first year of diagnosis, taking into account of the carcinoid syndrome status. METHODS: We used Surveillance, Epidemiology, and End Results Medicare data to identify elderly NET patients diagnosed between January 2003 and December 2011. Patients who had at least two claims indicative of carcinoid syndrome during the 3 months before and after the NET diagnosis were considered to have carcinoid syndrome. We adopted a payer's perspective and quantified economic outcomes using the following three measures: (a) total Medicare reimbursement amount, (b) inpatient amount, and (c) outpatient amount. We used a generalized linear model (GLM) to examine the association between syndrome and costs. RESULTS: Our study cohort included 6,749 elderly NET well-differentiated and moderately differentiated patients. Of these patients, 5,633 (83%) were alive 1 year after diagnosis with continuous enrollment, and 1,116 (17%) died within 1 year. The multivariable GLM showed significant association between the syndrome and higher total, inpatient, and outpatient costs among the group who survived the whole year; the association was insignificant among the group who died within the first year of diagnosis. CONCLUSION: This population-based study showed that NET patients with carcinoid syndrome incurred higher costs of care especially among those who survived the first year of diagnosis. IMPLICATIONS FOR PRACTICE: This is the first population-based study that examines the health care costs associated with carcinoid syndrome among neuroendocrine tumor patients. Among patients alive throughout the first year, the unadjusted analyses showed that total median monthly costs were above $1,000 higher ($3,801 vs. $2,481) for patients with carcinoid syndrome compared with patients without. A significant association was found between carcinoid syndrome and higher total inpatient and outpatient costs among the group that survived the whole year even after controlling for clinical factors, treatment received, and demographics and neighborhood socioeconomic status; the association was insignificant among the group that died within the first year of diagnosis.

Frequency of carcinoid syndrome at neuroendocrine tumour diagnosis: a population-based study.

BACKGROUND: Neuroendocrine tumours (NETs) can secrete bioactive amines into the bloodstream, causing carcinoid syndrome, with symptoms including flushing and diarrhoea. However, carcinoid syndrome frequency in the NET population has never been rigorously assessed, nor has its relationship to presenting clinicopathological characteristics. This analysis assessed the proportion of patients with NETs and carcinoid syndrome in the USA and associated clinical factors. METHODS: We identified patients (≥65 years of age) from the Surveillance, Epidemiology, and End Results-Medicare database, excluding those with pancreatic tumours or small-cell or large-cell lung cancer, as well as those without complete data. We assessed the incidence of patients with at least two insurance claims of flushing, diarrhoea, or carcinoid syndrome during the 3 months before and after NET diagnosis. We compared demographic and clinical characteristics between patients with and without carcinoid syndrome using χ2 tests. We used the Cochran-Armitage trend test to identify trends in carcinoid syndrome incidence and Cox regression to assess the relationship between carcinoid syndrome and survival. FINDINGS: Between April 1, 2000, and Dec 31, 2011, 9512 eligible patients were diagnosed with NETs, of whom 1786 (19%) had carcinoid syndrome. The number of patients with NETs and carcinoid syndrome increased from 50 (11%) of 465 patients in 2000 to 160 (19%) of 854 in 2011 (p<0·0001). The proportion of patients with carcinoid syndrome compared with those without did not differ significantly with respect to age at diagnosis (p=0·65), geographical region (p=0·054), or urban versus rural status (p=0·53). Patients with carcinoid syndrome were more frequently female than male (p=0·0003). Race was associated with a significant difference in the reported incidence of carcinoid syndrome (p<0·0001), as was tumour grade, stage, and primary tumour site (all p<0·0001). Patients with carcinoid syndrome had a shorter overall survival (median 5 years [95% CI 4·5-5·4]) than did those without carcinoid syndrome (5·6 years [5·4-5·9]; hazard ratio 1·102 [1·016-1·194]; p=0·019). Use of octreotide (p<0·0001) and chemotherapy (p=0·003) were more common in patients with carcinoid syndrome than in those without it, whereas surgery was used more frequently in patients without carcinoid syndrome (p=0·009); use of radiotherapy was not significantly associated with the presence of carcinoid syndrome at diagnosis (p=0·07). INTERPRETATION: This population-based analysis reveals that carcinoid syndrome is significantly associated with tumour grade, stage, and primary tumour site, and leads to shorter survival compared with those patients without carcinoid syndrome. An improved understanding of the heterogeneity of presenting symptoms among patients with NETs might permit more tailored assessment and management than at present and enable future research into the effect of carcinoid syndrome control on patient survival. FUNDING: Ipsen.

Adaptive dose modification for phase I clinical trials.

Most phase I dose-finding methods in oncology aim to find the maximum-tolerated dose from a set of prespecified doses. However, in practice, because of a lack of understanding of the true dose-toxicity relationship, it is likely that none of these prespecified doses are equal or reasonably close to the true maximum-tolerated dose. To handle this issue, we propose an adaptive dose modification (ADM) method that can be coupled with any existing dose-finding method to adaptively modify the dose, when it is needed, during the course of dose finding. To reflect clinical practice, we divide the toxicity probability into three regions: underdosing, acceptable, and overdosing regions. We adaptively add a new dose whenever the observed data suggest that none of the investigational doses are likely to be located in the acceptable region. The new dose is estimated via a nonparametric dose-toxicity model based on local polynomial regression. The simulation study shows that ADM substantially outperforms the similar existing method. We applied ADM to a phase I cancer trial. Copyright © 2016 John Wiley & Sons, Ltd.

Wogonin induces G1 phase arrest through inhibiting Cdk4 and cyclin D1 concomitant with an elevation in p21Cip1 in human cervical carcinoma HeLa cells.

Wogonin, a naturally occurring flavonoid, has been shown to have tumor therapeutic potential both in vitro and in vivo. To better understand its anticancer mechanism, we examined the effect of wogonin on human cervical carcinoma HeLa cells. In this study, we observed that G1 phase arrest was involved in wogonin-induced growth inhibition in HeLa cells. Over a 24 h exposure of HeLa cells to 90 micromol x L(-1) wogonin, the promoters of G1-S transition, including cyclin D1/Cdk4 and pRb, decreased within 12 h and E2F-1 depleted in the nucleus at the same time. As the G1 phase arrest developed, p53 and the Cdk inhibitor p21Cip1 elevated both at protein and mRNA levels. Furthermore, the up-regulation of p21Cip1 induced by wogonin was dramatically inhibited by siRNA-mediated p53 gene silencing. Collectively, our data suggested that wogonin induced G1 phase arrest in HeLa cells by modulating several key G1 regulatory proteins, such as Cdk4 and cyclin D1, as well as up-regulation of a p53-mediated p21Cip1 expression. This mechanism of wogonin may play an important role in the killing of cancerous cells and offer a potential mechanism for its anticancer action in vivo.