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Geographic access to cancer care is known to significantly impact utilization and outcomes. Longer travel times have negative impacts for patients requiring highly specialized care, such as for rare cancers, and for those in rural areas. Scant population-based research informs geographic access to care for rare cancers and whether rurality impacts that access.Using Medicare data (2014-2015), we identified prevalent cancers and cancer-directed surgeries, chemotherapy, and radiation. We classified cancers as rare (incidence6/100,000/year) or common (incidence ≥6/100,000/year) using previously published thresholds and categorized rurality from ZIP code of beneficiary residence. We estimated travel time between beneficiaries and providers for each service based on ZIP code. Descriptive statistics summarized travel time by rare versus common cancers, service type, and rurality.We included 1,169,761 Medicare beneficiaries (21.9% in nonmetropolitan areas), 87,399; 7.5% had rare cancers, with 9,133,003 cancer-directed services. Travel times for cancer services ranged from approximately 29 minutes (25th percentile) to 68 minutes (75th percentile). Travel times were similar for rare and common cancers overall (median: 45 vs 43 minutes) but differed by service type; 13.4% of surgeries were2 hours away for rare cancers, compared to 8.3% for common cancers. Increasing rurality disproportionately increased travel time to surgical care for rare compared to common cancers.Travel times to cancer services are longest for surgery, especially among rural residents, yet not markedly longer overall between rare versus common cancers. Understanding geographic access to cancer care for patients with rare cancers is important to delivering specialized care.

IMPORTANCE: Children with medical complexity (CMC) have substantial health care needs and frequently experience poor health care quality. Understanding the population prevalence and associated health care needs can inform clinical and public health initiatives. OBJECTIVE: To estimate the prevalence of CMC using open-source pediatric algorithms, evaluate performance of these algorithms in predicting health care utilization and in-hospital mortality, and identify associations between medical complexity as defined by these algorithms and clinical outcomes. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study used all-payer claims data from Colorado, Massachusetts, and New Hampshire from 2012 through 2017. Children and adolescents younger than 18 years residing in these states were included if they had 12 months or longer of enrollment in a participating health care plan. Analyses were conducted from March 12, 2021, to January 7, 2022. EXPOSURES: The pediatric Complex Chronic Condition Classification System, Pediatric Medical Complexity Algorithm, and Children With Disabilities Algorithm were applied to 3 years of data to identify children with complex and disabling conditions, first in their original form and then using more conservative criteria that required multiple health care claims or involvement of 3 or more body systems. MAIN OUTCOMES AND MEASURES: Primary outcomes, examined over 2 years, included in-hospital mortality and a composite measure of health care services, including specialized therapies, specialized medical equipment, and inpatient care. Outcomes were modeled using logistic regression. Model performance was evaluated using C statistics, sensitivity, and specificity. RESULTS: Of 1 936 957 children, 48.4% were female, 87.8% resided in urban core areas, and 45.1% had government-sponsored insurance as their only primary payer. Depending on the algorithm and coding criteria applied, 0.67% to 11.44% were identified as CMC. All 3 algorithms had adequate discriminative ability, sensitivity, and specificity to predict in-hospital mortality and composite health care services (C statistic = 0.76 [95% CI, 0.73-0.80] to 0.81 [95% CI, 0.78-0.84] for mortality and 0.77 [95% CI, 0.76-0.77] to 0.80 [95% CI, 0.79-0.80] for composite health care services). Across algorithms, CMC had significantly greater odds of mortality (adjusted odds ratio [aOR], 9.97; 95% CI, 7.70-12.89; to aOR, 69.35; 95% CI, 52.52-91.57) and composite health care services (aOR, 4.59; 95% CI, 4.44-4.73; to aOR, 18.87; 95% CI, 17.87-19.93) than children not identified as CMC. CONCLUSIONS AND RELEVANCE: In this study, open-source algorithms identified different cohorts of CMC in terms of prevalence and magnitude of risk, but all predicted increased health care utilization and in-hospital mortality. These results can inform research, programs, and policies for CMC.

Background Delays between breast cancer diagnosis and surgery are associated with worsened survival. Delays are more common in urban-residing patients, although factors specific to surgical delays among rural and urban patients are not well understood. Methods We used a 100% sample of fee-for-service Medicare claims during 2007–2014 to identify 238,491 women diagnosed with early-stage breast cancer undergoing initial surgery and assessed whether they experienced biopsy-to-surgery intervals > 90 days. We employed multilevel regression to identify associations between delays and patient, regional, and surgeon characteristics, both in combined analyses and stratified by rurality of patient residence. Results Delays were more prevalent among urban patients (2.5%) than rural patients (1.9%). Rural patients with medium- or high-volume surgeons had lower odds of delay than patients with low-volume surgeons (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.58–0.88; OR = 0.74, 95% CI = 0.61–0.90). Rural patients whose surgeon operated at ≥ 3 hospitals were more likely to experience delays (OR = 1.29, 95% CI = 1.01–1.64, Ref: 1 hospital). Patient driving times ≥ 1 h were associated with delays among urban patients only. Age, black race, Hispanic ethnicity, multimorbidity, and academic/specialty hospital status were associated with delays. Conclusions Sociodemographic, geographic, surgeon, and facility factors have distinct associations with > 90-day delays to initial breast cancer surgery. Interventions to improve timeliness of breast cancer surgery may have disparate impacts on vulnerable populations by rural-urban status.

PDF file - 171K, Effect of ectopic expression of RKIP on cytoskeletal organization in melanoma cells

PDF file - 1.8MB, Expression of MDA-9 and RKIP in clinical samples

PDF file - 652K, Characterization of MDA-9 overexpressed FM-516 clones

PDF file - 413K, ERK activation negatively regulate RKIP expression

PDF file - 180K, Effect of RKIP expression on B-RAF mutant cells

PDF file - 622K, Effects of RKIP expression on cell growth

PDF file - 604K, MDA-9 activates ERK1/2

PDF file - 205K, Expression of RKIP mRNA in different melanoma cells

Background In response to the COVID-19 pandemic, cancer centers rapidly adopted telehealth to deliver care remotely. Telehealth will likely remain a model of care for years to come and may not only affect the way oncologists deliver care to their own patients but also the physicians with whom they share patients. Objective This study aimed to examine oncologist characteristics associated with telehealth use and compare patient-sharing networks before and after the COVID-19 pandemic in a rural catchment area with a particular focus on the ties between physicians at the comprehensive cancer center and regional facilities. Methods In this retrospective observational study, we obtained deidentified electronic health record data for individuals diagnosed with breast, colorectal, or lung cancer at Dartmouth Health in New Hampshire from 2018-2020. Hierarchical logistic regression was used to identify physician factors associated with telehealth encounters post COVID-19. Patient-sharing networks for each cancer type before and post COVID-19 were characterized with global network measures. Exponential-family random graph models were performed to estimate homophily terms for the likelihood of ties existing between physicians colocated at the hub comprehensive cancer center. Results Of the 12,559 encounters between patients and oncologists post COVID-19, 1228 (9.8%) were via telehealth. Patient encounters with breast oncologists who practiced at the hub hospital were over twice as likely to occur via telehealth compared to encounters with oncologists who practiced in regional facilities (odds ratio 2.2, 95% CI 1.17-4.15; P=.01). Patient encounters with oncologists who practiced in multiple locations were less likely to occur via telehealth, and this association was statistically significant for lung cancer care (odds ratio 0.26, 95% CI 0.09-0.76; P=.01). We observed an increase in ties between oncologists at the hub hospital and oncologists at regional facilities in the lung cancer network post COVID-19 compared to before COVID-19 (93/318, 29.3%, vs 79/370, 21.6%, respectively), which was also reflected in the lower homophily coefficients post COVID-19 compared to before COVID-19 for physicians being colocated at the hub hospital (estimate: 1.92, 95% CI 1.46-2.51, vs 2.45, 95% CI 1.98-3.02). There were no significant differences observed in breast cancer or colorectal cancer networks. Conclusions Telehealth use and associated changes to patient-sharing patterns associated with telehealth varied by cancer type, suggesting disparate approaches for integrating telehealth across clinical groups within this health system. The limited changes to the patient-sharing patterns between oncologists at the hub hospital and regional facilities suggest that telehealth was less likely to create new referral patterns between these types of facilities and rather replace care that would otherwise have been delivered in person. However, this study was limited to the 2 years immediately following the initial outbreak of COVID-19, and longer-term follow-up may uncover delayed effects that were not observed in this study period.

ImportancePhysician headcounts provide useful information about the cancer care delivery workforce; however, efforts to track the oncology workforce would benefit from new measures that capture how essential a physician is for meeting the multidisciplinary cancer care needs of the region. Physicians are considered linchpins when fewer of their peers are connected to other physicians of the same specialty as the focal physician. Because they are locally unique for their specialty, these physicians’ networks may be particularly vulnerable to their removal from the network (eg, through relocation or retirement).ObjectiveTo examine a novel network-based physician linchpin score within nationwide cancer patient-sharing networks and explore variation in network vulnerability across hospital referral regions (HRRs).Design, Setting, and ParticipantsThis cross-sectional study analyzed fee-for-service Medicare claims and included Medicare beneficiaries with an incident diagnosis of breast, colorectal, or lung cancer from 2016 to 2018 and their treating physicians. Data were analyzed from March 2022 to October 2022.ExposuresPhysician characteristics assessed were specialty, rurality, and Census region. HRR variables assessed include sociodemographic and socioeconomic characteristics and use of cancer services.Main Outcomes and MeasuresOncologist linchpin score, which examined the extent to which a physician’s peers were connected to other physicians of the same specialty as the focal physician. Network vulnerability, which distinguished HRRs with more linchpin oncologists than expected based on oncologist density. χ2 and Fisher exact tests were used to examine relationships between oncologist characteristics and linchpin score. Spearman rank correlation coefficient (ρ) was used to measure the strength and direction of relationships between HRR network vulnerability, oncologist density, population sociodemographic and socioeconomic characteristics, and cancer service use.ResultsThe study cohort comprised 308 714 patients with breast, colorectal, or lung cancer. The study cohort of 308 714 patients included 161 206 (52.2%) patients with breast cancer, 76 604 (24.8%) patients with colorectal cancer, and 70 904 (23.0%) patients with lung cancer. In our sample, 272 425 patients (88%) were White, and 238 603 patients (77%) lived in metropolitan areas. The cancer patient-sharing network included 7221 medical oncologists and 3573 radiation oncologists. HRRs with more vulnerable networks for medical oncology had a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.19; 95% CI, 0.08 to 0.29). HRRs with more vulnerable networks for radiation oncology had a higher percentage of beneficiaries living in poverty (ρ, 0.17; 95% CI, 0.06 to 0.27), and a higher percentage of beneficiaries eligible for Medicaid (ρ, 0.21; 95% CI, 0.09 to 0.31), and lower rates of cohort patients receiving radiation therapy (ρ, –0.18; 95% CI, –0.28 to –0.06; P = .003). The was no association between network vulnerability for medical oncology and percent of cohort patients receiving chemotherapy (ρ, –0.03; 95% CI, –0.15 to 0.08).Conclusions and RelevanceThis study found that patient-sharing network vulnerability was associated with poverty and lower rates of radiation therapy. Health policy strategies for addressing network vulnerability may improve access to interdisciplinary care and reduce treatment disparities.

The rise of life-threatening carbapenem-resistant Enterobacteriaceae (CRE) infections has become a critical medical threat. Some of the most dangerous CRE bacteria can produce enzymes that degrade a wide range of antibiotics, including carbapenems and β-lactams. Infections by CRE have a high mortality rate, and survivors can have severe morbidity from treatment with toxic last-resort antibiotics. CRE have mobile genetic elements that transfer resistance genes to other species. These bacteria also circulate throughout the healthcare system. The mobility and spread of CRE need to be curtailed, but these goals are impeded by having few agents that target a limited range of pathogenic CRE species. Against CRE possessing the metallo-β-lactamase NDM-1, Klebsiella pneumoniae ATCC BAA-2146 and Escherichia coli ATCC BAA-2452, the potentiation of meropenem and imipenem is possible with low-molecular weight branched polyethylenimine (600 Da BPEI) and its poly(ethylene glycol) (PEG)ylated derivative (PEG-BPEI) that has a low in vivo toxicity. The mechanism of action is elucidated with fluorescence assays of drug influx and isothermal calorimetry data showing the chelation of essential Zn2+ ions. These results suggested that 600 Da BPEI and PEG-BPEI may also improve the uptake of antibiotics and β-lactamase inhibitors. Indeed, the CRE E. coli strain is rendered susceptible to the combination of piperacillin and tazobactam. These results expand the possible utility of 600 Da BPEI potentiators, where previously we have demonstrated the ability to improve antibiotic efficacy against antibiotic resistant clinical isolates of Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis.

Background Drivers behind the adoption of gene expression profiling in breast cancer oncology have been shown to include exposure to physician colleagues’ use of a given genomic test. We examined adoption of the Oncotype DX 21‐gene breast cancer recurrence score assay (ODX) in the United States after its incorporation into clinical guidelines. The influence of patient‐sharing ties and co‐location with prior adopters and the role of these potential exposures across medical specialties on peers’ adoption of the test were examined. Methods We conducted a retrospective cohort study of women with incident breast cancer using a 100% sample of fee‐for‐service Medicare enrollee claims over 2008–2011. Peer networks connecting medical oncologists and surgeons treating these patients were constructed using patient‐sharing and geographic co‐location. The impact of peer connections on the adoption of ODX by physicians and testing of patients was modeled with multivariable hierarchical regression. Results Altogether, 156,229 women identified with incident breast cancer met criteria for cohort inclusion. A total of 7689 ODX prescribing physicians were identified. Co‐location with medical oncologists who adopted the test in the early period (2008–2009) was associated with a 1.38‐fold increase in the odds of a medical oncologist adopting ODX in 2010–2011 (95% CI = 1.04–1.83), as was co‐location with early‐adopting surgeons (odds ratio [OR] = 1.25, 95% CI = 1.00–1.58). Patients whose primary medical oncologist was linked to an early‐adopting surgeon through co‐location (OR = 1.17, 95% CI = 1.04–1.32) or both patient‐sharing and co‐location (OR = 1.17, 95% CI = 1.03–1.34) were more likely to receive ODX. Conclusions Exposure to surgeon early adopters through peer networks and co‐location was predictive of ODX uptake by medical oncologists and testing of patients. Interventions focused on the role of surgeons in molecular testing may improve the implementation of best practices in breast cancer care., Surgeons have been engaged in the development of clinical algorithms involving postoperative molecular testing criteria for breast cancer patients, though promotion efforts and research into the dissemination of these technologies has primarily been focused on medical oncologists. This study demonstrates that peer influence from both early‐adopting surgeons and medical oncologists may have facilitated the uptake of the Oncotype DX recurrence score assay by their medical oncologist peers. Initiatives aimed at improving efficient and equitable incorporation of genomic and molecular innovations into breast cancer care would benefit from engaging surgeons as well as medical oncologists.

Bacterial biofilms, often impenetrable to antibiotic medications, are a leading cause of poor wound healing. The prognosis is worse for wounds with biofilms of antimicrobial-resistant (AMR) bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA), methicillin-resistant S. epidermidis (MRSE), and multi-drug resistant Pseudomonas aeruginosa (MDR-PA). Resistance hinders initial treatment of standard-of-care antibiotics. The persistence of MRSA, MRSE, and/or MDR-PA often allows acute infections to become chronic wound infections. The water-soluble hydrophilic properties of low-molecular-weight (600 Da) branched polyethylenimine (600 Da BPEI) enable easy drug delivery to directly attack AMR and biofilms in the wound environment as a topical agent for wound treatment. To mitigate toxicity issues, we have modified 600 Da BPEI with polyethylene glycol (PEG) in a straightforward one-step reaction. The PEG–BPEI molecules disable β-lactam resistance in MRSA, MRSE, and MDR-PA while also having the ability to dissolve established biofilms. PEG-BPEI accomplishes these tasks independently, resulting in a multifunction potentiation agent. We envision wound treatment with antibiotics given topically, orally, or intravenously in which external application of PEG–BPEIs disables biofilms and resistance mechanisms. In the absence of a robust pipeline of new drugs, existing drugs and regimens must be re-evaluated as combination(s) with potentiators. The PEGylation of 600 Da BPEI provides new opportunities to meet this goal with a single compound whose multifunction properties are retained while lowering acute toxicity.

[Image: see text] Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a serious threat worldwide. MRSA is the predominant species isolated from medical-device-related biofilm infections and chronic wounds. Its ability to form biofilms grants it resistance to almost all antibiotics on the market. Answering the call for alternative treatments, our lab has been investigating the efficacy of 600 Da branched polyethylenimine (BPEI) as a β-lactam potentiator against bacterial biofilms. Our previous study showed promise against methicillin-resistant Staphylococcus epidermidis biofilms. This study extends our previous findings to eradicate a more virulent pathogen: MRSA biofilms. Microtiter minimum biofilm eradication concentration models, crystal violet assays, and electron microscopy images show synergistic effects between BPEI and ampicillin as a two-step mechanism: step one is the removal of the extracellular polymeric substances (EPS) to expose individual bacteria targets, and step two involves electrostatic interaction of BPEI with anionic teichoic acid in the cell wall to potentiate the antibiotic.

Network centrality measures assign importance to influential or key nodes in a network based on the topological structure of the underlying adjacency matrix. In this work, we define the importance of a node in a network as being dependent on whether it is the only one of its kind among its neighbors’ ties. We introduce linchpin score, a measure of local uniqueness used to identify important nodes by assessing both network structure and a node attribute. We explore linchpin score by attribute type and examine relationships between linchpin score and other established network centrality measures (degree, betweenness, closeness, and eigenvector centrality). To assess the utility of this measure in a real-world application, we measured the linchpin score of physicians in patient-sharing networks to identify and characterize important physicians based on being locally unique for their specialty. We hypothesized that linchpin score would identify indispensable physicians who would not be easily replaced by another physician of their specialty type if they were to be removed from the network. We explored differences in rural and urban physicians by linchpin score compared with other network centrality measures in patient-sharing networks representing the 306 hospital referral regions in the United States. We show that linchpin score is uniquely able to make the distinction that rural specialists, but not rural general practitioners, are indispensable for rural patient care. Linchpin score reveals a novel aspect of network importance that can provide important insight into the vulnerability of health care provider networks. More broadly, applications of linchpin score may be relevant for the analysis of social networks where interdisciplinary collaboration is important.

Delays between breast cancer diagnosis and surgery are associated with worsened survival. Delays are more common in urban-residing patients, although factors specific to surgical delays among rural and urban patients are not well understood.We used a 100% sample of fee-for-service Medicare claims during 2007-2014 to identify 238,491 women diagnosed with early-stage breast cancer undergoing initial surgery and assessed whether they experienced biopsy-to-surgery intervals 90 days. We employed multilevel regression to identify associations between delays and patient, regional, and surgeon characteristics, both in combined analyses and stratified by rurality of patient residence.Delays were more prevalent among urban patients (2.5%) than rural patients (1.9%). Rural patients with medium- or high-volume surgeons had lower odds of delay than patients with low-volume surgeons (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.58-0.88; OR = 0.74, 95% CI = 0.61-0.90). Rural patients whose surgeon operated at ≥ 3 hospitals were more likely to experience delays (OR = 1.29, 95% CI = 1.01-1.64, Ref: 1 hospital). Patient driving times ≥ 1 h were associated with delays among urban patients only. Age, black race, Hispanic ethnicity, multimorbidity, and academic/specialty hospital status were associated with delays.Sociodemographic, geographic, surgeon, and facility factors have distinct associations with 90-day delays to initial breast cancer surgery. Interventions to improve timeliness of breast cancer surgery may have disparate impacts on vulnerable populations by rural-urban status.

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules – such as gene promoter context, CpG island relationship, or user-defined groupings – and relate them to diagnostic and prognostic outcomes. We demonstrate these models’ utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep learning analyses’ interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

Microbial biofilms are ubiquitous in nature, and they pose a serious threat to public health. Staphylococcus epidermidis is the most common clinical isolate from healthcare-and medical device-related biofilm infections. No antibiotic currently on the market can eradicate pathogenic biofilms, which contain complex defense mechanisms composed of slimelike extracellular polymeric substances. Understanding the need to develop alternative approaches, we examine 600 Da branched polyethylenimine (BPEI) against methicillin-resistant Staphylococcus epidermidis (MRSE) bio-films. Here, a microtiter biofilm model is used to test the synergistic effects between the two components of our combination treatment: BPEI and β-lactam antibiotics. Electron microscopy was used to confirm the growth of MRSE biofilms from the model. Minimum biofilm eradication concentration assays, crystal violet assays, and biofilm kill curves suggest that BPEI exhibits antibiofilm activity and can potentiate β-lactams to eradicate MRSE biofilms.

The rise of life-threatening carbapenem-resistant Enterobacteriaceae (CRE) infections has become a critical medical threat. Some of the most dangerous CRE bacteria can produce enzymes that degrade a wide range of antibiotics, including carbapenems and β-lactams. Infections by CRE have a high mortality rate, and survivors can have severe morbidity from treatment with toxic last-resort antibiotics. CRE have mobile genetic elements that transfer resistance genes to other species. These bacteria also circulate throughout the healthcare system. The mobility and spread of CRE need to be curtailed, but these goals are impeded by having few agents that target a limited range of pathogenic CRE species. Against CRE possessing the metallo-β-lactamase NDM-1, Klebsiella pneumoniae ATCC BAA-2146 and Escherichia coli ATCC BAA-2452, the potentiation of meropenem and imipenem is possible with low-molecular weight branched polyethylenimine (600 Da BPEI) and its poly(ethylene glycol) (PEG)ylated derivative (PEG-BPEI) that has a low in vivo toxicity. The mechanism of action is elucidated with fluorescence assays of drug influx and isothermal calorimetry data showing the chelation of essential Zn(2+) ions. These results suggested that 600 Da BPEI and PEG-BPEI may also improve the uptake of antibiotics and β-lactamase inhibitors. Indeed, the CRE E. coli strain is rendered susceptible to the combination of piperacillin and tazobactam. These results expand the possible utility of 600 Da BPEI potentiators, where previously we have demonstrated the ability to improve antibiotic efficacy against antibiotic resistant clinical isolates of Pseudomonas aeruginosa, Staphylococcus aureus, and Staphylococcus epidermidis.

IMPORTANCE: Knowledge of health outcomes among opioid-exposed infants is limited, particularly for those not diagnosed with neonatal opioid withdrawal syndrome (NOWS). OBJECTIVES: To describe infant mortality among opioid-exposed infants and identify how mortality risk differs in opioid-exposed infants with and without a diagnosis of NOWS compared with infants without opioid exposure. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study of maternal-infant dyads was conducted, linking health care claims with vital records for births from January 1, 2010, to December 31, 2014, with follow-up of infants until age 1 year (through 2015). Maternal-infant dyads were included if the infant was born in Texas at 22 to 43 weeks’ gestational age to a woman aged 15 to 44 years insured by Texas Medicaid. Data analysis was performed from May 2019 to October 2020. EXPOSURE: The primary exposure was prenatal opioid exposure, with infants stratified by the presence or absence of a diagnosis of NOWS during the birth hospitalization. MAIN OUTCOMES AND MEASURES: Risk of infant mortality (death at age

To study racial/ethnic differences in the utilization of low-dose computerized tomography (LDCT) scan for lung cancer among adult smokers. Cross-sectional data (n=2,640) of adults aged 55-74, were from the 2017 Behavioral Risk Factor Surveillance System, Lung Cancer Screening module. Weighted, multivariable logistic regression was conducted. Most, 70.9%, were White and 52.2% male. About 16.0 % reported receiving LDCT scan in the past 12 months, 12.0% of Blacks and 17.4% of Whites. More Whites (55.0%) had ≥30 pack-years smoking history than Blacks (20%). Blacks had lower odds, .52 (CI: 0.28-0.96) of receiving LDCT scan than Whites. The odds of receiving LDCT scan were higher for those who were male, who tried to quit smoking in the past year, and for those with more education, health insurance, high blood pressure, lung disease, or cancer history (other than skin or lung cancer). This study suggests racial differences in the use of LDCT scan.

e20585 Background: Patients with node-negative non-small cell lung cancer (NSCLC) whose tumors are completely resected account for approximately 17% of all patients with lung cancer, and disease recurrence occurs in approximately 1 in 5 of these patients. The lack of consensus on factors associated with risk of disease recurrence among node-negative NSCLC patients is a significant barrier to applying precision medicine strategies in this patient population. Clustering similar patients based on distances between various features of data is an emerging topic in precision medicine. Patient similarity networks represent a new model for clustering patients based on heterogeneous data, whereby any data type is converted into a similarity network by defining a similarity measure. The objective of this study was to examine the utility of patient similarity networks to identify NSCLC patients at higher risk of adverse outcomes. Methods: We conducted a retrospective, observational study of 6,020 node-negative NSCLC patients with an initial diagnosis in 2011-2014 in the CancerLinQ Discovery database. A patient similarity network was assembled based on comorbidities and network communities of patients with similar comorbidities at diagnosis were identified. Using Cox proportional-hazards modeling, we examined the extent to which patient age, sex, race, ethnicity, and network community predicted 2-year disease recurrence and 2-year mortality. Results: In the adjusted analyses, patients in the network community enriched for renal disease and congestive heart failure had an 83% increased risk of mortality (95% CI = 1.39-2.41). Patients in the network community enriched for pulmonary disease had a 37% increased risk of mortality (95% CI = 1.06-1.74) yet a lower risk of recurrence (HR = 0.5, 95% CI = 0.34-0.75). After adjusting for comorbidity network community, male patients had a 14% increased risk of mortality (95%CI = 1.02-1.28) and a 21% increased risk of recurrence (95% CI = 1.05-1.40) and black patients had a lower mortality risk (HR = 0.71, 95% CI = 0.58-0.86). Conclusions: Future studies applying patient similar networks to integrate additional diverse and high dimensional data types may afford more clarity in assigning risk of adverse outcomes.

Background Oncotype DX® (ODX) is used to assess risk of disease recurrence in hormone receptor positive, HER2-negative breast cancer and to guide decisions regarding adjuvant chemotherapy. Little is known about how physician factors impact treatment decisions. The purpose of this study was to examine patient and physician factors associated with ODX testing and adjuvant chemotherapy for breast cancer patients in New Hampshire. Methods We examined New Hampshire State Cancer Registry data on 5630 female breast cancer patients diagnosed from 2010 to 2016. We performed unadjusted and adjusted hierarchical logistic regression to identify factors associated with a patient’s receipt of ODX, being recommended and receiving chemotherapy, and refusing chemotherapy. We calculated intraclass correlation coefficients (ICCs) to examine the proportion of variance in clinical decisions explained by between-physician and between-hospital variation. Results Over the study period, 1512 breast cancer patients received ODX. After adjustment for patient and tumor characteristics, we found that patients seen by a male medical oncologist were less likely to be recommended chemotherapy following ODX (OR = 0.50 (95% CI = 0.34–0.74), p p 29 years: OR = 4.48 (95% CI = 1.68–11.95), p Conclusions In addition to patient clinicopathologic characteristics, physician gender and clinical experience were associated with chemotherapy treatment following ODX testing. The significant variation between physicians indicates the potential for interventions to reduce variation in care.

Infections from antibiotic resistant Staphylococcus aureus and Pseudomonas aeruginosa are a serious threat because reduced antibiotic efficacy complicates treatment decisions and prolongs the disease state in many patients. To expand the arsenal of treatments against antimicrobial resistant (AMR) pathogens, 600-Da branched polyethylenimine (BPEI) can overcome antibiotic resistance mechanisms and potentiate β-lactam antibiotics against Gram-positive bacteria. BPEI binds cell wall teichoic acids and disables resistance factors from penicillin binding proteins PBP2a and PBP4. The present study describes a new mechanism of action for BPEI potentiation of antibiotics generally regarded as agents effective against Gram-positive pathogens but not Gram-negative bacteria. 600-Da BPEI is able to reduce the barriers to drug influx and facilitate the uptake of a non-β-lactam co-drug, erythromycin, that targets the intracellular machinery. Also, BPEI can suppress production of the cytokine interleukin IL-8 by human epithelial keratinocytes. This enables BPEI to function as a broad-spectrum antibiotic potentiator which expands the opportunities to improve drug design, antibiotic development, and therapeutic approaches against pathogenic bacteria, especially for wound care.

Clinicians prescribe hundreds of millions of β-lactam antibiotics to treat the majority of patients presenting with bacterial infections. Patient outcomes are positive unless resistant bacteria, such as Pseudomonas aeruginosa (P. aeruginosa), are present. P. aeruginosa has both intrinsic and acquired antibiotic resistance, making clinical management of infection a real challenge, particularly when these bacteria are sequestered in biofilms. These problems would be alleviated if, upon the initial presentation of bacterial infection symptoms, clinicians were able to administer an antibiotic that kills both susceptible and otherwise resistant bacteria and eradicates biofilms. As the most common class of antibiotics, β-lactams could be used in a new drug if the leading causes of β-lactam antibiotic resistance, permeation barriers from lipopolysaccharide, efflux pumps, and β-lactamase enzymes, were also defeated. Against P. aeruginosa and their biofilms, the potency of β-lactam antibiotics is restored with 600 Da branched polyethylenimine (600 Da BPEI). Checkerboard assays using microtiter plates demonstrate the potentiation of piperacillin, cefepime, Meropenem, and erythromycin antibiotics. Growth curves demonstrate that only a combination of 600 Da BPEI and piperacillin produces growth inhibition antibiotic resistant P. aeruginosa. Scanning electron microscopy (SEM) was used to confirm that the combination treatment leads to abnormal P. aeruginosa morphology. Data collected with isothermal titration calorimetry and fluorescence spectroscopy demonstrate a mechanism of action in which potentiation at low concentrations of 600 Da BPEI reduces diffusion barriers from lipopolysaccharides without disrupting the outer membrane itself. Coupled with the ability to overcome a reduction in antibiotic activity created by biofilm exopolymers, targeting anionic sites on lipopolysaccharides and biofilm exopolysaccharides with the same compound provides new opportunities to counter the rise of multidrug-resistant infections.

With >70,000 yearly publications using mouse data, mouse models represent the best engrained research system to address numerous biological questions across all fields of science. Concerns of poor study and microbiome reproducibility also abound in the literature. Despite the well-known, negative-effects of data clustering on interpretation and study power, it is unclear why scientists often house >4 mice/cage during experiments, instead of ≤2. We hypothesized that this high animal-cage-density practice abounds in published literature because more mice/cage could be perceived as a strategy to reduce housing costs. Among other sources of ‘artificial’ confounding, including cyclical oscillations of the ‘dirty-cage/excrement microbiome’, we ranked by priority the heterogeneity of modern husbandry practices/perceptions across three professional organizations that we surveyed in the USA. Data integration (scoping-reviews, professional-surveys, expert-opinion, and ‘implementability-score-statistics’) identified Six-Actionable Recommendation Themes (SART) as a framework to re-launch emerging protocols and intuitive statistical strategies to use/increase study power. ‘Cost-vs-science’ discordance was a major aspect explaining heterogeneity, and scientists’ reluctance to change. With a ‘housing-density cost-calculator-simulator’ and fully-annotated statistical examples/code, this themed-framework streamlines the rapid analysis of cage-clustered-data and promotes the use of ‘study-power-statistics’ to self-monitor the success/reproducibility of basic and translational research. Examples are provided to help scientists document analysis for study power-based sample size estimations using preclinical mouse data to support translational clinical trials, as requested in NIH/similar grants or publications.

We develop methodology that allows peer effects (also referred to as social influence and contagion) to be modified by the structural importance of the focal actor's position in the network. The methodology is first developed for a single peer effect and then extended to simultaneously model multiple peer-effects and their modifications by the structural importance of the focal actor. This work is motivated by the diffusion of implantable cardioverter defibrillators (ICDs) in patients with congestive heart failure across a cardiovascular disease patient-sharing network of United States hospitals. We apply the general methodology to estimate peer effects for the adoption of capability to implant ICDs, the number of ICD implants performed by hospitals that are capable, and the number of patients referred to other hospitals by noncapable hospitals. Applying our novel methodology to study ICD diffusion across hospitals, we find evidence that exposure to ICD-capable peer hospitals is strongly associated with the chance a hospital becomes ICD-capable and that the direction and magnitude of the association is extensively modified by the strength of that hospital's position in the network, even after controlling for effects of geography. Therefore, interhospital networks, rather than geography per se, may explain key patterns of regional variations in healthcare utilization.

Staphylococcus epidermidis is one of the most prevalent prokaryotic species on human skin and mucosal membranes that constitute the commensal flora. S. epidermidis has become one of the most common causes of primary bacteremia. Infections are difficult to diagnose because the pathogen has natural niches on human skin and the ability to adhere to inanimate surfaces via biofilms. Alarmingly, S. epidermidis has acquired resistance to many antibiotics, which presents a danger to human health. Known as methicillin-resistant S. epidermidis (MRSE), most clinical isolates of MRSE in North America exhibit β-lactam resistance primarily due to the presence of mecA, a gene that bestows β-lactam antibiotic resistance in a manner similar to methicillin-resistant Staphylococcus aureus (MRSA). MecA encodes for expression of penicillin-binding protein 2a (PBP2a), which is absent in β-lactam susceptible strains of S. epidermidis. We can disable this resistance factor in MRSE with 600-Da branched polyethylenimine (BPEI). Cationic BPEI targets anionic wall teichoic acid (WTA), an essential cofactor for proper functioning of PBP2a. We found that BPEI synergizes the activity of β-lactam antibiotics against MRSE. Growth curves suggest that the combination of BPEI and oxacillin is bactericidal. Electron micrographs indicate abnormalities in the cellular septa and cell walls of treated samples. Therefore, first-line clinical treatments can be effective against MRSE when used in combination with BPEI.

Background Phosphatase and tensin homolog (PTEN) negatively regulates downstream protein kinase B signaling, resulting in decreased cellular growth and proliferation. PTEN is mutated in a subset of children with autism spectrum disorder (ASD); however, the mechanism by which specific point mutations alter PTEN function is largely unknown. Here, we assessed how ASD-associated single-nucleotide variations in PTEN (ASD-PTEN) affect function. Methods We used viral-mediated molecular substitution of human PTEN into Pten knockout mouse neurons and assessed neuronal morphology to determine the functional impact of ASD-PTEN. We employed molecular cloning to examine how PTEN’s stability, subcellular localization, and catalytic activity affect neuronal growth. Results We identified a set of ASD-PTEN mutations displaying altered lipid phosphatase function and subcellular localization. We demonstrated that wild-type PTEN can rescue the neuronal hypertrophy, while PTEN H93R, F241S, D252G, W274L, N276S, and D326N failed to rescue this hypertrophy. A subset of these mutations lacked nuclear localization, prompting us to examine the role of nuclear PTEN in regulating neuronal growth. We found that nuclear PTEN alone is sufficient to regulate soma size. Furthermore, forced localization of the D252G and W274L mutations into the nucleus partially restores regulation of soma size. Conclusions ASD-PTEN mutations display decreased stability, catalytic activity, and/or altered subcellular localization. Mutations lacking nuclear localization uncover a novel mechanism whereby lipid phosphatase activity in the nucleus can regulate mammalian target of rapamycin signaling and neuronal growth.

BACKGROUND Implantable cardioverter defibrillator (ICD) therapy is used for primary prevention of death among people with heart failure, and new evidence in 2005 on its effectiveness changed practice guidelines in the United States. OBJECTIVES The objective of this study is to examine how the connectedness of physicians and hospitals, measured using network analysis, relates to guideline-consistent ICD implantation. RESEARCH DESIGN We constructed physician and hospital networks for cardiovascular disease. Physicians were linked if they shared cardiovascular disease patients; these links were aggregated by hospital affiliation to construct a hospital network. SUBJECTS Medicare beneficiaries who underwent ICD therapy for primary prevention from 2007 to 2011. MEASURES The clinical outcome of interest was guideline-consistent ICD implantation, calculated using the National Cardiovascular Data Registry. The exposure variables of interest were the network measures of the ICD surgeon, the referring hospital, and the hospital where the ICD surgery occurred. RESULTS We focused on patients who were referred between hospitals for ICD implantation because they were more likely influenced by the hospital network (n=28,179). Patients were less likely to meet guidelines if their referring hospital had more connections to other hospitals (OR, 0.49; 95% confidence interval, 0.25-0.96) and more likely to meet guidelines if their ICD surgery hospital had more connections (OR, 1.61; 95% confidence interval, 0.98-2.64). The ICD surgeon's network measures were not associated with guideline-consistent implantation. CONCLUSIONS Associations between the hospital network measures and guideline adherence suggests new approaches to better disseminate clinical guidelines across health systems.

Methicillin-resistant Staphylococcus aureus (MRSA) is a medical concern. Here, we show that branched polyethylenimine (BPEI), a nontoxic, cationic polymer, restores MRSA’s susceptibility to β-lactam antibiotics. Checkerboard assays with MRSA demonstrated synergy between BPEI and β-lactam antibiotics. A time-killing curve showed BPEI to be bactericidal in combination with oxacillin. BPEI did not potentiate efficacy with vancomycin, chloramphenicol, or linezolid. When exposed to BPEI, MRSA increased in size and had difficulty forming septa. BPEI electrostatically binds to wall teichoic acid (WTA), a cell wall anionic polymer of Gram-positive bacteria that is important for localization of certain cell wall proteins. Lack of potentiation in a WTA knockout mutant supports the WTA-based mechanism. These data suggest that BPEI may prevent proper localization of cell wall machinery by binding to WTA; leading to cell death when administered in combination with β-lactam antibiotics. Negligible in vitro toxicity sug...

The negative effects of data clustering due to (intra-class/spatial) correlations are well-known in statistics to interfere with interpretation and study power. Therefore, it is unclear why housing many laboratory mice (≥4), instead of one-or-two per cage, with the improper use/reporting of clustered-data statistics, abound in the literature. Among other sources of ‘artificial’ confounding, including cyclical oscillations of the ‘cage microbiome’, we quantified the heterogeneity of modern husbandry practices/perceptions. The objective was to identify actionable themes to re-launch emerging protocols and intuitive statistical strategies to increase study power. Amenable for interventions, ‘cost-vs-science’ discordance was a major aspect explaining heterogeneity and the reluctance to change. Combined, four sources of information (scoping-reviews, professional-surveys, expert-opinion, and ‘implementability-score-statistics’) indicate that a six-actionable-theme framework could minimize ‘artificial’ heterogeneity. With a ‘Housing Density Cost Simulator’ in Excel and fully annotated statistical examples, this framework could reignite the use of ‘study power’ to monitor the success/reproducibility of mouse-microbiome studies.

OBJECTIVE: To evaluate two novel measures of physician network centrality and their associations with implantable cardioverter defibrillator (ICD) procedure volume and health outcomes. DATA SOURCES: Medicare claims and the National Cardiovascular Data Registry data from 2007 to 2011. STUDY DESIGN: We constructed a national cardiovascular disease patient‐sharing physician network and used network analysis to characterize physician network centrality with two measures: within‐hospital degree centrality (number of connections within a hospital) and across‐hospital degree centrality (number of connections across hospitals). The primary outcome was risk‐adjusted 2‐year case fatality. Hierarchical logistic regression estimated the effects of physician's within‐hospital and across‐hospital degree centrality on case fatality. We included 105 109 ICD therapy patients and 3474 ICD implanting physicians in our analyses. PRINCIPAL FINDINGS: After controlling for other physician and hospital characteristics, we observed greater risk‐adjusted case fatality among patients treated by physicians in the highest across‐hospital degree tertile compared to lowest tertile (OR [95% CI] = 1.10 [1.04‐1.16], P = 0.001) and lowest tertile volume physicians compared with highest volume (OR [95% CI] = 0.90 [0.84‐0.95], P