Distinct regulatory networks control toxin gene expression in elapid and viperid snakes.

BACKGROUND: Venom systems are ideal models to study genetic regulatory mechanisms that underpin evolutionary novelty. Snake venom glands are thought to share a common origin, but there are major distinctions between venom toxins from the medically significant snake families Elapidae and Viperidae, and toxin gene regulatory investigations in elapid snakes have been limited. Here, we used high-throughput RNA-sequencing to profile gene expression and microRNAs between active (milked) and resting (unmilked) venom glands in an elapid (Eastern Brown Snake, Pseudonaja textilis), in addition to comparative genomics, to identify cis- and trans-acting regulation of venom production in an elapid in comparison to viperids (Crotalus viridis and C. tigris). RESULTS: Although there is conservation in high-level mechanistic pathways regulating venom production (unfolded protein response, Notch signaling and cholesterol homeostasis), there are differences in the regulation of histone methylation enzymes, transcription factors, and microRNAs in venom glands from these two snake families. Histone methyltransferases and transcription factor (TF) specificity protein 1 (Sp1) were highly upregulated in the milked elapid venom gland in comparison to the viperids, whereas nuclear factor I (NFI) TFs were upregulated after viperid venom milking. Sp1 and NFI cis-regulatory elements were common to toxin gene promoter regions, but many unique elements were also present between elapid and viperid toxins. The presence of Sp1 binding sites across multiple elapid toxin gene promoter regions that have been experimentally determined to regulate expression, in addition to upregulation of Sp1 after venom milking, suggests this transcription factor is involved in elapid toxin expression. microRNA profiles were distinctive between milked and unmilked venom glands for both snake families, and microRNAs were predicted to target a diversity of toxin transcripts in the elapid P. textilis venom gland, but only snake venom metalloproteinase transcripts in the viperid C. viridis venom gland. These results suggest differences in toxin gene posttranscriptional regulation between the elapid P. textilis and viperid C. viridis. CONCLUSIONS: Our comparative transcriptomic and genomic analyses between toxin genes and isoforms in elapid and viperid snakes suggests independent toxin regulation between these two snake families, demonstrating multiple different regulatory mechanisms underpin a venomous phenotype.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model.

BACKGROUND: Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors. METHODS: The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines. RESULTS: Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202). CONCLUSION: In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance. PLAIN LANGUAGE SUMMARY: Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer.

PURPOSE: In advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitor (ICI) monotherapy is often preferred over intensive ICI treatment for frail patients and those with poor performance status (PS). Among those with poor PS, the additional effect of frailty on treatment selection and mortality is unknown. METHODS: Patients in the veterans affairs national precision oncology program from 1/2019-12/2021 who received first-line ICI for advanced NSCLC were followed until death or study end 6/2022. Association of an electronic frailty index with treatment selection was examined using logistic regression stratified by PS. We also examined overall survival (OS) on intensive treatment using Cox regression stratified by PS. Intensive treatment was defined as concurrent use of platinum-doublet chemotherapy and/or dual checkpoint blockade and non-intensive as ICI monotherapy. RESULTS: Of 1547 patients receiving any ICI, 66.2% were frail, 33.8% had poor PS (≥ 2), and 25.8% were both. Frail patients received less intensive treatment than non-frail patients in both PS subgroups (Good PS: odds ratio [OR] 0.67, 95% confidence interval [CI] 0.51 - 0.88; Poor PS: OR 0.69, 95% CI 0.44 - 1.10). Among 731 patients receiving intensive treatment, frailty was associated with lower OS for those with good PS (hazard ratio [HR] 1.53, 95% CI 1.2 - 1.96), but no association was observed with poor PS (HR 1.03, 95% CI 0.67 - 1.58). CONCLUSION: Frail patients with both good and poor PS received less intensive treatment. However, frailty has a limited effect on survival among those with poor PS. These findings suggest that PS, not frailty, drives survival on intensive treatment.

Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis.

BACKGROUND: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. DESIGN: Comparative modeling analysis. DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. TARGET POPULATION: 1960 U.S. birth cohort. TIME HORIZON: 45 years. PERSPECTIVE: U.S. health care sector. INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors. CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).

Risk of developing glioblastoma following non-CNS primary cancer: a SEER analysis between 2000 and 2018.

BACKGROUND: Patients with a prior malignancy are at elevated risk of developing subsequent primary malignancies (SPMs). However, the risk of developing subsequent primary glioblastoma (SPGBM) in patients with a prior cancer history is poorly understood. METHODS: We used the Surveillance, Epidemiology, and End Results (SEER) database and identified patients diagnosed with non-CNS malignancy between 2000 and 2018. We calculated a modified standardized incidence ratio (M-SIR), defined as the ratio of the incidence of SPGBM among patients with initial non-CNS malignancy to the incidence of GBM in the general population, stratified by sex latency, and initial tumor location. RESULTS: Of the 5,326,172 patients diagnosed with a primary non-CNS malignancy, 3559 patients developed SPGBM (0.07%). Among patients with SPGBM, 2312 (65.0%) were men, compared to 2,706,933 (50.8%) men in the total primary non-CNS malignancy cohort. The median age at diagnosis of SPGBM was 65 years. The mean latency between a prior non-CNS malignancy and developing a SPGBM was 67.3 months (interquartile range [IQR] 27-100). Overall, patients with a primary non-CNS malignancy had a significantly elevated M-SIR (1.13, 95% CI 1.09-1.16), with a 13% increased incidence of SPGBM when compared to the incidence of developing GBM in the age-matched general population. When stratified by non-CNS tumor location, patients diagnosed with primary melanoma, lymphoma, prostate, breast, renal, or endocrine malignancies had a higher M-SIR (M-SIR ranges: 1.09-2.15). Patients with lung cancers (M-SIR 0.82, 95% CI 0.68-0.99), or stomach cancers (M-SIR 0.47, 95% CI 0.24-0.82) demonstrated a lower M-SIR. CONCLUSION: Patients with a history of prior non-CNS malignancy are at an overall increased risk of developing SPGBM relative to the incidence of developing GBM in the general population. However, the incidence of SPGBM after prior non-CNS malignancy varies by primary tumor location, with some non-CNS malignancies demonstrating either increased or decreased predisposition for SPGBM depending on tumor origin. These findings merit future investigation into whether these relationships represent treatment effects or a previously unknown shared predisposition for glioblastoma and non-CNS malignancy.

Predictors of spine metastases at initial presentation of pediatric brain tumor patients: a single-institution study.

PURPOSE: Given the rarity of disseminated disease at the time of initial evaluation for pediatric brain tumor patients, we sought to identify clinical and radiographic predictors of spinal metastasis (SM) at the time of presentation. METHODS: We performed a single-institution retrospective chart review of pediatric brain tumor patients who first presented between 2004 and 2018. We extracted information regarding patient demographics, radiographic attributes, and presenting symptoms. Univariate and multivariate logistic regression was used to estimate the association between measured variables and SMs. RESULTS: We identified 281 patients who met our inclusion criteria, of whom 19 had SM at initial presentation (6.8%). The most common symptoms at presentation were headache (n = 12; 63.2%), nausea/vomiting (n = 16; 84.2%), and gait abnormalities (n = 8; 41.2%). Multivariate models demonstrated that intraventricular and posterior fossa tumors were more frequently associated with SM (OR: 5.28, 95% CI: 1.79-15.59, p = 0.003), with 4th ventricular (OR: 7.42, 95% CI: 1.77-31.11, p = 0.006) and cerebellar parenchymal tumor location (OR: 4.79, 95% CI: 1.17-19.63, p = 0.030) carrying the highest risk for disseminated disease. In addition, evidence of intracranial leptomeningeal enhancement on magnetic resonance imaging (OR: 46.85, 95% CI: 12.31-178.28, p < 0.001) and hydrocephalus (OR: 3.19; 95% CI: 1.06-9.58; p = 0.038) were associated with SM. CONCLUSIONS: Intraventricular tumors and the presence of intracranial leptomeningeal disease were most frequently associated with disseminated disease at presentation. These findings are consistent with current clinical expectations and offer empirical evidence that heightened suspicion for SM may be prospectively applied to certain subsets of pediatric brain tumor patients at the time of presentation.

Incident comorbidities after tamoxifen or aromatase inhibitor therapy in a racially and ethnically diverse cohort of women with breast cancer.

PURPOSE: As survival with early-stage, hormone receptor (HR)-positive breast has improved, it is essential to understand the long-term risks of incident comorbidities with different adjuvant endocrine therapy (ET) options. METHODS: Women treated with tamoxifen and/or an aromatase inhibitor (AI) for stages 1-3, HR-positive/HER2-negative breast cancer from 2000 to 2016 in either of two healthcare systems in the San Francisco Bay Area were included. We considered the following comorbidities: cerebrovascular accidents, congestive heart failure, dementia, depression/anxiety, diabetes mellitus, hyperlipidemia, myocardial infarction, non-alcoholic steatohepatitis, osteoporosis/fracture, peripheral vascular disease, and venous thromboembolism. Cause-specific Cox proportional hazards models were fit to time-to-new-diagnosis for each comorbidity, accounting for death as a competing risk. Hazard ratios (HR) and 95% confidence intervals (CI) for tamoxifen versus AI were reported. RESULTS: Among 2,902 analyzed patients, the median age at diagnosis was 58.3 years; 67.6% were non-Hispanic white, 22.3% Asian, 7.5% Hispanic, and 1.7% non-Hispanic Black. Half (54.7%) used AIs only, 27.6% used tamoxifen only and 17.7% used both tamoxifen and AIs sequentially. Tamoxifen was associated with a lower risk of osteoporosis than AI (multivariable HR 0.45, 95% CI 0.32-0.62). No other incident comorbidity risk varied between users of tamoxifen versus AIs. CONCLUSION: In a diverse, multi-institutional, contemporary breast cancer cohort, the only incident comorbidity that differed between ET options was osteoporosis, a known side effect of AIs. These results may inform clinical decision-making about ET, and reassure patients who have bothersome symptoms on AIs that they are unlikely to develop worse comorbidities if they switch to tamoxifen.

An integrated risk model stratifying seizure risk following brain tumor resection among seizure-naive patients without antiepileptic prophylaxis.

OBJECTIVE: The natural history of seizure risk after brain tumor resection is not well understood. Identifying seizure-naive patients at highest risk for postoperative seizure events remains a clinical need. In this study, the authors sought to develop a predictive modeling strategy for anticipating postcraniotomy seizures after brain tumor resection. METHODS: The IBM Watson Health MarketScan Claims Database was canvassed for antiepileptic drug (AED)- and seizure-naive patients who underwent brain tumor resection (2007-2016). The primary event of interest was short-term seizure risk (within 90 days postdischarge). The secondary event of interest was long-term seizure risk during the follow-up period. To model early-onset and long-term postdischarge seizure risk, a penalized logistic regression classifier and multivariable Cox regression model, respectively, were built, which integrated patient-, tumor-, and hospitalization-specific features. To compare empirical seizure rates, equally sized cohort tertiles were created and labeled as low risk, medium risk, and high risk. RESULTS: Of 5470 patients, 983 (18.0%) had a postdischarge-coded seizure event. The integrated binary classification approach for predicting early-onset seizures outperformed models using feature subsets (area under the curve [AUC] = 0.751, hospitalization features only AUC = 0.667, patient features only AUC = 0.603, and tumor features only AUC = 0.694). Held-out validation patient cases that were predicted by the integrated model to have elevated short-term risk more frequently developed seizures within 90 days of discharge (24.1% high risk vs 3.8% low risk, p < 0.001). Compared with those in the low-risk tertile by the long-term seizure risk model, patients in the medium-risk and high-risk tertiles had 2.13 (95% CI 1.45-3.11) and 6.24 (95% CI 4.40-8.84) times higher long-term risk for postdischarge seizures. Only patients predicted as high risk developed status epilepticus within 90 days of discharge (1.7% high risk vs 0% low risk, p = 0.003). CONCLUSIONS: The authors have presented a risk-stratified model that accurately predicted short- and long-term seizure risk in patients who underwent brain tumor resection, which may be used to stratify future study of postoperative AED prophylaxis in highest-risk patient subpopulations.

Performance of a rule-based semi-automated method to optimize chart abstraction for surveillance imaging among patients treated for non-small cell lung cancer.

BACKGROUND: We aim to develop and test performance of a semi-automated method (computerized query combined with manual review) for chart abstraction in the identification and characterization of surveillance radiology imaging for post-treatment non-small cell lung cancer patients. METHODS: A gold standard dataset consisting of 3011 radiology reports from 361 lung cancer patients treated at the Veterans Health Administration from 2008 to 2016 was manually created by an abstractor coding image type, image indication, and image findings. Computerized queries using a text search tool were performed to code reports. The primary endpoint of query performance was evaluated by sensitivity, positive predictive value (PPV), and F1 score. The secondary endpoint of efficiency compared semi-automated abstraction time to manual abstraction time using a separate dataset and the Wilcoxon rank-sum test. RESULTS: Query for image type demonstrated the highest sensitivity of 85%, PPV 95%, and F1 score 0.90. Query for image indication demonstrated sensitivity 72%, PPV 70%, and F1 score 0.71. The image findings queries ranged from sensitivity 75-85%, PPV 23-25%, and F1 score 0.36-0.37. Semi-automated abstraction with our best performing query (image type) improved abstraction times by 68% per patient compared to manual abstraction alone (from median 21.5 min (interquartile range 16.0) to 6.9 min (interquartile range 9.5), p < 0.005). CONCLUSIONS: Semi-automated abstraction using the best performing query of image type improved abstraction efficiency while preserving data accuracy. The computerized query acts as a pre-processing tool for manual abstraction by restricting effort to relevant images. Determining image indication and findings requires the addition of manual review for a semi-automatic abstraction approach in order to ensure data accuracy.

A Likelihood Ratio Test for Gene-Environment Interaction Based on the Trend Effect of Genotype Under an Additive Risk Model Using the Gene-Environment Independence Assumption.

Several statistical methods have been proposed for testing gene-environment (G-E) interactions under additive risk models using data from genome-wide association studies. However, these approaches have strong assumptions from underlying genetic models, such as dominant or recessive effects that are known to be less robust when the true genetic model is unknown. We aimed to develop a robust trend test employing a likelihood ratio test for detecting G-E interaction under an additive risk model, while incorporating the G-E independence assumption to increase power. We used a constrained likelihood to impose 2 sets of constraints for: 1) the linear trend effect of genotype and 2) the additive joint effects of gene and environment. To incorporate the G-E independence assumption, a retrospective likelihood was used versus a standard prospective likelihood. Numerical investigation suggests that the proposed tests are more powerful than tests assuming dominant, recessive, or general models under various parameter settings and under both likelihoods. Incorporation of the independence assumption enhances efficiency by 2.5-fold. We applied the proposed methods to examine the gene-smoking interaction for lung cancer and gene-apolipoprotein E $\varepsilon$4 interaction for Alzheimer disease, which identified 2 interactions between apolipoprotein E $\varepsilon$4 and loci membrane-spanning 4-domains subfamily A (MS4A) and bridging integrator 1 (BIN1) genes at genome-wide significance that were replicated using independent data.

A Robust Test for Additive Gene-Environment Interaction Under the Trend Effect of Genotype Using an Empirical Bayes-Type Shrinkage Estimator.

Evaluating gene by environment (G × E) interaction under an additive risk model (i.e., additive interaction) has gained wider attention. Recently, statistical tests have been proposed for detecting additive interaction, utilizing an assumption on gene-environment (G-E) independence to boost power, that do not rely on restrictive genetic models such as dominant or recessive models. However, a major limitation of these methods is a sharp increase in type I error when this assumption is violated. Our goal was to develop a robust test for additive G × E interaction under the trend effect of genotype, applying an empirical Bayes-type shrinkage estimator of the relative excess risk due to interaction. The proposed method uses a set of constraints to impose the trend effect of genotype and builds an estimator that data-adaptively shrinks an estimator of relative excess risk due to interaction obtained under a general model for G-E dependence using a retrospective likelihood framework. Numerical study under varying levels of departures from G-E independence shows that the proposed method is robust against the violation of the independence assumption while providing an adequate balance between bias and efficiency compared with existing methods. We applied the proposed method to the genetic data of Alzheimer disease and lung cancer.

Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography: Modeling Study for the US Preventive Services Task Force.

Importance: The US Preventive Services Task Force (USPSTF) is updating its 2013 lung cancer screening guidelines, which recommend annual screening for adults aged 55 through 80 years who have a smoking history of at least 30 pack-years and currently smoke or have quit within the past 15 years. Objective: To inform the USPSTF guidelines by estimating the benefits and harms associated with various low-dose computed tomography (LDCT) screening strategies. Design, Setting, and Participants: Comparative simulation modeling with 4 lung cancer natural history models for individuals from the 1950 and 1960 US birth cohorts who were followed up from aged 45 through 90 years. Exposures: Screening with varying starting ages, stopping ages, and screening frequency. Eligibility criteria based on age, cumulative pack-years, and years since quitting smoking (risk factor-based) or on age and individual lung cancer risk estimation using risk prediction models with varying eligibility thresholds (risk model-based). A total of 1092 LDCT screening strategies were modeled. Full uptake and adherence were assumed for all scenarios. Main Outcomes and Measures: Estimated lung cancer deaths averted and life-years gained (benefits) compared with no screening. Estimated lifetime number of LDCT screenings, false-positive results, biopsies, overdiagnosed cases, and radiation-related lung cancer deaths (harms). Results: Efficient screening programs estimated to yield the most benefits for a given number of screenings were identified. Most of the efficient risk factor-based strategies started screening at aged 50 or 55 years and stopped at aged 80 years. The 2013 USPSTF-recommended criteria were not among the efficient strategies for the 1960 US birth cohort. Annual strategies with a minimum criterion of 20 pack-years of smoking were efficient and, compared with the 2013 USPSTF-recommended criteria, were estimated to increase screening eligibility (20.6%-23.6% vs 14.1% of the population ever eligible), lung cancer deaths averted (469-558 per 100 000 vs 381 per 100 000), and life-years gained (6018-7596 per 100 000 vs 4882 per 100 000). However, these strategies were estimated to result in more false-positive test results (1.9-2.5 per person screened vs 1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (83-94 per 100 000 vs 69 per 100 000), and radiation-related lung cancer deaths (29.0-42.5 per 100 000 vs 20.6 per 100 000). Risk model-based vs risk factor-based strategies were estimated to be associated with more benefits and fewer radiation-related deaths but more overdiagnosed cases. Conclusions and Relevance: Microsimulation modeling studies suggested that LDCT screening for lung cancer compared with no screening may increase lung cancer deaths averted and life-years gained when optimally targeted and implemented. Screening individuals at aged 50 or 55 years through aged 80 years with 20 pack-years or more of smoking exposure was estimated to result in more benefits than the 2013 USPSTF-recommended criteria and less disparity in screening eligibility by sex and race/ethnicity.

Correction: Risk prediction models for selection of lung cancer screening candidates: A retrospective validation study.

[This corrects the article DOI: 10.1371/journal.pmed.1002277.].

Deep Brain Stimulation Results in Greater Symptomatic Improvement in Tourette Syndrome than Conservative Measures: A Meta-Analysis.

INTRODUCTION: Deep brain stimulation (DBS) has emerged as a safe and effective therapy for refractory Tourette syndrome (TS). Recent studies have identified several neural targets as effective in reducing TS symptoms with DBS, but, to our knowledge, none has compared the effectiveness of DBS with conservative therapy. METHODS: A literature review was performed to identify studies investigating adult patient outcomes reported as Yale Global Tic Severity Scale (YGTSS) scores after DBS surgery, pharmacotherapy, and psychotherapy. Data were pooled using a random-effects model of inverse variance-weighted meta-analysis (n = 168 for DBS, n = 131 for medications, and n = 154 for behavioral therapy). RESULTS: DBS resulted in a significantly greater reduction in YGTSS total score (49.9 ± 17.5%) than pharmacotherapy (22.5 ± 15.2%, p = 0.001) or psychotherapy (20.0 ± 11.3%, p < 0.001), with a complication (adverse effect) rate of 0.15/case, 1.13/case, and 0.60/case, respectively. CONCLUSION: Our data suggest that adult patients with refractory TS undergoing DBS experience greater symptomatic improvement with surprisingly low morbidity than can be obtained with pharmacotherapy or psychotherapy.

Sex differences in symptom presentation and functional outcomes: a pilot study in a matched sample of veterans with mild TBI.

Primary Objective: Research focused on mild traumatic brain injury in active military and veteran populations details the psychological, neurological and functional outcomes of mTBI, in a primarily male (~95%) cohort. This may misrepresent female symptoms and outcomes. Here we assess for genuine sex differences in symptom presentation and functional outcomes.Research Design: We used matched pairs to preclude potential sex bias in outcome data.Methods and Procedures: We matched 49 female/male pairs on; 1) mechanism of injury, 2) time from injury to assessment and 3) age at assessment. Statistics were t-tests, chi-square, correlations and post hoc linear regression.Main outcomes and results: Outcome assessment revealed four significant (p < .05) sex differences; Living situation, Marital status, Vocation and Branch of service. Only the Neurobehavioral Symptom Inventory (NSI) composite cognitive domain factor was significantly different between females (mean: 10.26) and males (mean: 7.58). Linear regression confirmed a significant effect of sex for the cognitive composite (p = .002).Conclusion: We conclude that sex has a moderate effect on mTBI post-concussive symptom presentation. The significant sex difference in the NSI cognitive domain characterizes sex-related symptomology profiles providers can focus on for better rehabilitation management. Replication in the larger cohort would improve generalizability.Abbreviation: TBI: Traumatic Brain Injuries; mTBI: mild Traumatic Brain Injuries; OIF: Operation Iraqi Freedom; OEF: Operation Enduring Freedom; VA: Veterans Affairs Health Care System; PSC: Polytrauma System of Care; PRC: Polytrauma Rehabilitation Center; PTRP: Polytrauma Transitional Rehabilitation Program; PNS: Polytrauma Network Site; PTSD: Post Traumatic Stress Disorder; DoD: Department of Defense; NSI: Neurobehavioral Symptom Inventory; LOC: loss of consciousness; AOC: alteration of consciousness; PTA: posttraumatic amnesia; CPRS: computerized patient record system; CTBIE: Comprehensive TBI Evaluation; OCD: obsessive compulsive disorder; ETOH: alcohol abuse.

Genomic landscape of ductal carcinoma in situ and association with progression.

PURPOSE: The detection rate of breast ductal carcinoma in situ (DCIS) has increased significantly, raising the concern that DCIS is overdiagnosed and overtreated. Therefore, there is an unmet clinical need to better predict the risk of progression among DCIS patients. Our hypothesis is that by combining molecular signatures with clinicopathologic features, we can elucidate the biology of breast cancer progression, and risk-stratify patients with DCIS. METHODS: Targeted exon sequencing with a custom panel of 223 genes/regions was performed for 125 DCIS cases. Among them, 60 were from cases having concurrent or subsequent invasive breast cancer (IBC) (DCIS + IBC group), and 65 from cases with no IBC development over a median follow-up of 13 years (DCIS-only group). Copy number alterations in chromosome 1q32, 8q24, and 11q13 were analyzed using fluorescence in situ hybridization (FISH). Multivariable logistic regression models were fit to the outcome of DCIS progression to IBC as functions of demographic and clinical features. RESULTS: We observed recurrent variants of known IBC-related mutations, and the most commonly mutated genes in DCIS were PIK3CA (34.4%) and TP53 (18.4%). There was an inverse association between PIK3CA kinase domain mutations and progression (Odds Ratio [OR] 10.2, p < 0.05). Copy number variations in 1q32 and 8q24 were associated with progression (OR 9.3 and 46, respectively; both p < 0.05). CONCLUSIONS: PIK3CA kinase domain mutations and the absence of copy number gains in DCIS are protective against progression to IBC. These results may guide efforts to distinguish low-risk from high-risk DCIS.

Intracranial Hemorrhage in Deep Vein Thrombosis/Pulmonary Embolus Patients Without Atrial Fibrillation.

Background and Purpose- Deep vein thrombosis (DVTs) is a common disease with high morbidity if it progresses to pulmonary embolus (PE). Anticoagulation is the treatment of choice; warfarin has long been the standard of care. Early experience with direct oral anticoagulants (DOACs) suggests that these agents may be may be a safer and equally effective alternative in the treatment of DVT/PE. Nontraumatic intracranial hemorrhage (ICH) is one of the most devastating potential complications of anticoagulation therapy. We sought to compare the rates of ICH in patients treated with DOACs versus those treated with warfarin for DVT/PE. Methods- The MarketScan Commercial Claims and Medicare Supplemental databases were used. Adult DVT/PE patients without known atrial fibrillation and with prescriptions for either a DOAC or warfarin were followed for the occurrence of inpatient admission for ICH. Coarsened exact matching was used to balance the treatment cohorts. Cox proportional-hazards regressions and Kaplan-Meier survival curves were used to estimate the association between DOACs and the risk of ICH compared with warfarin. Results- The combined cohort of 218 620 patients had a median follow-up of 3.0 months, mean age of 55.4 years, and was 52.1% women. The DOAC cohort had 26 980 patients and 8 ICH events (1.0 cases per 1000 person-years), and the warfarin cohort had 191 640 patients and 324 ICH events (3.3 cases per 1000 person-years; P<0.0001). The DOAC cohort had a lower hazard ratio for ICH compared with warfarin in both the unmatched (hazard ratio=0.26; P=0.0002) and matched (hazard ratio=0.20; P=0.0001) Cox proportional-hazards regressions. Conclusions- DOACs show superior safety to warfarin in terms of risk of ICH in patients with DVT/PE.

Disparities in hepatocellular carcinoma incidence by race/ethnicity and geographic area in California: Implications for prevention.

BACKGROUND: The incidence of hepatocellular carcinoma (HCC) has been rising rapidly in the United States. California is an ethnically diverse state with the largest number of incident HCC cases in the country. Characterizing HCC disparities in California may inform priorities for HCC prevention. METHODS: By using data from the Surveillance, Epidemiology, and End Results 18-Registry Database and the California Cancer Registry, age-adjusted HCC incidence in California from 2009 through 2013 was calculated by race/ethnicity and neighborhood ethnic enclave status. A geographic analysis was conducted using Medical Service Study Areas (MSSAs) as the geographic unit, and race/ethnicity-specific standardized incidence ratios (SIRs) were calculated to identify MSSAs with higher-than-expected HCC incidence compared with the statewide average. RESULTS: During 2009 through 2013, the age-adjusted incidence of HCC in California was the highest in Asians/Pacific Islanders (APIs) and Hispanics (>100% higher than whites), especially those living in more ethnic neighborhoods (20%-30% higher than less ethnic neighborhoods). Of the 542 MSSAs statewide, 42 had elevated HCC incidence (SIR ≥ 1.5; lower bound of 95% confidence interval > 1) for whites, 14 for blacks, 24 for APIs, and 36 for Hispanics. These MSSAs have 24% to 52% higher proportions of individuals below the 100% federal poverty line than other MSSAs. CONCLUSIONS: APIs and Hispanics residing in more ethnic neighborhoods and individuals residing in lower income neighborhoods require more extensive preventive efforts tailored toward their unique risk factor profiles. The current race/ethnicity-specific geographic analysis can be extended to other states to inform priorities for HCC targeted prevention at the subcounty level, eventually reducing HCC burden in the country.

Circadian genes and risk of prostate cancer in the prostate cancer prevention trial.

Circadian genes have been considered as a possible biological mechanism for the observed relationship between circadian rhythm disruptions and increased risk of hormone-related cancers. In the current study, we investigated the relationship between circadian gene variants and prostate cancer risk and whether reducing bioavailable testosterone modifies the circadian genes-prostate cancer relationship. We conducted a nested case-control study among Caucasian men in the Prostate Cancer Prevention Trial (PCPT), a randomized placebo-controlled clinical trial to assess if finasteride (an androgen bioactivation inhibitor) could prevent prostate cancer. We evaluated the associations between 240 circadian gene variations and prostate cancer risk among 1092 biopsy-confirmed prostate cancer cases and 1089 biopsy-negative controls in the study (642 cases and 667 controls from the placebo group; 450 cases and 422 controls from the finasteride group), stratified by treatment group. Among men in the finasteride group, there were suggestive associations between NPAS2 variants and total prostate cancer risk, with one SNP remaining statistically significant after Bonferroni correction (rs746924, odds ratio [OR] = 1.5, P = 9.6 × 10-5 ). However, we found little evidence of increased prostate cancer risk (overall or by low/high grade) associated with circadian gene variations in men of the placebo group, suggesting potential modification of genetic effects by treatment. We did not find strong evidence that circadian gene variants influenced prostate cancer risk in men who were not on finasteride treatment. There were suggestive associations between NPAS2 variants and prostate cancer risk among men using finasteride, which warrants further investigations.