Goal-Guided Graph Attention Network with Interactive State Refinement for Multi-Agent Trajectory Prediction.

The accurate prediction of the future trajectories of traffic participants is crucial for enhancing the safety and decision-making capabilities of autonomous vehicles. Modeling social interactions among agents and revealing the inherent relationships is crucial for accurate trajectory prediction. In this context, we propose a goal-guided and interaction-aware state refinement graph attention network (SRGAT) for multi-agent trajectory prediction. This model effectively integrates high-precision map data and dynamic traffic states and captures long-term temporal dependencies through the Transformer network. Based on these dependencies, it generates multiple potential goals and Points of Interest (POIs). Through its dual-branch, multimodal prediction approach, the model not only proposes various plausible future trajectories associated with these POIs, but also rigorously assesses the confidence levels of each trajectory. This goal-oriented strategy enables SRGAT to accurately predict the future movement trajectories of other vehicles in complex traffic scenarios. Tested on the Argoverse and nuScenes datasets, SRGAT surpasses existing algorithms in key performance metrics by adeptly integrating past trajectories and current context. This goal-guided approach not only enhances long-term prediction accuracy, but also ensures its reliability, demonstrating a significant advancement in trajectory forecasting.

Conductivity reactivity index for monitoring of cerebrovascular autoregulation in early cerebral ischemic rabbits.

BACKGROUND: Cerebrovascular autoregulation (CVAR) is the mechanism that maintains constant cerebral blood flow by adjusting the caliber of the cerebral vessels. It is important to have an effective, contactless way to monitor and assess CVAR in patients with ischemia. METHODS: The adjustment of cerebral blood flow leads to changes in the conductivity of the whole brain. Here, whole-brain conductivity measured by the magnetic induction phase shift method is a valuable alternative to cerebral blood volume for non-contact assessment of CVAR. Therefore, we proposed the correlation coefficient between spontaneous slow oscillations in arterial blood pressure and the corresponding magnetic induction phase shift as a novel index called the conductivity reactivity index (CRx). In comparison with the intracranial pressure reactivity index (PRx), the feasibility of the conductivity reactivity index to assess CVAR in the early phase of cerebral ischemia has been preliminarily confirmed in animal experiments. RESULTS: There was a significant difference in the CRx between the cerebral ischemia group and the control group (p = 0.002). At the same time, there was a significant negative correlation between the CRx and the PRx (r = - 0.642, p = 0.002) after 40 min after ischemia. The Bland-Altman consistency analysis showed that the two indices were linearly related, with a minimal difference and high consistency in the early ischemic period. The sensitivity and specificity of CRx for cerebral ischemia identification were 75% and 20%, respectively, and the area under the ROC curve of CRx was 0.835 (SE = 0.084). CONCLUSION: The animal experimental results preliminarily demonstrated that the CRx can be used to monitor CVAR and identify CVAR injury in early ischemic conditions. The CRx has the potential to be used for contactless, global, bedside, and real-time assessment of CVAR of patients with ischemic stroke.

Self-oxygenation mesoporous MnO2 nanoparticles with ultra-high drug loading capacity for targeted arteriosclerosis therapy.

Atherosclerosis (AS) is a leading cause of vascular diseases that severely threats the human health due to the lack of efficient therapeutic methods. During the development and progress of AS, macrophages play critical roles, which are polarized into pro-inflammatory M1 phenotype to excrete abundant cytokines and overproduce reactive oxygen species (ROS), and take up excess amount of lipid to form foam cells. In this work, we developed a MnO2-based nanomedicine to re-educate macrophages for targeting AS therapy. The MnO2 was one-pot synthesized under mild condition, showing intrinsic catalase-mimic activity for self-oxygenation by using endogenous H2O2 as substrate. Moreover, the mesoporous structure as well as the abundant metal coordination sites in MnO2 structure facilitated the loading of an anti-AS drug of curcumin (Cur), achieving extraordinarily high drug loading capacity of 54%. Cur displayed a broad spectrum of anti-oxidant and anti-inflammatory capabilities to repolarize M1 macrophages into M2 phenotype, and the catalytic MnO2 recovered the function of lipid efflux transporter to remove lipid from cells by suppressing HIF-1α. Collectively, the nanocarrier and the payload drug functioned as an all-active nanoplatform to synergistically alleviate the syndromes of AS. In ApoE-/- mice model, the nanosystem could significantly prolong the circulation half-life of Cur by sixfold, and enhance drug accumulation in atherosclerotic lesion by 3.5-fold after intravenous injection by virtue of surface hyaluronic acid (HA) modification. As a result, a robust anti-AS efficacy was achieved as evidenced by the decrease of atherosclerotic lesion, plaque area, lipid level.

Baseline characteristics and first-line treatment patterns in patients with HER2-positive metastatic breast cancer in the SystHERs registry.

BACKGROUND: Systemic Therapies for HER2-Positive Metastatic Breast Cancer Study (SystHERs, NCT01615068) was a prospective, observational disease registry designed to identify treatment patterns and clinical outcomes in patients with HER2-positive metastatic breast cancer (MBC) in real-world treatment settings. METHODS: SystHERs enrolled patients aged ≥ 18 years with recently diagnosed HER2-positive MBC. Treatment regimens and clinical management were determined by the treating physician. In this analysis, patients were compared descriptively by first-line treatment, age, or race. Multivariate logistic regression was used to examine the associations between baseline variables and treatment selections. Clinical outcomes were assessed in patients treated with trastuzumab (Herceptin [H]) + pertuzumab (Perjeta [P]). RESULTS: Patients were enrolled from June 2012 to June 2016. As of February 22, 2018, 948 patients from 135 US treatment sites had received first-line treatment, including HP (n = 711), H without P (n = 175), or no H (n = 62) (with or without chemotherapy and/or hormonal therapy). Overall, 68.7% received HP + taxane and 9.3% received H without P + taxane. Patients aged < 50 years received HP (versus H without P) more commonly than those ≥ 70 years (odds ratio 4.20; 95% CI, 1.62-10.89). Chemotherapy was less common in patients ≥ 70 years (68.2%) versus those < 50 years (88.0%) or 50-69 years (87.4%). Patients treated with HP had median overall survival of 53.8 months and median progression-free survival of 15.8 months. CONCLUSIONS: Our analysis of real-world data shows that most patients with HER2-positive MBC received first-line treatment with HP + taxane. However, older patients were less likely to receive dual HER2-targeted therapy and chemotherapy.

De Novo Versus Recurrent HER2-Positive Metastatic Breast Cancer: Patient Characteristics, Treatment, and Survival from the SystHERs Registry.

BACKGROUND: Limited data exist describing real-world treatment of de novo and recurrent HER2-positive metastatic breast cancer (MBC). MATERIALS AND METHODS: The Systemic Therapies for HER2-Positive Metastatic Breast Cancer Study (SystHERs) was a fully enrolled (2012-2016), observational, prospective registry of patients with HER2-positive MBC. Patients aged ≥18 years and ≤6 months from HER2-positive MBC diagnosis were treated and assessed per their physician's standard practice. The primary endpoint was to characterize treatment patterns by de novo versus recurrent MBC status, compared descriptively. Secondary endpoints included patient characteristics, progression-free and overall survival (PFS and OS, by Kaplan-Meier method; hazard ratio [HR] and 95% confidence interval [CI] by Cox regression), and patient-reported outcomes. RESULTS: Among 977 eligible patients, 49.8% (n = 487) had de novo and 50.2% (n = 490) had recurrent disease. A higher proportion of de novo patients had hormone receptor-negative disease (34.9% vs. 24.9%), bone metastasis (57.1% vs. 45.9%), and/or liver metastasis (41.9% vs. 33.1%), and a lower proportion had central nervous system metastasis (4.3% vs. 13.5%). De novo patients received first-line regimens containing chemotherapy (89.7%), trastuzumab (95.7%), and pertuzumab (77.8%) more commonly than recurrent patients (80.0%, 85.9%, and 68.6%, respectively). De novo patients had longer median PFS (17.7 vs. 11.9 months; HR, 0.69; 95% CI, 0.59-0.80; p < .0001) and OS (not estimable vs. 44.5 months; HR, 0.55; 95% CI, 0.44-0.69; p < .0001). CONCLUSION: Patients with de novo versus recurrent HER2-positive MBC exhibit different disease characteristics and survival durations, suggesting these groups have distinct outcomes. These differences may affect future clinical trial design. Clinical trial identification number. NCT01615068 (clinicaltrials.gov). IMPLICATIONS FOR PRACTICE: SystHERs was an observational registry of patients with HER2-positive metastatic breast cancer (MBC), which is a large, modern, real-world data set for this population and, thereby, provides a unique opportunity to study patients with de novo and recurrent HER2-positive MBC. In SystHERs, patients with de novo disease had different baseline demographics and disease characteristics, had superior clinical outcomes, and more commonly received first-line chemotherapy and/or trastuzumab versus those with recurrent disease. Data from this and other studies suggest that de novo and recurrent MBC have distinct outcomes, which may have implications for disease management strategies and future clinical study design.

High-sensitivity C-reactive protein, hemoglobin A1c and breast cancer risk: a nested case-control study from Alberta's Tomorrow Project cohort.

PURPOSE: Our aim is to examine the associations between high-sensitivity C-reactive protein (hsCRP) and hemoglobin A1c (HbA1c), common biomarkers of inflammation and insulin resistance, respectively, with breast cancer risk, while adjusting for measures of excess body size. METHODS: We conducted a nested case-control study within the Alberta's Tomorrow Project cohort (Alberta, Canada) including 197 incident breast cancer cases and 394 matched controls. The sample population included both pre- and postmenopausal women. Serum concentrations of hsCRP and HbA1c were measured from blood samples collected at baseline, along with anthropometric measurements, general health and lifestyle data. Conditional logistic regression was used to evaluate associations between hsCRP, HbA1c, and breast cancer risk adjusted for excess body size (body fat percentage) and other risk factors for breast cancer. RESULTS: Higher concentrations of hsCRP were associated with elevated breast cancer risk (odds ratio [OR] 1.27; 95% confidence interval [95% CI] 1.03-1.55). The observed associations were unchanged with adjustment for body fat percentage. Higher HbA1c concentrations were not significantly associated with an increased breast cancer risk (OR 1.22; 95% CI 0.17-8.75). CONCLUSION: These data suggest that hsCRP may be associated with elevated breast cancer risk, independent of excess body size. However, elevated concentrations of HbA1c did not appear to increase breast cancer risk in apparently healthy women.

Downregulation of DLGAP1-Antisense RNA 1 Alleviates Vascular Endothelial Cell Injury Via Activation of the Phosphoinositide 3-kinase/Akt Pathway Results from an Acute Limb Ischemia Rat Model.

OBJECTIVE: This study aimed to investigate the effect of long non-coding RNA (lncRNA) DLGAP1 antisense RNA 1 (DLGAP1-AS1) on vascular endothelial cell (VEC) injury via the phosphoinositide 3-kinase (PI3K)/Akt pathway in rat models of acute lower limb ischaemia-reperfusion (I/R). METHODS: Differentially expressed lncRNAs related to I/R were screened using the gene expression omnibus database. Acute lower limb I/R models were induced in male Wistar rats, in which the regulatory mechanisms of DLGAP1-AS1 silencing were analysed after the treatment of small interfering RNA (siRNA) against DLGAP1-AS1 or an inhibitor of the PI3K/Akt pathway. The relationship between DLGAP1-AS1 and the PI3K/Akt pathway was analysed. The levels of tumour necrosis factor (TNF)-α and vascular cell adhesion molecule-1 (VCAM-1), as well as malondialdehyde (MDA) concentration and creatine kinase (CK) activity, were measured. The number of circulating endothelial cells (CECs) and apoptosis of VECs were identified. RESULTS: Microarray based analysis indicated that DLGAP1-AS1 was highly expressed in I/R, which was further confirmed by detection of expression in rat models of acute lower limb I/R. Notably, the treatment of siRNA against DLGAP1-AS1 led to the activation of the PI3K/Akt pathway. In response to siRNA against DLGAP1-AS1, the levels of TNF-α and VCAM-1 were decreased, and MDA concentration and CK activity was downregulated. Reduced CEC numbers and suppressed VEC apoptosis were also observed. CONCLUSION: DLGAP1-AS1 silencing could further suppress the oxidative stress, exert an anti-apoptosis effect, and reduce inflammatory reaction, whereby VEC injury is alleviated by activation of the PI3K/Akt pathway in rats with acute lower limb I/R.

Immediate-term cognitive impairment following intravenous (IV) chemotherapy: a prospective pre-post design study.

BACKGROUND: Cognitive impairment is commonly reported in patients receiving chemotherapy, but the acuity of onset is not known. This study utilized the psychomotor vigilance test (PVT) and trail-making test B (TMT-B) to assess cognitive impairment immediately post-chemotherapy. METHODS: Patients aged 18-80 years receiving first-line intravenous chemotherapy for any stage of breast or colorectal cancer were eligible. Patient symptoms, peripheral neuropathy and Stanford Sleepiness Scale were assessed. A five-minute PVT and TMT-B were completed on a tablet computer pre-chemotherapy and immediately post-chemotherapy. Using a mixed linear regression model, changes in reciprocal transformed PVT reaction time (mean 1/RT) were assessed. A priori, an increase in median PVT reaction times by > 20 ms (approximating PVT changes with blood alcohol concentrations of 0.04-0.05 g%) was considered clinically relevant. RESULTS: One hundred forty-two cancer patients (73 breast, 69 colorectal, median age 55.5 years) were tested. Post-chemotherapy, mean 1/RT values were significantly slowed compared to pre-chemotherapy baseline (p = 0.01). This corresponded to a median PVT reaction time slowed by an average of 12.4 ms. Changes in PVT reaction times were not correlated with age, sex, cancer type, treatment setting, or use of supportive medications. Median post-chemotherapy PVT reaction time slowed by an average of 22.5 ms in breast cancer patients and by 1.6 ms in colorectal cancer patients. Post-chemotherapy median PVT times slowed by > 20 ms in 57 patients (40.1%). Exploratory analyses found no statistically significant association between the primary outcome and self-reported anxiety, fatigue or depression. TMT-B completion speed improved significantly post-chemotherapy (p = 0.03), likely due to test-retest phenomenon. CONCLUSIONS: PVT reaction time slowed significantly immediately post-chemotherapy compared to a pre-chemotherapy baseline, and levels of impairment similar to effects of alcohol consumption in other studies was seen in 40% of patients. Further studies assessing functional impact of cognitive impairment on patients immediately after chemotherapy are warranted.

Determinants of changes in physical activity from pre-diagnosis to post-diagnosis in a cohort of prostate cancer survivors.

PURPOSE: Physical activity (PA) has been shown to improve quality of life and survival in cancer survivors; however, a cancer diagnosis may change PA patterns. We examine determinants of changes in meeting the PA guidelines (150 min/week of moderate aerobic PA) before and after a prostate cancer diagnosis. METHODS: Eight hundred and thirty prostate cancer survivors who participated in a population-based case-control study between 1997 and 2000 in Alberta, Canada, enrolled in a prospective cohort study. Past year activity levels were self-reported at diagnosis (pre-diagnosis measure) and again 2 years post-diagnosis. Determinants were collected by questionnaires and medical chart abstractions. Four PA patterns were created: non-exercisers (fail to meet guidelines pre-diagnosis and post-diagnosis), adopters (fail to meet guidelines pre-diagnosis, meet guidelines post-diagnosis), maintainers (meet guidelines pre-diagnosis and post-diagnosis) and relapsers (meet guidelines pre-diagnosis, fail to meet guidelines post-diagnosis). RESULTS: Multinomial logistic regression analyses identified that being a non-exerciser compared to maintainer was associated with being employed, rural location, high PSA, smoking status, not attending support groups and less than average physical quality of life (QoL). Being a relapser compared to maintainer was associated with rural location and lack of friend support. Finally, being a non-exerciser compared to adopter was associated with urinary incontinence, smoking status and less than average physical and mental QoL. CONCLUSIONS: Demographic, health and lifestyle variables are associated with changes in meeting PA guidelines from pre-diagnosis to post-diagnosis in prostate cancer survivors. Programming should be aimed at offering interventions to help inactive survivors adopt PA and active survivors to maintain PA.

Three-part joint modeling methods for complex functional data mixed with zero-and-one-inflated proportions and zero-inflated continuous outcomes with skewness.

We take a functional data approach to longitudinal studies with complex bivariate outcomes. This work is motivated by data from a physical activity study that measured 2 responses over time in 5-minute intervals. One response is the proportion of time active in each interval, a continuous proportions with excess zeros and ones. The other response, energy expenditure rate in the interval, is a continuous variable with excess zeros and skewness. This outcome is complex because there are 3 possible activity patterns in each interval (inactive, partially active, and completely active), and those patterns, which are observed, induce both nonrandom and random associations between the responses. More specifically, the inactive pattern requires a zero value in both the proportion for active behavior and the energy expenditure rate; a partially active pattern means that the proportion of activity is strictly between zero and one and that the energy expenditure rate is greater than zero and likely to be moderate, and the completely active pattern means that the proportion of activity is exactly one, and the energy expenditure rate is greater than zero and likely to be higher. To address these challenges, we propose a 3-part functional data joint modeling approach. The first part is a continuation-ratio model to reorder the ordinal valued 3 activity patterns. The second part models the proportions when they are in interval (0,1). The last component specifies the skewed continuous energy expenditure rate with Box-Cox transformations when they are greater than zero. In this 3-part model, the regression structures are specified as smooth curves measured at various time points with random effects that have a correlation structure. The smoothed random curves for each variable are summarized using a few important principal components, and the association of the 3 longitudinal components is modeled through the association of the principal component scores. The difficulties in handling the ordinal and proportional variables are addressed using a quasi-likelihood type approximation. We develop an efficient algorithm to fit the model that also involves the selection of the number of principal components. The method is applied to physical activity data and is evaluated empirically by a simulation study.

Drug development for breast, colorectal, and non-small cell lung cancers from 1979 to 2014.

BACKGROUND: Understanding the drug development pathway is critical for streamlining the development of effective cancer treatments. The objective of the current study was to delineate the drug development timeline and attrition rate of different drug classes for common cancer disease sites. METHODS: Drugs entering clinical trials for breast, colorectal, and non-small cell lung cancer were identified using a pharmaceutical business intelligence database. Data regarding drug characteristics, clinical trials, and approval dates were obtained from the database, clinical trial registries, PubMed, and regulatory Web sites. RESULTS: A total of 411 drugs met the inclusion criteria for breast cancer, 246 drugs met the inclusion criteria for colorectal cancer, and 315 drugs met the inclusion criteria for non-small cell lung cancer. Attrition rates were 83.9% for breast cancer, 87.0% for colorectal cancer, and 92.0% for non-small cell lung cancer drugs. In the case of non-small cell lung cancer, there was a trend toward higher attrition rates for targeted monoclonal antibodies compared with other agents. No tumor site-specific differences were noted with regard to cytotoxic chemotherapy, immunomodulatory, or small molecule kinase inhibitor drugs. Drugs classified as "others" in breast cancer had lower attrition rates, primarily due to the higher success of hormonal medications. Mean drug development times were 8.9 years for breast cancer, 6.7 years for colorectal cancer, and 6.6 years for non-small cell lung cancer. CONCLUSIONS: Overall oncologic drug attrition rates remain high, and drugs are more likely to fail in later-stage clinical trials. The refinement of early-phase trial design may permit the selection of drugs that are more likely to succeed in the phase 3 setting. Cancer 2017;123:4672-4679. © 2017 American Cancer Society.

The Evolution of Metastatic Colorectal Cancer Clinical Trials: Application of the ASCO Framework for Assessing Value.

Background: Phase III trials in metastatic colorectal cancer (mCRC) have collectively led to progressive advancements in patient outcomes over the past decades. This study characterizes the evolution of mCRC phase III trials through assessing the value of cancer therapy, as measured by the ASCO Value Framework. Methods: Phase III trial results of systemic therapy for mCRC published between 1980 and 2015 were identified, and their outcome, statistical significance, journal impact factor, and citation by the 2016 NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for CRC were recorded. For each trial, the net health benefit (NHB) score was calculated using the June 2015 (original) and May 2016 (revised) ASCO Value Framework: Advanced Disease. Results: There were 114 mCRC phase III trials eligible for calculation of the NHB score. Using the revised framework, the median NHB score was 4.6 (range, -30 to 43.5); 12% of trials received bonus points. Trials with statistically significant results had higher NHB scores compared with nonsignificant trials (median NHB score, 21.6 vs 2.9; P<.0001). Clinical trials cited in the NCCN Guidelines had higher NHB scores than those not cited (median score, 8.0 vs 0.3; P=.02). In multivariate linear regression analysis, the only significant predictor of high NHB score was statistically significant studies. Conclusions: The median NHB score for mCRC phase III trials was 4.6. Higher NHB scores are associated with statistically significant studies and are cited in the NCCN Guidelines, a surrogate for practice-changing trials. The 2016 ASCO Value Framework may not fully capture the benefits on an individual patient level.

Atypical teratoid rhabdoid tumor in the first year of life: the Canadian ATRT registry experience and review of the literature.

While 2/3 of patients with ATRT are less than 3 years at diagnosis, the literature suggests younger children present with more aggressive disease and poorer outcome. However, little data exist on characteristics and outcome of patients diagnosed with ATRT in the first year of life. In particular, it is unclear whether they access similar treatments as do older children. We compared the cohort of patients ≤12 months from the Canadian ATRT registry to all cases extracted from the literature reported between 1996 and 2014 to describe their clinical and treatment characteristics, and potential prognostic factors. Twenty-six (33.7%) patients from the Canadian registry were ≤12 months at diagnosis as were 120 cases identified in the literature. Post-operatively, 46% of the registry's patients underwent palliation as opposed to 10.8% in the literature cohort. Palliative patients were significantly younger than those who received active therapy (3.3 vs. 6.6 months). While the use of high-dose chemotherapy (HDC) was relatively similar in both cohorts (42.9 and 35.5% respectively), radiotherapy (RT) use was significantly lower in the Canadian cohort (14.3 vs 44.9%). Children ≤6 months, who received active therapy, had a worst outcome than older ones. Gross total resection, HDC and adjuvant RT were associated with better outcomes. Eighty percent of the tested patients had evidence of germline mutation of INI1. While 1/3 of ATRT occurs within the first year of life, a large proportion only received palliative therapy. Even when actively treated, children ≤6 months fare worse. Some selected patients benefit from HDC.

A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study.

Incidence and risk factor of hemorrhagic cystitis after allogeneic transplantation with fludarabine, busulfan, and anti-thymocyte globulin myeloablative conditioning.

BACKGROUND: Hemorrhagic cystitis (HC) is a complication of allogeneic stem cell transplantation (SCT), associated with factors such as BK polyomavirus reactivation, age, conditioning regimen, and presence of graft-versus-host disease (GVHD). The incidence and impact of HC in patients receiving fludarabine (Flu), busulfan (Bu), and anti-thymocyte globulin (ATG) conditioning is unknown. METHODS: We conducted a case-control study of patients undergoing SCT at our center between January 1, 2003 and Dec 31, 2012, to determine the incidence of HC and its effect on patient outcomes including overall survival (OS), relapse, non-relapse mortality (NRM), GVHD, and healthcare resource use. RESULTS: In total, 94 cases of HC were identified and matched to controls based on age, donor type, disease type, and disease status at transplantation. The total incidence of HC was 17.7% (117 of 661 patients). Cases had a higher rate (43.6% vs 27.1%, P=.0394) of acute GVHD (Grade II-IV), and chronic GVHD requiring systemic steroids (34.9% vs 18.6%, P=.004). Male gender was found to be a risk factor (hazard ratio [HR]=1.725, P=.017). OS and progression-free survival did not differ between cases and controls (OS HR=1.128, 95% confidence interval [CI] 0.7807-1.639; progression-free survival HR=0.8809, 95% CI 0.6320-1.234), however the rate of NRM was higher in cases (HR=1.632, 95% CI 1.007-2.830). Median length of hospitalization was longer for patients with HC than matched controls (65.5 days vs 40.5 days, P<.0001). CONCLUSION: HC is common in patients undergoing allogeneic SCT with FluBuATG conditioning, and affects the duration of hospitalization. Rate of GVHD is higher among patients with HC. While OS is not affected, an association was seen with higher NRM in our study. Improvement in treatment for HC may lead to reductions in morbidity and healthcare resource utilization.

Atypical Meningioma: Referral Patterns, Treatment and Adherence to Guidelines.

OBJECTIVE: To determine the referral rate to radiation oncologist (RO), use of postoperative radiotherapy (PORT) and the impact of a clinical practice guideline (CPG) on patients with atypical meningioma (AM). METHODS: A retrospective review of meningioma patients (n=526) treated between 2003 and 2013 was undertaken. Patients' characteristics, extent of surgical resection (EOR), RO referral, PORT, date and treatment of first recurrence were collected for all patients >18 years with a new diagnosis of AM after surgical resection (n=83). Progression free survival (PFS) and overall survival (OS) according to EOR were assessed by the Log-Rank test of Kaplan-Meier survival. RESULTS: Median age was 57 years. EOR was gross total (GTR) in 44 patients, subtotal (STR) in 36 patients and 3 patients had unknown EOR. RO referral rate was 26.5% (n=22); 5 patients initially had GTR and 17 had STR. Only 7 patients received PORT. At a median follow up time of 29 months, recurrences occurred in 28 patients, 4 had GTR, 21 had STR and 3 had an unknown EOR. With PORT, 2 patients developed recurrence. 5-year PFS was 62% after GTR and 33% after STR (P=0.002). 5-year OS was 92% after GTR and 83% after STR (P=0.45). CONCLUSION: In this cohort with AM, RO referral rate was low and was not influenced by the CPG. Use of PORT was also low. Given the lack of conclusive evidence supporting PORT in such patients, a multidisciplinary approach, including RO consultation, is needed to provide patients with optimal and individualised care.

A novel method of micro-tomography geometric angle calibration with random phantom.

The objective of this study is to develop and test the feasibility of applying a machine learning method for geometry calibration of angles in micro-tomography systems. Increasing importance of micro-tomography systems are manifested with escalating applications in various scenarios including but not limited to oral and maxillofacial surgery, vascular and intervention radiology, among other specific applications for purposes of diagnosis and treatments planning. There is possibility, however, actual pathology is confused by artifact of tissue structures after volume reconstruction as a result of CT construction errors. A Kernel Ridge Regression algorithm for micro-tomography geometry estimation and its corresponding phantom is developed and tested in this study. Several projection images of a rotating Random Phantom of some steel ball bearings in an unknown geometry with gantry angle information were utilized to calibrate both in-plane and out-plane rotation of the detector. The described method can also be expanded to calibrate other parameters of CT construction effortlessly. Using computer simulation, the study results validated that geometry parameters of micro-tomography system were accurately calibrated.

Quantifying Benefit of Autologous Transplantation for Relapsed Follicular Lymphoma Patients via Instrumental Variable Analysis.

The role of autologous stem cell transplantation (ASCT) in patients with relapsed follicular lymphoma (FL) remains controversial because of a lack of proven overall survival (OS) benefit versus nontransplant strategies. We conducted a comparative effectiveness research study involving 3 tertiary Canadian cancer centers to determine whether the ASCT-based approach used at 1 center improved OS relative to non-ASCT approaches used at the other centers. Of 1082 consecutive patients aged 18 to 60 years and diagnosed with FL from 2001 to 2010, the study population included 355 patients who experienced relapse from chemotherapy (center A = 96, center B = 84, center C = 175). Data were analyzed according to the instrumental variable of treatment center to control for confounding factors. The frequency of using ASCT at first or second relapse was significantly different between the centers (A = 58%, B = 7%, C = 5%, P < .001). With a median follow-up of 69.1 months, the actuarial 5-year OS rates after first chemotherapy relapse were 89%, 60%, and 60% for centers A, B, and C respectively (log rank P < .0001). Based on instrumental variable analysis, the use of ASCT at relapse 1 or 2 significantly decreased the risk of death from first relapse (HR .127, P = .004) and from initial diagnosis (HR .116, P = .004). In conclusion, for FL patients who relapse after chemotherapy, these results strongly support more frequent use of ASCT at first or second relapse.

Methods to assess an exercise intervention trial based on 3-level functional data.

Motivated by data recording the effects of an exercise intervention on subjects' physical activity over time, we develop a model to assess the effects of a treatment when the data are functional with 3 levels (subjects, weeks and days in our application) and possibly incomplete. We develop a model with 3-level mean structure effects, all stratified by treatment and subject random effects, including a general subject effect and nested effects for the 3 levels. The mean and random structures are specified as smooth curves measured at various time points. The association structure of the 3-level data is induced through the random curves, which are summarized using a few important principal components. We use penalized splines to model the mean curves and the principal component curves, and cast the proposed model into a mixed effects model framework for model fitting, prediction and inference. We develop an algorithm to fit the model iteratively with the Expectation/Conditional Maximization Either (ECME) version of the EM algorithm and eigenvalue decompositions. Selection of the number of principal components and handling incomplete data issues are incorporated into the algorithm. The performance of the Wald-type hypothesis test is also discussed. The method is applied to the physical activity data and evaluated empirically by a simulation study.

Low ATM protein expression in malignant tumor as well as cancer-associated stroma are independent prognostic factors in a retrospective study of early-stage hormone-negative breast cancer.

INTRODUCTION: The serine/threonine protein kinase ataxia telangiectasia mutated (ATM) is critical in maintaining genomic integrity. Upon DNA double-strand breaks, ATM phosphorylates key downstream proteins including p53 and BRCA1/2, thereby orchestrating complex signaling pathways involved in cell cycle arrest, DNA repair, senescence and apoptosis. Although sporadic mutation of ATM occurs rarely in breast cancer, the status of its protein expression and its clinical significance in breast cancer remain not well established. Our study was designed to investigate the influence of ATM protein in both tumor and cancer-associated stroma on clinical outcome in hormone-positive (HPBC) and hormone-negative (HNBC) early-stage breast cancer (EBC). METHODS: Tissue microarrays (TMAs), containing formalin-fixed, paraffin-embedded resected tumors from two cohorts of patients (HPBC cohort: n=130; HNBC cohort: n=168) diagnosed at the Tom Baker Cancer Centre, Calgary, Canada, were analyzed for ATM protein expression using fluorescence immunohistochemistry (IHC) and automated quantitative analysis (AQUA). ATM expression levels were measured within the tumor as a whole (tATM) as indicated by pan-cytokeratin expression, tumor nuclear compartment (nATM) as indicated by both DAPI and pan-cytokeratin-positive results, and cancer-associated stroma (csATM) as indicated by vimentin-positive and pan-cytokeratin-negative results. ATM expression levels within these compartments were correlated with clinical outcome. RESULTS: While tATM and nATM were significantly lower in tumors compared to normal breast epithelial tissues, csATM was significantly higher than the corresponding normal tissue compartment. In addition, the median expression level of both tATM and nATM were two- to threefold lower (P<0.001) in HNBC than in HPBC. In both HNBC and HPBC cohorts, patients with low tATM, nATM and csATM tumors had significantly poorer survival outcomes than those with a high tATM, nATM and csATM, but this effect was more pronounced in HNBC. A multivariate analysis demonstrates that these biomarkers predict survival independent of tumor size and lymph node status, but only in the HNBC cohort (P<0.001). CONCLUSIONS: Low ATM protein expression in both malignant tumor and stromal compartments likely contributes to the aggressive nature of breast cancer and is an independent prognostic factor associated with worse survival in HNBC patients.