Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data.

BACKGROUND: Laboratory data can provide great value to support research aimed at reducing the incidence, prolonging survival and enhancing outcomes of cancer. Data is characterized by the information it carries and the format it holds. Data captured in Alberta's biomarker laboratory repository is free text, cluttered and rouge. Such data format limits its utility and prohibits broader adoption and research development. Text analysis for information extraction of unstructured data can change this and lead to more complete analyses. Previous work on extracting relevant information from free text, unstructured data employed Natural Language Processing (NLP), Machine Learning (ML), rule-based Information Extraction (IE) methods, or a hybrid combination between them. METHODS: In our study, text analysis was performed on Alberta Precision Laboratories data which consisted of 95,854 entries from the Southern Alberta Dataset (SAD) and 6944 entries from the Northern Alberta Dataset (NAD). The data covers all of Alberta and is completely population-based. Our proposed framework is built around rule-based IE methods. It incorporates topics such as Syntax and Lexical analyses to achieve deterministic extraction of data from biomarker laboratory data (i.e., Epidermal Growth Factor Receptor (EGFR) test results). Lexical analysis compromises of data cleaning and pre-processing, Rich Text Format text conversion into readable plain text format, and normalization and tokenization of text. The framework then passes the text into the Syntax analysis stage which includes the rule-based method of extracting relevant data. Rule-based patterns of the test result are identified, and a Context Free Grammar then generates the rules of information extraction. Finally, the results are linked with the Alberta Cancer Registry to support real-world cancer research studies. RESULTS: Of the original 5512 entries in the SAD dataset and 5017 entries in the NAD dataset which were filtered for EGFR, the framework yielded 5129 and 3388 extracted EGFR test results from the SAD and NAD datasets, respectively. An accuracy of 97.5% was achieved on a random sample of 362 tests. CONCLUSIONS: We presented a text analysis framework to extract specific information from unstructured clinical data. Our proposed framework has shown that it can successfully extract relevant information from EGFR test results.

Development and Validation of a Prognostic Risk Model for Patients with Advanced Melanoma Treated with Immune Checkpoint Inhibitors.

BACKGROUND: Risk stratification tools for patients with advanced melanoma (AM) treated with immune checkpoint inhibitors (ICI) are lacking. We identified a new prognostic model associated with overall survival (OS). PATIENTS AND METHODS: A total of 318 treatment naïve patients with AM receiving ICI were collected from a multi-centre retrospective cohort study. LASSO Cox regression identified independent prognostic factors associated with OS. Model validation was carried out on 500 iterations of bootstrapped samples. Harrel's C-index was calculated and internally validated to outline the model's discriminatory performance. External validation was carried out in 142 advanced melanoma patients receiving ICI in later lines. RESULTS: High white blood cell count (WBC), high lactate dehydrogenase (LDH), low albumin, Eastern Cooperative Oncology Group (ECOG) performance status ≥1, and the presence of liver metastases were included in the model. Patients were parsed into 3 risk groups: favorable (0-1 factors) OS of 52.9 months, intermediate (2-3 factors) OS 13.0 months, and poor (≥4 factors) OS 2.7 months. The C-index of the model from the discovery cohort was 0.69. External validation in later-lines (N = 142) of therapy demonstrated a c-index of 0.65. CONCLUSIONS: Liver metastases, low albumin, high LDH, high WBC, and ECOG≥1 can be combined into a prognostic model for AM patients treated with ICI.

Impact of the COVID-19 pandemic on cancer diagnoses, stage and survival in Alberta.

BACKGROUND: The COVID-19 pandemic is suspected to have affected cancer care and outcomes among patients in Canada. In this study, we evaluated the impact of the state of emergency period during the COVID-19 pandemic (Mar. 17 to June 15, 2020) on cancer diagnoses, stage at diagnosis and 1-year survival in Alberta. METHODS: We included new diagnoses of the 10 most prevalent cancer types from Jan. 1, 2018, to Dec. 31, 2020. We followed patients up to Dec. 31, 2021. We used interrupted time series analysis to examine the impact of the first COVID-19-related state of emergency in Alberta on the number of cancer diagnoses. We used multivariable Cox regression to compare 1-year survival of the patients who received a diagnosis during 2020 after the state of emergency with those who received a diagnosis during 2018 and 2019. We also performed stage-specific analyses. RESULTS: We observed significant reductions in diagnoses of breast cancer (incidence rate ratio [IRR] 0.67, 95% confidence interval [CI] 0.59-0.76), prostate cancer (IRR 0.64, 95% CI 0.56-0.73) and colorectal cancer (IRR 0.64, 95% CI 0.56- 0.74) and melanoma (IRR 0.57, 95% CI 0.47-0.69) during the state of emergency period compared with the period before it. These decreases largely occurred among early-stage rather than late-stage diagnoses. Patients who received a diagnosis of colorectal cancer, non-Hodgkin lymphoma and uterine cancer in 2020 had lower 1-year survival than those diagnosed in 2018; no other cancer sites had lower survival. INTERPRETATION: The results from our analyses suggest that health care disruptions during the COVID-19 pandemic in Alberta considerably affected cancer outcomes. Given that the largest impact was observed among early-stage cancers and those with organized screening programs, additional system capacity may be needed to mitigate future impact.

Association Between Endoscopist Specialty and Colonoscopy Quality: A Systematic Review and Meta-analysis.

BACKGROUND & AIMS: Colonoscopy quality indicators provide measurable assessments of performance, but significant provider-level variations exist. We performed a systematic review and meta-analysis to assess whether endoscopist specialty is associated with adenoma detection rate (ADR) - the primary outcome - or cecal intubation rate, adverse event rates, and post-colonoscopy colorectal cancer rates. METHODS: We searched EMBASE, Google Scholar, MEDLINE, and the Cochrane Central Registry of Controlled Trials from inception to December 14, 2020. Two reviewers independently screened titles and abstracts. Citations underwent duplicate full-text review, with disagreements resolved by a third reviewer. Data were abstracted in duplicate. The DerSimonian and Laird random effects model was used to calculate pooled odds ratios (ORs) with respective 95% confidence intervals (CIs). Risk of bias was assessed using Risk of Bias in Non-randomised Studies of Interventions. RESULTS: Of 11,314 citations, 36 studies representing 3,500,832 colonoscopies were included. Compared with colonoscopies performed by gastroenterologists, those by surgeons were associated with lower ADRs (OR, 0.81; 95% CI, 0.74-0.88) and lower cecal intubation rates (OR, 0.76; 95% CI, 0.63-0.92). Compared with colonoscopies performed by gastroenterologists, those by other (non-gastroenterologist, non-surgeon) endoscopists were associated with lower ADRs (OR, 0.91; 95% CI, 0.87-0.96), higher perforation rates (OR, 3.02; 95% CI, 1.65-5.51), and higher post-colonoscopy colorectal cancer rates (OR, 1.23; 95% CI, 1.14-1.33). Substantial to considerable heterogeneity existed for most analyses, and overall certainty in the evidence was low according to the Grading of Recommendations, Assessment, Development, and Evaluations framework. CONCLUSION: Colonoscopies performed by surgeons or other endoscopists were associated with poorer quality metrics and outcomes compared with those performed by gastroenterologists. Targeted quality improvement efforts may be warranted.

The efficacy of chemopreventive agents on the incidence of colorectal adenomas: A systematic review and network meta-analysis.

Colorectal cancer (CRC) is the fourth most common cancer and third leading cause of cancer-related death worldwide. Use of chemopreventive agents (CPAs) to reduce the incidence of precursor colorectal adenomas could lower the future burden of CRC. Many classes of potential CPAs have been investigated. To identify the most effective CPAs, we conducted a systematic review and a network meta-analysis (NMA). An electronic search was performed through August 2020 to identify all randomized controlled trials (RCTs) assessing the efficacy of CPAs in reducing the incidence of colorectal adenomas at the time of surveillance colonoscopy among patients who had previously undergone polypectomy during an index colonoscopy. In total, 33 RCTs were included in the NMA, which was conducted under a Bayesian inference framework. Random effects models were used with adjustment for follow-up length and control group event rates to yield relative risks (RRs) and 95% credible intervals (CrIs). Our full network consisted of 13 interventions in addition to a placebo arm. Of 20,925 included patients, 7766 had an adenoma. Compared to placebo, the combination of difluoromethylornithine (DFMO) + Sulindac (RR 0.24, CrI 0.10-0.55) demonstrated a protective effect, while aspirin had a RR of 0.77 (CrI 0.60-1.00), celecoxib 800 mg had a RR of 0.56 (CrI 0.31-1.01) and metformin had a RR of 0.56 (CrI 0.22-1.39). Our results suggest that select CPAs may be efficacious in preventing the development of adenomas. Further studies are needed to identify those patients most likely to benefit and the minimum effective dosages of CPAs.

Development and validation of a risk prediction model for high-risk adenomas at the time of first screening colonoscopy among screening aged Canadians.

The aim of this study was to develop a risk prediction model for high risk adenomas (HRAs) detected at screening colonoscopy based on readily available participant information. The cohort consisted of 3035 participants aged 50 to 74 years with no history of cancer who underwent a primary screening colonoscopy at a centralized colon cancer screening centre between 2008 and 2016. A multivariable logistic regression model was created using CRC risk factors identified from prior research. Model covariates were collected from a baseline questionnaire and included participant demographics (age and sex), lifestyle parameters (body mass index, alcohol, smoking, and vitamin D supplement use) and medical history (family history of CRC and diabetes). Mean participant age was 58.8 years, and 54.7% were male. 249 participants with HRAs were identified (8.2%). An adjusted c-statistic of 0.67 was calculated, and a specificity and negative predictive value of 97.2% (95% CI: 96.5-97.8) and 92.5% (95% CI: 92.2-92.8) for the detection of HRAs, respectively, were achieved using 20% predicted probability as a high-risk threshold. However, only a sensitivity of 12.1% (95% CI: 8.3-16.8) was achieved. Our model has moderate predictive ability, with strengths in being able to rule out those with an absence of HRAs on screening colonoscopy. Maximizing screening efficiency through improved risk prediction can enhance resource allocation. Ultimately, this model has the potential to improve patient care by reducing unnecessary colonoscopies, limiting this invasive procedure to those most likely to have significant findings.

Symptom burden in patients with common cancers near end-of-life and its associations with clinical characteristics: a real-world study.

BACKGROUND: Patients dying with cancer can experience various physical and psychological symptoms. We aimed to determine the type and severity of symptoms within the last 6 months of life in a large real-world cohort of patients with cancer. METHODS: We examined prospectively collected patient-reported outcomes of patients with lung, colorectal, breast, prostate or pancreatic cancer using the revised Edmonton Symptom Assessment System (ESASr) questionnaire from a large province in Canada from 2016 to 2017. The ESASr was categorized into physical and psychological symptom subscores and total symptom score, and each was classified as none to mild (0-3) or moderate to severe (4-10) based on intensity. Multivariable logistic regression analyses were performed to evaluate the relationship between clinical characteristics and symptom scores. RESULTS: We identified 1159 patients eligible for analysis, of whom 52.2% were men and median age was 68 years. There were 613, 192, 149, 111 and 94 patients with lung, colorectal, breast, prostate and pancreatic cancer, respectively. While approximately half of patients reported moderate to severe physical symptom subscores and total symptom scores, only one-third reported moderate to severe psychological subscores. On multivariable logistic regression analyses, women were more likely to report moderate to severe physical (odds ratio [OR], 1.52; 95% confidence interval [CI], 1.08-2.12; P = 0.016), psychological (OR, 1.60; 95% CI, 1.14-2.26; P = 0.006) and total symptom scores (OR, 1.80; 95% CI, 1.28-2.51; P = 0.001). Patients with lung cancer were also more likely to report moderate to severe physical and psychological subscores (OR, 1.95; 95% CI, 1.28-2.96; P = 0.002 and OR, 1.78; 95% CI, 1.13-2.81; P = 0.013) and total symptom scores (OR, 1.83; 95% CI, 1.20-2.81; P = 0.005). Finally, those closer to death were more likely to report moderate to severe physical symptom subscores (OR, 2.07; 95% CI, 1.33-3.23; P = 0.001) and total symptom scores (OR, 2.29; 95% CI, 1.46-3.60; P < 0.001), but not psychological symptom scores (OR, 1.34; 95% CI, 0.84-2.14; P = 0.210). CONCLUSIONS: There is significant symptom burden in patients with cancer near the end-of-life. Further, physical symptoms appear to be more intense than psychological symptoms. Symptom-directed care is still needed to improve the quality of end-of-life.

Associations between baseline symptom burden as assessed by patient-reported outcomes and overall survival of patients with metastatic cancer.

BACKGROUND: Serial symptom assessments using patient-reported outcomes may be challenging to implement in routine clinical practices. We aimed to determine if a single measurement of symptom burden at the time of metastatic diagnosis is associated with survival. METHODS: We examined baseline patient-reported outcomes (within 90 days of diagnosis) of patients newly diagnosed with metastatic breast, lung, colorectal, or prostate cancer using the revised Edmonton Symptom Assessment System (ESASr) questionnaire. The ESASr was categorized into physical, psychological, and total symptom domains whereby scores were classified as none to mild (0-3) or moderate to severe (4-10). Multivariable Cox proportional hazards models were constructed to evaluate the effect of baseline symptom scores on overall survival. RESULTS: We identified 1316 patients eligible for analysis. There were 181, 601, 240, and 294 patients with breast, lung, colorectal, and prostate cancer, respectively. Approximately one-quarter of all patients reported moderate to severe physical, psychological, and total symptom subscores. On multivariable Cox regression analysis, older age (P < 0.001), male sex (P = 0.002), primary lung cancer (P < 0.001), and smoking in the previous month (P = 0.007) were predictive of inferior overall survival as were baseline moderate to severe physical (hazard ratio, 1.49; 95% confidence interval, 1.16-1.90; P = 0.002) and total symptom subscores (hazard ratio, 1.38; 95% confidence interval, 1.06-1.81; P = 0.017). CONCLUSIONS: A single assessment of baseline symptom burden using the ESASr in patients with metastatic cancer has significant prognostic value. This may represent a feasible first step towards routine collection of patient-reported outcomes in real-world settings where serial symptom measurements can be challenging to implement.

Patient-Reported Symptom Burden Near the End of Life in Patients With Gynaecologic Cancers.

OBJECTIVE: There are limited data on patient-reported outcomes near the end of life in patients with gynaecologic cancers. This study aimed to assess the symptom burden in the last 6 months of life in a real-world cohort. METHODS: Patients diagnosed with metastatic gynaecologic malignancies from 2016 to 2019 who completed the revised Edmonton Symptom Assessment System (ESASr) questionnaire within 6 months of death in a large Canadian province were identified. Patient-reported symptom scores were categorized as none to mild (0-3) and moderate to severe (4-10). Individual symptoms were subsequently grouped into physical, psychological, and total subscores. The severity of symptoms was further analyzed for any associations with age, time to death, and primary tumour site (ovarian vs. uterocervical and vulvovaginal). RESULTS: We identified 107 patients with gynaecologic malignancies including 59 ovarian, 29 uterocervical, and 19 vulvovaginal cancers. The median ages at diagnosis and questionnaire completion were 64 and 65 years, respectively. The median time from completing the ESASr questionnaire to death was 65 days. Overall, physical and psychological symptoms were moderate to severe in 57.9% and 40.2% of patients, respectively. Among the individual symptoms, tiredness was the most commonly reported moderate to severe symptom (74.9%), while shortness of breath was least commonly reported (31.6%). While physical (P < 0.001) and total symptom (P = 0.009) subscores were more likely to be moderate to severe in intensity as death approached, the psychological subscore (P = 0.744) had no relationship with time to death. Longer time to death was predictive of lower physical (P = 0.002) and total symptom (P = 0.002) subscores, while a primary uterocervical cancer site was associated with a lower psychological symptom subscore (P = 0.042). CONCLUSIONS: In the real-world setting, unique symptom trajectories can emerge for patients with gynaecologic cancer near the end of life. Knowledge of these specific symptom patterns can help inform the development and delivery of targeted palliative interventions to improve quality of life for these patients.

Association Between Endoscopist Annual Procedure Volume and Colonoscopy Quality: Systematic Review and Meta-analysis.

BACKGROUND & AIMS: In addition to monitoring adverse events (AEs) and post-colonoscopy colorectal cancers (PCCRC), indicators for assessing colonoscopy quality include adenoma detection rate (ADR) and cecal intubation rate (CIR). It is unclear whether there is an association between annual colonoscopy volume and ADR, CIR, AEs, or PCCRC. METHODS: We searched publication databases through March 2019 for studies assessing the relationship between annual colonoscopy volume and outcomes, including ADR, CIR, AEs, or PCCRC. Pooled odds ratios (ORs) were calculated using DerSimonian and Laird random effects models. Sensitivity analyses were performed to assess for potential methodological or clinical factors associated with outcomes. RESULTS: We performed a systematic review of 9235 initial citations, generating 27 retained studies comprising 11,276,244 colonoscopies. There was no association between procedural volume and ADR (OR, 1.00; 95% CI, 0.98-1.02 per additional 100 annual procedures). CIR improved with each additional 100 annual procedures (OR, 1.17; 95% CI, 1.08-1.28). There was a non-significant trend toward decreased overall AEs per additional 100 annual procedures (OR, 0.95; 95% CI, 0.90-1.00). There was considerable heterogeneity among most analyses. CONCLUSIONS: In a systematic review and meta-analysis, we found higher annual colonoscopy volumes to correlate with higher CIR, but not with ADR or PCCRC. Trends toward fewer AEs were associated with higher annual colonoscopy volumes. There are few data available from endoscopists who perform fewer than 100 annual colonoscopies. Studies are needed on extremes in performance volumes to more clearly elucidate associations between colonoscopy volumes and outcomes.

Network meta analysis of first-line therapy for advanced EGFR mutation positive non-small-cell lung cancer: updated overall survival.

Aim: To update overall survival (OS) results from a previous network meta analysis comparing the relative clinical efficacy of epidermal growth factor receptor-targeted tyrosine kinase inhibitors (EGFR TKIs) for EGFR mutation positive (EGFR+) advanced non-small-cell lung cancer (NSCLC). Materials & methods: A Bayesian network meta analysis was conducted using updated/mature randomized controlled trial OS results in response to first-line EGFR TKI therapies. Results: Dacomitinib showed a numerical improvement of OS relative to other EGFR TKIs: afatinib (hazard ratio [HR]: 0.87; 95% credible interval [CrI]: 0.61-1.24), erlotinib (HR: 0.79; 95% CrI: 0.44-1.42), gefitinib (HR: 0.75; 95% CrI: 0.59-0.95) and osimertinib (HR: 0.94; 95% CrI: 0.68-1.29). Conclusion: Dacomitinib should be considered as a first-line treatment option for patients diagnosed with advanced EGFR+ NSCLC.

Patient-reported symptom burden and supportive care needs at cancer diagnosis: a retrospective cohort study.

PURPOSE: Patient-reported outcomes (PROs) are used to assess patients' symptoms and supportive care needs. While PROs are increasingly employed in clinical practice, research utilizing these data remains limited. Our goal was to evaluate PROs from a provincial cancer program. METHODS: A retrospective, population-based cohort study using administrative health data of patients in Alberta, Canada, diagnosed with cancer between January 1, 2016, and October 23, 2017. Adults who completed PROs (Edmonton Symptom Assessment System, ESAS) and supportive care needs inventory (Canadian Problem Checklist)) within ± 60 days of diagnosis were included. Patients were stratified by tumor types (breast, colorectal, lung, prostate, hematological, or other). Descriptive statistics were used to characterize symptom burden and supportive care needs. Multivariate logistic regression was used to evaluate factors associated with higher symptom severity. RESULTS: We included 1310 patients (mean age 64 years; 51% female), the majority of whom had breast (19%), lung (25%), or other cancers (26%). For the cohort, severity of symptoms based on ESAS was low, but prevalence of specific symptoms was high including tiredness (84%), anxiety (60%), pain (60%), and low well-being (80%). Seventy percent of the cohort reported at least one supportive care need. The highest-ranking problems were fears and worries and needing information about illness/treatment. There were differences across tumor types with respect to symptoms and supportive care needs. Comorbidity and having a high number of supportive care needs were associated with higher symptom severity. DISCUSSION: Our results underscore the need to develop and implement tumor-specific supportive care interventions.

Patient-level factors associated with chronic opioid use in cancer: a population-based cohort study.

PURPOSE: Concerns around chronic opioid use (COU), misuse, and harms have led to increased scrutiny of opioid prescribing in oncology. There is lack of research examining patient-level factors associated with COU. Our aim was to examine patient-level factors associated with COU in newly diagnosed cancer patients. METHODS: Population-based retrospective cohort study using administrative health data of patients in Alberta, Canada, diagnosed between February 2016 and October 2017. Adult cancer patients who completed a symptom survey within ± 60 days of diagnosis were included. Patients were divided into two groups: COU (defined as continuous opioid prescriptions for at least 90 days post-diagnosis) and non-chronic opioid use (NCOU). Logistic regression was used to evaluate factors associated with COU. RESULTS: We included 694 patients (mean age 65 years; 51% female). Most had breast (20%), colorectal (13%), and lung (33%) cancers. Of the 14% with COU, 79% were opioid naïve at diagnosis. Those in the COU group were more often diagnosed with advanced cancer (66% versus 40%), had lung cancer (47%), and were opioid tolerant (> 90 days of continuous opioids within one-year pre-diagnosis). A total of 64% of COU versus 27% of NCOU had moderate to severe pain at diagnosis (p < 0.001). Irrespective of treatment type or stage, those with moderate to severe pain, were opioid tolerant at diagnosis, or had multiple prescribers were at greater risk for COU. CONCLUSIONS: Specific patient groups were at increased risk of COU and should be the focus of adaptive prescribing approaches to ensure that opioid use is appropriate.

Endoscopic ultrasound-guided transmural approach versus ERCP-guided transpapillary approach for primary decompression of malignant biliary obstruction: a meta-analysis.

BACKGROUND: Primary decompression in patients with malignant biliary obstruction can be achieved via endoscopic retrograde cholangiopancreatography (ERCP) with transpapillary stenting, or, more recently, via transmural endoscopic ultrasound-guided biliary drainage (EUS-BD). It is unclear whether either approach is superior in terms of clinical success or adverse events in the primary setting. METHODS: A comprehensive systematic electronic search was performed for studies comparing EUS-BD and ERCP as the primary approach with respect to clinical success and any other outcome(s). Pooled relative risks (RRs) and weighted mean differences were obtained as appropriate using DerSimonian and Laird random effects models. Sensitivity analyses were also performed. RESULTS: 5 out of 776 studies with a total of 396 patients were included. Overall clinical success was not significantly different between EUS-BD and ERCP (RR 0.98, 95 % confidence interval [CI] 0.93 to 1.03). There was no significant difference in overall adverse events (RR 0.84, 95 %CI 0.35 to 2.01), though results suggested that EUS-BD may be associated with a reduced risk of pancreatitis (RR 0.22, 95 %CI 0.05 to 1.02). There were no significant differences between EUS-BD and ERCP in terms of procedure time or the risk of stent occlusion. CONCLUSIONS: EUS-BD had similar clinical success rates and occlusion rates to ERCP in the primary decompression of malignant biliary obstruction from meta-analysis including a modest number of patients. EUS-BD may be a practical alternative to the ERCP-guided approach in such patients, but further well-designed prospective studies with larger numbers of patients are required to more clearly delineate potential differences in adverse events and cost.

Bayesian Networks for Risk Prediction Using Real-World Data: A Tool for Precision Medicine.

OBJECTIVE: The fields of medicine and public health are undergoing a data revolution. An increasing availability of data has brought about a growing interest in machine-learning algorithms. Our objective is to present the reader with an introduction to a knowledge representation and machine-learning tool for risk estimation in medical science known as Bayesian networks (BNs). STUDY DESIGN: In this article we review how BNs are compact and intuitive graphical representations of joint probability distributions (JPDs) that can be used to conduct causal reasoning and risk estimation analysis and offer several advantages over regression-based methods. We discuss how BNs represent a different approach to risk estimation in that they are graphical representations of JPDs that take the form of a network representing model random variables and the influences between them, respectively. METHODS: We explore some of the challenges associated with traditional risk prediction methods and then describe BNs, their construction, application, and advantages in risk prediction based on examples in cancer and heart disease. RESULTS: Risk modeling with BNs has advantages over regression-based approaches, and in this article we focus on three that are relevant to health outcomes research: (1) the generation of network structures in which relationships between variables can be easily communicated; (2) their ability to apply Bayes's theorem to conduct individual-level risk estimation; and (3) their easy transformation into decision models. CONCLUSIONS: Bayesian networks represent a powerful and flexible tool for the analysis of health economics and outcomes research data in the era of precision medicine.

BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses.

BACKGROUND: Several reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines. RESULTS: To better facilitate the conduct and reporting of NMAs, we have created an R package called "BUGSnet" (Bayesian inference Using Gibbs Sampling to conduct a Network meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines. CONCLUSION: BUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.

Dose-response effects of exercise on bone mineral density and content in post-menopausal women.

Exercise is one of the most widely used non-pharmacological strategies to prevent bone resorption during menopause. Given the detrimental consequences of bone demineralization, the purpose of this study was to examine the effects of prescribing different exercise volumes on bone mineral density and content in previously inactive, post-menopausal women during a 12-month intervention and 1 year after intervention completion. Four hundred post-menopausal women were randomized to either 150 min/wk (MODERATE dose group) or 300 min/wk (HIGH dose group) of aerobic exercise. Total bone mineral density (g/cm2 ) and bone mineral content (g) were assessed at baseline, 12 months (end of the intervention) and 24 months (follow-up) using whole body dual-energy X-ray absorptiometry. At 12 months, mean bone mineral density among women in the HIGH dose group was estimated to be 0.006 g/cm2 (95% CI: 0.001-0.010; P = 0.02) higher than that of women randomized to the MODERATE dose group. At 24 months, the mean difference between groups remained statistically significant, indicating higher mean bone mineral density among women in the HIGH dose group (0.007 g/cm2 ; 0.001-0.001; P = 0.04). No significant differences between groups were found at any time point for bone mineral content. In an exploratory analysis, women who completed more min/wk of impact exercises had significantly higher mean levels of bone mineral density at 12 months compared to baseline (0.006 g/cm2 , 95% CI: 0.006-0.012; P = 0.03). These findings suggest that higher volumes of exercise, especially impact exercise, lead to a smaller decline in total bone mineral density, which may remain following intervention completion.

Endogenous sex hormone exposure and repetitive element DNA methylation in healthy postmenopausal women.

PURPOSE: Epigenetic mechanisms may help to explain the complex and heterogeneous relation between sex hormones and cancer. Few studies have investigated the effects of sex hormones on epigenetic markers related to cancer risk such as levels of methylation within repetitive DNA elements. Our objective was to describe the association between endogenous sex hormone exposure and levels of LINE-1 and Alu methylation in healthy postmenopausal women. METHODS: We nested a cross-sectional study within the Alberta Physical Activity and Breast Cancer Prevention Trial (2003-2006). Study participants consisted of healthy postmenopausal women who had never been diagnosed with cancer (n = 289). Sex hormone exposures included serum concentrations of estradiol, estrone, testosterone, androstenedione, and sex hormone-binding globulin. We estimated the participants' lifetime number of menstrual cycles (LNMC) as a proxy for cumulative exposure to ovarian sex hormones. Buffy coat samples were assessed for DNA methylation. Linear regression was used to model the associations of interest and to control for confounding. RESULTS: Both estradiol and estrone had a significant positive dose-response association with LINE-1 methylation. LNMC was associated with both LINE-1 and Alu methylation. Specifically, LNMC had a non-linear "U-shaped" association with LINE-1 methylation regardless of folate intake and a negative linear association with Alu methylation, but only amongst low folate consumers. Androgen exposure was not associated with either outcome. CONCLUSION: Current and cumulative estrogen exposure was associated with repetitive element DNA methylation in a group of healthy postmenopausal women. LINE-1 and Alu methylation may be epigenetic mechanisms through which estrogen exposure impacts cancer risk.

Plasmonic gold nanostars as optical nano-additives for injection molded polymer composites.

Nanoscale engineering of noble metal particles has provided numerous material configurations to selectively confine and manipulate light across the electromagnetic spectrum. Transitioning these materials to a composite form while maintaining the desired resonance properties has proven challenging. In this work, the successful integration of plasmon-focusing gold nanostars (GNSs) into polymer nanocomposites (PNCs) is demonstrated. Tailored GNSs are produced with over a 90% yield and methods to control the branching structures are shown. A protective silica capping shell is employed on the nanomaterials to facilitate survivability in the high temperate/high shear processing parameters to create optically-tuned injection molded PNCs. The developed GNS PNCs possess dichroic scattering and absorption behavior, opening up potential applications in the fields of holographic imaging, optical filtering and photovoltaics.

Sensing with prism-based near-infrared surface plasmon resonance spectroscopy on nanohole array platforms.

Nanohole arrays exhibit unique surface plasmon resonance (SPR) characteristics according to hole periodicity, diameter, and excitation wavelength (λ(SPR)). This contribution investigates the SPR characteristics and surface sensitivity of various nanohole arrays with the aim of tuning the parameters for optimal sensing capability. Both the Bragg surface plasmons (SPs) arising from diffraction by the periodic holes and the traditional propagating SPs are characterized with emphasis on sensing capability of the propagating SPs. Several trends in bulk sensitivity and penetration depth were established, and the surface sensitivity was calculated from bulk sensitivity and penetration depth of the SPs for different analyte thicknesses. Increased accuracy and precision in penetration depth values were achieved by incorporating adsorbate effects on substrate permittivity. The optimal nanohole array conditions for highest surface sensitivity were determined (820 nm periodicity, 0.27 diameter/periodicity, and λ(SPR) = 1550 nm), which demonstrated an increase in surface sensitivity for the 10 nm analyte over continuous gold films at their optimal λ(SPR) (1300 nm) and conventional visible λ(SPR) (700 nm).