Browsing by Author "Brenner, Darren"
Now showing 1 - 10 of 10
Results Per Page
Sort Options
Item Open Access Ancestry and frequency of genetic variants in the general population are confounders in the characterization of germline variants linked to cancer(2020-05-06) Bobyn, Anna; Zarrei, Mehdi; Zhu, Yuankun; Hoffman, Mary; Brenner, Darren; Resnick, Adam C; Scherer, Stephen W; Gallo, MarcoAbstract Background Pediatric high-grade gliomas (pHGGs) are incurable malignant brain cancers. Clear somatic genetic drivers are difficult to identify in the majority of cases. We hypothesized that this may be due to the existence of germline variants that influence tumor etiology and/or progression and are filtered out using traditional pipelines for somatic mutation calling. Methods In this study, we analyzed whole-genome sequencing (WGS) datasets of matched germlines and tumor tissues to identify recurrent germline variants in pHGG patients. Results We identified two structural variants that were highly recurrent in a discovery cohort of 8 pHGG patients. One was a ~ 40 kb deletion immediately upstream of the NEGR1 locus and predicted to remove the promoter region of this gene. This copy number variant (CNV) was present in all patients in our discovery cohort (n = 8) and in 86.3% of patients in our validation cohort (n = 73 cases). We also identified a second recurrent deletion 55.7 kb in size affecting the BTNL3 and BTNL8 loci. This BTNL3–8 deletion was observed in 62.5% patients in our discovery cohort, and in 17.8% of the patients in the validation cohort. Our single-cell RNA sequencing (scRNA-seq) data showed that both deletions result in disruption of transcription of the affected genes. However, analysis of genomic information from multiple non-cancer cohorts showed that both the NEGR1 promoter deletion and the BTNL3–8 deletion were CNVs occurring at high frequencies in the general population. Intriguingly, the upstream NEGR1 CNV deletion was homozygous in ~ 40% of individuals in the non-cancer population. This finding was immediately relevant because the affected genes have important physiological functions, and our analyses showed that NEGR1 expression levels have prognostic value for pHGG patient survival. We also found that these deletions occurred at different frequencies among different ethnic groups. Conclusions Our study highlights the need to integrate cancer genomic analyses and genomic data from large control populations. Failure to do so may lead to spurious association of genes with cancer etiology. Importantly, our results showcase the need for careful evaluation of differences in the frequency of genetic variants among different ethnic groups.Item Open Access BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses(2019-10-22) Béliveau, Audrey; Boyne, Devon J; Slater, Justin; Brenner, Darren; Arora, PaulAbstract 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.Item Open Access Epidemiology of Alcohol-Related Hepatitis, Alcohol-Related Cirrhosis, and Non-Alcohol-Related Cirrhosis in Alberta, Canada: An Administrative Data Validation and Population-Based Study(2024-07-22) Swain, Liam Andrew; Shaheen, Abdel-Aziz; Godley, Jenny; McLaren, Lindsay; Tang, Karen; Brenner, DarrenBackground: Population-based studies evaluating the epidemiology of chronic liver diseases rely on accurate case definitions. This thesis aimed to develop new coding algorithms for alcohol- (AC) and non-alcohol-related cirrhosis (NAC) to use alongside a previously validated alcohol-related hepatitis (AH) coding algorithm to examine population-level AC, NAC, and AH hospitalization rate trends from 2012-2022, in Alberta, Canada. Methods: Using a randomly selected cohort of 700 admissions with diagnostic codes for alcohol- and cirrhosis-related conditions from the 2008-2022 Calgary Discharge Abstract Database (DAD), we validated (using electronic medical record review) newly developed and commonly used AC/NAC case definitions. The newly validated coding algorithms were used to select all adult AC/NAC/AH hospitalizations in the Alberta DAD from 2012-2022. All admissions were postal code matched to the 2016 Alberta Census data aggregated to the DA level. Temporal trends in annual sex/age-standardized hospitalization rates per 100,000 Alberta population were examined using Joinpoint analysis stratified by sex, age, area-level income quartile, and rural/urban residency. Results: Our new AC algorithm selecting codes for AC, alcohol-related hepatic failure, or alcohol use disorder (AUD) with a decompensated cirrhosis condition or NAC code provided higher accuracy than previous methods (AUROC 0.88 vs. 0.50-0.81, p<0.001). Our new NAC algorithm, excluding AUD codes and selecting for a NAC or a primary decompensated cirrhosis condition code provided higher accuracy than previous approaches (AUORC 0.87 vs. 0.58-0.76, p<0.001). Using these new algorithms, we determined that between 2012-2022, AC hospitalization rates increased only for urban females, those <35 years of age, and for those living in regions with the highest area-level income. AH hospitalization rates increased predominantly for people <35 years and for females. During the COVID-19 pandemic AC/AH hospitalization rates significantly increased for those from rural and low-income areas. NAC hospitalization rates were not impacted by the COVID-19 pandemic, only increasing in people ≥65 years. Conclusions: The new case definitions exhibit enhanced AC/NAC identification accuracy compared to previous methods. Over the past decade, AC/AH hospitalizations increased in younger and female populations, and NAC hospitalizations steadily increased in older populations.Item Open Access Examining and predicting outcomes among early-onset breast cancer patients in Alberta using real-world and genomic data(2023-11-23) Basmadjian, Robert Barkev; Brenner, Darren; Cheung, Winson; Quan, May Lynn; Lupichuk, Sasha; Xu, YuanBackground: It is well accepted patients with early-onset breast cancer (EoBC), defined by a diagnosis <40 years of age, are at greater risks of recurrence and mortality compared to later-onset cases (≥40 years). However, robust evidence of tailored treatment approaches in EoBC is lacking. This thesis intersected causal inference methodology, outcomes prediction research, and bioinformatics to better understand the effectiveness of real-world treatments and decision support tools in EoBC, as well as discover biological drivers of poor prognosis. Methods: Three manuscripts were produced using population-based data of adult breast cancer diagnoses <40 years in Alberta from 2004 to 2020 and whole-exome sequence data from 100 tumour samples in this population. In Manuscript One, we described treatment patterns of ovarian function suppression (OFS) and applied the target trial emulation framework to estimate two treatments effects: 1) 2-year per-protocol effect of tamoxifen alone (TAM) vs. TAM + OFS (T-OFS) vs. aromatase inhibitor + OFS (AI-OFS); and 2) the effect of remaining on hormone therapy + OFS (H-OFS) for ≥2 years vs. <2 years on recurrence-free survival (RFS). In Manuscript Two, we assessed the performance of PREDICT v2.1 for predicting 10-year all-cause mortality in EoBC and developed 10-year mortality prediction models using machine learning. In Manuscript Three, we characterize somatic mutational signatures in 100 EoBC tumour samples and examine their association with clinicopathological variables and survival outcomes. Results: In a target trial that included 2647 premenopausal hormone receptor-positive breast cancer patients, RFS tended to be better in the AI-OFS group (HR=0.76; 95% CI: 0.41-1.37) and T-OFS group (HR=0.87; 95% CI: 0.50-1.45) compared to TAM. Patients on H-OFS for ≥ 2 years had significantly better RFS compared to those on H-OFS for <2 years (HR=0.69; 95% CI:0.54-0.90). In data from 1414 EoBC patients, PREDICT showed good discrimination (AUC=0.76) but tended to overestimate 10-year mortality in patients with high predicted risk. Building a 10-year mortality prediction model on EoBC patient data using penalized multivariable Cox regression showed better discrimination and calibration statistics versus using random survival forests. Among 100 EoBC tumour samples, we extracted five single-base substitution (SBS) and two insertion-deletion signatures. The SBS13-like signature was more common in the HER2 subtype. Higher than median expression of the SBS13-like signature may be associated with better RFS (HR=0.29; 95% CI: 0.08-1.06). Conclusions: These investigations contribute knowledge of tailored approaches in the clinical management of EoBC in Alberta. Our findings provide clearer understandings of the effectiveness of real world treatments and the performance of routinely used prediction models in EoBC. We also provide insights on how additional routinely collected variables and novel mutational variables may improve outcome prediction.Item Embargo The Impact of Sex on Survival in Patients with Non-Small Cell Lung Cancer(2023-01-16) Ford-Sahibzada, Chelsea A.; Peters, Cheryl; Brenner, Darren; Cheung, Winson; Hao, Desiree; Ezeife, DoreenBackground Lung cancer is the leading cause of cancer-related mortality in Canada and globally. Non-small cell lung cancer (NSCLC) is the most common histological subtype of the disease in Canada, with several known prognostic factors. There is growing evidence of the role of sex in NSCLC survival, which is of great clinical and population health interest. The aim of this study was to assess the impact of sex on survival in a real-world population of Canadian NSCLC patients. Methods Retrospective cohort studies were completed using real-world data from the Glans-Look Lung Cancer Research database (GLR). The analyses included patients diagnosed with NSCLC between 2010 and 2020 in Alberta, Canada. The primary study analyzed 10,849 NSCLC patients, where the secondary study analyzed 627 NSCLC patients who tested positive for specific biomarkers and were treated with targeted or immunotherapy. Descriptive statistics were used for cohort characterization, with basic survival analyses completed with Kaplan-Meier estimates and log rank tests. Cox proportional hazards models were utilized for univariable and multivariable analyses. Results In the primary analysis, there was a significant association between male sex and increased hazard of death. The unadjusted and adjusted hazard ratios (HR) for male sex were 1.32 (95% CI 1.26-1.37) and 1.28 (95% CI 1.23-1.34), respectively. The effect of sex remained among advanced stage patients (Stage 4 adjusted HR: 1.26, 95% CI: 1.19 – 1.33). In the secondary analysis, there was no survival differences by sex for the total, ALK mutated, and PD-L1 high expression cohorts. The EGFR cohort found a crude HR for male sex of 1.24 (95% CI: 1.01 – 1.54), but the significance of the association disappeared in the adjusted model 1.30 (95% CI: 0.94 – 1.82). Conclusions In this population-based Canadian cohort, females with NSCLC tended to have longer survival than males with NSCLC, after accounting for the effect of known prognostic factors. There is suggestion of differences in this association based on biomarker status. Future research should focus on examining potential biological and behavioural based explanations for the female survival advantage in NSCLC.Item Open Access Influence of dietary antioxidant and oxidant intake on leukocyte telomere length(2017) Mickle, Alexis Tory; Friedenreich, Christine Marthe; Brenner, Darren; Beattie, Tara; Williamson, TylerBackground: Telomeric DNA is highly susceptible to oxidative damage, and dietary habits may impact telomere attrition rates through the mediation of oxidative stress and chronic inflammation. Objectives: To examine the association between both the Dietary Inflammatory Index 2010 (DII) and the Alternative Healthy Eating Index 2010 (AHEI) with relative Leukocyte Telomere Length. Design: We conducted a cross-sectional analysis using baseline data from 301 healthy, inactive post-menopausal women. Diet quality was estimated using DII and AHEI scores derived from food frequency questionnaire data. LTL was measured using qPCR. Associations were examined using multivariable adjusted linear regression. Results: No statistically significant associations were detected between AHEI (p=0.20) or DII (p=0.91) and LTL in multivariable adjusted models. Conclusions: AHEI or DII scores were not related to LTL in this population. Future research is warranted to enhance understanding regarding the molecular processes involved in the relations between diet, telomere length and chronic disease risk.Item Open Access Predicting the Risk of Post Endoscopic Retrograde Cholangiopancreatography Pancreatitis(2023-07) Meng, Zhao Wu; Forbes, Nauzer; Brenner, Darren; Heitman, SteveBackground Post- endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) can lead to significant morbidity and even mortality. The aim of this study was to develop a PEP prediction model using easily accessible patient- and procedure-related variables. Methods Using a multi center prospective ERCP registry, we conducted logistic regression using stepwise selection on several patient- and procedure-related variables that were determined a priori. Variables were included or excluded based on an initial alpha cut-off of 0.2. The final model was based on a combination of Bayesian information criterion (BIC) and Akaike's information criterion (AIC) performance, as well as on the inclusion of variables deemed to be of clinical relevance, while maintaining face validity. All available data was used for model development, with subsequent internal validation performed on bootstrapped data using 10-fold cross validation. Results From September 1, 2019 to January 16, 2022, 3021 ERCP procedures were enrolled and included in our study. There were 151 (5.0%) cases of PEP. Variables included in the final model were patient sex, patient age, pancreatic duct cannulation, native papilla status, presence of precut sphincterotomy, cannulation time, presence of biliary stricture, and pancreatic duct stenting. The final model had an AIC, BIC, and receiver operating characteristic (ROC) curve of 822.28, 886.77, and 0.79, respectively. Bootstrapped data using 800 replicates revealed a C-statistic of 0.78 and expected to observed (E:O) ratio of 1.003. Conclusion This study successfully established and internally validated a promising PEP predictive model using easily obtainable variables that are known at baseline or observed during the ERCP procedure. The model achieved an area under the curve of 0.79. External validation is required prior to clinical use.Item Open Access Staying in Motion: Using Technology to Support Physical Activity Maintenance in Exercise Oncology(2023-05-10) Ester, Manuel; Culos-Reed, Nicole; McDonough, Meghan H.; McNeely, Margaret L.; Brenner, Darren; Phillips, Siobhan M.Given the broad range of physical and psychosocial health benefits of physical activity (PA) for individuals living with cancer, experts recommend regular PA as well as structured exercise (aerobic, strength, flexibility, and balance) to improve overall well-being among this population. However, most individuals living with and beyond cancer remain insufficiently active, struggling to maintain consistent PA habits post-diagnosis. Exercise oncology behavior change interventions have been shown to increase PA post-intervention, yet challenges remain to ensure that participants stay physically active long-term (i.e. PA maintenance: continued PA up to and beyond 6 months after initial PA behavior change), and thereby continue to reap the benefits of PA. Individuals living with and beyond cancer face significant challenges to PA maintenance, including cost, lack of time, lack of equipment or access to facilities, lack of motivation, and lack of support. Those living in rural and remote locations may experience a greater impact of these PA maintenance barriers, and usually lack access to in-person exercise oncology programs, which are primarily delivered in urban settings. Some of these barriers may be addressed via PA behavior change interventions delivered using electronic health technology (eHealth). Despite increased research, few studies have explored the potential of eHealth to support PA maintenance, especially among rural cancer populations who may need greater PA support given their lower PA levels and greater PA barriers. The present PhD project addressed this knowledge gap, developing novel insights to better understand the potential of eHealth to support PA maintenance among individuals living with and beyond cancer. First, the effectiveness of eHealth to support PA behaviors in exercise oncology was systematically reviewed. Next, a survey of exercise oncology program participants explored technology use, literacy, and perceptions on the value of technology to support PA habits. The review and survey were then followed by a participant-oriented tailoring process to customize an existing self-monitoring app for use in a PA maintenance intervention. Finally, the effectiveness of the self-monitoring app to support PA maintenance was tested in a randomized controlled trial, which was evaluated using quantitative (i.e. self-report and objective PA levels) and qualitative (i.e. semi-structured 1-1 interviews) methods. The project contributed new knowledge to better understand the potential value of eHealth to support PA maintenance among individuals living with cancer, especially those in rural and remote locations, and highlighted important next steps to optimize and comprehensively evaluate its positive impact on PA behavior change.Item Open Access The Intersection of Scientific Misinformation on Social Media and the COVID-19 Pandemic and 2022 Monkeypox Outbreak(2023-04-28) Dalton, Maria Elizabeth; Peters, Cheryl; Brenner, Darren; Yang, Lin; Rainham, DanielThe propagation, and rapid increase of misinformation online, resulted in the World Health Organization declaring an “infodemic” in 2020. The 2022 monkeypox outbreak, alongside the ongoing COVID-19 pandemic, resulted in new discussions surrounding the current misinformation outbreak online – primarily on social media. The COVID-19 pandemic has highlighted the presence of misinformation online, and the direct impacts misinformation can have on action, for example, racially motivated attacks and profiling, and the burning of 5G towers in Europe. Beginning in May of 2022, the monkeypox outbreak was initially reported as a cluster of cases in the United Kingdom following travel to the African continent whereby the spread of misinformation surrounding the disease followed, with dialogues focused on men who have sex with men. A thematic analysis of Instagram posts under #monkeypox and #justsayno was conducted to critically evaluate the dominant themes present on social media related to both the COVID-19 pandemic, and 2022 Monkeypox outbreak. While posts related to COVID-19 were more likely to be flagged as misinformation, posts related to the monkeypox outbreak were typically classified as anti-misinformation or factual, perhaps signifying a shift, and algorithmic changes, in the way Instagram flags information shared on the platform. By increasing our awareness of misinformation spread, we can work to develop strategies to curb its spread and quantify areas for improvement related to social media algorithms.Item Open Access Treatment at Disease-progression in EGFR-mutated NSCLC Patients: Results from a single Canadian Institution(2016) Tudor, Roxana; Bebb, Gwyn; Kopciuk, Karen; Brenner, Darren; Tremblay, Alain; MacEachern, PaulOptimal treatment beyond disease-progression (PD) in non-small cell lung cancer (NSCLC) patients harboring activating epidermal growth factor receptor (EGFR) mutations, treated with tyrosine kinase inhibitors (TKIs), is not well-defined. In this retrospective study, the following aims were set out: 1) compare outcomes and profile of EGFRmut+ NSCLC patients to large cohorts of lung-cancer patients from the Glans-Look lung cancer database -GLD; 2) examine the frequency of continuing TKI treatment beyond PD in EGFRmut+ patients; 3) examine overall survival (OS) and post-progression survival (PPS) according to clinicopathological characteristics and; 4) propose a new PD-scoring model to help guide subsequent treatment formulation. Compared to the GLD-NSCLC cohort without systemic chemotherapy, EGFRmut+ patients were more likely to be younger, female and Asian. Further, continuing TKI treatment beyond PD was associated with improved OS and PPS vs. discontinuation of TKI. A non-independent relationship between EGFRmutation type and smoking history was identified.