The Association between Mutational Signatures and Clinical Outcomes among Patients with Early-Onset Breast Cancer.

Early-onset breast cancer (EoBC), defined by a diagnosis <40 years of age, is associated with poor prognosis. This study investigated the mutational landscape of non-metastatic EoBC and the prognostic relevance of mutational signatures using 100 tumour samples from Alberta, Canada. The MutationalPatterns package in R/Bioconductor was used to extract de novo single-base substitution (SBS) and insertion-deletion (indel) mutational signatures and to fit COSMIC SBS and indel signatures.

Achieving high inter-rater reliability in establishing data labels: a retrospective chart review study.

Background: In medical research, the effectiveness of machine learning algorithms depends heavily on the accuracy of labeled data. This study aimed to assess inter-rater reliability (IRR) in a retrospective electronic medical chart review to create high quality labeled data on comorbidities and adverse events (AEs).

Methods: Six registered nurses with diverse clinical backgrounds reviewed patient charts, extracted data on 20 predefined comorbidities and 18 AEs.

Adjuvant Ovarian Function Suppression in Premenopausal Hormone Receptor-Positive Breast Cancer.

Importance: Few oncology studies have assessed the effectiveness of adjuvant ovarian function suppression (OFS) in observational settings for premenopausal hormone receptor-positive breast cancer. Target trial emulation is increasingly used for estimating treatment outcomes in observational cohorts.

Objectives: To describe hormone therapy and OFS treatment patterns (aim 1), examine the association between adding OFS to tamoxifen (TAM) or aromatase inhibitor (AI) and survival (aim 2), and examine the association between duration of hormone treatment (TAM or AI) plus OFS (H-OFS) and survival (aim 3).

BERT-Based Neural Network for Inpatient Fall Detection From Electronic Medical Records: Retrospective Cohort Study.

Background: Inpatient falls are a substantial concern for health care providers and are associated with negative outcomes for patients. Automated detection of falls using machine learning (ML) algorithms may aid in improving patient safety and reducing the occurrence of falls.

Objective: This study aims to develop and evaluate an ML algorithm for inpatient fall detection using multidisciplinary progress record notes and a pretrained Bidirectional Encoder Representation from Transformers (BERT) language model.

Breast Cancer After Reduction Mammoplasty: A Population-Based Analysis of Incidence, Treatment and Screening Patterns.

Background: The risk of breast cancer may be decreased in women who undergo reduction mammoplasty. The purpose of this study was to describe the incidence and treatment of breast cancer after reduction mammoplasty and to better understand the use of breast cancer screening modalities in these patients.

Methods: This population-based retrospective analysis utilized the Discharge Abstract Database held by the Canadian Institute for Health Information and the National Ambulatory Care Reporting System to identify all women aged 20 years or older who underwent reduction mammoplasty in Alberta, Canada.

Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study.

Background: Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection.

Methods: This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020.

Investigating Factors Associated with Postmastectomy Emergency Department Visits: A Population-Based Analysis.

Background: In 2016, a multi-pronged pathway was implemented across 13 hospitals to improve the mastectomy perioperative care experience with one objective being to safely allow same day surgery mastectomy. While the pathway successfully increased same day mastectomy rates from 1.7 to 73.

Improvement in patient-reported pain among patients with metastatic cancer and its association with opioid prescribing.

Purpose: Opioids are a mainstay of cancer pain management; however, patients with metastatic cancer are often excluded from studies, leading to a lack of evidence on whether increased prescribing (dosage and/or duration) results in improved outcomes for this population. This study aimed to investigate whether increased opioid prescribing is associated with an improvement in patient-reported pain among patients with metastatic cancer.

Patients And Methods: A retrospective cohort of all adult patients diagnosed with stage IV cancers, who completed at least two patient-reported outcomes (PROs) within 30 days of each other, was identified from administrative data.

The Association between Early-Onset Diagnosis and Clinical Outcomes in Triple-Negative Breast Cancer: A Systematic Review and Meta-Analysis.

Early-onset diagnosis, defined by age <40 years, has historically been associated with inferior outcomes in breast cancer. Recent evidence suggests that this association is modified by molecular subtype. We performed a systematic review and meta-analysis of the literature to synthesize evidence on the association between early-onset diagnosis and clinical outcomes in triple-negative breast cancer (TNBC).

Patient and disease characteristics, treatment practices and oncologic outcomes among patients with colorectal cancer: a population-based analysis.

Background: The incidence of colorectal cancer (CRC) is increasing among young adults. We sought to report on patient and disease characteristics, treatment practice patterns and outcomes in this population.

Methods: We conducted a retrospective cohort study using administrative health data from the Alberta Cancer Registry (2004-2015), including demographic and tumour characteristics, and treatment received.

Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis.

Background: Medical researchers and clinicians have shown much interest in developing machine learning (ML) algorithms to detect/predict surgical site infections (SSIs). However, little is known about the overall performance of ML algorithms in predicting SSIs and how to improve the algorithm's robustness. We conducted a systematic review and meta-analysis to summarize the performance of ML algorithms in SSIs case detection and prediction and to describe the impact of using unstructured and textual data in the development of ML algorithms.

A New Method of Identifying Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer Patients Using a Population-Based Electronic Medical Record System.

Background: Accurate identification of pathologic complete response (pCR) from population-based electronic narrative data in a timely and cost-efficient manner is critical. This study aimed to derive and validate a set of natural language processing (NLP)-based machine-learning algorithms to capture pCR from surgical pathology reports of breast cancer patients who underwent neoadjuvant chemotherapy (NAC).

Methods: This retrospective cohort study included all invasive breast cancer patients who underwent NAC and subsequent curative-intent surgery during their admission at all four tertiary acute care hospitals in Calgary, Alberta, Canada, between 1 January 2010 and 31 December 2017.

Developing EMR-based algorithms to Identify hospital adverse events for health system performance evaluation and improvement: Study protocol.

Background: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive information regarding all aspects of patient care, offering a valuable complement to administrative data.

Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real-world data.

Background: Understanding occurrence and timing of second events (recurrence and second primary cancer) is essential for cancer specific survival analysis. However, this information is not readily available in administrative data.

Methods: Alberta Cancer Registry, physician claims, and other administrative data were used.

New method for determining breast cancer recurrence-free survival using routinely collected real-world health data.

Background: In cancer survival analyses using population-based data, researchers face the challenge of ascertaining the timing of recurrence. We previously developed algorithms to identify recurrence of breast cancer. This is a follow-up study to detect the timing of recurrence.

Developing a Prediction Model for Pathologic Complete Response Following Neoadjuvant Chemotherapy in Breast Cancer: A Comparison of Model Building Approaches.

Purpose: The optimal characteristics among patients with breast cancer to recommend neoadjuvant chemotherapy is an active area of clinical research. We developed and compared several approaches to developing prediction models for pathologic complete response (pCR) among patients with breast cancer in Alberta.

Methods: The study included all patients with breast cancer who received neoadjuvant chemotherapy in Alberta between 2012 and 2014 identified from the Alberta Cancer Registry.

Validity of ICD-10 codes for COVID-19 patients with hospital admissions or ED visits in Canada: a retrospective cohort study.

Objective: To evaluate the validity of COVID-19 International Classification of Diseases, 10th Revision (ICD-10) codes and their combinations.

Design: Retrospective cohort study.

Setting: Acute care hospitals and emergency departments (EDs) in Alberta, Canada.

Extent of Groin Dissection in Melanoma: A Mixed-Methods, Population-Based Study of Practice Patterns and Outcomes.

Melanoma metastases to the groin are frequently managed by therapeutic lymph node dissection. Evidence is lacking regarding the extent of dissection required. Thus, we sought to describe practice patterns for the use of inguinal vs.

Acute Care Use by Breast Cancer Patients on Adjuvant Chemotherapy in Alberta: Demonstrating the Importance of Measurement to Improving Quality.

Breast cancer patients receiving adjuvant chemotherapy are at increased risk of acute care use. The incidence of emergency department (ED) visits and hospitalizations (H) have been characterized in other provinces but never in Alberta. We conducted a retrospective population-based cohort study using administrative data of women with stage I-III breast cancer receiving adjuvant chemotherapy.

Associations Between the Density of Oil and Gas Infrastructure and the Incidence, Stage and Outcomes of Solid Tumours: A Population-Based Geographic Analysis.

Background: We hypothesized that there are geographic areas of increased cancer incidence in Alberta, and that these are associated with high densities of oil and gas(O+G) infrastructure. Our objective was to describe the relationship between O+G infrastructure and incidence of solid tumours on a population level.

Methods: We analyzed all patients >=18 years old with urological, breast, upper GI, colorectal, head and neck, hepatobiliary, lung, melanoma, and prostate cancers identified from the Alberta Cancer Registry from 2004-2016.

Outcomes and Healthcare Utilization Among New Persistent Opioid Users and Nonopioid Users After Curative-intent Surgery for Cancer.

Objective: The aim of the study was to compare the health outcomes and resource use of cancer patients who were new persistent opioid users with those who were not, after undergoing curative intent surgery for cancer.

Background: Little is known about long-term health outcomes (overdose, mortality) and resource utilization of new persistent opioid users among cancer patients undergoing curative-intent surgery.

Methods: This retrospective cohort study included all adults with a diagnosis of solid cancers who underwent curative-intent surgery during the study period (2011-2015) in Alberta, Canada and were opioid-naïve before surgery, with a follow-up period until December 31, 2019.

Higher-risk breast cancer in women aged 80 and older: Exploring the effect of treatment on survival.

Background: To understand the association between various treatments and survival for older women with higher-risk breast cancer when controlling for patient and tumor factors.

Materials And Methods: We conducted a retrospective, population-based study. Women aged 80 years or older and diagnosed between 2004 and 2017 with non-metastatic, higher-risk breast cancer were identified form the provincial cancer registry in Alberta, Canada.

Indicators of missing Electronic Medical Record (EMR) discharge summaries: A retrospective study on Canadian data.

Introduction And Objectives: Electronic medical records (EMRs), specifically the discharge summary (DS), can improve secondary use data availability and interprofessional communication. We aimed to describe the completeness of our EMRs by assessing the presence of a DS in the EMR. Additionally, we assessed for indicators of a missing DS.

Associations Between Physician Prescribing Behavior and Persistent Postoperative Opioid Use Among Cancer Patients Undergoing Curative-intent Surgery: A Population-based Cohort Study.

Objective: This study aimed to evaluate the association between prescribers' opioid prescribing history and persistent postoperative opioid use in cancer patients undergoing curative-intent surgery.

Background: Study has shown that patients may be over-prescribed analgesics after surgery. However, whether and how the prescriber's opioid prescribing behavior impacts persistent opioid use is unclear.