Browsing by Author "Quan, May L"
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Item Open Access Development and validation of case-finding algorithms for recurrence of breast cancer using routinely collected administrative data(2019-03-08) Xu, Yuan; Kong, Shiying; Cheung, Winson Y; Bouchard-Fortier, Antoine; Dort, Joseph C; Quan, Hude; Buie, Elizabeth M; McKinnon, Geoff; Quan, May LAbstract Background Recurrence is not explicitly documented in cancer registry data that are widely used for research. Patterns of events after initial treatment such as oncology visits, re-operation, and receipt of subsequent chemotherapy or radiation may indicate recurrence. This study aimed to develop and validate algorithms for identifying breast cancer recurrence using routinely collected administrative data. Methods The study cohort included all young (≤ 40 years) breast cancer patients (2007–2010), and all patients receiving neoadjuvant chemotherapy (2012–2014) in Alberta, Canada. Health events (including mastectomy, chemotherapy, radiation, biopsy and specialist visits) were obtained from provincial administrative data. The algorithms were developed using classification and regression tree (CART) models and validated against primary chart review. Results Among 598 patients, 121 (20.2%) had recurrence after a median follow-up of 4 years. The high sensitivity algorithm achieved 94.2% (95% CI: 90.1–98.4%) sensitivity, 93.7% (91.5–95.9%) specificity, 79.2% (72.5–85.8%) positive predictive value (PPV), and 98.5% (97.3–99.6%) negative predictive value (NPV). The high PPV algorithm had 75.2% (67.5–82.9%) sensitivity, 98.3% (97.2–99.5%) specificity, 91.9% (86.6–97.3%) PPV, and 94% (91.9–96.1%) NPV. Combining high PPV and high sensitivity algorithms with additional (7.5%) chart review to resolve discordant cases resulted in 94.2% (90.1–98.4%) sensitivity, 98.3% (97.2–99.5%) specificity, 93.4% (89.1–97.8%) PPV, and 98.5% (97.4–99.6%) NPV. Conclusion The proposed algorithms based on routinely collected administrative data achieved favorably high validity for identifying breast cancer recurrences in a universal healthcare system in Canada.Item Open Access Identifying opportunities to support patient-centred care for ductal carcinoma in situ: qualitative interviews with clinicians(2020-04-30) Nyhof, Bryanna B; Wright, Frances C; Look Hong, Nicole J; Groot, Gary; Helyer, Lucy; Meiers, Pamela; Quan, May L; Baxter, Nancy N; Urquhart, Robin; Warburton, Rebecca; Gagliardi, Anna RAbstract Background Women with ductal carcinoma in situ (DCIS) report poor patient-clinician communication, and long-lasting confusion and anxiety about their treatment and prognosis. Research shows that patient-centred care (PCC) improves patient experience and outcomes. Little is known about the clinician experience of delivering PCC for DCIS. This study characterized communication challenges faced by clinicians, and interventions they need to improve PCC for DCIS. Methods Purposive and snowball sampling were used to recruit Canadian clinicians by specialty, gender, years of experience, setting, and geographic location. Qualitative interviews were conducted by telephone. Data were analyzed using constant comparison. Findings were mapped to a cancer-specific, comprehensive PCC framework to identify opportunities for improvement. Results Clinicians described approaches they used to address the PCC domains of fostering a healing relationship, exchanging information, and addressing emotions, but do not appear to be addressing the domains of managing uncertainty, involving women in making decisions, or enabling self-management. However, many clinicians described challenges or variable practices for all PCC domains but fostering a healing relationship. Clinicians vary in describing DCIS as cancer based on personal beliefs. When exchanging information, most find it difficult to justify treatment while assuring women of a good prognosis, and feel frustrated when women remain confused despite their efforts to explain it. While they recognize confusion and anxiety among women, clinicians said that patient navigators, social workers, support groups and high-quality information specific to DCIS are lacking. Despite these challenges, clinicians said they did not need or want communication interventions. Conclusions Findings represent currently unmet opportunities by which to help clinicians enhance PCC for DCIS, and underscore the need for supplemental information and supportive care specific to DCIS. Future research is needed to develop and test communication interventions that improve PCC for DCIS. If effective and widely implemented, this may contribute to improved care experiences and outcomes for women diagnosed with and treated for DCIS.Item Open Access Mutational landscape differences between young-onset and older-onset breast cancer patients(2020-03-12) Mealey, Nicole E; O’Sullivan, Dylan E; Pader, Joy; Ruan, Yibing; Wang, Edwin; Quan, May L; Brenner, Darren RAbstract Background The incidence of breast cancer among young women (aged ≤40 years) has increased in North America and Europe. Fewer than 10% of cases among young women are attributable to inherited BRCA1 or BRCA2 mutations, suggesting an important role for somatic mutations. This study investigated genomic differences between young- and older-onset breast tumours. Methods In this study we characterized the mutational landscape of 89 young-onset breast tumours (≤40 years) and examined differences with 949 older-onset tumours (> 40 years) using data from The Cancer Genome Atlas. We examined mutated genes, mutational load, and types of mutations. We used complementary R packages “deconstructSigs” and “SomaticSignatures” to extract mutational signatures. A recursively partitioned mixture model was used to identify whether combinations of mutational signatures were related to age of onset. Results Older patients had a higher proportion of mutations in PIK3CA, CDH1, and MAP3K1 genes, while young-onset patients had a higher proportion of mutations in GATA3 and CTNNB1. Mutational load was lower for young-onset tumours, and a higher proportion of these mutations were C > A mutations, but a lower proportion were C > T mutations compared to older-onset tumours. The most common mutational signatures identified in both age groups were signatures 1 and 3 from the COSMIC database. Signatures resembling COSMIC signatures 2 and 13 were observed among both age groups. We identified a class of tumours with a unique combination of signatures that may be associated with young age of onset. Conclusions The results of this exploratory study provide some evidence that the mutational landscape and mutational signatures among young-onset breast cancer are different from those of older-onset patients. The characterization of young-onset tumours could provide clues to their etiology which may inform future prevention. Further studies are required to confirm our findings.