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Frailty After Cancer Surgery Among Older Adults: A Geriatric Oncology Perspective

Samuel Dubé and Shabbir M.H. Alibhai

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Applying Quality Indicators to Examine Quality of Care During Active Surveillance in Low-Risk Prostate Cancer: A Population-Based Study

Narhari Timilshina, Antonio Finelli, George Tomlinson, Beate Sander, and Shabbir M.H. Alibhai

Background: Although a few studies have reported wide variations in quality of care in active surveillance (AS), there is a lack of research using validated quality indicators (QIs). The aim of this study was to apply evidence-based QIs to examine the quality of AS care at the population level. Methods: QIs were measured using a population-based retrospective cohort of patients with low-risk prostate cancer diagnosed between 2002 and 2014. We developed 20 QIs through a modified Delphi approach with clinicians targeting the quality of AS care at the population level. QIs included structure (n=1), process of care (n=13), and outcome indicators (n=6). Abstracted pathology data were linked to cancer registry and administrative databases in Ontario, Canada. A total of 17 of 20 QIs could be applied based on available information in administrative databases. Variations in QI performance were explored according to patient age, year of diagnosis, and physician volume. Results: The cohort included 33,454 men with low-risk prostate cancer, with a median age of 65 years (IQR, 59–71 years) and a median prostate-specific antigen level of 6.2 ng/mL. Compliance varied widely for 10 process QIs (range, 36.6%–100.0%, with 6 [60%] QIs >80%). Initial AS uptake was 36.6% and increased over time. Among outcome indicators, significant variations were observed by patient age group (10-year metastasis-free survival was 95.0% for age 65–74 years and 97.5% in age <55 years) and physician average annual AS volume (10-year metastasis-free survival was 94.5% for physicians with 1–2 patients with AS and 95.8% for those with ≥6 patients with AS annually). Conclusions: This study establishes a foundation for quality-of-care assessments and monitoring during AS implementation at a population level. Considerable variations appeared with QIs related to process of care by physician volume and QIs related to outcome by patient age group. These findings may represent areas for targeted quality improvement initiatives.

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Frailty in Patients With Newly Diagnosed Diffuse Large B-Cell Lymphoma Receiving Curative-Intent Therapy: A Population-Based Study

Abi Vijenthira, Lee Mozessohn, Chenthila Nagamuthu, Ning Liu, Danielle Blunt, Shabbir Alibhai, Anca Prica, and Matthew C. Cheung

Background: The objectives of this study were to determine whether frailty is associated with survival in a population-based sample of patients with diffuse large B-cell lymphoma (DLBCL) and to describe the healthcare utilization patterns of frail versus nonfrail patients during treatment. Methods: A retrospective cohort study was conducted using population-based data in Ontario, Canada. Patients aged ≥66 years diagnosed between 2006 and 2017 with DLBCL or transformed follicular lymphoma who received first-line curative-intent chemoimmunotherapy were included. Frailty was defined using a modified version of a generalizable frailty index developed for use with Ontario administrative data. Cox regression was performed to examine the association between frailty and 1-year mortality. Results: A total of 5,527 patients were included (median age, 75 years [interquartile range, 70–80 years]; 48% female), of whom 2,699 (49%) were classified as frail. Within 1 year of first-line treatment, 32% (n=868) of frail patients had died compared with 20% (n=553) of nonfrail patients (unadjusted hazard ratio, 1.8; 95% CI, 1.6–2.0; P<.0001). Frail patients had higher healthcare utilization during treatment, with most hospitalizations related to infection and/or lymphoma. In multivariable modeling controlling for age, inpatient diagnosis, number of chemoimmunotherapy cycles received, comorbidity burden, and healthcare utilization, frailty remained independently associated with 1-year mortality (adjusted hazard ratio, 1.5; 95% CI, 1.3–1.7; P<.0001). Conclusions: In a population-based sample of older adult patients with DLBCL receiving front-line curative-intent therapy, half were classified as frail, and their adjusted relative rate of death in the first year after starting treatment was 50% higher than that of nonfrail patients. Frailty seems to be associated with poor treatment tolerance and a higher likelihood of requiring acute hospital-based care.

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The Senior Toronto Oncology Panel (STOP) Study: Research Participation for Older Adults With Cancer and Caregivers

Martine T.E. Puts, Schroder Sattar, Takami Fossat, Margaret I. Fitch, Geraldine J. Macdonald, Tina Hsu, Ewa Szumacher, Douglas A. Stephens, Joseph Robinson, David Macdonald, Andrew S. Choate, Eric Pitters, Barbara Liu, Lianne Jeffs, Katherine S. McGilton, and Shabbir M.H. Alibhai

Background: Patient engagement in research may lead to better-designed studies and improved health outcomes. The objectives of this study were to identify the research priorities of older adults with cancer (OAWCs) and their caregivers and examine how to engage these individuals in research teams and what supports are needed. Methods: We conducted 3 public meetings and 7 focus groups to delineate research priorities and the supports needed to facilitate integration of OAWCs and their caregivers on research teams. Results: A total of 33 older adults and 19 caregivers attended a public meeting and 27 older adults and 17 caregivers participated in a focus group. Most of the OAWCs and their caregivers had never participated in research before. Three themes were identified from the focus groups: (1) motivation to be on a team; (2) ability to make meaningful contributions; and (3) logistical considerations to facilitate engagement. Most participants were motivated to be a research team member and be involved in all steps of research if it could benefit them or future patients and caregivers. OAWCs and their caregivers were highly motivated to improve outcomes. Required logistics included flexibility regarding time and location, accessibility to computer technology, transportation support, materials worded in lay language, and attending/having short training sessions, as well as the presence of peer support. Conclusions: OAWCs and their caregivers are very motivated and willing to participate in research and to be research team members. Logistics and the social aspects of being on a team are important.