Initial health care costs for COVID-19 in British Columbia and Ontario, Canada: an interprovincial population-based cohort study.

BACKGROUND: COVID-19 imposed substantial health and economic burdens. Comprehensive population-based estimates of health care costs for COVID-19 are essential for planning and policy evaluation. We estimated publicly funded health care costs in 2 Canadian provinces during the pandemic's first wave. METHODS: In this historical cohort study, we linked patients with their first positive SARS-CoV-2 test result by June 30, 2020, in 2 Canadian provinces (British Columbia and Ontario) to health care administrative databases and matched to negative or untested controls. We stratified patients by highest level of initial care: community, long-term care, hospital (without admission to the intensive care unit [ICU]) and ICU. Mean publicly funded health care costs for patients and controls, mean net (attributable to COVID-19) costs and total costs were estimated from 30 days before to 120 days after the index date, or to July 31, 2020, in 30-day periods for patients still being followed by the start of each period. RESULTS: We identified 2465 matched people with a positive test result for SARS-CoV-2 in BC and 28 893 in Ontario. Mean age was 53.4 (standard deviation [SD] 21.8) years (BC) and 53.7 (SD 22.7) years (Ontario); 55.7% (BC) and 56.1% (Ontario) were female. Net costs in the first 30 days after the index date were $22 010 (95% confidence interval [CI] 19 512 to 24 509) and $15 750 (95% CI 15 354 to 16 147) for patients admitted to hospital, and $65 828 (95% CI 58 535 to 73 122) and $56 088 (95% CI 53 721 to 58 455) for ICU patients in BC and Ontario, respectively. In the community and long-term care settings, net costs were near 0. Total costs for all people, from 30 days before to 30 days after the index date, were $22 128 330 (BC) and $175 778 210 (Ontario). INTERPRETATION: During the first wave, we found that mean costs attributable to COVID-19 were highest for patients with ICU admission and higher in BC than Ontario. Reducing the number of people who acquire COVID-19 and severity of illness are required to mitigate the economic impact of COVID-19.

"Bring the Hoses to Where the Fire Is!": Differential Impacts of Marginalization and Socioeconomic Status on COVID-19 Case Counts and Healthcare Costs.

OBJECTIVES: Local health leaders and the Director General of the World Health Organization alike have observed that COVID-19 "does not discriminate." Nevertheless, the disproportionate representation of people of low socioeconomic status among those infected resembles discrimination. This population-based retrospective cohort study examined COVID-19 case counts and publicly funded healthcare costs in Ontario, Canada, with a focus on marginalization. METHODS: Individuals with their first positive severe acute respiratory syndrome coronavirus 2 test from January 1, 2020 to June 30, 2020, were linked to administrative databases and matched to negative/untested controls. Mean net (COVID-19-attributable) costs were estimated for 30 days before and after diagnosis, and differences among strata of age, sex, comorbidity, and measures of marginalization were assessed using analysis of variance tests. RESULTS: We included 28 893 COVID-19 cases (mean age 54 years, 56% female). Most cases remained in the community (20 545, 71.1%) or in long-term care facilities (4478, 15.5%), whereas 944 (3.3%) and 2926 (10.1%) were hospitalized, with and without intensive care unit, respectively. Case counts were skewed across marginalization strata with 2 to 7 times more cases in neighborhoods with low income, high material deprivation, and highest ethnic concentration. Mean net costs after diagnosis were higher for males ($4752 vs $2520 for females) and for cases with higher comorbidity ($1394-$7751) (both P < .001) but were similar across levels of most marginalization dimensions (range $3232-$3737, all P ≥ .19). CONCLUSIONS: This study suggests that allocating resources unequally to marginalized individuals may improve equality in outcomes. It highlights the importance of reducing risk of COVID-19 infection among marginalized individuals to reduce overall costs and increase system capacity.

Impact of cancer on income, wealth and economic outcomes of adult cancer survivors: a scoping review.

OBJECTIVE: To summarise peer-reviewed evidence on the effect of a cancer diagnosis on the different sources of income of individuals diagnosed with cancer during adulthood (age ≥18 years). DESIGN: A scoping review following the Joanna Briggs Institute's methodological framework for conducting scoping reviews and reporting results following the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews checklist. DATA SOURCES: Ovid MEDLINE, PsycINFO, CINAHL, EMBASE, Econ-Lit and Evidence-based Medicine Reviews, and reference lists of evidence syntheses. Published literature of any study type in English was searched from January 2000 to December 2020. ELIGIBILITY AND CRITERIA: Study participants were individuals diagnosed with cancer during adulthood (age ≥18 years). Studies from any country and/or healthcare system were included. Primary outcomes were employment income (eg, individual or household); investment income (eg, stocks/bonds, properties, savings); government transfer payments (eg, disability income/pension); debt and bankruptcy. DATA EXTRACTION AND SYNTHESIS: Findings are summarised descriptively and in tabular form. RESULTS: From 6297 citations retrieved, 63 studies (67 articles) met our inclusion criteria. Most (51%) were published in 2016-2020; 65% were published in the USA or Scandinavia. Survivors incurred debt (24 studies), depleted savings (13 studies) and liquidated stocks/bonds (7 studies) in response to a cancer diagnosis. 41 studies reported changes to employment income; of these, 12 case-control studies reported varying results: 5 reported survivors earned less than controls, 4 reported no significant differences, 2 reported mixed results and 1 reported income increased. Initial declines in income tended to lessen over time. CONCLUSIONS: Cancer's impact on survivors' income is complex and time-varying. Longitudinal studies are needed to document the trend of initial declines in income, with declines lessening over time, and its variations. Study designs using standardised income measures and capturing treatment type and follow-up time will improve our understanding of cancer's impact on survivors' income.

Impact of a cancer diagnosis on the income of adult cancer survivors: a scoping review protocol.

INTRODUCTION: While the socioeconomic impact of a cancer diagnosis on cancer survivors has gained some attention in the literature, to our knowledge, a review of the evidence on changes in income due to cancer has yet to be undertaken. In this paper, we describe a scoping review protocol to review the evidence on the effect of a cancer diagnosis on the income of individuals diagnosed with cancer during adulthood (≥18 years). The purpose is to summarise existing evidence, identify gaps in current research and highlight priority areas for future research. METHODS AND ANALYSIS: This study will follow the methodological framework for conducting scoping reviews by the Joanna Briggs Institute In collaboration with a health science librarian, we developed a search strategy to be performed in Ovid MEDLINE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, EMBASE, Econ-Literature and Evidence-Based Medicine Reviews. This scoping review will search the scientific literature published in English from 1 January 2000 to 31 December 2020. Studies that measured the impact of cancer on income of adults will be eligible for inclusion. Studies exclusively focused on employment outcomes (eg, return to work, unemployment, productivity loss), financial expenditures, childhood cancer survivors and/or the caregivers of cancer survivors will be excluded. Three independent reviewers will conduct screening and extract data. Descriptive information will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews. ETHICS AND DISSEMINATION: This scoping review will analyse data from publicly available materials and thus does not require ethics approval. Results from this review will be disseminated through a peer-reviewed publication and/or conference presentation with the potential to identify gaps in the literature, suggest strategies for standardised terminology and provide directions for future research.

Long-term effects of cancer on earnings of childhood, adolescent and young adult cancer survivors - a population-based study from British Columbia, Canada.

BACKGROUND: The patterns and determinants of long-term income among young people surviving cancer, and differences compared to peers, have not yet been fully explored. The objectives of this paper are to describe long-term income among young survivors of cancer, the impact of socio-demographic, disease, and treatment factors on long-term income, and income relative to the general population. METHODS: Retrospective cohort study with comparison group from the general population, using linked population-based registries, clinical data, and tax-records. Multivariate random effects regression models were used to determine survivor income, compare long-term income between survivors and comparators, and assess income determinants. Subjects included all residents of British Columbia (BC), Canada, diagnosed with cancer before 25 years of age and surviving 5 years or more. Comparators were selected from the BC general population matched by gender and birth year. RESULTS: Young cancer survivors earned significantly less than the general population. In addition, survivors of central nervous system tumors have significantly lower incomes than lymphoma survivors. Survivors who received radiation therapy have significantly lower income. Results should be interpreted with caution as the comparator group was matched by gender and date of birth. CONCLUSIONS: Depending on original diagnosis, treatment, and other characteristics, survivors face significantly lower income than peers and may require supports to gain and retain paid employment. Lower income will affect their opportunity for independent living, and will reduce productivity in the labour force.

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

CONTEXT: Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. OBJECTIVES: To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. METHODS: Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. RESULTS: Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. CONCLUSIONS: The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential.

Mapping the FACT-G cancer-specific quality of life instrument to the EQ-5D and SF-6D.

OBJECTIVE: To help facilitate economic evaluations of oncology treatments, we mapped responses on cancer-specific instrument to generic preference-based measures. METHODS: Cancer patients (n = 367) completed one cancer-specific instrument, the FACT-G, and two preference-based measures, the EQ-5D and SF-6D. Responses were randomly divided to form development (n = 184) and cross-validation (n = 183) samples. Relationships between the instruments were estimated using ordinary least squares (OLS), generalized linear models (GLM), and censored least absolute deviations (CLAD) regression approaches. The performance of each model was assessed in terms of how well the responses to the cancer-specific instrument predicted EQ-5D and SF-6D utilities using mean absolute error (MAE) and root mean squared error (RMSE). RESULTS: Physical, functional, and emotional well-being domain scores of the FACT-G best explained the EQ-5D and SF-6D. In terms of accuracy of prediction as measured in RMSE, the CLAD model performed best for the EQ-5D (RMSE = 0.095) whereas the GLM model performed best for the SF-6D (RMSE = 0.061). The GLM predicted SF-6D scores matched the observed values more closely than the CLAD and OLS. CONCLUSION: Our results demonstrate that the estimation of both EQ-5D and SF-6D utility indices using the FACT-G responses can be achieved. The CLAD model for the EQ-5D and the GLM model for the SF-6D are recommended. Thus, it is possible to estimate quality-adjusted life years for economic evaluation from studies where only cancer-specific instrument have been administered.

Mapping utilities from cancer-specific health-related quality of life instruments: a review of the literature.

Cancer-specific health-related quality of life instruments are often used to evaluate the patients' quality of life in clinical trials. However, these instruments cannot be used in economic evaluation to guide resource allocation decisions. Mapping is an approach that enables utilities to be predicted for use in cost-utility analysis. The purpose of this study was to review the literature on the mapping methods used to determine utilities from two cancer-specific instruments. Thirteen studies were identified and a total of 53 models were reported. Most of the studies employed an ordinary least squares method and did not conduct an out-of-sample validation. There is a need for more rigorous and robust mapping studies to be conducted to ensure appropriate funding recommendations are being made.

The ability of cancer-specific and generic preference-based instruments to discriminate across clinical and self-reported measures of cancer severities.

OBJECTIVE: To evaluate the validity of cancer-specific and generic preference-based instruments to discriminate across different measures of cancer severities. METHODS: Patients with breast (n = 66), colorectal (n = 57), and lung (n = 61) cancer completed the EORTC QLQ-C30 and the FACT-G, as well as three generic instruments: the EQ-5D, the SF-6D, and the HUI2/3. Disease severity was quantified using cancer stage, Eastern Cooperative Oncology Group Performance Status (ECOG-PS) score, and self-reported health status. Comparative analyses confirmed the multi-dimensional conceptualization of the instruments in terms of construct and convergent validity. RESULTS: In general, the instruments were able to discriminate across severity measures. The instruments demonstrated moderate to strong correlation with each other (r = 0.37-0.73). Not all of the measures could discriminate between different groups of disease severity: the EQ-5D and SF-6D were less discriminative than the HUI2/3 and the cancer-specific instruments. CONCLUSION: The cancer-specific and generic preference-based instruments demonstrated to be valid in discriminating across levels of ECOG-PS scores and self-reported health states. However, the usefulness of the generic instruments may be limited if they are not able to detect small changes in health status within cancer patients. This raises concerns regarding the appropriateness of these instruments when comparing different cancer treatments within an economic evaluation framework.

Childhood, adolescent, and young adult cancer survivors research program of British Columbia: objectives, study design, and cohort characteristics.

BACKGROUND: The Childhood, Adolescent, and Young Adult Cancer Survivors Research Program (CAYACS) has been established in the province of British Columbia (BC), Canada, to carry out research into late effects and survivor care in multiple domains, and to inform policy and practice. PROCEDURE: This program identifies a survivor cohort and comparison groups from population-based registries and links their records to population-based files of outcomes and outcome determinants, to create a research database and conduct studies of long-term outcomes and care. RESULTS: The initial cohort consisted of all 5-year survivors of cancer or a tumor diagnosed under age 25 years from 1970 to 1995, who were residents in BC at the time of diagnosis, and followed till 2000 (3,841 subjects). Seven percent have died, and 77% have treatment information available. Data on death and second cancer occurring in BC are available. Late morbidity and healthcare utilization information is available for 68% of survivors (79% of those diagnosed from 1981). Education outcomes are available for 71% of those born during 1978-1995 and diagnosed under age 15 years. CONCLUSIONS: Use of registries, administrative databases, and record linkage methodologies is a cost-effective and comprehensive means to conduct survivorship research. This program should add to knowledge of risks of late effects and impacts on care, inform development of strategies to manage risks, evaluate the effects of surveillance and interventions, and assess new risks as the cohort ages, more recent survivors enter the cohort, and treatments change.