Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.

Barriers and Facilitators of Using R for Decision Analytic Modeling in Health Technology Assessment: Focus Group Results.

BACKGROUND AND OBJECTIVE: Decision models for health technology assessment (HTA) are largely submitted to HTA agencies using commercial software, which has known limitations. The use of the open-source programming language R has been suggested because of its efficiency, transparency, reproducibility, and ability to consider complex analyses. However, its use in HTA remains limited. This qualitative study aimed to explore the main reasons for this slow uptake of R in HTA and identify tangible facilitators. METHODS: We undertook two semi-structured focus group discussions with 24 key stakeholders from government agencies, consultancy, pharmaceutical companies, and academia. Two 1.5-hour discussions reflected on barriers identified in a previous study and highlighted additional barriers. Discussions were recorded and semi-transcribed, and data were organized and summarized into key themes. RESULTS: Human resources constraints were identified as a key barrier, including a lack of training, prioritization and collaboration, and resistance to change. Another key barrier was the lack of acceptance, or clear guidance, around submissions in R by HTA agencies. Participants also highlighted a lack of communication around accepted packages and decision model structures, and between HTA agencies on standard decision modeling structures. CONCLUSIONS: There is a need for standardization, which can facilitate decision model sharing, coding homogeneity, and improved country adaptations. The creation of training materials and tailored workshops was identified as a key short-term facilitator. Increased communication and engagement of stakeholders could also facilitate the use of R by identifying needs and opportunities, encouraging HTA agencies to address structural barriers, and increasing incentives to use R.

Cost and cost-effectiveness of immunotherapy in childhood ALL: A systematic review.

Survival rates for pediatric acute lymphoblastic leukemia (pALL) have improved dramatically; relapsed/refractory (r/r) acute lymphoblastic leukemia (ALL) remains challenging. Immunotherapies are rapidly evolving treatments for r/r ALL with limited cost-effectiveness data. This study identifies existing economic evaluations of immunotherapy in pALL and summarizes cost-effectiveness. Medline, Embase, and other databases were searched from inception to October 2022. Cost-effectiveness analyses evaluating immunotherapy in pALL were included. Costs reported in 2021 USD. Of 2960 studies, 11 met inclusion criteria. Tisagenlecleucel was compared to standard of care, clofarabine monotherapy, clofarabine combination therapy, or blinatumomab. No studies have evaluated blinatumomab or inotuzumab ozogamicin. Six studies found tisagenlecleucel to be cost-effective, five of which were supported by Novartis. Four found that it had the potential to be cost-effective, and one found that it was not cost-effective. The cost-effectiveness of tisagenlecleucel was highly dependent on list price and cure rates. This study can inform the use of tisagenlecleucel in pALL.

Late mortality among 5-year survivors of childhood cancer: A systematic review and meta-analysis.

BACKGROUND: Childhood cancer survivors are at increased risk of late mortality (death ≥5 years after diagnosis) from cancer recurrence and treatment-related late effects. The authors conducted a systematic review and meta-analysis to provide comprehensive estimates of late mortality risk among survivors internationally and to investigate differences in risk across world regions. METHODS: Health sciences databases were searched for cohort studies comprised of 5-year childhood cancer survivors in which the risk of mortality was evaluated across multiple cancer types. Eligible studies assessed all-cause mortality risk in survivors relative to the general population using the standardized mortality ratio (SMR). The absolute excess risk (AER) was assessed as a secondary measure to examine excess deaths. Cause-specific mortality risk was also assessed, if reported. SMRs from nonoverlapping cohorts were combined in subgroup meta-analysis, and the effect of world region was tested in univariate meta-regression. RESULTS: Nineteen studies were included, and cohort sizes ranged from 314 to 77,423 survivors. Throughout survivorship, SMRs for all-cause mortality generally declined, whereas AERs increased after 15-20 years from diagnosis in several cohorts. All-cause SMRs were significantly lower overall in North American studies than in European studies (relative SMR, 0.63; 95% confidence interval, 0.49-0.80). SMRs for subsequent malignant neoplasms and for cardiovascular, respiratory, and external causes did not vary significantly between world regions. CONCLUSIONS: The current findings suggest that late mortality risk may differ significantly between world regions, but these conclusions are based on a limited number of studies with considerable heterogeneity. Reasons for regional differences remain unclear but may be better elucidated through future analyses of individual-level data.

Validation of a Costing Algorithm and Cost Drivers for Neonates Admitted to the Neonatal Intensive Care Unit.

OBJECTIVE: Neonatal intensive care units (NICUs) account for over 35% of pediatric in-hospital costs. A better understanding of NICU expenditures may help identify areas of improvements. This study aimed to validate the Canadian Neonatal Network (CNN) costing algorithm for seven case-mix groups with actual costs incurred in a tertiary NICU and explore drivers of cost. STUDY DESIGN: A retrospective cohort study of infants admitted within 24 hours of birth to a Level-3 NICU from 2016 to 2019. Patient data and predicted costs were obtained from the CNN database and were compared to actual obtained from the hospital accounting system (Coût par Parcours de Soins et de Services). Cost estimates (adjusted to 2017 Canadian Dollars) were compared using Spearman correlation coefficient (rho). RESULTS: Among 1,795 infants included, 169 (9%) had major congenital anomalies, 164 (9%) with <29 weeks' gestational age (GA), 189 (11%) with 29 to 32 weeks' GA, and 452 (25%) with 33 to 36 weeks' GA. The rest were term infants: 86 (5%) with hypoxic-ischemic encephalopathy treated with therapeutic hypothermia, 194 (11%) requiring respiratory support, and 541 (30%) admitted for other reasons. Median total NICU costs varied from $6,267 (term infants admitted for other reasons) to $211,103 (infants born with <29 weeks' GA). Median daily costs ranged from $1,613 to $2,238. Predicted costs correlated with actual costs across all case-mix groups (rho range 0.78-0.98, p < 0.01) with physician and nursing representing the largest proportion of total costs (65-82%). CONCLUSION: The CNN algorithm accurately predicts NICU total costs for seven case-mix groups. Personnel costs account for three-fourths of in-hospital total costs of all infants in the NICU. KEY POINTS: · Very preterm infants born below 33 weeks of gestation account for most of NICU resource use.. · Human resources providing direct patient care represented the largest portion of costs.. · The algorithm strongly predicted total costs for all case-mix groups..

The impact of referring hospital resources on interfacility overtriage: A population-based analysis.

BACKGROUND: Nearly half of patients transferred from non-trauma to trauma centres have minor injuries. The transfer of patients with minor injuries to trauma centres is not associated with any known patient benefit and represents an opportunity to reduce healthcare costs and improve patient experience. In this study, we evaluated the relationship between hospital resources and overtriage, with the objective of identifying targets for system-level intervention. METHODS: We conducted a population-based cohort study of adults, age ≥ 16, presenting with minor injuries to non-trauma centres in Ontario, Canada (2009-2020). The primary outcome was overtriage, defined as transfer to a trauma centre. Hierarchical logistic regression was used to evaluate the association between hospital resources and a patient's likelihood of being overtriaged, adjusting for case-mix. RESULTS: amongst 165,302 patients with minor injuries, 15,641 (9.5 %) were transferred to a trauma centre (overtriage). Presence of a CT scanner, surgical support, or intensive care unit had no impact on a patient's likelihood of overtriage. Relative to community hospitals, presentation to a teaching hospital was independently associated with greater odds of overtriage (OR 2.97, 95 % CI: 1.26-7.00). Accounting for case-mix and resources, the median difference in a patient's odds of overtriage varied 3.7-fold across non-trauma centres (MOR 3.76). CONCLUSIONS: There is significant variability in overtriage across non-trauma centres, even after adjusting for case-mix and hospital resources. These finding suggests that some centres have developed processes to minimize overtriage independent of available resources. Broad implementation of these processes may represent an opportunity for system-wide quality improvement.

Internal and external validation of an updated ICD-10-CA to AIS-2005 update 2008 algorithm.

BACKGROUND: Administrative data are a powerful tool for population-level trauma research but lack the trauma-specific diagnostic and injury severity codes needed for risk-adjusted comparative analyses. The objective of this study was to validate an algorithm to derive Abbreviated Injury Scale (AIS-2005 update 2008) severity scores from Canadian International Classification of Diseases (ICD-10-CA) diagnostic codes in administrative data. METHODS: This was a retrospective cohort study using data from the 2009 to 2017 Ontario Trauma Registry for the internal validation of the algorithm. This registry includes all patients treated at a trauma center who sustained a moderate or severe injury or were assessed by a trauma team. It contains both ICD-10-CA codes and injury scores assigned by expert abstractors. We used Cohen's kappa (𝜅) coefficient to compare AIS-2005 Update 2008 scores assigned by expert abstractors to those derived using the algorithm and the intraclass correlation coefficient to compare assigned and derived Injury Severity Scores. Sensitivity and specificity for detection of a severe injury (AIS score, ≥ 3) were then calculated. For the external validation of the algorithm, we used administration data to identify adults who either died in an emergency department or were admitted to hospital in Ontario secondary to a traumatic injury (2009-2017). Logistic regression was used to evaluate the discriminative ability and calibration of the algorithm. RESULTS: Of 41,869 patients in the Ontario Trauma Registry, 41,793 (99.8%) had at least one diagnosis matched to the algorithm. Evaluation of AIS scores assigned by expert abstractors and those derived using the algorithm demonstrated a high degree of agreement in identification of patients with at least one severe injury (𝜅 = 0.75; 95% confidence interval [CI], 0.74-0.76). Likewise, algorithm-derived scores had a strong ability to rule in or out injury with AIS ≥ 3 (specificity, 78.5%; 95% CI, 77.7-79.4; sensitivity, 95.1; 95% CI, 94.8-95.3). There was strong correlation between expert abstractor-assigned and crosswalk-derived Injury Severity Score (intraclass correlation coefficient, 0.80; 95% CI, 0.80-0.81). Among the 130,542 patients identified using administrative data, the algorithm retained its discriminative properties. CONCLUSION: Our ICD-10-CA to AIS-2005 update 2008 algorithm produces reliable estimates of injury severity and retains its discriminative properties with administrative data. Our findings suggest that this algorithm can be used for risk adjustment of injury outcomes when using population-based administrative data. LEVEL OF EVIDENCE: Diagnostic Tests/Criteria; Level II.

Pharmacologic Procedural Distress Management During Laceration Repair in Children: A Systematic Review.

OBJECTIVES: To systematically appraise the literature on the relative effectiveness of pharmacologic procedural distress management agents for children undergoing laceration repair. METHODS: Six databases were searched in August 2021, and the search was updated in January 2023. We included completed randomized or quasi-randomized trials involving ( a ) children younger than 15 years undergoing laceration repair in the emergency department; ( b ) randomization to at least one anxiolytic, sedative, and/or analgesic agent versus any comparator agent or placebo; ( c ) efficacy of procedural distress management measured on any scale. Secondary outcomes were pain during the procedure, administration acceptance, sedation duration, additional sedation, length of stay, and stakeholder satisfaction. Cochrane Collaboration's risk-of-bias tool assessed individual studies. Ranges and proportions summarized results where applicable. RESULTS: Among 21 trials (n = 1621 participants), the most commonly studied anxiolytic agents were midazolam, ketamine, and N 2 O. Oral midazolam, oral ketamine, and N 2 O were found to reduce procedural distress more effectively than their comparators in 4, 3, and 2 studies, respectively. Eight studies comparing routes, doses, or volumes of administration of the same agent led to indeterminate results. Meta-analysis was not performed because of heterogeneity in comparators, routes, and outcome measures across studies. CONCLUSIONS: Based on procedural distress reduction, this study favors oral midazolam and oral ketamine. However, this finding should be interpreted with caution because of heterogeneous comparators across studies and minor conflicting results. An optimal agent for procedural distress management cannot be recommended based on the limited evidence. Future research should seek to identify the minimal, essential measures of patient distress during pharmacologic anxiolysis and/or sedation in laceration repair to guide future trials and reviews.

Variations in Site-Specific Costs for Infants Born Extremely Preterm in Canadian Neonatal Intensive Care Units.

OBJECTIVE: To quantify site-specific costs and their association with survival without major morbidity (SWMM) in Canada for neonates <28 weeks of gestation admitted to large tertiary neonatal intensive care units. METHODS: We conducted a retrospective analysis of infants born at <28 weeks of gestation and admitted to Canadian Neonatal Network sites from 2010 through 2021. Sites that cared for at least 50 eligible infants by gestational age in weeks over the study period were included. Using a validated costing algorithm that assessed physician, nursing, respiratory therapy, diagnostic imaging, transfusions, procedural, medication, and certain indirect costs, we calculated site and resource-specific costs in 2017 Canadian dollars (CAD) and evaluated their relationship with SWMM. RESULTS: Seven sites with 8180 (range 841-1605) eligible neonates with a mean (SD) gestation of 25.4 [1.3] weeks were included. Survival to discharge or transfer was 85.3% with a mean (SD) length of stay of 75 (46) days. The mean (SD) total and daily costs per neonate varied between $94 992 ($60 283) and $174 438 ($130 501) CAD and $1833 ($916) to $2307 ($1281) CAD, respectively. Between sites, there was no relationship between costs and SWMM. CONCLUSIONS: There was marked variation in costs and SWMM between sites in Canada with universal health care. The lack of concordance between both outcomes and costs among sites may provide possibilities for outcomes improvement and cost containment.

The PSY-SIM Model: Using Real-World Data to Inform Health Care Policy for Individuals With Chronic Psychotic Disorders.

BACKGROUND AND HYPOTHESIS: Few microsimulation models have been developed for chronic psychotic disorders, severe and disabling mental disorders associated with poor medical and psychiatric outcomes, and high costs of care. The objective of this work was to develop a microsimulation model for individuals with chronic psychotic disorders and to use the model to examine the impact of a smoking cessation initiative on patient outcomes. STUDY DESIGN: Using health records and survey data from Ontario, Canada, the PSY-SIM model was developed to simulate health and cost outcomes of individuals with chronic psychotic disorders. The model was then used to examine the impact of the Smoking Treatment for Ontario Patients (STOP) program from Ontario on the development of chronic conditions, life expectancy, quality of life, and lifetime health care costs. STUDY RESULTS: Individuals with chronic psychotic disorders had a lifetime risk of 63% for congestive heart failure and roughly 50% for respiratory disease, cancer and diabetes, and a life expectancy of 76 years. The model suggests the STOP program can reduce morbidity and lead to survival and quality of life gains with modest increases in health care costs. At a long-term quit rate of 4.4%, the incremental cost-effectiveness ratio of the STOP program was $41,936/QALY compared with status quo. CONCLUSIONS: Smoking cessation initiatives among individuals with chronic psychotic disorders can be cost-effective. These findings will be relevant for decision-makers and clinicians looking to improving health outcomes among this patient population.

Incidence of Diabetes in Children and Adolescents During the COVID-19 Pandemic: A Systematic Review and Meta-Analysis.

Importance: There are reports of increasing incidence of pediatric diabetes since the onset of the COVID-19 pandemic. Given the limitations of individual studies that examine this association, it is important to synthesize estimates of changes in incidence rates. Objective: To compare the incidence rates of pediatric diabetes during and before the COVID-19 pandemic. Data Sources: In this systematic review and meta-analysis, electronic databases, including Medline, Embase, the Cochrane database, Scopus, and Web of Science, and the gray literature were searched between January 1, 2020, and March 28, 2023, using subject headings and text word terms related to COVID-19, diabetes, and diabetic ketoacidosis (DKA). Study Selection: Studies were independently assessed by 2 reviewers and included if they reported differences in incident diabetes cases during vs before the pandemic in youths younger than 19 years, had a minimum observation period of 12 months during and 12 months before the pandemic, and were published in English. Data Extraction and Synthesis: From records that underwent full-text review, 2 reviewers independently abstracted data and assessed the risk of bias. The Meta-analysis of Observational Studies in Epidemiology (MOOSE) reporting guideline was followed. Eligible studies were included in the meta-analysis and analyzed with a common and random-effects analysis. Studies not included in the meta-analysis were summarized descriptively. Main Outcomes and Measures: The primary outcome was change in the incidence rate of pediatric diabetes during vs before the COVID-19 pandemic. The secondary outcome was change in the incidence rate of DKA among youths with new-onset diabetes during the pandemic. Results: Forty-two studies including 102 984 incident diabetes cases were included in the systematic review. The meta-analysis of type 1 diabetes incidence rates included 17 studies of 38 149 youths and showed a higher incidence rate during the first year of the pandemic compared with the prepandemic period (incidence rate ratio [IRR], 1.14; 95% CI, 1.08-1.21). There was an increased incidence of diabetes during months 13 to 24 of the pandemic compared with the prepandemic period (IRR, 1.27; 95% CI, 1.18-1.37). Ten studies (23.8%) reported incident type 2 diabetes cases in both periods. These studies did not report incidence rates, so results were not pooled. Fifteen studies (35.7%) reported DKA incidence and found a higher rate during the pandemic compared with before the pandemic (IRR, 1.26; 95% CI, 1.17-1.36). Conclusions and Relevance: This study found that incidence rates of type 1 diabetes and DKA at diabetes onset in children and adolescents were higher after the start of the COVID-19 pandemic than before the pandemic. Increased resources and support may be needed for the growing number of children and adolescents with diabetes. Future studies are needed to assess whether this trend persists and may help elucidate possible underlying mechanisms to explain temporal changes.

Mismatch-repair deficiency, microsatellite instability, and lynch syndrome in ovarian cancer: A systematic review and meta-analysis.

OBJECTIVE: Investigating for mismatch repair protein deficiency (MMRd), microsatellite instability (MSI), and Lynch syndrome (LS) is widely accepted in endometrial cancer, but knowledge is limited on its value in epithelial ovarian cancer (EOC). The primary objective was to evaluate the prevalence of mismatch repair protein deficiency (MMRd), microsatellite instability (MSI)-high, and Lynch syndrome (LS) in epithelial ovarian cancer (EOC), as well as the diagnostic accuracy of LS screening tests. The secondary objective was to determine the prevalence of MMRd, MSI-high, and LS in synchronous ovarian endometrial cancer and in histological subtypes. METHODS: We systematically searched the MEDLINE, Epub Ahead of Print, MEDLINE In-Process and Other Non-Indexed Citations, Cochrane Central Register of Controlled Trials, and Embase databases. We included studies analysing MMR, MSI, and/or LS by sequencing. RESULTS: A total of 55 studies were included. The prevalence of MMRd, MSI-high, and LS in EOC was 6% (95% confidence interval (CI) 5-8%), 13% (95% CI 12-15%), and 2% (95% CI 1-3%) respectively. Hypermethylation was present in 76% of patients with MLH1 deficiency (95% CI 64-84%). The MMRd prevalence was highest in endometrioid (12%) followed by non-serous non-mucinous (9%) and lowest in serous (1%) histological subtypes. MSI-high prevalence was highest in endometrioid (12%) and non-serous non-mucinous (12%) and lowest in serous (9%) histological subtypes. Synchronous and endometrioid EOC had the highest prevalence of LS pathogenic variants at 7% and 3% respectively, with serous having lowest prevalence (1%). Synchronous ovarian and endometrial cancers had highest rates of MMRd (28%) and MSI-high (28%). Sensitivity was highest for IHC (91.1%) and IHC with MSI (92.8%), while specificity was highest for IHC with methylation (92.3%). CONCLUSION: MMRd and germline LS testing should be considered for non-serous non-mucinous EOC, particularly for endometrioid. PRECIS: The rates of mismatch repair deficiency, microsatellite instability high, and mismatch repair germline mutations are highest in endometrioid subtype and non-serous non-mucinous ovarian cancer. The rates are lowest in serous histologic subtype.

Financial toxicity among adolescent and young adult cancer survivors: A systematic review of educational attainment, employment, and income.

PURPOSE: To identify, evaluate and summarize the evidence on educational attainment, employment status and income of AYAs surviving cancer. METHODS: A search of six databases for articles published between 01/01/2010 and 03/31/2022 was performed. Articles with an AYA survivorship population, quantitative design and a cancer-free comparator group were included. Data extraction was conducted, and quality appraisal was completed using ROBINS-I. Results were summarized using a narrative synthesis. RESULTS: A total of 2801 articles were identified, of which 12 were included. Among the limited evidence, educational attainment did not differ from cancer-free peers. Survivors were more likely to be unemployed, have lower incomes and require social security for income supplementation. Evidence suggested that females, diagnosis of brain cancer and the presence of late-effects were among the risk factors for severe outcomes. CONCLUSIONS: Limited socioeconomic evidence exists for AYAs surviving cancer. Long-lasting financial toxicities occur and highlights a need for further investigation.

A Tutorial on Time-Dependent Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.

In an introductory tutorial, we illustrated building cohort state-transition models (cSTMs) in R, where the state transition probabilities were constant over time. However, in practice, many cSTMs require transitions, rewards, or both to vary over time (time dependent). This tutorial illustrates adding 2 types of time dependence using a previously published cost-effectiveness analysis of multiple strategies as an example. The first is simulation-time dependence, which allows for the transition probabilities to vary as a function of time as measured since the start of the simulation (e.g., varying probability of death as the cohort ages). The second is state-residence time dependence, allowing for history by tracking the time spent in any particular health state using tunnel states. We use these time-dependent cSTMs to conduct cost-effectiveness and probabilistic sensitivity analyses. We also obtain various epidemiological outcomes of interest from the outputs generated from the cSTM, such as survival probability and disease prevalence, often used for model calibration and validation. We present the mathematical notation first, followed by the R code to execute the calculations. The full R code is provided in a public code repository for broader implementation.

An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example.

Decision models can combine information from different sources to simulate the long-term consequences of alternative strategies in the presence of uncertainty. A cohort state-transition model (cSTM) is a decision model commonly used in medical decision making to simulate the transitions of a hypothetical cohort among various health states over time. This tutorial focuses on time-independent cSTM, in which transition probabilities among health states remain constant over time. We implement time-independent cSTM in R, an open-source mathematical and statistical programming language. We illustrate time-independent cSTMs using a previously published decision model, calculate costs and effectiveness outcomes, and conduct a cost-effectiveness analysis of multiple strategies, including a probabilistic sensitivity analysis. We provide open-source code in R to facilitate wider adoption. In a second, more advanced tutorial, we illustrate time-dependent cSTMs.

Clinical Health Outcomes of Siblings of Children with Chronic Conditions: A Systematic Review and Meta-Analysis.

OBJECTIVE: The objective of the study was to assess clinical mental and physical health outcomes of siblings of children with chronic health condition(s) compared with siblings of healthy children or normative data. STUDY DESIGN: We searched Ovid MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL through August 9, 2021. We included English-language studies that reported clinically diagnosable mental or physical health outcomes among siblings of children (<18 years old) with a chronic health condition, included a comparison group, and used an experimental or observational study design. Two reviewers extracted data and independently assessed risk of bias using the Newcastle Ottawa Scale. RESULTS: Of 9899 screened studies, 34 were included; 28 studies reported on mental health, 3 reported on physical health, and 3 reported on mortality. Siblings of children with chronic conditions had greater depression rating scale scores than their comparison groups (standardized mean difference = 0.53; 95% CI = 0.38-0.68; P < .001 [6 studies]), whereas anxiety scores were not substantially increased (standardized mean difference = 0.21; 95% CI = -0.02 to 0.43; P = .07 [7 studies]). The effects for confirmed psychiatric diagnoses (7 studies), mortality (3 studies), or physical health outcomes (3 studies) could not be meta-analyzed given the limited number of studies and between-study heterogeneity. CONCLUSION: Siblings of children with chronic health conditions may be at an increased risk of depression. Our findings suggest the need for targeted interventions to support the psychological well-being of siblings of children with chronic health conditions.

Healthcare utilization and costs associated with acute lymphoblastic leukemia in children with and without Down syndrome.

BACKGROUND: Children with Down syndrome (DS) and acute lymphoblastic leukemia (ALL) are at increased risk of treatment-related morbidity and mortality compared to non-DS-ALL, requiring increased supportive care. We examined the healthcare utilization and costs in DS-ALL patients to inform future evaluations of novel therapies. METHODS: A provincial registry identified all children (1-17 years) diagnosed with B-lineage ALL in Ontario, Canada between 2002 and 2012. Detailed demographic, disease, treatment, and outcome data were abstracted. Linkage to population-based health services databases identified all outpatient and emergency department (ED) visits, hospitalizations, and physician billings. Healthcare utilization costs were available for patients diagnosed during 2006-2012 using validated algorithms (2018 Canadian dollars). Healthcare utilization rates and costs were compared between DS and non-DS patients using regression models, adjusting for all covariates. RESULTS: Of 711 patients, 28 (3.9%) had DS. Adjusting for all covariates, children with DS-ALL experienced substantially higher rates of ED visits (rate ratio [RR] 1.5, 95% confidence interval [95% CI]: 1.2-2.0; p = .001) and inpatient days (RR 2.5, 95% CI: 1.4-4.5; p = .002) compared to non-DS children. Outpatient visit rates were similar (RR 1.1, 95% CI: 0.9-1.3; p = .41). Among patients with available cost data (N = 533, DS = 19), median 5-year healthcare utilization cost was $247,700 among DS patients (interquartile range [IQR]: 200,900-354,500) and $196,200 among non-DS patients (IQR: 148,900-280,300; p = .02). In adjusted analyses, DS-associated costs were 50% higher (RR 1.5, 95% CI: 1.2-1.9; p < .002). CONCLUSIONS: Healthcare utilization and treatment costs of DS-ALL patients are substantially higher than those of non-DS-ALL. Our data provide a baseline for future DS-specific cost-effectiveness studies.

The impact of provincial lockdown policies and COVID-19 case and mortality rates on anxiety in Canada.

AIM: COVID-19 has had significant mental health impacts internationally and anxiety rates are estimated to have tripled during the pandemic, but the specific causes remain underexplored. This study's purpose was to investigate the associations of sociodemographic factors, COVID-19-related policies, and COVID-19 case/mortality rates with levels of anxiety among Canadians during the pandemic. METHODS: This study used linear regression models populated with three integrated sources of data: a repeated cross-sectional survey (n = 7008), Oxford COVID-19 Government Response Tracker data, and COVID-19 case/mortality rates. Sociodemographic factors included were age, gender, race, province, income, education, rurality, household composition, and factors related to employment. RESULTS: Local COVID-19 case and mortality rates and stay-at-home orders were positively associated with anxiety symptom severity. Anxiety was most severe among those who: were female, Indigenous, or Middle Eastern; had postsecondary education; lived with others; and became unemployed or had working hours altered during the pandemic. Anxiety was less severe among: older adults; male, Caucasians, and black individuals; those with high incomes, and; those for whom employment did not change during the pandemic. CONCLUSION: Anxiety was primarily driven by socioeconomic factors among Canadians during the COVID-19 pandemic. Policies that alleviate socioeconomic uncertainty for groups that are most vulnerable may reduce the long-term harm of the pandemic and associated lockdown policies.

Interpreting and assessing confidence in network meta-analysis results: an introduction for clinicians.

PURPOSE: We aimed to provide clinicians with introductory guidance for interpreting and assessing confidence in on Network meta-analysis (NMA) results. METHODS: We reviewed current literature on NMA and summarized key points. RESULTS: Network meta-analysis (NMA) is a statistical method for comparing the efficacy of three or more interventions simultaneously in a single analysis by synthesizing both direct and indirect evidence across a network of randomized clinical trials. It has become increasingly popular in healthcare, since direct evidence (head-to-head randomized clinical trials) are not always available. NMA methods are categorized as either Bayesian or frequentist, and while the two mostly provide similar results, the two approaches are theoretically different and require different interpretations of the results. CONCLUSIONS: We recommend a careful approach to interpreting NMA results and the validity of an NMA depends on its underlying statistical assumptions and the quality of the evidence used in the NMA.

The Trend in Costs of Tertiary-Level Neonatal Intensive Care for Neonates Born Preterm at 220/7-286/7 Weeks of Gestation from 2010 to 2019 in Canada.

OBJECTIVE: To describe the trend in costs over 10 years for tertiary-level neonatal care of infants born 220/7-286/7 weeks of gestation during an ongoing Canadian national quality improvement project. STUDY DESIGN: Clinical characteristics, outcomes, and third-party payor costs for the tertiary neonatal care of infants born 220/7-286/7 weeks of gestation between the years 2010 and 2019 were analyzed from the Canadian Neonatal Network database. Costs were estimated using resource use data from the Canadian Neonatal Network and cost inputs from hospitals, physician billing, and administrative databases in Ontario, Canada. Cost estimates were adjusted to 2017 Canadian dollars (CAD). A generalized linear mixed-effects model with gamma regression was used to estimate trends in costs. RESULTS: Between 2010 and 2019, the number of infants born <24 weeks of gestation increased from 4.4% to 7.7%. The average length of stay increased from 68 days to 75 days. Unadjusted average ± SD total costs per neonate were $120 717 ± $93 062 CAD in 2010 and $132 774 ± $93 161 CAD in 2019. After adjustment for year, center, and gestation, total costs and length of stay increased significantly, by $13 612 CAD (P < .01) and 8.1 days (P < .01) over 10 years, respectively; whereas costs accounting for LOS remained stable. CONCLUSIONS: The total costs and length of stay for infants 220/7-286/7 weeks of gestation have increased over the past decade in Canada during an ongoing national quality improvement initiative; however, there was an increase in the number and survival of neonates at the age of periviability.