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.

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.

SurvdigitizeR: an algorithm for automated survival curve digitization.

BACKGROUND: Decision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan-Meier (KM) curves. However, manually extracting these probabilities from KM curves is time-consuming, expensive, and error-prone. We developed an efficient and accurate algorithm that automates extraction of survival probabilities from KM curves. METHODS: The automated digitization algorithm processes images from a JPG or PNG format, converts them in their hue, saturation, and lightness scale and uses optical character recognition to detect axis location and labels. It also uses a k-medoids clustering algorithm to separate multiple overlapping curves on the same figure. To validate performance, we generated survival plots form random time-to-event data from a sample size of 25, 50, 150, and 250, 1000 individuals split into 1,2, or 3 treatment arms. We assumed an exponential distribution and applied random censoring. We compared automated digitization and manual digitization performed by well-trained researchers. We calculated the root mean squared error (RMSE) at 100-time points for both methods. The algorithm's performance was also evaluated by Bland-Altman analysis for the agreement between automated and manual digitization on a real-world set of published KM curves. RESULTS: The automated digitizer accurately identified survival probabilities over time in the simulated KM curves. The average RMSE for automated digitization was 0.012, while manual digitization had an average RMSE of 0.014. Its performance was negatively correlated with the number of curves in a figure and the presence of censoring markers. In real-world scenarios, automated digitization and manual digitization showed very close agreement. CONCLUSIONS: The algorithm streamlines the digitization process and requires minimal user input. It effectively digitized KM curves in simulated and real-world scenarios, demonstrating accuracy comparable to conventional manual digitization. The algorithm has been developed as an open-source R package and as a Shiny application and is available on GitHub: https://github.com/Pechli-Lab/SurvdigitizeR and https://pechlilab.shinyapps.io/SurvdigitizeR/ .

Cost-effectiveness of the McGill interactive pediatric oncogenetic guidelines in identifying Li-Fraumeni syndrome in female patients with osteosarcoma.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a penetrant cancer predisposition syndrome (CPS) associated with the development of many tumor types in young people including osteosarcoma and breast cancer (BC). The McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG) decision-support tool provides a standardized approach to identify patients at risk of CPSs. METHODS: We conducted a cost-utility analysis, from the healthcare payer perspective, to compare MIPOGG-guided, physician-guided, and universal genetic testing strategies to detect LFS in female patients diagnosed at an age of less than 18 years with osteosarcoma. We developed a decision tree and discrete-event simulation model to simulate the clinical and cost outcomes of the three genetic referral strategies on a cohort of female children diagnosed with osteosarcoma, especially focused on BC as subsequent cancer. Outcomes included BC incidence, quality-adjusted life-years (QALYs), healthcare costs, and incremental cost-utility ratios (ICURs). We conducted probabilistic and scenario analyses to assess the uncertainty surrounding model parameters. RESULTS: Compared to the physician-guided testing, the MIPOGG-guided strategy was marginally more expensive by $105 (-$516; $743), but slightly more effective by 0.003 (-0.04; 0.045) QALYs. Compared to MIPOGG, the universal testing strategy was $1333 ($732; $1953) more costly and associated with 0.011 (-0.043; 0.064) additional QALYs. The ICUR for the MIPOGG strategy was $33,947/QALY when compared to the physician strategy; the ICUR for universal testing strategy was $118,631/QALY when compared to the MIPOGG strategy. DISCUSSION: This study provides evidence for clinical and policy decision-making on the cost-effectiveness of genetic referral strategies to identify LFS in the setting of osteosarcoma. MIPOGG-guided strategy was most likely to be cost-effective at a willingness-to-pay threshold value of $50,000/QALY.

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..

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.

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.

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.

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.

Cost-effectiveness of noninvasive fetal RhD blood group genotyping in nonalloimmunized and alloimmunized pregnancies.

BACKGROUND: We sought to determine the cost-effectiveness of noninvasive fetal RhD blood group genotyping in nonalloimmunized and alloimmunized pregnancies in Canada. STUDY DESIGN AND METHODS: We developed two probabilistic state-transition (Markov) microsimulation models to compare fetal genotyping followed by targeted management versus usual care (i.e., universal Rh immunoglobulin [RhIG] prophylaxis in nonalloimmunized RhD-negative pregnancies, or universal intensive monitoring in alloimmunized pregnancies). The reference case considered a healthcare payer perspective and a 10-year time horizon. Sensitivity analysis examined assumptions related to test cost, paternal screening, subsequent pregnancies, other alloantibodies (e.g., K, Rh c/C/E), societal perspective, and lifetime horizon. RESULTS: Fetal genotyping in nonalloimmunized pregnancies (at per-sample test cost of C$247/US$311) was associated with a slightly higher probability of maternal alloimmunization (22 vs. 21 per 10,000) and a reduced number of RhIG injections (1.427 vs. 1.795) than usual care. It was more expensive (C$154/US$194, 95% Credible Interval [CrI]: C$139/US$175-C$169/US$213) and had little impact on QALYs (0.0007, 95%CrI: -0.01-0.01). These results were sensitive to the test cost (threshold achieved at C$88/US$111), and inclusion of paternal screening. Fetal genotyping in alloimmunized pregnancies (at test cost of C$328/US$413) was less expensive (-C$6280/US$7903, 95% CrI: -C$6325/US$7959 to -C$6229/US$7838) and more effective (0.19 QALYs, 95% CrI 0.17-0.20) than usual care. These cost savings remained robust in sensitivity analyses. DISCUSSION: Noninvasive fetal RhD genotyping saves resources and represents good value for the management of alloimmunized pregnancies. If the cost of genotyping is substantially decreased, the targeted intervention can become a viable option for nonalloimmunized pregnancies.

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.

Clinical and economic impact of molecular testing for BRAF fusion in pediatric low-grade Glioma.

BACKGROUND: Treatment personalization via tumor molecular testing holds promise for improving outcomes for patients with pediatric low-grade glioma (PLGG). We evaluate the health economic impact of employing tumor molecular testing to guide treatment for patients diagnosed with PLGG, particularly the avoidance of radiation therapy (RT) for patients with BRAF-fusion. METHODS: We performed a model-based cost-utility analysis comparing two strategies: molecular testing to determine BRAF fusion status at diagnosis against no molecular testing. We developed a microsimulation to model the lifetime health and cost outcomes (in quality-adjusted life years (QALYs) and 2018 CAD, respectively) for a simulated cohort of 100,000 patients newly diagnosed with PLGG after their initial surgery. RESULTS: The life expectancy after diagnosis for individuals who did not receive molecular testing was 39.01 (95% Confidence Intervals (CI): 32.94;44.38) years and 40.08 (95% CI: 33.19;45.76) years for those who received testing. Our findings indicate that patients who received molecular testing at diagnosis experienced a 0.38 (95% CI: 0.08;0.77) gain in QALYs and $1384 (95% CI: $-3486; $1204) reduction in costs over their lifetime. Cost and QALY benefits were driven primarily by the avoidance of long-term adverse events (stroke, secondary neoplasms) associated with unnecessary use of radiation. CONCLUSIONS: We demonstrate the clinical benefit and cost-effectiveness of molecular testing in guiding the decision to provide RT in PLGG. While our results do not consider the impact of targeted therapies, this work is an example of the value of simulation modeling in assessing the long-term costs and benefits of precision oncology interventions for childhood cancer, which can aid decision-making about health system reimbursement.

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 clinical utility of exome and genome sequencing across clinical indications: a systematic review.

Exome sequencing and genome sequencing have the potential to improve clinical utility for patients undergoing genetic investigations. However, evidence of clinical utility is limited to pediatric populations; we aimed to fill this gap by conducting a systematic review of the literature on the clinical utility of exome/genome sequencing across disease indications in pediatric and adult populations. MEDLINE, EMBASE and Cochrane Library were searched between 2016 and 2020. Quantitative studies evaluating diagnostic yield were included; other measures of clinical utility such as changes to clinical management were documented if reported. Two reviewers screened, extracted data, and appraised risk of bias. Fifty studies met our inclusion criteria. All studies reported diagnostic yield, which ranged from 3 to 70%, with higher range of yields reported for neurological indications and acute illness ranging from 22 to 68% and 37-70%, respectively. Diagnoses triggered a range of clinical management changes including surveillance, reproductive-risk counseling, and identifying at-risk relatives in 4-100% of patients, with higher frequencies reported for acute illness ranging from 67 to 95%. The frequency of variants of uncertain significance ranged from 5 to 85% across studies with a potential trend of decreasing frequency over time and higher rates identified in patients of non-European ancestry. This review provides evidence for a higher range of diagnostic yield of exome/genome sequencing compared to standard genetic tests, particularly in neurological and acute indications. However, we identified significant heterogeneity in study procedures and outcomes, precluding a meaningful meta-analysis and certainty in the evidence available for decision-making. Future research that incorporates a comprehensive and consistent approach in capturing clinical utility of exome/genome sequencing across broader ancestral groups is necessary to improve diagnostic accuracy and yield and allow for analysis of trends over time.Prospero registration CRD42019094101.

Clinical and psychological outcomes of receiving a variant of uncertain significance from multigene panel testing or genomic sequencing: a systematic review and meta-analysis.

This study systematically reviewed and synthesized the literature on psychological and clinical outcomes of receiving a variant of uncertain significance (VUS) from multigene panel testing or genomic sequencing. MEDLINE and EMBASE were searched. Two reviewers screened studies and extracted data. Data were synthesized through meta-analysis and meta-aggregation. The search identified 4539 unique studies and 15 were included in the review. Patients with VUS reported higher genetic test-specific concerns on the Multidimensional Impact of Cancer Risk Assessment (MICRA) scale than patients with negative results (mean difference 3.73 [95% CI 0.80 to 6.66] P = 0.0126), and lower than patients with positive results (mean difference -7.01 [95% CI -11.31 to -2.71], P = 0.0014). Patients with VUS and patients with negative results were similarly likely to have a change in their clinical management (OR 1.41 [95% CI 0.90 to 2.21], P = 0.182), and less likely to have a change in management than patients with positive results (OR 0.09 [95% CI 0.05 to 0.19], P < 0.0001). Factors that contributed to how patients responded to their VUS included their interpretation of the result and their health-care provider's counseling and recommendations. Review findings suggest there may be a need for practice guidelines or clinical decision support tools for VUS disclosure and management.

Costs of Neonatal Intensive Care for Canadian Infants with Preterm Birth.

OBJECTIVE: To develop and validate an itemized costing algorithm for in-patient neonatal intensive care unit (NICU) costs for infants born prematurely that can be used for quality improvement and health economic analyses. STUDY DESIGN: We sourced patient resource use data from the Canadian Neonatal Network database, with records from infants admitted to 30 tertiary NICUs in Canada. We sourced unit cost inputs from Ontario hospitals, schedules of benefits, and administrative sources. Costing estimates were generated by matching patient resource use data to the appropriate unit costs. All cost estimates were in 2017 Canadian dollars and assigned from the perspective of a provincial public payer. Results were validated using previous estimates of inpatient NICU costs and hospital case-cost estimates. RESULTS: We assigned costs to 27 742 infants born prematurely admitted from 2015 to 2017. Mean (SD) gestational age and birth weight of the cohort were 31.8 (3.5) weeks and 1843 (739) g, respectively. The median (IQR) cost of hospitalization before NICU discharge was estimated as $20 184 ($9739-51 314) for all infants; $11 810 ($6410-19 800) for infants born at gestational age of 33-36 weeks; $30 572 ($16 597-$51 857) at gestational age of 29-32 weeks; and $100 440 ($56 858-$159 3867) at gestational age of <29 weeks. Cost estimates correlated with length of stay (r = 0.97) and gestational age (r = -0.65). The estimates were consistent with provincial resource estimates and previous estimates from Canada. CONCLUSIONS: NICU costs for infants with preterm birth increase as gestation decreases and length of stay increases. Our cost estimates are easily accessible, transparent, and congruent with previous cost estimates.

Impact of limited sample size and follow-up on single event survival extrapolation for health technology assessment: a simulation study.

INTRODUCTION: Extrapolation of time-to-event data from clinical trials is commonly used in decision models for health technology assessment (HTA). The objective of this study was to assess performance of standard parametric survival analysis techniques for extrapolation of time-to-event data for a single event from clinical trials with limited data due to small samples or short follow-up. METHODS: Simulated populations with 50,000 individuals were generated with an exponential hazard rate for the event of interest. A scenario consisted of 5000 repetitions with six sample size groups (30-500 patients) artificially censored after every 10% of events observed. Goodness-of-fit statistics (AIC, BIC) were used to determine the best-fitting among standard parametric distributions (exponential, Weibull, log-normal, log-logistic, generalized gamma, Gompertz). Median survival, one-year survival probability, time horizon (1% survival time, or 99th percentile of survival distribution) and restricted mean survival time (RMST) were compared to population values to assess coverage and error (e.g., mean absolute percentage error). RESULTS: The true exponential distribution was correctly identified using goodness-of-fit according to BIC more frequently compared to AIC (average 92% vs 68%). Under-coverage and large errors were observed for all outcomes when distributions were specified by AIC and for time horizon and RMST with BIC. Error in point estimates were found to be strongly associated with sample size and completeness of follow-up. Small samples produced larger average error, even with complete follow-up, than large samples with short follow-up. Correctly specifying the event distribution reduced magnitude of error in larger samples but not in smaller samples. CONCLUSIONS: Limited clinical data from small samples, or short follow-up of large samples, produce large error in estimates relevant to HTA regardless of whether the correct distribution is specified. The associated uncertainty in estimated parameters may not capture the true population values. Decision models that base lifetime time horizon on the model's extrapolated output are not likely to reliably estimate mean survival or its uncertainty. For data with an exponential event distribution, BIC more reliably identified the true distribution than AIC. These findings have important implications for health decision modelling and HTA of novel therapies seeking approval with limited evidence.

Phase-specific risks of outpatient visits, emergency visits, and hospitalizations during Children's Oncology Group-based treatment for childhood acute lymphoblastic leukemia: A population-based study.

BACKGROUND: Therapy for childhood acute lymphoblastic leukemia (ALL) is associated with substantial health care utilization and burden on families. Little is known about health care utilization during specific treatment phases. PROCEDURES: We identified children with ALL diagnosed during 2002-2012 in Ontario, Canada and treated according to Children's Oncology Group (COG) protocols. Disease and treatment data were chart abstracted. Population-based health care databases identified all outpatient visits, emergency department (ED) visits, and hospitalizations. In addition to comparing standard and intensified versions of treatment phases, we compared patients receiving different steroids (dexamethasone vs. prednisone) and different versions of interim maintenance (IM) (Capizzi vs. high-dose methotrexate [HD-MTX]). RESULTS: Six hundred thirty-seven children met inclusion criteria. During intensified consolidation, 76.2% of patients were hospitalized at least once, compared to only 32.3% of patients receiving standard consolidation (p < .0001). Similarly, 72.9% of patients receiving intensified delayed intensification (DI) were hospitalized during this phase compared to 50.3% of patients receiving standard DI (p < .0001). Among patients receiving a four-drug induction, those receiving dexamethasone had an 85% higher rate of ED visits (adjusted rate ratio [aRR] 1.85, 95th confidence interval [95CI] 1.14-3.00; p = .01) and a 44% higher rate of hospitalization (aRR 1.44, 95CI 1.24-1.68) compared to those receiving prednisone. Among high-risk B-ALL and T-ALL patients in IM, Capizzi MTX was not associated with an increased rate of ED visits versus HD-MTX. CONCLUSIONS: These results can be used to inform anticipatory guidance for families, particularly those undergoing intensified therapy. Our results also suggest that increased toxicity rates associated with dexamethasone during Induction seen in clinical trials reflect real-world practice.

Prioritisation and design of clinical trials.

Clinical trials require participation of numerous patients, enormous research resources and substantial public funding. Time-consuming trials lead to delayed implementation of beneficial interventions and to reduced benefit to patients. This manuscript discusses two methods for the allocation of research resources and reviews a framework for prioritisation and design of clinical trials. The traditional error-driven approach of clinical trial design controls for type I and II errors. However, controlling for those statistical errors has limited relevance to policy makers. Therefore, this error-driven approach can be inefficient, waste research resources and lead to research with limited impact on daily practice. The novel value-driven approach assesses the currently available evidence and focuses on designing clinical trials that directly inform policy and treatment decisions. Estimating the net value of collecting further information, prior to undertaking a trial, informs a decision maker whether a clinical or health policy decision can be made with current information or if collection of extra evidence is justified. Additionally, estimating the net value of new information guides study design, data collection choices, and sample size estimation. The value-driven approach ensures the efficient use of research resources, reduces unnecessary burden to trial participants, and accelerates implementation of beneficial healthcare interventions.