Keith R. Abrams

PURPOSE: Widespread adoption of the tropomyosin receptor kinase (TRK) inhibitor larotrectinib has been hampered by limited comparisons against non–TRK inhibitor standard of care (SoC) regimens because of the rarity of TRK fusions. Cross-trial comparisons may be facilitated using matching-adjusted indirect comparison (MAIC), a validated methodology that balances baseline population characteristics. MATERIALS AND METHODS: MAIC was conducted using individual patient-level data from three larotrectinib trials, compared with aggregate real-world data (RWD) from adult patients with locally advanced/metastatic TRK fusion–positive cancer in the Hartwig Medical Foundation database. Patient populations were matched on available clinical characteristics. Estimates of overall survival (OS; defined as the time from start of first postbiopsy treatment [or larotrectinib] to death) were compared between larotrectinib and non–TRK inhibitor SoC. RESULTS: The analysis included 24 patients receiving nontargeted TRK inhibitor SoC and 120 receiving larotrectinib. After matching, median OS was 50.3 months (IQR, 23.3-not estimable) for larotrectinib versus 13 months (IQR, 6.4-18.3) for SoC; larotrectinib was associated with an 84% risk reduction of death (adjusted hazard ratio, 0.16 [95% CI, 0.07 to 0.36]). To account for the longer follow-up time in the larotrectinib group than in the SoC group (median: 56.7 v 23.2 months), a restricted mean survival analysis was conducted up to 26.2 months (largest observed event time in SoC arm), which showed median survival of 22.6 months for larotrectinib and 12.8 months for SoC (mean difference: 9.8 months [95% CI, 5.6 to 14.0]). CONCLUSION: In patients with TRK fusion–positive cancer, larotrectinib was associated with a mean survival advantage of 9.8 months compared with non–TRK inhibitor SoC, corroborating favorable findings for larotrectinib from a previous analysis that used a different set of RWD.

Background: The COVID-19 pandemic resulted in increased mortality directly and indirectly associated with COVID-19. Aim: To assess the impact of the COVID-19 pandemic on all-cause and disease-specific mortality and explore potential health inequalities associated with area-level deprivation in Wales. Methods: Two population-based cohort studies were derived from multi-sourced, linked demographic, administrative and electronic health record data from 2016 to 2019 (n = 3,113,319) and 2020 to 2022 (n = 3,571,471). Data were analysed using generalised linear models adjusting for age, sex, area-level deprivation and time at risk. Results: COVID-19 deaths peaked in January 2021 (54.9/100,000 person-months, 95% confidence interval (CI): 52.4–57.5). The pandemic indirectly affected deaths, with higher than expected maximum relative mortality rates (RR) related to cancer (RR: 1.24, 95% CI: 1.13–1.36), infectious diseases (excluding respiratory infections) (RR: 2.09, 95% CI: 1.27– 3.43), circulatory system (RR: 1.41, 95% CI: 1.28–1.56), trauma (RR: 2.04, 95% CI: 1.57– 2.65), digestive system (RR: 1.54, 95% CI: 1.25–1.91), nervous system (RR: 1.63; 95% CI: 1.34–2.00) and mental and behavioural disorders (RR: 1.85, 95% CI: 1.58–2.16). Mortality associated with respiratory diseases (unrelated to COVID-19) were lower than expected (minimum RR: 0.52, 95% CI: 0.45–0.60). All-cause mortality was lower in least deprived communities compared with most deprived (RR: 0.61, 95% CI: 0.60–0.62), and the magnitude of this effect increased during the pandemic. Conclusions: All-cause and disease-specific mortality directly and indirectly associated with COVID-19 increased during the COVID-19 pandemic. Socioeconomic disparities were exacerbated during this time.

Aim: Comparative effectiveness research (CER) is essential for making informed decisions about drug access. It provides insights into the effectiveness and safety of new drugs compared with existing treatments, thereby guiding better healthcare decisions and ensuring that new therapies meet the real-world needs of patients and healthcare systems. Objective: To provide a tool that assists analysts and decision-makers in identifying the most suitable analytical approach for answering a CER question, given specific data availability contexts. Methods: A systematic literature review of the scientific literature was performed and existing regulatory and health technology assessment (HTA) guidance were evaluated to identify and compare recommendations and best practices. Based on this review a methods flowchart that synthesizes current practices and requirements was proposed. Results: The review did not find any papers that clearly identified the most appropriate analytical approach for answering CER questions under various conditions. Therefore, a methods flowchart was designed to inform analyst and decision makers choices starting from a well-defined scientific question. Conclusion: The proposed methods flowchart offers clear guidance on CER methodologies across a range of settings and research needs. It begins with a well-defined research question and considers multiple feasibility aspects related to CER. This tool aims to standardize methods, ensure rigorous and consistent research quality and promote a culture of evidence-based decision-making in healthcare.

PURPOSE: Evidence suggests that neurotrophic tyrosine receptor kinase ( NTRK) gene fusions in solid tumors are predictive biomarkers for targeted inhibition across a number of adult and pediatric tumor types. However, despite robust clinical response to tyrosine receptor kinase (TRK) inhibitors, the natural history and prognostic implications of NTRK fusions in solid tumors are poorly understood. It is important to evaluate their prognostic significance on survival to provide some context to the clinical effectiveness observed in clinical trials of TRK-targeted therapies. METHODS: A systematic literature review was conducted in Medline, Embase, Cochrane, and PubMed to identify studies comparing the overall survival (OS) of patients with NTRK fusion–positive ( NTRK+) versus NTRK fusion–negative ( NTRK–) tumors. Five retrospective matched case-control studies published before 11 August 2022 were assessed for inclusion, and three were selected for the meta-analysis (sample size: 69 NTRK+, 444 NTRK–). Risk of bias was assessed using the Risk of Bias Assessment tool for Non-randomized Studies tool. The pooled hazard ratio (HR) was estimated using a Bayesian random-effects model. RESULTS: In the meta-analysis, the median follow-up ranged from 2 to 14 years and the median OS was between 10.1 and 12.7 months (where reported). Comparing patients with tumors NTRK+ and NTRK–, the pooled HR estimate for OS was 1.51 (95% credible interval, 1.01 to 2.29). The patients analyzed had no previous or current exposure to TRK inhibitors. CONCLUSION: In patients not treated with TRK inhibitor therapies, those with NTRK+ solid tumors have a 50% increased risk of mortality within 10 years from diagnosis or the start of standard therapy compared with those with NTRK– status. Although this is the most robust estimate of the comparative survival rate to date, further studies are required to reduce uncertainty.

Objectives This paper presents an Australian model that formed part of the health technology assessment for public investment in siltuximab for the rare condition of idiopathic Multicentric Castleman Disease (iMCD) in Australia. Methods Two literature reviews were conducted to identify the appropriate comparator and model structure. Survival gain based on available clinical trial data were modelled using an Excel-based model semi-Markov model including time-varying transition probabilities, an adjustment for trial crossover and long-term data. A 20-year horizon was taken, and an Australian healthcare system perspective was adopted, with both benefits and costs discounted at 5%. The model was informed with an inclusive stakeholder approach that included a review of the model by an independent economist, Australian clinical expert opinion and feedback from the Pharmaceutical Benefits Advisory Committee (PBAC). The price used in the economic evaluation reflects a confidential discounted price, which was agreed to with the PBAC. Results An incremental cost-effectiveness ratio of A$84,935 per quality-adjusted life-year (QALY) gained was estimated. At a willingness-to-pay threshold of A$100,000 per QALY, siltuximab has a 72.1% probability of being cost-effective compared with placebo and best supportive care. Sensitivity analyses results were most sensitive to the length of interval between administrations (from 3- to 6-weekly) and crossover adjustments. Conclusion Within a collaborative and inclusive stakeholder framework, the model submitted to the Australian PBAC found siltuximab to be cost-effective for the treatment of iMCD.

Hyperthyroidism has been linked to long-term cardiovascular and metabolic morbidity and increased mortality. We aimed to assess differences in mortality and cardiometabolic outcomes depending on treatment modality to better inform patient-clinician decision-making. Methods: We identified 62,474 patients with newly diagnosed hyperthyroidism, treated with antithyroid drugs (ATD), radioiodine or thyroidectomy from a UK population-based GP database (>16M patients). Health records were linked with Hospital Episode Statistics, Office for National Statistics mortality data, and Index of Multiple Deprivation. All-cause mortality, major cardiovascular events (MACE: cardiovascular death, heart failure or stroke) and post-treatment obesity diagnosis were studied. A “target trial” approach was used to elucidate causal effects. Average treatment effects (ATE) were estimated using inverse-probability weights with regression adjustment. Mortality was assessed as time-to-event; other outcomes were modelled as binary (funding: NIHR RfPB, NIHR200772). Results: Patients treated with ATD comprised 73.4% of the cohort; 19.5% were treated with radioiodine, and 7.1% with thyroidectomy. Patients were followed for a median of 10 years (IQR: 6-15). Estimated mean survival was 11.7 years with ATD treatment. Definitive treatment increased survival: radioiodine by 1.7y. (95%CI: 1.1-2.4; PP=0.003). The estimated risk of MACE if the population were treated with ATD was 9.9% (9.6-10.3), which increased by an additional 0.7% (0.1-1.3; P=0.02) with radioiodine but not with thyroidectomy (0.02% [(-0.8)-1.2], P=0.7). The estimated risk of post-treatment obesity was 7.6%, which increased by 0.9% (0.3-1.6, P=0.005) with radioiodine and 1.7% (0.5-2.8, P=0.003) with thyroidectomy. Conclusion: EGRET is the first large study using population-based linked community and hospital data to elucidate the long-term consequences of treatment modalities for hyperthyroidism. We confirmed a decreased mortality in patients undergoing definitive treatment whereas a slightly increased risk of obesity was found in patients treated with radioiodine and surgery. Compared to medical treatment, a small increase in cardiovascular events was noted with radioiodine.

Bivariate meta‐analysis provides a useful framework for combining information across related studies and has been utilized to combine evidence from clinical studies to evaluate treatment efficacy on two outcomes. It has also been used to investigate surrogacy patterns between treatment effects on the surrogate endpoint and the final outcome. Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final outcome and to predict clinical benefit or harm. The standard bivariate meta‐analytic approach models the observed treatment effects on the surrogate and the final outcome outcomes jointly, at both the within‐study and between‐studies levels, using a bivariate normal distribution. For binomial data, a normal approximation on log odds ratio scale can be used. However, this method may lead to biased results when the proportions of events are close to one or zero, affecting the validation of surrogate endpoints. In this article, we explore modeling the two outcomes on the original binomial scale. First, we present a method that uses independent binomial likelihoods to model the within‐study variability avoiding to approximate the observed treatment effects. However, the method ignores the within‐study association. To overcome this issue, we propose a method using a bivariate copula with binomial marginals, which allows the model to account for the within‐study association. We applied the methods to an illustrative example in chronic myeloid leukemia to investigate the surrogate relationship between complete cytogenetic response and event‐free‐survival.

Background: Healthcare workers (HCWs), particularly those from ethnic minority groups, have been shown to be at disproportionately higher risk of infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) compared to the general population. However, there is insufficient evidence on how demographic and occupational factors influence infection risk among ethnic minority HCWs. Methods and findings: We conducted a cross-sectional analysis using data from the baseline questionnaire of the United Kingdom Research study into Ethnicity and Coronavirus Disease 2019 (COVID-19) Outcomes in Healthcare workers (UK-REACH) cohort study, administered between December 2020 and March 2021. We used logistic regression to examine associations of demographic, household, and occupational risk factors with SARS-CoV-2 infection (defined by polymerase chain reaction (PCR), serology, or suspected COVID-19) in a diverse group of HCWs. The primary exposure of interest was self-reported ethnicity. Among 10,772 HCWs who worked during the first UK national lockdown in March 2020, the median age was 45 (interquartile range [IQR] 35 to 54), 75.1% were female and 29.6% were from ethnic minority groups. A total of 2,496 (23.2%) reported previous SARS-CoV-2 infection. The fully adjusted model contained the following dependent variables: demographic factors (age, sex, ethnicity, migration status, deprivation, religiosity), household factors (living with key workers, shared spaces in accommodation, number of people in household), health factors (presence/absence of diabetes or immunosuppression, smoking history, shielding status, SARS-CoV-2 vaccination status), the extent of social mixing outside of the household, and occupational factors (job role, the area in which a participant worked, use of public transport to work, exposure to confirmed suspected COVID-19 patients, personal protective equipment [PPE] access, aerosol generating procedure exposure, night shift pattern, and the UK region of workplace). After adjustment, demographic and household factors associated with increased odds of infection included younger age, living with other key workers, and higher religiosity. Important occupational risk factors associated with increased odds of infection included attending to a higher number of COVID-19 positive patients (aOR 2.59, 95% CI 2.11 to 3.18 for ≥21 patients per week versus none), working in a nursing or midwifery role (1.30, 1.11 to 1.53, compared to doctors), reporting a lack of access to PPE (1.29, 1.17 to 1.43), and working in an ambulance (2.00, 1.56 to 2.58) or hospital inpatient setting (1.55, 1.38 to 1.75). Those who worked in intensive care units were less likely to have been infected (0.76, 0.64 to 0.92) than those who did not. Black HCWs were more likely to have been infected than their White colleagues, an effect which attenuated after adjustment for other known risk factors. This study is limited by self-selection bias and the cross sectional nature of the study means we cannot infer the direction of causality. Conclusions: We identified key sociodemographic and occupational risk factors associated with SARS-CoV-2 infection among UK HCWs, and have determined factors that might contribute to a disproportionate odds of infection in HCWs from Black ethnic groups. These findings demonstrate the importance of social and occupational factors in driving ethnic disparities in COVID-19 outcomes, and should inform policies, including targeted vaccination strategies and risk assessments aimed at protecting HCWs in future waves of the COVID-19 pandemic. Trial registration: The study was prospectively registered at ISRCTN (reference number: ISRCTN11811602).

Aim: To conduct indirect treatment comparisons between risdiplam and other approved treatments for spinal muscular atrophy (SMA). Patients & methods: Individual patient data from risdiplam trials were compared with aggregated data from published studies of nusinersen and onasemnogene abeparvovec, accounting for heterogeneity across studies. Results: In Type 1 SMA, studies of risdiplam and nusinersen included similar populations. Indirect comparison results found improved survival and motor function with risdiplam versus nusinersen. Comparison with onasemnogene abeparvovec in Type 1 SMA and with nusinersen in Types 2/3 SMA was challenging due to substantial differences in study populations; no concrete conclusions could be drawn from the indirect comparison analyses. Conclusion: Indirect comparisons support risdiplam as a superior alternative to nusinersen in Type 1 SMA.