The Patient-Centered Outcomes Research Institute (PCORI) funded multiple large-scale comparative effectiveness clinical trials evaluating palliative care (PC) and advance care planning (ACP) healthcare delivery models. This article provides an overview of the most common barriers our investigative teams encountered while implementing these trials and the strategies we utilized to overcome these challenges, with particular attention to identifying research partners for multisite trials; addressing contracting and regulatory issues; creating a team governance structure; training and engaging study staff across sites; recruiting, consenting, and enrolling study participants; collecting PC and ACP data and study outcomes; and managing multisite collaborations. The goal of this article is to provide guidance on how to best plan for and conduct rigorous trials evaluating PC and ACP healthcare delivery interventions moving forward.

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This issue of AJE includes three articles (two reporting original analyses and one systematic review) in which non-interventional studies used an existing randomized controlled trial (RCT) as a reference standard to both inform non-interventional study design, and to benchmark results against. This commentary provides a brief background on the challenges of non-interventional comparative effectiveness research, before elaborating on (i) the potential benefits and challenges of basing non-interventional study design on a specified existing RCT, and (ii) the distinction between designing analysis based upon a specified existing RCT and studies based solely upon a hypothetical target trial. Finally, a number of recommendations for the conduct and reporting of non-interventional studies based upon existing RCTs are provided.

BACKGROUND: Studies comparing radical prostatectomy (RP) to radiation therapy (RT) have consistently shown that patients undergoing RT have a higher risk of other-cause mortality (OCM) compared to RP, signifying poor health status of the former patients. We aimed to evaluate the impact of RP versus RT on cancer-specific mortality (CSM) over a cohort with equivalent OCM risk.
METHODS: The SEER database was queried to identify patients with nonmetastatic PCa between 2004 and 2009. Patients were matched based on their calculated 10-year OCM risk and further stratified for D\'Amico Risk Score and Gleason Grade. A Cox-regression model was used to calculate the 10-year OCM risk. Propensity-score based on the calculated OCM risk were used to match RP and RT patients. Cumulative incidence curves and Competing-risk regression analyses were used to examine the impact of treatment on CSM in the matched cohort.
RESULTS: We identified 55,106 PCa patients treated with RP and 36,674 treated with RT. After match, 6,506 patients were equally distributed for RT versus RP, with no difference in OCM rates (P = .2). The 10-year CSM rates were 8.8% versus 0.6% (P = .01) for RT versus RP in patients with unfavorable-intermediate-risk (Gleason Score 4 + 3) and 7.9% versus 3.9% (P = .003) for high-risk disease. There was no difference in CSM among RT and RP patients for favorable-intermediate-risk (Gleason Score 3 + 4) and low-risk disease.
CONCLUSIONS: In a matched cohort of PCa patients with comparable OCM between the 2 arms, RP yielded a more favorable CSM rate compared to RT only for unfavorable-intermediate- and high-risk groups.

UNASSIGNED: The advent of biosimilars may increase the frequency of dose escalation with biologics in psoriasis.
UNASSIGNED: To explore the frequency and outcomes of dose escalation with adalimumab etanercept, and ustekinumab.
UNASSIGNED: Data were extracted from DermaReg-Pso, a psoriasis register in Stockholm, Sweden. The main exposure was treatment, and the main outcome was dose escalation. We describe outcomes with dose escalation by estimating drug survival and changes in the Psoriasis Area and Severity Index (PASI).
UNASSIGNED: 554 patients had 946 treatment episodes with adalimumab, etanercept, or ustekinumab. The cumulative incidence of dose escalation was 4.1 per 100 treatment years. The Hazard Ratios (HRs) for dose escalation with ustekinumab vs adalimumab and ustekinumab vs etanercept were 1.93 (95% CI: 1.25-2.98), and 2.20 (95% CI: 1.42-3.41), respectively. After dose escalation, the HRs for treatment discontinuation with adalimumab and etanercept compared with ustekinumab were 3.10 (95% CI: 1.56-6.18) and 7.15 (95% CI: 3.96-12.94), respectively. PASI was higher after compared to before dose escalation for etanercept (p = 0.036), but not for adalimumab (p = 0.832) or ustekinumab (p = 0.300).
UNASSIGNED: Dose escalation was comparatively more frequent with ustekinumab than with adalimumab or etanercept; however, treatment discontinuation after dose escalation was more common with adalimumab and etanercept than ustekinumab.

UNASSIGNED: Talquetamab is the first GPRC5D-targeting bispecific antibody approved for the treatment of triple-class exposed (TCE) relapsed/refractory multiple myeloma (RRMM). This matching-adjusted indirect comparison (MAIC) study was conducted to compare the effectiveness of talquetamab vs selinexor-dexamethasone (sel-dex) and vs belantamab mafodotin (belamaf) in patients with TCE RRMM.
UNASSIGNED: An unanchored MAIC was performed using individual patient-level data from patients treated with subcutaneous talquetamab 0.4 mg/kg weekly (QW) and 0.8 mg/kg every other week (Q2W) from MonumenTAL-1 (NCT03399799/NCT04636552) and published summary data for sel-dex from STORM (NCT02336815) and belamaf from DREAMM-2 (NCT0325678). Patients from MonumenTAL-1 who met key eligibility criteria for STORM and DREAMM-2 were included. Outcomes of interest were overall response rate (ORR), complete response or better (≥CR), duration of response (DOR), progression-free survival (PFS), and overall survival (OS).
UNASSIGNED: After adjustment for cross-trial differences, patients treated with both dosing schedules of talquetamab showed significantly better ORR, ≥CR, and DOR vs sel-dex and significantly higher ORR and ≥ CR vs belamaf; DOR was relatively similar to belamaf. PFS was significantly improved with talquetamab Q2W and numerically in favor of talquetamab QW vs sel-dex and significantly improved with both dosing schedules of talquetamab vs belamaf. OS was significantly improved with both dosing schedules of talquetamab vs sel-dex and was numerically in favor of both dosing schedules of talquetamab vs belamaf.
UNASSIGNED: These analyses show superior effectiveness of both talquetamab dosing schedules vs sel-dex and vs belamaf for most outcomes and highlight talquetamab as an effective treatment option for patients with TCE RRMM.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials.
OBJECTIVE: The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM.
METHODS: Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis.
RESULTS: Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13]).
CONCLUSIONS: In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD.

Aim: Although the US FDA encourages manufacturers of medical devices to submit real-world evidence (RWE) to support regulatory decisions, the ability of real-world data (RWD) to generate evidence suitable for decision making remains unclear. The 2017 Medical Device User Fee Amendments (MDUFA IV), authorized the National Evaluation System for health Technology Coordinating Center (NESTcc) to conduct pilot projects, or \'Test-Cases\', to assess whether current RWD captures the information needed to answer research questions proposed by industry stakeholders. We synthesized key lessons about the challenges conducting research with RWD and the strategies used by research teams to enhance their ability to generate evidence from RWD based on 18 Test-Cases conducted between 2020 and 2022. Materials & methods: We reviewed study protocols and reports from each Test-Case team and conducted 49 semi-structured interviews with representatives of participating organizations. Interview transcripts were coded and thematically analyzed. Results: Challenges that stakeholders encountered in working with RWD included the lack of unique device identifiers, capturing key data elements and their appropriate meaning in structured data, limited reliability of diagnosis and procedure codes in structured data, extracting information from unstructured electronic health record (EHR) data, limited capture of long-term study end points, missing data and data sharing. Successful strategies included using manufacturer and supply chain data, leveraging clinical registries and registry reporting processes to collect and aggregate data, querying standardized EHR data, implementing natural language processing algorithms and using multidisciplinary research teams. Conclusion: The Test-Cases identified numerous challenges working with RWD but also opportunities to address these challenges and improve researchers\' ability to use RWD to generate evidence on medical devices.

Comparing different medications is complicated when adherence to these medications differs. We can overcome the adherence issue by assessing effectiveness under sustained use, as in usual causal \'per-protocol\' estimands. However, when sustained use is challenging to satisfy in practice, the usefulness of these estimands can be limited. Here we propose a different class of estimands: separable effects for adherence. These estimands compare modified medications, holding fixed a component responsible for non-adherence. Under assumptions about treatment components\' mechanisms of effect, a separable effects estimand can quantify the effectiveness of medication initiation strategies on an outcome of interest under the adherence mechanism of one of the medications. These assumptions are amenable to interrogation by subject-matter experts and can be evaluated using causal graphs. We describe an algorithm for constructing causal graphs for separable effects, illustrate how these graphs can be used to reason about assumptions required for identification, and provide semi-parametric weighted estimators.

Aim: Regulatory and health technology assessment (HTA) agencies have increasingly published frameworks, guidelines, and recommendations for the use of real-world evidence (RWE) in healthcare decision-making. Variations in the scope and content of these documents, with updates running in parallel, may create challenges for their implementation especially during the market authorization and reimbursement phases of a medicine\'s life cycle. This environmental scan aimed to comprehensively identify and summarize the guidance documents for RWE developed by most well-established regulatory and reimbursement agencies, as well as other organizations focused on healthcare decision-making, and present their similarities and differences. Methods: RWE guidance documents, including white papers from regulatory and HTA agencies, were reviewed in March 2024. Data on scope and recommendations from each body were extracted by two reviewers and similarities and differences were summarized across four topics: study planning, choosing fit-for-purpose data, study conduct, and reporting. Post-authorization or non-pharmacological guidance was excluded. Results: Forty-six documents were identified across multiple agencies; US FDA produced the most RWE-related guidance. All agencies addressed specific and often similar methodological issues related to study design, data fitness-for-purpose, reliability, and reproducibility, although inconsistency in terminologies on these topics was noted. Two HTA bodies (National Institute for Health and Care Excellence [NICE] and Canada\'s Drug Agency) each centralized all related RWE guidance under a unified framework. RWE quality tools and checklists were not consistently named and some differences in preferences were noted. European Medicines Agency, NICE, Haute Autorité de Santé, and the Institute for Quality and Efficiency in Health Care included specific recommendations on the use of analytical approaches to address RWE complexities and increase trust in its findings. Conclusion: Similarities in agencies\' expectations on RWE studies design, quality elements, and reporting will facilitate evidence generation strategy and activities for manufacturers facing multiple, including global, regulatory and reimbursement submissions and re-submissions. A strong preference by decision-making bodies for local real-world data generation may hinder opportunities for data sharing and outputs from international federated data networks. Closer collaboration between decision-making agencies towards a harmonized RWE roadmap, which can be centrally preserved in a living mode, will provide manufacturers and researchers clarity on minimum acceptance requirements and expectations, especially as novel methodologies for RWE generation are rapidly emerging.