Generating and using real-world data: A worthwhile uphill battle.

The precision oncology paradigm challenges the feasibility and data generalizability of traditional clinical trials. Consequently, an unmet need exists for practical approaches to test many subgroups, evaluate real-world drug value, and gather comprehensive, accessible datasets to validate novel biomarkers. Real-world data (RWD) are increasingly recognized to have the potential to fill this gap in research methodology. Established applications of RWD include informing disease epidemiology, pharmacovigilance, and healthcare quality assessment. Currently, concerns regarding RWD quality and comprehensiveness, privacy, and biases hamper their broader application. Nonetheless, RWD may play a pivotal role in supplementing clinical trials, enabling conditional reimbursement and accelerated drug access, and innovating trial conduct. Moreover, purpose-built RWD repositories may support the extension or refinement of drug indications and facilitate the discovery and validation of new biomarkers. This perspective explores the potential of leveraging RWD to advance oncology, highlights its benefits and challenges, and suggests a path forward in this evolving field.

The Master Observational Trial: A New Class of Master Protocol to Advance Precision Medicine.

This commentary introduces a new clinical trial construct, the Master Observational Trial (MOT), which hybridizes the power of molecularly based master interventional protocols with the breadth of real-world data. The MOT provides a clinical venue to allow molecular medicine to rapidly advance, answers questions that traditional interventional trials generally do not address, and seamlessly integrates with interventional trials in both diagnostic and therapeutic arenas. The result is a more comprehensive data collection ecosystem in precision medicine.

An overview of real-world data sources for oncology and considerations for research.

Generating evidence on the use, effectiveness, and safety of new cancer therapies is a priority for researchers, health care providers, payers, and regulators given the rapid pace of change in cancer diagnosis and treatments. The use of real-world data (RWD) is integral to understanding the utilization patterns and outcomes of these new treatments among patients with cancer who are treated in clinical practice and community settings. An initial step in the use of RWD is careful study design to assess the suitability of an RWD source. This pivotal process can be guided by using a conceptual model that encourages predesign conceptualization. The primary types of RWD included are electronic health records, administrative claims data, cancer registries, and specialty data providers and networks. Careful consideration of each data type is necessary because they are collected for a specific purpose, capturing a set of data elements within a certain population for that purpose, and they vary by population coverage and longitudinality. In this review, the authors provide a high-level assessment of the strengths and limitations of each data category to inform data source selection appropriate to the study question. Overall, the development and accessibility of RWD sources for cancer research are rapidly increasing, and the use of these data requires careful consideration of composition and utility to assess important questions in understanding the use and effectiveness of new therapies.

Integrating Evidence to Guide Use of Biologics and Small Molecules for Inflammatory Bowel Diseases.

Advances in science have led to the development of multiple biologics and small molecules for the treatment of inflammatory bowel diseases (IBDs). This growth in advanced medical therapies has been accompanied by an increase in methodological innovation to study and compare therapies. Guidelines provide an evidence-based approach to integrating therapies into routine practice, but they are often unable to provide timely recommendations as new therapies come to market, and they have limited incorporation of real-world evidence when making recommendations. This limits the scope and usability of guidelines, and a gap remains in defining how best to position and integrate advanced medical therapies for IBD. In this review, we provide a framework for clinicians and researchers to understand key differences in sources of evidence, how different methodologies are applied to study the comparative effectiveness of advanced medical therapies in IBD, and considerations for how these sources of evidence can be used to better integrate current guideline recommendations. Over time, we anticipate this framework will allow for a transition to living guidelines and/or practice recommendations.

Association of GLP-1 Receptor Agonists and Hepatocellular Carcinoma Incidence and Hepatic Decompensation in Patients With Type 2 Diabetes.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a leading cause of cancer death. HCC is preventable with about 70% of HCC attributable to modifiable risk factors. Glucagon-like peptide-1 receptor agonists (GLP-1RAs), Food and Drug Administration-approved medications for treating type 2 diabetes mellitus (T2DM), have pleiotropic effects on counteracting risk factors for HCC. Here we evaluate the association of GLP-1RAs with incident HCC risk in a real-world population. METHODS: This retrospective cohort included 1,890,020 patients with a diagnosis of T2DM who were prescribed GLP-1RAs or other non-GLP-1RA anti-diabetes medications and had no prior diagnosis of HCC. Incident (first-time) diagnosis of HCC and hepatic decompensating events during a 5-year follow-up was compared between cohorts of patients prescribed GLP-1 RAs vs other anti-diabetes medications. Time-to-first-event analysis was performed using Kaplan-Meier survival analysis with hazard ratio and 95% confidence interval calculated. RESULTS: GLP-1RAs were associated with a lower risk of incident HCC with hazard ratio of 0.20 [0.14-0.31], 0.39 [0.21-0.69], 0.63 [0.26-1.50] compared with insulin, sulfonylureas, and metformin, respectively. GLP-1RAs were associated with a significantly lower risk of hepatic decompensation compared with 6 other anti-diabetes medications. Reduced risks were observed in patients without and with different stages of fatty liver diseases, with more profound effects in patients without liver diseases. Similar findings were observed in patients with and without obesity and alcohol or tobacco use disorders. GLP-1RA combination therapies were associated with decreased risk for HCC and hepatic decompensations compared with monotherapies. CONCLUSIONS: GLP-1RAs were associated with a reduced risk of incident HCC and hepatic decompensation compared with other anti-diabetes medications in patients with T2DM. These findings provide supporting evidence for future studies to investigate the underlying mechanisms and their clinical use.

Urgent Need to Understand and Prevent Gonococcal Infection: From the Laboratory to Real-World Context.

Neisseria gonorrhoeae is widespread globally. Primary prevention is unsuccessful and antimicrobial resistance threatens optimal management. There is no specific vaccine and natural infection studies show that N. gonorrhoeae can avoid and suppress immune responses. In addition to extensive variation in expression and specificity of many gonococcal surface antigens, it induces a robust inflammatory response through the Th17 pathway with a large influx of neutrophils and inflammatory cytokines but evades macrophages. The Th1- and Th2-mediated response is suppressed, resulting in low, short-lived antibody titers. Real-world evidence suggests that gonorrhea cases are reduced among recipients of N. meningitidis group B vaccines containing outer membrane vesicles (OMV). Although the first randomized trial of an OMV-containing MenB vaccine against N. gonorrhoeae infection did not show statistically significant vaccine efficacy, ongoing trials might shed further light. Several candidate vaccine antigens for a gonococcal-specific vaccine are being evaluated preclinically but only one has reached clinical trials.

Effectiveness of Immunization Products Against Medically Attended Respiratory Syncytial Virus Infection: Generic Protocol for a Test-Negative Case-Control Study.

Monitoring the real-life effectiveness of respiratory syncytial virus (RSV) products is of major public health importance. This generic protocol for a test-negative design study aims to address currently envisioned approaches for RSV prevention (monoclonal antibodies and vaccines) to study effectiveness of these products among target groups: children, older adults, and pregnant women. The generic protocol approach was chosen to allow for flexibility in adapting the protocol to a specific setting. This protocol includes severe acute respiratory infection (SARI) and acute respiratory infection (ARI), both due to RSV, as end points. These end points can be applied to studies in hospitals, primarily targeting patients with more severe disease, but also to studies in general practitioner clinics targeting ARI.

Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

Trajectories of BMI before and after diagnosis of type 2 diabetes in a real-world population.

AIMS/HYPOTHESIS: Few studies have examined the clinical characteristics associated with changes in weight before and after diagnosis of type 2 diabetes. Using a large real-world cohort, we derived trajectories of BMI before and after diabetes diagnosis, and examined the clinical characteristics associated with these trajectories, including assessing the impact of pre-diagnosis weight change on post-diagnosis weight change. METHODS: We performed an observational cohort study using electronic medical records from individuals in the Scottish Care Information Diabetes Collaboration database. Two trajectories were calculated, based on observed BMI measurements between 3 years and 6 months before diagnosis and between 1 and 5 years after diagnosis. In the post-diagnosis trajectory, each BMI measurement was time-dependently adjusted for the effects of diabetes medications and HbA1c change. RESULTS: A total of 2736 individuals were included in the study. There was a pattern of pre-diagnosis weight gain, with 1944 individuals (71%) gaining weight overall, and 875 (32%) gaining more than 0.5 kg/m2 per year. This was followed by a pattern of weight loss after diagnosis, with 1722 individuals (63%) losing weight. Younger age and greater social deprivation were associated with increased weight gain before diagnosis. Pre-diagnosis weight change was unrelated to post-diagnosis weight change, but post-diagnosis weight loss was associated with older age, female sex, higher BMI, higher HbA1c and weight gain during the peri-diagnosis period. When considering the peri-diagnostic period (defined as from 6 months before to 12 months after diagnosis), we identified 986 (36%) individuals who had a high HbA1c at diagnosis but who lost weight rapidly and were most aggressively treated at 1 year; this subgroup had the best glycaemic control at 5 years. CONCLUSIONS/INTERPRETATION: Average weight increases before diagnosis and decreases after diagnosis; however, there were significant differences across the population in terms of weight changes. Younger individuals gained weight pre-diagnosis, but, in older individuals, type 2 diabetes is less associated with weight gain, consistent with other drivers for diabetes aetiology in older adults. We have identified a substantial group of individuals who have a rapid deterioration in glycaemic control, together with weight loss, around the time of diagnosis, and who subsequently stabilise, suggesting that a high HbA1c at diagnosis is not inevitably associated with a poor outcome and may be driven by reversible glucose toxicity.

Can the introduction of a 12-lead ECG help reduce mortality in those presenting with foot ulceration to multidisciplinary diabetic foot clinics? An observational evaluation of a real-world implementation pilot in England.

AIMS/HYPOTHESIS: The risk of dying within 2 years of presentation with diabetic foot ulceration is over six times the risk of amputation, with CVD the major contributor. Using an observational evaluation of a real-world implementation pilot, we aimed to assess whether for those presenting with diabetic foot ulceration in England, introducing a 12-lead ECG into routine care followed by appropriate clinical action was associated with reduced mortality. METHODS: Between July 2014 and December 2017, ten multidisciplinary diabetic foot services in England participated in a pilot project introducing 12-lead ECGs for new attendees with foot ulceration. Inception coincided with launch of the National Diabetes Footcare Audit (NDFA), whereby all diabetic footcare services in England were invited to enter data on new attendees with foot ulceration. Poisson regression models assessed the mortality RR at 2 and 5 years following first assessment of those receiving care in a participating pilot unit vs those receiving care in any other unit in England, adjusting for age, sex, ethnicity, deprivation, type and duration of diabetes, ulcer severity, and morbidity in the year prior to first assessment. RESULTS: Of the 3110 people recorded in the NDFA at a participating unit during the pilot, 33% (1015) were recorded as having received an ECG. A further 25,195 people recorded in the NDFA had attended another English footcare service. Unadjusted mortality in the pilot units was 16.3% (165) at 2 years and 37.4% (380) at 5 years for those who received an ECG, and 20.5% (430) and 45.2% (950), respectively, for those who did not receive an ECG. For people included in the NDFA at other units, unadjusted mortality was 20.1% (5075) and 42.6% (10,745), respectively. In the fully adjusted model, mortality was not significantly lower for those attending participating units at 2 (RR 0.93 [95% CI 0.85, 1.01]) or 5 years (RR 0.95 [95% CI 0.90, 1.01]). At participating units, mortality in those who received an ECG vs those who did not was lower at 5 years (RR 0.86 [95% CI 0.76, 0.97]), but not at 2 years (RR 0.87 [95% CI 0.72, 1.04]). Comparing just those that received an ECG with attendees at all other centres in England, mortality was lower at 5 years (RR 0.87 [95% CI 0.78, 0.96]), but not at 2 years (RR 0.86 [95% CI 0.74, 1.01]). CONCLUSIONS/INTERPRETATION: The evaluation confirms the high mortality seen in those presenting with diabetic foot ulceration. Overall mortality at the participating units was not significantly reduced at 2 or 5 years, with confidence intervals just crossing parity. Implementation of the 12-lead ECG into the routine care pathway proved challenging for clinical teams-overall a third of attendees had one, although some units delivered the intervention to over 60% of attendees-and the evaluation was therefore underpowered. Nonetheless, the signals of potential mortality benefit among those who had an ECG suggest that units in a position to operationalise implementation may wish to consider this. DATA AVAILABILITY: Data from the National Diabetes Audit can be requested through the National Health Service Digital Data Access Request Service process at: https://digital.nhs.uk/services/data-access-request-service-dars/dars-products-and-services/data-set-catalogue/national-diabetes-audit-nda.

Patient-reported outcomes in advanced NSCLC before and during the COVID-19 pandemic: Real-world data from the German prospective CRISP Registry (AIO-TRK-0315).

Patients with lung cancer under treatment have been associated with a high risk of COVID-19 infection and potentially worse outcome, but real-world data on patient-reported outcomes (PROs) are rare. We assess patients' characteristics and PROs before and during the COVID-19 pandemic in an advanced non-small cell lung cancer (NSCLC) cohort in Germany. Patients with locally advanced or metastatic NSCLC from the prospective, multicentre, observational CRISP Registry (NCT02622581) were categorised as pre-pandemic (March 2019 to Feb 2020, n = 1621) and pandemic (March 2020 to Feb 2021, n = 1317). From baseline to month 15, patients' health-related quality of life (HRQoL) was assessed by FACT-L, anxiety and depression by PHQ-4. Association of pandemic status with time to deterioration (TTD) in QoL scales adjusted for potential covariates was estimated using Cox modelling. PROs were documented for 1166 patients (72%) in the pre-pandemic, 979 (74%) in the pandemic group. Almost 60% of patients were male, median age was 66 years, comorbidities occurred in 85%. Regarding HRQoL, mean-change-from-baseline plots hardly differed between both samples. Approximately 15%-21% of patients reported anxiety, about 19%-27% signs of depression. For the pandemic group, TTD was slightly, but statistically significantly, worse for the physical well-being-FACT-G subscale (HR 1.15 [95%CI 1.02-1.30]) and the anxiety-GAD-2 subscale (HR 1.14 [95%CI 1.01-1.29]). These prospectively collected real-world data provide valuable insights into PROs before and during the COVID-19 pandemic in advanced NSCLC. For the patients, the pandemic seemed to be less of a burden than the disease itself, as there was a considerable proportion of patients with anxiety and depression in both groups.

Real-world safety and effectiveness of radium-223 in patients with metastatic castration-resistant prostate cancer: Interim analyses of the prospective, observational RAPIT study.

Several life-prolonging therapies for metastatic castration-resistant prostate cancer (mCRPC) are available, including radium-223 dichloride (223Ra), which was approved based on phase 3 data demonstrating improved overall survival (OS) and a favorable safety profile. To date, real-world evidence for 223Ra use in Taiwan is from three studies of <50 patients. This observational study (NCT04232761) enrolled male patients with histologically/cytologically confirmed mCRPC with bone metastases from centers across Taiwan. 223Ra was prescribed as part of routine practice by investigators. Patients with prior 223Ra treatment were excluded. The primary objective was to assess 223Ra safety; secondary objectives evaluated efficacy parameters, including OS. Overall, 224 patients were enrolled. Most patients had an Eastern Cooperative Oncology Group performance status of 0/1 (79.0%) and ≤20 bone metastases (69.2%); no patients had visceral metastases. 223Ra was first- or second-line therapy in 23.2% and 47.7% of patients, respectively. The total proportion of patients who received 5-6 223Ra cycles was 68.8%; this proportion was greater with first-line use (84.3%) than second- (65.7%) or third-/fourth-line use (64.1%). More chemotherapy-naïve patients (61.9%) completed the 6-cycle 223Ra treatment than chemotherapy-exposed patients (56.7%). Any-grade treatment-emergent adverse events (TEAEs) and serious TEAEs occurred in 54.0% and 28.6% of patients, respectively, while 12% experienced 223Ra-related adverse events. Median OS was 15.7 months (95% confidence interval 12.13-19.51); patients receiving 5-6 223Ra injections and earlier 223Ra use had longer OS than those receiving fewer injections and later 223Ra use. 223Ra provides a well-tolerated and effective treatment for Taiwanese patients with mCRPC and bone metastases.

Real-world treatment patterns for palbociclib plus an aromatase inhibitor, or an aromatase inhibitor alone, for patients with metastatic breast cancer in the Flatiron Database.

There are limited real-world comparative effectiveness data for palbociclib plus an aromatase inhibitor (AI) as a first-line (1L) treatment examining endpoints that require long term follow-up and post 1L progression. The Flatiron Health Analytic Database was used to characterize treatment and dosing patterns in patients with hormone receptor-positive/human epidermal growth factor 2-negative (HR+/HER2-) metastatic breast cancer (mBC) receiving palbociclib plus an AI vs an AI alone in routine US clinical practice. In addition, time to chemotherapy (TTC) and real-world progression-free survival (rwPFS) when combining 1L and second-line of therapy (rwPFS2) were assessed. Of 1324 patients who received palbociclib plus an AI between February 3, 2015 and March 31, 2020, 1110 (83.8%) started palbociclib at the recommended 125 mg/day dose. After stabilized inverse probability treatment-weighting (sIPTW), median TTC in patients treated with palbociclib plus an AI and AI alone was 37.4 months (95% confidence interval [CI], 33.7-40.7) and 29.2 months (95% CI, 26.8-33.5), respectively (hazard ratio [HR] = 0.77 [95% CI, 0.69-0.86], P < .0001); median rwPFS2 was 32.6 months (95% CI, 29.4-35.2) and 20.7 months (95% CI, 18.9-22.6), respectively (HR = 0.62 [95% CI, 0.54-0.70], P < .0001). Sensitivity analyses with propensity score matching showed similar results to sIPTW analyses. Results from this large real-world study examining additional effectiveness outcomes beyond 1L rwPFS and overall survival support the use of palbociclib plus an AI as a 1L treatment for patients with HR+/HER2- mBC.

Exploring the impact of patient-specific clinical features on osimertinib effectiveness in a real-world cohort of patients with EGFR mutated non-small cell lung cancer.

Osimertinib is prescribed to patients with metastatic non-small cell lung cancer (NSCLC) and a sensitizing EGFR mutation. Limited data exists on the impact of patient characteristics or osimertinib exposure on effectiveness outcomes. This was a Dutch, multicenter cohort study. Eligible patients were ≥18 years, with metastatic EGFRm+ NSCLC, receiving osimertinib. Primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS) and safety. Kaplan-Meier analyses and multivariate Cox proportional hazard models were performed. In total, 294 patients were included. Primary EGFR-mutations were mainly exon 19 deletions (54%) and p.L858R point mutations (30%). Osimertinib was given in first-line (40%), second-line (46%) or beyond (14%), with median PFS 14.4 (95% CI: 9.4-19.3), 13.9 (95% CI: 11.3-16.1) and 8.7 months (95% CI: 4.6-12.7), respectively. Patients with low BMI (<20.0 kg/m2 ) had significantly shorter PFS/OS compared to all other subgroups. Patients with a high plasma trough concentration in steady state (Cmin,SS ; >271 ng/mL) had shorter PFS compared to a low Cmin,SS (<163 ng/mL; aHR 2.29; 95% CI: 1.13-4.63). A significant longer PFS was seen in females (aHR = 0.61, 95% CI: 0.45-0.82) and patients with the exon 19 deletion (aHR = 0.58, 95% CI: 0.36-0.92). A trend towards longer PFS was seen for TP53 wild-type patients, while age did not impact PFS. Patients with a primary EGFR exon 19 deletion had longer PFS, while a low BMI, male sex and a high Cmin,SS were indicative for shorter PFS and/or OS. Age was not associated with effectiveness outcomes of osimertinib.

The use of pembrolizumab monotherapy for the management of head and neck squamous cell carcinoma (HNSCC) in the UK.

Pembrolizumab has received approval in the UK as first-line monotherapy for recurrent and/or metastatic HNSCC (R/M HNSCC) following the results of the KEYNOTE-048 trial, which demonstrated a longer overall survival (OS) in comparison to the EXTREME chemotherapy regimen in patients with a combined positive score (CPS) ≥1. In this article, we provide retrospective real-world data on the role of pembrolizumab monotherapy as first-line systemic therapy for HNSCC across 18 centers in the UK from March 20, 2020 to May 31, 2021. 211 patients were included, and in the efficacy analysis, the objective response rate (ORR) was 24.7%, the median progression-free survival (PFS) was 4.8 months (95% confidence interval [CI]: 3.6-6.1), and the median OS was 10.8 months (95% CI 9.0-12.5). Pembrolizumab monotherapy was well tolerated, with 18 patients having to stop treatment owing to immune-related adverse events (irAEs). 53 patients proceeded to second-line treatment with a median PFS2 of 10.2 months (95% CI: 8.8-11.5). Moreover, patients with documented irAEs had a statistically significant longer median PFS (11.3 vs. 3.3 months; log-rank p value = <.001) and median OS (18.8 vs. 8.9 months; log-rank p value <.001). The efficacy and safety of pembrolizumab first-line monotherapy for HNSCC has been validated using real-world data.

Building transparency and reproducibility into the practice of pharmacoepidemiology and outcomes research.

Real-world evidence (RWE) studies are increasingly used to inform policy and clinical decisions. However, there remain concerns about the credibility and reproducibility of RWE studies. Observational researchers should highlight the level of transparency of their studies by providing a succinct statement addressing study transparency with the publication of every paper, poster, or presentation that reports on a RWE study. In this paper, we propose a framework for an explicit transparency statement that declares the level of transparency a given RWE study has achieved across five key domains: 1) protocol, 2) pre-registration, 3) data, 4) code sharing, and 5) reporting checklists.

Validation of algorithms in studies based on routinely collected health data: general principles.

Clinicians, researchers, regulators, and other decision-makers increasingly rely on evidence from real-world data (RWD), including data routinely accumulating in health and administrative databases. RWD studies often rely on algorithms to operationalize variable definitions. An algorithm is a combination of codes or concepts used to identify persons with a specific health condition or characteristic. Establishing the validity of algorithms is a prerequisite for generating valid study findings that can ultimately inform evidence-based health care. This paper aims to systematize terminology, methods, and practical considerations relevant to the conduct of validation studies of RWD-based algorithms. We discuss measures of algorithm accuracy; gold/reference standard; study size; prioritizing accuracy measures; algorithm portability; and implication for interpretation. Information bias is common in epidemiologic studies, underscoring the importance of transparency in decisions regarding choice and prioritizing measures of algorithm validity. The validity of an algorithm should be judged in the context of a data source, and one size does not fit all. Prioritizing validity measures within a given data source depends on the role of a given variable in the analysis (eligibility criterion, exposure, outcome or covariate). Validation work should be part of routine maintenance of RWD sources.

Invited Commentary: Raising a High-Pressure Alarm About Pediatric Hypertension.

Hypertension is a common "silent killer" in adult medicine, but epidemiologic estimates of elevated blood pressure in children and adolescents are challenged by under-diagnosis and resultant low utilization of relevant administrative or billing codes. In the article by Horgan et al (Am J Epidemiol 2024), children and adolescents with hypertension and elevated blood pressure were identified using direct assessment of blood pressure measurements available in the electronic health record from both inpatient and outpatient visits ("clinical cohort") in comparison to diagnosis codes ("claims-based cohort"). The study population included 3.75 million pediatric healthcare visits available in the US Food and Drug Administration's Sentinel System. While the study applied a relatively novel methodology to interrogate available clinical data within the EHR to better understand the prevalence of pediatric hypertension and raised concern for a higher occurrence of hypertension among children and adolescents than previously realized using claims codes, the utility of the prevalence estimates may be limited by the potential for misclassification bias inherent in EHR data. However, these data raise important concerns about relaying solely on ICD-9-CM/ICD-10-CM codes to quantify the epidemiology of pediatric hypertension and highlight opportunities to address elevated blood pressure in children that could improve long-term cardiovascular health.

Cardiorenal effects of Angiotensin-converting enzyme inhibitors and Angiotensin receptor blockers in people underrepresented in trials: analysis of routinely collected data with emulation of a reference trial (ONTARGET).

Cardiovascular disease (CVD) is a leading cause of death globally. Angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB), compared in the ONTARGET trial, each prevent CVD. However, trial results may not be generalisable and their effectiveness in underrepresented groups is unclear. Using trial emulation methods within routine-care data to validate findings, we explored generalisability of ONTARGET results. For people prescribed an ACEi/ARB in the UK Clinical Practice Research Datalink GOLD from 1/1/2001-31/7/2019, we applied trial criteria and propensity-score methods to create an ONTARGET trial-eligible cohort. Comparing ARB to ACEi, we estimated hazard ratios for the primary composite trial outcome (cardiovascular death, myocardial infarction, stroke, or hospitalisation for heart failure), and secondary outcomes. As the pre-specified criteria were met confirming trial emulation, we then explored treatment heterogeneity among three trial-underrepresented subgroups: females, those aged ≥75 years and those with chronic kidney disease (CKD). In the trial-eligible population (n=137,155), results for the primary outcome demonstrated similar effects of ARB and ACEi, (HR 0.97 [95% CI: 0.93, 1.01]), meeting the pre-specified validation criteria. When extending this outcome to trial-underrepresented groups, similar treatment effects were observed by sex, age and CKD. This suggests that ONTARGET trial findings are generalisable to trial-underrepresented subgroups.

Power to the People: Why person-generated health data is important for pharmacoepidemiology.

Person-generated health data (PGHD) are valuable to study outcomes relevant to everyday living, to obtain information not otherwise available, for long-term follow-up and in situations where decisions cannot wait for traditional clinical research to be completed. While there is no dispute that these data are subject to bias, insights gained may be better than an information void, provided the biases are understood and acknowledged. People will share information known uniquely to them about exposures that may affect drug tolerance, safety and effectiveness, e.g., using non-prescription and complementary medications, alcohol, tobacco, illicit drugs, exercise, etc. Patients may be the best source of safety information when long-term follow-up is needed, e.g., the 5-15-year follow-up required for some gene therapies. Validation studies must be performed to evaluate what people can accurately report and when supplementary confirmation information is needed. But PGHD has already proven valuable in quantifying and contrasting COVID-19 vaccine benefits and risks, and for evaluating disease transmission and the accuracy of COVID-19 testing. Going forward, PGHD will be used for patient-measured and patient-relevant outcomes, including regulatory purposes, and will be linked to broader health data networks using tokenization, becoming a mainstay for signals about risks and benefits for diverse populations.