Evaluating the Capabilities of Generative AI Tools in Understanding Medical Papers: Qualitative Study.

BACKGROUND: Reading medical papers is a challenging and time-consuming task for doctors, especially when the papers are long and complex. A tool that can help doctors efficiently process and understand medical papers is needed. OBJECTIVE: This study aims to critically assess and compare the comprehension capabilities of large language models (LLMs) in accurately and efficiently understanding medical research papers using the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist, which provides a standardized framework for evaluating key elements of observational study. METHODS: The study is a methodological type of research. The study aims to evaluate the understanding capabilities of new generative artificial intelligence tools in medical papers. A novel benchmark pipeline processed 50 medical research papers from PubMed, comparing the answers of 6 LLMs (GPT-3.5-Turbo, GPT-4-0613, GPT-4-1106, PaLM 2, Claude v1, and Gemini Pro) to the benchmark established by expert medical professors. Fifteen questions, derived from the STROBE checklist, assessed LLMs' understanding of different sections of a research paper. RESULTS: LLMs exhibited varying performance, with GPT-3.5-Turbo achieving the highest percentage of correct answers (n=3916, 66.9%), followed by GPT-4-1106 (n=3837, 65.6%), PaLM 2 (n=3632, 62.1%), Claude v1 (n=2887, 58.3%), Gemini Pro (n=2878, 49.2%), and GPT-4-0613 (n=2580, 44.1%). Statistical analysis revealed statistically significant differences between LLMs (P<.001), with older models showing inconsistent performance compared to newer versions. LLMs showcased distinct performances for each question across different parts of a scholarly paper-with certain models like PaLM 2 and GPT-3.5 showing remarkable versatility and depth in understanding. CONCLUSIONS: This study is the first to evaluate the performance of different LLMs in understanding medical papers using the retrieval augmented generation method. The findings highlight the potential of LLMs to enhance medical research by improving efficiency and facilitating evidence-based decision-making. Further research is needed to address limitations such as the influence of question formats, potential biases, and the rapid evolution of LLM models.

Two assumptions of the prior event rate ratio approach for controlling confounding can be evaluated by self-controlled case series and dynamic random intercept modeling.

OBJECTIVES: The prior event rate ratio (PERR) is a recently developed approach for controlling confounding by measured and unmeasured covariates in real-world evidence research and observational studies. Despite its rising popularity in studies of safety and effectiveness of biopharmaceutical products, there is no guidance on how to empirically evaluate its model assumptions. We propose two methods to evaluate two of the assumptions required by the PERR, specifically, the assumptions that occurrence of outcome events does not alter the likelihood of receiving treatment, and that earlier event rate does not affect later event rate. STUDY DESIGN AND SETTING: We propose using self-controlled case series (SCCS) and dynamic random intercept modeling (DRIM), respectively, to evaluate the two aforementioned assumptions. A nonmathematical introduction of the methods and their application to evaluate the assumptions are provided. We illustrate the evaluation with secondary analysis of deidentified data on pneumococcal vaccination and clinical pneumonia in The Gambia, West Africa. RESULTS: SCCS analysis of data on 12,901 vaccinated Gambian infants did not reject the assumption of clinical pneumonia episodes had no influence on the likelihood of pneumococcal vaccination. DRIM analysis of 14,325 infants with a total of 1719 episodes of clinical pneumonia did not reject the assumption of earlier episodes of clinical pneumonia had no influence on later incidence of the disease. CONCLUSION: The SCCS and DRIM methods can facilitate appropriate use of the PERR approach to control confounding. PLAIN LANGUAGE SUMMARY: The prior event rate ratio is a promising approach for analysis of real-world data and observational studies. We propose two statistical methods to evaluate the validity of two assumptions it is based on. They can facilitate appropriate use of the prior even rate ratio.

Cadmium exposure and risk of hypertension: a systematic review and dose-response meta-analysis.

BACKGROUND: Exposure to environmental toxic metals represents a significant global public health concern. Many studies have reported that cadmium (Cd) exposure increases the risk of hypertension. Since the shape of such relation has not been well characterized, we assessed it by performing a systematic review and dose-response meta-analysis of human studies. METHODS: We searched the literature through September 5, 2024 to identify papers related to Cd, hypertension, and blood pressure. Inclusion criteria were: observational design, adult population, assessment of exposure using Cd biomarkers, and availability of exposure category-specific risk estimates for hypertension. We performed a dose-response meta-analysis of the results from included studies. RESULTS: Of the 18 studies published between 2006-2024, most had a cross-sectional design. Cd was measured in whole blood and/or urine in almost all studies, whereas only two studies measured Cd in serum. The dose-response meta-analysis indicated an almost linear relation between urinary Cd concentrations and hypertension risk with RR=1.18, 95% CI 1.02-1.37 at 2.0 µg/g creatinine compared with no exposure. In contrast, the association between blood Cd concentrations and hypertension risk was non-linear: there was a steep monotonic increase in risk for Cd concentrations below 2 µg/L, reaching a RR of 1.48 (95% CI 1.17-1.86) at 2.0 µg/L, after which a plateau seemed reached. We found similar trends when restricting to studies of Asian population, while when considering North American studies, hypertension risk increased above 1.0 µg/g creatinine. CONCLUSIONS: In this dose-response meta-analysis, risk of hypertension showed a non-linear positive association with blood Cd concentrations and a linear positive association with urinary Cd concentrations. Inconsistency in the shape of associations could relate to the different timing of exposure assessed by the biomarkers or the alteration Cd excretion at increasing exposure levels. Mitigation of Cd exposure is confirmed as a public health priority for chronic disease prevention.

Arthroscopic Assessment of the Incidence of Biceps Pulley Lesions Associated With Rotator Cuff Tears: An Observational Study.

The shoulder joint houses a stabilizing structure called the biceps pulley. Biceps pulley lesions can trigger anterior shoulder pain and frequently coincide with rotator cuff tears, whose prevalence rises with age. In our study, we aim to assess the incidence of biceps pulley lesions associated with rotator cuff tears in patients undergoing arthroscopic repair, the possible associated factors, and whether MRI findings were correlated with them. This study was a prospective observational one conducted at Al-Hadra University Hospital. The patients aged 40 to 65 years were indicated for arthroscopic repair of a rotator cuff tear. We used IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp. to conduct the analysis. A total of 60 patients were enrolled in the study. The mean age was 50.97 ± 6.90. The overall incidence of biceps pulley lesions was 85%. Older age was found to be significantly associated with increased incidence. On the other hand, gender, and the mode of injury (cuff tear) had no significant associations with the incidence. Also, formal MR had no significance in diagnosing biceps pulley lesions. The overall incidence of biceps pulley lesions in the current study was 85%. The older the patient with a cuff tear, the greater the incidence of finding a pulley lesion arthroscopically. Moreover, MRI did not have a significant role in diagnosing the biceps pulley lesions.

Development of a Canadian Guidance for Reporting Real-world Evidence for Regulatory and Health-Technology Assessment (HTA) Decision Making.

Real-world evidence (RWE) can complement and fill knowledge gaps from randomized controlled trials to assist in health-technology assessment (HTA) for regulatory decision-making. However, the generation of RWE is an intricate process with many sequential decision points, and different methods and approaches may impact the quality and reliability of evidence. Standardization and transparency in reporting these decisions is imperative to appraise RWE and incorporate it into HTA decision-making. A partnership between Canadian health system stakeholders, namely Health Canada and Canada's Drug Agency (formerly the Canadian Agency for Drugs and Technologies in Health (CADTH)), was established to develop a guidance for standardization of reporting of RWE for regulatory and HTA decision-making in Canada. In this article, we describe the methods to develop the Guidance for Reporting Real-World Evidence document and checklist for reporting RWE for regulatory and HTA decision-making in Canada. This guidance can be adapted for other jurisdictions and will have future extensions to incorporate emerging issues with RWE and HTA decision-making.

The impact of multimorbidity on QoL in inflammatory myopathies: COVAD cluster analysis.

OBJECTIVE: The presence of comorbidities can substantially affect patients' quality of life, but data regarding their impact on idiopathic inflammatory myopathies (IIMs) are limited. METHODS: We examined the prevalence of comorbidities in IIM patients, other autoimmune rheumatic diseases (oAIRDs), and healthy controls (HCs), using data from the self-reported COVAD-2 survey. We defined Basic Multimorbidity (BM) as the presence of ≥ 2 non-rheumatic chronic conditions and Complex Multimorbidity (CM) as the presence of ≥ 3 non-rheumatic chronic conditions affecting ≥3 organ systems. Hierarchical Clustering on Principal Components was performed for grouping. RESULTS: Among the COVAD respondents, 1558 IIMs, 4591 oAIRDs, and 3652 HCs were analysed. IIMs exhibited a high burden of comorbidities (OR: 1.62 vs oAIRDs and 2.95 vs HCs, p< 0.01), BM (OR 1.66 vs oAIRDs and 3.52 vs HCs, p< 0.01), CM (OR: 1.69 vs AIRDs and 6.23 vs HCs, p< 0.01), and mental health disorders (MHDs) (OR 1.33 vs oAIRDs and 2.63 vs HCs, p< 0.01). Among the IIM patients, those with comorbidities or MHDs had lower PROMIS Global Physical (PGP), PROMIS Global Mental (PGM), and PROMIS Physical Function (SF10) scores, and higher fatigue (F4a) scores (all p< 0.001). PGP, PGM, SF10a and F4a were influenced by age, active disease, BM, and MHDs. Four distinct clusters were identified among the IIMs according to comorbidities and PROMIS scores. CONCLUSION: Patients with IIMs have a higher burden of comorbidities that influence physical and mental health, identifiable as clinical clusters for optimized and holistic management approaches.

Using a Quality Management System and Risk-based Approach in Observational Studies to Obtain Robust Real-World Evidence.

The results of observational studies using real-world data, known as real-world evidence, have gradually started to be used in drug development and decision-making by policymakers. A good quality management system-a comprehensive system of process, data, and documentation to ensure quality-is important in obtaining real-world evidence. A risk-based approach is a common quality management system used in interventional studies. We used a quality management system and risk-based approach in an observational study on a designated intractable disease. Our multidisciplinary team assessed the risks of the real-world data study comprehensively and systematically. When using real-world data and evidence to support regulatory decisions, both the quality of the database and the validity of the outcome are important. We followed the seven steps of the risk-based approach for both database selection and research planning. We scored the risk of two candidate databases and chose the Japanese National Database of designated intractable diseases for this study. We also conducted a quantitative assessment of risks associated with research planning. After prioritizing the risks, we revised the research plan and outcomes to reflect the risk-based approach. We concluded that implementing a risk-based approach is feasible for an observational study using real-world data. Evaluating both database selection and research planning is important. A risk-based approach can be essential to obtain robust real-world evidence.

Decoding betaine: A critical analysis of therapeutic potential vs. marketing hype - a narrative review.

Research interest in betaine supplementation has surged in recent years, for both enhancing sports performance and treating metabolic conditions. This surge aligns with an expanding market for betaine supplements, which are often marketed as promising aids for a range of metabolic conditions. Despite numerous in vitro and in vivo studies elucidating betaine's involvement in crucial metabolic pathways, consensus remains elusive on its clinical efficacy as a dietary supplement, based on results from randomized controlled trials. One analysis of dietary betaine intake in 28 observational studies showed a mean intake of 182 mg/day of betaine, with the main sources including grain-based foods, baked products, grains, cereals, and vegetables. Analysis of the results from human randomized clinical trials has shown that betaine supplementation improves body composition when combined with physical activity. Additionally, betaine supplementation decreases serum homocysteine (Hcy) levels, but does not affect liver enzymes, triglycerides (TG), or high-density lipoprotein (HDL) cholesterol levels, though it does increase total cholesterol (TC) and low-density lipoprotein (LDL) cholesterol levels at doses ≥ 4 g/day. Market analysis has demonstrated that betaine is a popular supplement for supporting various physiological processes, such as digestibility, methylation, physical performance, and liver or cardiovascular health. Manufacturers suggest a diverse range of applications for betaine supplements, with fourteen different uses identified. Additionally, high variability can be seen in the recommended usage directions for betaine. This narrative research sheds light on the evolving landscape of betaine supplementation and highlights the need for further investigation to clarify its clinical efficacy.

Dietary inflammatory potential and severe headache or migraine: a systematic review of observational studies.

OBJECTIVES: We conducted the current systematic review to investigate the association between dietary inflammatory index (DII) and severe headaches or migraine among adults via synthesizing observational evidence. METHOD: We conducted a systematic literature search of observational studies through PubMed, Scopus, and Web of Science databases from inception until July 2024. The PECO framework was implemented to select eligible studies as follows: Population (adults with severe headache or migraine), Exposure (individuals with the highest adherence to a pro-inflammatory diet), Comparison (individuals with the lowest adherence to a pro-inflammatory diet), Outcome (risk of developing severe headache or migraine, headaches frequency, duration, severity, and migraine-related disability). RESULTS: After reviewing six studies involving 31,958 individuals, we found that following an anti-inflammatory diet is associated with a lower frequency and severity of migraine headaches. Additionally, our research revealed that individuals with migraines tend to have lower adherence to an anti-inflammatory diet when compared to people without migraines. Surprisingly, adherence to a pro-inflammatory diet was linked to a reduced risk of chronic daily headaches. CONCLUSION: Present findings imply a negative link between an inflammatory diet and severe headaches or migraine. However, further well-designed longitudinal studies are needed to interpret the causality and shed light on the underlying mechanisms.

Effectiveness of cladribine compared to fingolimod, natalizumab, ocrelizumab and alemtuzumab in relapsing-remitting multiple sclerosis.

BACKGROUND: Comparisons between cladribine and other potent immunotherapies for multiple sclerosis (MS) are lacking. OBJECTIVES: To compare the effectiveness of cladribine against fingolimod, natalizumab, ocrelizumab and alemtuzumab in relapsing-remitting MS. METHODS: Patients with relapsing-remitting MS treated with cladribine, fingolimod, natalizumab, ocrelizumab or alemtuzumab were identified in the global MSBase cohort and two additional UK centres. Patients were followed for ⩾6/12 and had ⩾3 in-person disability assessments. Patients were matched using propensity score. Four pairwise analyses compared annualised relapse rates (ARRs) and disability outcomes. RESULTS: The eligible cohorts consisted of 853 (fingolimod), 464 (natalizumab), 1131 (ocrelizumab), 123 (alemtuzumab) or 493 (cladribine) patients. Cladribine was associated with a lower ARR than fingolimod (0.07 vs. 0.12, p = 0.006) and a higher ARR than natalizumab (0.10 vs. 0.06, p = 0.03), ocrelizumab (0.09 vs. 0.05, p = 0.008) and alemtuzumab (0.17 vs. 0.04, p < 0.001). Compared to cladribine, the risk of disability worsening did not differ in patients treated with fingolimod (hazard ratio (HR) 1.08, 95% confidence interval (CI) 0.47-2.47) or alemtuzumab (HR 0.73, 95% CI 0.26-2.07), but was lower for patients treated with natalizumab (HR 0.35, 95% CI 0.13-0.94) and ocrelizumab (HR 0.45, 95% CI 0.26-0.78). There was no evidence for a difference in disability improvement. CONCLUSION: Cladribine is an effective therapy that can be viewed as a step up in effectiveness from fingolimod, but is less effective than the most potent intravenous MS therapies.

Metadata for Data dIscoverability aNd Study rEplicability in obseRVAtional Studies (MINERVA): Development and Pilot of a Metadata List and Catalogue in Europe.

PURPOSE: Metadata for data dIscoverability aNd study rEplicability in obseRVAtional studies (MINERVA), a European Medicines Agency-funded project (EUPAS39322), defined a set of metadata to describe real-world data sources (RWDSs) and piloted metadata collection in a prototype catalogue to assist investigators from data source discoverability through study conduct. METHODS: A list of metadata was created from a review of existing metadata catalogues and recommendations, structured interviews, a stakeholder survey, and a technical workshop. The prototype was designed to comply with the FAIR principles (findable, accessible, interoperable, reusable), using MOLGENIS software. Metadata collection was piloted by 15 data access partners (DAPs) from across Europe. RESULTS: A total of 442 metadata variables were defined in six domains: institutions (organizations connected to a data source); data banks (data collections sustained by an organization); data sources (collections of linkable data banks covering a common underlying population); studies; networks (of institutions); and common data models (CDMs). A total of 26 institutions were recorded in the prototype. Each DAP populated the metadata of one data source and its selected data banks. The number of data banks varied by data source; the most common data banks were hospital administrative records and pharmacy dispensation records (10 data sources each). Quantitative metadata were successfully extracted from three data sources conforming to different CDMs and entered into the prototype. CONCLUSIONS: A metadata list was finalized, a prototype was successfully populated, and a good practice guide was developed. Setting up and maintaining a metadata catalogue on RWDSs will require substantial effort to support discoverability of data sources and reproducibility of studies in Europe.

Specifying a target trial protocol to estimate the effect of preconception treatment of periodontitis on time-to-pregnancy: A commentary and applied example.

BACKGROUND: The target trial framework was developed as a strategy to design and analyze observational epidemiologic studies with the aim of reducing bias due to analytic decisions. It involves designing a hypothetical randomized trial to answer a question of interest and systematically considering how to use observational data to emulate each trial component. AIMS: The primary aim of this paper is to provide a detailed example of the application of the target trial framework to a research question in oral epidemiology. MATERIALS AND METHODS: We describe the development of a hypothetical target trial and emulation protocol to evaluate the effect of preconception periodontitis treatment on time-to-pregnancy. We leverage data from Pregnancy Study Online (PRESTO), a preconception cohort, to ground our example in existing observational data. We discuss the decision-making process for each trial component, as well as limitations encountered. RESULTS: Our target trial application revealed data limitations that precluded us from carrying out the proposed emulation. Implications for data quality are discussed and we provide recommendations for researchers interested in conducting trial emulations in the field of oral epidemiology. DISCUSSION: The target trial framework has the potential to improve the validity of observational research in oral health, when properly applied. CONCLUSION: We encourage the broad adoption of the target trial framework to the field of observational oral health research and demonstrate its value as a tool to identify directions for future research.

Exposure variables in veterinary epidemiology: are they telling us what we think they are?

This manuscript summarizes a presentation delivered by the first author at the 2024 symposium for the Calvin Schwabe Award for Lifetime Achievement in Veterinary Epidemiology and Preventive Medicine, which was awarded to Dr. Jan Sargeant. Epidemiologic research plays a crucial role in understanding the complex relationships between exposures and health outcomes. However, the accuracy of the conclusions drawn from these investigations relies upon the meticulous selection and measurement of exposure variables. Appropriate exposure variable selection is crucial for understanding disease etiologies, but it is often the case that we are not able to directly measure the exposure variable of interest and use proxy measures to assess exposures instead. Inappropriate use of proxy measures can lead to erroneous conclusions being made about the true exposure of interest. These errors may lead to biased estimates of associations between exposures and outcomes. The consequences of such biases extend beyond research concerns as health decisions can be made based on flawed evidence. Recognizing and mitigating these biases are essential for producing reliable evidence that informs health policies and interventions, ultimately contributing to improved population health outcomes. To address these challenges, researchers must adopt rigorous methodologies for exposure variable selection and validation studies to minimize measurement errors.

Practice-based research in dentistry: Exploring methodologies, benefits, and challenges.

BACKGROUND: Practice-Based Research Network (PBRN) studies typically assess the effectiveness of clinical interventions in settings that match real-world conditions. Dental PBRNs have the capacity to amass, identify, and analyze vast amounts of data from patient populations that include diverse racial, ethnic, socio-economic, and geographic backgrounds. These dental studies encompass a broad spectrum of healthcare aspects, including prevention, diagnosis, symptom and disease treatment, quality enhancement, and care coordination. METHODS: An extensive range of research methodologies can be employed within dental PBRNs to investigate these topics, including randomized controlled trials. Dental PBRNs have evolved from primarily focusing on case observations to leveraging advanced network infrastructure and collaborating across multiple regional and national sites. In addition to producing numerous high-impact peer-reviewed publications, study results have led to improved clinical care. However, PBRNs encounter challenges, such as the sustainability of research capacity (relying heavily on ongoing support from funding agencies), diverse research cultures, and an imperative to design studies that are both feasible and relevant to everyday clinical practice. Recognizing the pivotal role of real-world evidence, it is important to have sustained investment in dental PBRN infrastructure and feasible opportunities for practitioners to participate in network activities nationwide. CONCLUSION: Practice-Based Research Network studies capitalize on an important research context within which to investigate a range of clinical topics that can employ multiple research methodologies. However, sustaining productive networks requires strategic effort, ongoing financial support, and customized organizational skills.

crossnma: An R package to synthesize cross-design evidence and cross-format data using network meta-analysis and network meta-regression.

BACKGROUND: Although aggregate data (AD) from randomised clinical trials (RCTs) are used in the majority of network meta-analyses (NMAs), other study designs (e.g., cohort studies and other non-randomised studies, NRS) can be informative about relative treatment effects. The individual participant data (IPD) of the study, when available, are preferred to AD for adjusting for important participant characteristics and to better handle heterogeneity and inconsistency in the network. RESULTS: We developed the R package crossnma to perform cross-format (IPD and AD) and cross-design (RCT and NRS) NMA and network meta-regression (NMR). The models are implemented as Bayesian three-level hierarchical models using Just Another Gibbs Sampler (JAGS) software within the R environment. The R package crossnma includes functions to automatically create the JAGS model, reformat the data (based on user input), assess convergence and summarize the results. We demonstrate the workflow within crossnma by using a network of six trials comparing four treatments. CONCLUSIONS: The R package crossnma enables the user to perform NMA and NMR with different data types in a Bayesian framework and facilitates the inclusion of all types of evidence recognising differences in risk of bias.

Racial and ethnic associations with interstitial lung disease and healthcare utilization in patients with systemic sclerosis.

OBJECTIVE: Racial and ethnic differences in presentation and outcomes have been reported in systemic sclerosis (SSc) and SSc-interstitial lung disease (ILD). However, prior studies have limited diversity. We aim to evaluate if there are racial/ethnic differences associated with ILD, time intervals between SSc and ILD and with emergency department (ED) visit or hospitalization rates. METHODS: Clinical and sociodemographic variables were extracted for 756 patients with SSc from longitudinal health records in an integrated health-system. Logistic regression models analyzed the association of covariates with ILD and age at SSc-ILD. Healthcare outcomes were analyzed with complementary log-log regression models. RESULTS: Overall, 33.7% of patients in the cohort had an ILD code, with increased odds for Asian (odds ratio [OR], 2.60; 95% confidence interval [CI], 1.29-5.28; p=0.008) compared with White patients. The predicted age in years of SSc-ILD was younger for Hispanic (estimate, -6.5; 95% CI, -13--0.21; p = 0.04) and Black/African American patients (-10; 95% CI -16--4.9; p < 0.001) compared with White patients. Black/African American patients were more likely to have an ILD code before an SSc code (59% compared with 20.6% of White patients), and the shortest interval from SSc to ILD (3 months). Black/African American (HR, 2.59; 95% CI 1.47-4.49; p = 0.001) and Hispanic patients (HR 2.29; 95% CI 1.37- 3.82; p = 0.002) had higher rates of an ED visit. CONCLUSION: We found that odds of SSc-ILD differed by racial/ethnic group, minoritized patients had earlier age of presentation, and greater rates of an ED visit.

Evaluation of the proportional hazards assumption and covariate adjustment methods in comparative surgical observational studies with time-to-event endpoints.

INTRODUCTION: Comparative studies on surgical treatments with time-to-event endpoints have provided substantial evidence for clinical practice, but the accurate use of survival data analysis and the control of confounding bias remain big challenges. METHODS: This was a survey of surgical studies with survival outcomes published in four general medical journals and five general surgical journals in 2021. The two most concerned statistical issues were evaluated, including confounding control by propensity score analysis (PSA) or multivariable analysis and testing of proportional hazards (PH) assumption in Cox model. RESULTS: A total of 74 studies were included, comprising 63 observational studies and 11 randomized controlled trials. Among the observational studies, the proportion of studies utilizing PSA in surgical oncology and non-oncology studies was similar (40.9 % versus 36.8 %, P = 0.762). However, the former reported a significantly lower proportion of PH assumption assessments compared to the latter (13.6 % versus 42.1 %, P = 0.020). Twenty-five observational studies (25/63) used PSA methods, but two-thirds of them (17/25) showed unclear balance of baseline data after PSA. And the proportion of PH assumption testing after PSA was slightly lower than that before PSA, but the difference was not statistically significant (24.0 % versus 28.0 %, P = 0.317). Comprehensive suggestions were given on confounding control in survival analysis and alternative resolutions for non-compliance with PH assumption. CONCLUSION: This study highlights suboptimal reporting of PH assumption evaluation in observational surgical studies both before and after PSA. Efforts and consensus are needed with respect to the underlying assumptions of statistical methods.

Motivators, Barriers, and Facilitators to Choosing Care in VA Facilities Versus VA-Purchased Care.

Many Veterans receive Department of Veterans Affairs (VA)-purchased care from non-VA facilities but little is known about factors that Veterans consider for this choice. Between May 2020 and August 2021, we surveyed VA-purchased care-eligible VA patients about barriers and facilitators to choosing where to receive care. We examined the association between travel time to their VA facility and their choice of VA-purchased care (VA-paid health care received in non-VA settings) versus VA facility and whether this association was modified by distrust. We received 1,662 responses and 692 (42%) chose a VA facility. Eighty percent reported quality care was in their top three factors that influenced their decision. Respondents with the highest distrust and who lived >1 hr from the nearest VA facility had the lowest predicted probability (PP) of choosing VA (PP 15%; 95% confidence interval: 10%-20%). Veterans value quality of care. VA and other health care systems should consider patient-centered ways to improve and publicize quality and reduce distrust.

Intention to treat and per protocol analyses: differences and similarities.

Randomized trials can take more explanatory or more pragmatic approaches. Pragmatic studies, conducted closer to real-world conditions, assess treatment effectiveness while considering factors like protocol adherence. In these studies, intention-to-treat (ITT) analysis is fundamental, comparing outcomes regardless of the actual treatment received. Explanatory trials, conducted closer to optimal conditions, evaluate treatment efficacy, commonly with a per protocol (PP) analysis, which includes only outcomes from adherent participants. ITT and PP are strategies used in the conception, design, conduct (protocol execution), analysis, and interpretation of trials. Each serves distinct objectives. While both can be valid, when bias is controlled, and complementary, each has its own limitations. By excluding nonadherent participants, PP analyses can lose the benefits of randomization, resulting in group differences in factors (influencing adherence and outcomes) that were present at baseline. Additionally, clinical and social factors affecting adherence can also operate during follow-up, that is, after randomization. Therefore, incomplete adherence may introduce postrandomization confounding. Conversely, ITT analysis, including all participants regardless of adherence, may dilute treatment effects. Moreover, varying adherence levels could limit the applicability of ITT findings in settings with diverse adherence patterns. Both ITT and PP analyses can be affected by selection bias due to differential losses and nonresponse (ie, missing data) during follow-up. Combining high-quality and comprehensive data with advanced statistical methods, known as g-methods, like inverse probability weighting, may help address postrandomization confounding in PP analysis as well as selection bias in both ITT and PP analyses.