Citations

Objectives To understand the trade-offs between different statistical modeling approaches, using real world data with small sub-populations, with rare exposures and increasingly rare outcomes. In particular, to compare adjusted regression, inverse probability weighting, and matching. Methods Data for these analyses came from the RADAR (N=1,134) and combined CNICS/JHHCC (N=14,434) cohorts. We estimated prevalence ratios (PRs) for self-reported use of specific substances comparing subpopulations (SP), SP-1 vs SP-3 and SP-2 vs SP-3, where SP-1 was the largest proportion (92% in RADAR, 81% in CNICS/JHHCC), SP2 was moderate proportion (18% in CNICS/JHHCC) and SP-3 was the smallest proportion (8% in RADAR, 1% in CNICS/JHHCC) of the population. We calculated PRs using 1) unadjusted relative risk regression (RR); and adjusted estimates controlling for age, race/ethnicity, study site, and year of interview using: 2) standard adjustment in RR; 3) stabilized inverse probability of treatment weighting (IPTW); and 4) matching with up to 3 matches from SP-1 or SP-2 per SP-3 participant. Results For most substances, all methods yielded consistent estimates. There were large weights in some of the IPTW analyses and in three cases these resulted in substantially divergent estimates. For the comparison between SP-1 and SP-3, the estimate for smoking was 1.3-fold greater in the matched analysis (PR=1.33, 95% CI: 1.02-1.75) than in IPTW (PR=1.03, 95% CI: 0.78-1.37 ATE and PR=1.05, 95% CI: 0.88-1.26 ATT). Even more extreme divergence in estimates was observed for differences between SP-2 and SP-3 with respect to methamphetamine/amphetamine, (IPTW-ATE: PR=1.51, 95% CI: 0.79-2.89; IPTW-ATT: PR=2.36, 95% CI: 1.36-4.12); vs Matching: PR=2.71, 95%CI: 1.47-4.99) and cocaine (IPTW-ATE: PR=1.15, 95% CI: 0.55-2.38; IPTW-ATT: PR=1.81, 95% CI: 1.03-3.18); vs Matching: PR=1.38, 95%CI: 0.76-2.53). Conclusion The combination of a rare exposure and a rare outcome can produce challenges for commonly used confounding adjustment strategies, and it is often best to compare different modeling approaches to gain greater insight.

Background/Objectives: The PRO-CTCAE Average Composite Score (ACS), calculated as the mean of PRO-CTCAE composite scores, summarizes overall symptom and side effect burden. This study evaluated the test–retest reliability, responsiveness to change, known-groups validity, and sensitivity to group differences in the ACS. Methods: Analyses used the original PRO-CTCAE validation dataset, including lung (n = 174), breast (n = 222), and head and neck (n = 139) cancer cohorts, and data from the COMET-2 randomized phase III trial comparing cabozantinib (n = 53) and mitoxantrone–prednisone (n = 54) in men with previously treated prostate cancer. Test–retest reliability was assessed using intraclass correlation coefficients (ICCs) from two-way mixed-effects models for agreement. Responsiveness was evaluated by relating ACS change scores (Visit 1 minus follow-up Visit 2) to patient-reported global ratings of change (GRC; worsened, unchanged, or improved) using standardized response means (SRMs) and Jonckheere–Terpstra trend tests. Known-groups validity was examined by comparing mean ACS values between ECOG performance status groups (0–1 vs. 2–4). Sensitivity to treatment group differences was assessed using model-based area-under-the-curve (AUC) comparisons of longitudinal ACS trajectories. Results: Test–retest reliability was acceptable, with ICCs among GRC-defined stable patients of 0.80 (95% CI: 0.70–0.87) in lung cancer, 0.84 (95% CI: 0.77–0.89) in breast cancer, and 0.77 (95% CI: 0.63–0.86) in head and neck cancer; ICCs based on assessments completed one day apart ranged from 0.88 to 0.90. The ACS demonstrated responsiveness, with SRMs of 0.30/0.15/−0.37 (lung), 0.29/0.14/−0.40 (breast), and −0.01/−0.20/−0.56 (head/neck) for improved/no-change/worsened groups, respectively, and significant monotonic trends across GRC categories (all p < 0.01). Known-groups validity was supported by conceptually expected differences in ACS values across distinct levels of self-reported patient-reported physical functioning and ECOG performance status categories. Mean ACS values were lower among patients with good versus limited physical functioning (0.71 vs. 1.23 in lung cancer, 0.52 vs. 1.19 in breast cancer, and 0.69 vs. 1.29 in head and neck cancer) and among patients with ECOG PS 0–1 versus 2–4 (0.93 vs. 1.31, 0.74 vs. 1.22, and 0.90 vs. 1.06, respectively). In COMET-2, higher symptom burden was detected in the cabozantinib arm compared with the mitoxantrone–prednisone arm (AUC difference = 1.5, 95% CI: 0.2–2.8, p = 0.02). Conclusions: The ACS demonstrated acceptable test–retest reliability, responsiveness, and known-groups validity across multiple cancer populations. These findings support its use as a complementary summary measure of overall symptomatic adverse event burden alongside individual symptom-level analyses.

Abstract Introduction Underwater endoscopic mucosal resection (uEMR) technique has gained popularity for removal of large non-pedunculated colorectal polyps (LNPCPs) due to high en-bloc resection rates and lower recurrence rates. However, there is no information regarding outcomes of uEMR for giant colorectal polyps. Therefore, we aimed to evaluate the outcomes of uEMR for giant colorectal polyps across multiple centers in North America. Methods We conducted a multicenter retrospective study of adults with giant colorectal polyps undergoing uEMR between January 2019 and November 2025. Giant colorectal polyps were defined as LNPCPs ≥40 mm. Primary outcomes were technical success and rate of recurrent adenoma. Secondary outcomes were severe adverse events (SAEs) and predictors of technical success, recurrence, and SAEs. Results A total of 137 polyps, with mean polyp size 47.6 mm were included. Majority of the lesions were located in right colon (61%, n = 83) with the most common histopathology being high-grade dysplasia (HGD) (31.4%, n = 43). Technical success was achieved in 90.5% (n = 124) with en-bloc resection rate of 11.7% (n = 16). Polyp fibrosis (OR: 0.08) and HGD (OR: 0.15) were independent predictors of inability to achieve technical success. Of 92 (67.1%) patients with follow-up, recurrent polyp was present in 8.7% (n = 8). SAEs were noted in 9.5%, consisting of delayed bleeding (9.5%, n = 13), while no delayed perforation or post polypectomy syndrome was noted. Discussion Our study demonstrates that uEMR is technically feasible for the removal of giant colorectal polyps with an acceptable safety profile and recurrence rate.

Importance Ischemic heart disease (IHD), the leading cause of death in the US, is predominantly due to modifiable risk factors. Estimates of IHD mortality attributable to risk factors provide evidence for health policy decision-making. Objective To estimate the burden of IHD death attributable to risk factors in the US from 1990-2023. Design, Setting, and Participants The Global Burden of Disease Study 2023 (GBD 2023) used vital records and a broad set of epidemiologic data to estimate IHD death rates, risk factor exposure, and relative risk curves for risk-outcome pairs for 1990-2023 for the general population. Data analysis was performed from October 2024 to December 2025. Exposure Twelve metabolic, behavioral, and environmental risk factors. Main Outcomes and Measures The primary outcomes were IHD death rates per 100 000 persons, counts, and attributable risks from 1990-2023 by age, sex, and US state. Estimates include 95% uncertainty intervals (UI). IHD death rates were estimated using ensemble modeling methods. Risk exposures were estimated using bayesian meta-regression methods. Relative risks were estimated following the Burden of Proof framework. Results In 2023, there were 473 000 IHD deaths (95% UI, 414 000-510 000) in the US, a decrease of 58.7% (95% UI, 56.8%-61.0%) in age-standardized rate since 1990. Between 2010 and 2023, there was a 19.0% decrease (95% UI, 15.0%-22.9%) for males and a 24.5% decrease (95% UI, 20.3%-29.7%) for females in IHD death rates. High systolic blood pressure (SBP), dietary risks, and high low-density lipoprotein cholesterol (LDL-C) were the leading risk factors for IHD deaths in 2023, accounting for 47.2% (95% UI, 36.4%-57.0%), 38.6% (95% UI, 17.2%-56.8%), and 28.5% (95% UI, 19.3%-39.6%) of IHD deaths, respectively. Increased exposure to several risk factors substantially increased their attributable burden for IHD deaths in 2023, with high fasting plasma glucose (FPG) increasing 38.8% (95% UI, 11.5%-81.1%) and high body mass index (BMI) increasing 54.5% (95% UI, 41.8%-66.3%) since 1990. Smoking and particulate matter pollution had the greatest decrease in attributable IHD mortality since 1990, at 33.3% (95% UI, 23.6%-41.7%) and 74.9% (95% UI, 46.7%-88.8%), respectively. Conclusion and Relevance Per the results of this systematic analysis of GBD 2023, a total of 88.7% (95% UI, 83.4%-92.5%) of IHD deaths were attributable to modifiable risk factors in the US in 2023, with high SBP, dietary risks, and high LDL-C being the greatest contributors. High BMI and high FPG showed the largest attribution increases, while exposure to other risks did not increase significantly for the population.

Importance As the use of robotic cholecystectomy increases, its value remains poorly defined for complex elective cholecystectomy (CEC), where complex gallbladder pathology results in increased technical difficulty. Objective To determine whether a robotic approach is associated with improved clinical outcomes and altered total hospital cost as compared with a laparoscopic approach for patients undergoing CEC. Design, Setting, and Participants This cohort study analyzed data from an academic hepatobiliary referral center for patients who underwent cholecystectomy from August 2018 to August 2024. CEC was defined by preoperative criteria: prior aborted or partial cholecystectomy, presence of a cholecystostomy tube, and/or history of gallbladder perforation or fistula. Exposure Robotic-assisted vs laparoscopic cholecystectomy. Main Outcomes and Measures The primary outcome was a composite of an unplanned postoperative endoscopic retrograde cholangiopancreatography or interventional radiology procedure. Secondary outcomes included operative time, postoperative complications, and operative and total hospital costs. Results A total of 863 patients underwent cholecystectomy and met inclusion criteria; 525 (60.8%) were female and 338 (39.2%) were male, and their median (IQR) age was 61 (45-71) years. Among patients undergoing CEC, the laparoscopic approach was independently associated with an increased need for unplanned endoscopic or percutaneous intervention compared with the robotic group (odds ratio, 4.24; 95% CI, 1.24-14.52; P = .02). There were no significant differences in postoperative outcomes between the laparoscopic and robotic groups in patients undergoing non-CEC. Patients undergoing the laparoscopic approach had significantly reduced operating room costs when compared with patients undergoing a robotic approach in both the CEC ($7720 vs $8936, respectively) and non-CEC groups ($6368 vs $ 8351, respectively). However, there was no difference in the overall total cost of care between laparoscopic CEC and robotic CEC groups ($14 309 vs $14 476, respectively). The overall total cost of care was significantly higher for patients undergoing robotic non-CEC as compared with laparoscopic non-CEC ($11 416 vs $9925, respectively). Conclusions and Relevance This study found that for complex gallbladder disease, robotic cholecystectomy offers a clinical advantage, reducing complications and downstream interventions without increasing the overall costs of care. These findings suggest strategic application of the robotic platform may offer clinical advantages in high-complexity gallbladder surgery, maximizing patient benefit and resource efficiency.

OBJECTIVE Endovascular thrombectomy (EVT) for acute large-vessel occlusion stroke is well established, yet its role in patients presenting with minor stroke symptoms (National Institutes of Health Stroke Scale [NIHSS] score < 6) remains unclear. Prior studies have not accounted for intraprocedural factors that may influence outcomes in this subgroup. METHODS The authors analyzed 5693 patients from the STAR (Stroke and Thrombectomy and Aneurysm Registry), including 398 with low NIHSS scores, to evaluate the association between procedure time (PT) and outcomes. Among patients with low NIHSS scores, propensity score matching was used to compare outcomes between those with PT ≤ 35 versus > 35 minutes, a cutoff defined using receiver operating characteristic curve analysis. The authors performed a meta-analysis of studies reporting best medical management (BMM) outcomes in patients with low NIHSS scores. To compare these with EVT-treated patients, a matched BMM comparator cohort using stratification on pooled baseline characteristics was constructed. Outcomes included 90-day functional independence (modified Rankin Scale [mRS] scores 0–2), intracranial hemorrhage, and mortality. RESULTS PT had a stronger negative effect on outcomes in patients with low NIHSS scores compared with those with high scores, with a steeper decline in functional independence per minute of PT (slope: –0.45% vs –0.21%; p = 0.03 for interaction). Among patients with low scores, PT ≤ 35 minutes was associated with higher 90-day functional independence compared with the propensity score–matching cohort with PT > 35 minutes (82.6% vs 59.0%, p < 0.001). When benchmarked against BMM (75.2% mRS scores 0–2), patients undergoing EVT within 35 minutes had superior outcomes (85.1%, p = 0.047). In contrast, EVT with PT > 35 minutes resulted in worse outcomes than BMM (mRS scores 0–2: 59.8%, p = 0.008). The number needed to treat for PT ≤ 35 minutes was 10, whereas PT > 35 minutes yielded a number needed to harm of 6. CONCLUSIONS PT critically modulates the benefit of EVT in minor stroke. While efficient EVT yields better outcomes than BMM, prolonged procedures are associated with harm. These findings may explain prior inconsistent evidence on EVT in patients with low NIHSS scores and underscore the need to individualize procedural thresholds in this population.

ABSTRACT Ischemic events after contemporary percutaneous coronary intervention (PCI) are uncommon but carry high morbidity/mortality. Identifying patients at highest risk is critical to guide dual antiplatelet therapy (DAPT) intensity while minimizing bleeding. Current machine learning (ML) model‐developed risk scores do not incorporate pharmacogenetic data. To develop and externally validate ML models that integrate clinical, demographic, and CYP2C19 genetic information to predict 1‐year ischemic outcomes post‐PCI to refine clinical decision making. We analyzed 8317 patients from TAILOR‐PCI trial ( n = 4572) and the Precision PCI registry ( n = 3745). The outcome was a composite of cardiovascular death, myocardial infarction, stroke, and stent thrombosis at 1 year. Boruta feature selection identified 11 predictors. Multiple ML algorithms were trained in TAILOR‐PCI and validated in Precision PCI using cross‐validation and synthetic minority oversampling (SMOTE). Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The best external performance was achieved with a support vector machine (SVM, polynomial kernel) (AUC 0.667; sensitivity 0.871; specificity 0.282), while XGBoost provided a more balanced profile (AUC 0.619; sensitivity 0.442; specificity 0.688). Variable importance for the SVM polynomial model demonstrated that all 11 included Boruta feature selected predictors had relatively high importance (> 75). ML models trained on large clinical trial and real‐world registry datasets can help identify the small subset of patients at high ischemic risk after PCI. This distinction is of relevance because ischemic events are rare, and most patients may safely de‐escalate DAPT to reduce bleeding risk while maintaining ischemic protection through a multimodal approach to risk stratification. Trial Registration: TAILOR‐PCI URL: https://clinicaltrials.gov/ct2/show/NCT01742117

ABSTRACT Background Olfactory neuroblastoma (ONB) exhibits variable recurrence patterns, with significant late recurrences occurring years after treatment. We investigated cutoff periods to define late recurrence and identified predictors that distinguish patients at risk of late recurrence from those considered cured. Methods From a multi‐institutional cohort of 219 ONB patients treated at nine centers, we analyzed 77 patients with documented recurrence. Using a 48‐month cutoff to define early (< 48 months) versus late (≥ 48 months) recurrence, we evaluated 35 clinical, anatomic, and treatment variables using Firth penalized logistic regression across three comparisons: (1) late versus early recurrence timing, (2) late recurrence versus no recurrence, and (3) early recurrence versus no recurrence. Results Thirty‐four of the 77 (44.2%) recurrences were classified as late. Among the 77 patients who recurred, smaller tumor volume (OR 0.243, p = 0.035) and lower novel Dulguerov staging (OR 0.802, p = 0.038) were associated with late, rather than early recurrence. When patients with late recurrence were compared to those who remained disease‐free, radiographic skull base bone involvement was the strongest independent predictor (OR 2.90, 95% CI 1.14–8.64, p = 0.025), and this effect strengthened after adjusting for tumor volume (OR 3.80, p = 0.029). Pathologic dural invasion (OR 3.29, p = 0.013), Kadish stage (OR 2.02, p = 0.026), and T‐stage (OR 1.32, p = 0.040) were also significant. Conclusions A 48‐month cutoff effectively stratifies ONB recurrence risk. Skull base bone involvement independently predicts recurrence when compared to nonrecurrent cases and uniquely persists as a risk factor for late recurrence. These findings establish skull base bone involvement as a novel biomarker for risk‐stratified surveillance protocols.