Shah, Nilay

The optimal patient panel size (PPS) in primary care and the factors determining it remain unclear. We conducted a meta-narrative review of the literature to evaluate factors influencing PPS and assess its association with patient outcomes. A comprehensive search of electronic databases was performed from inception through December 2023, focusing on original studies reporting factors used to determine PPS and related outcomes (eg, clinical outcomes, process measures, and resource utilization). A total of 48 studies were included, identifying 7 key factors influencing PPS. Smaller panels were associated with improved patient satisfaction, continuity of care, and health promotion, while clinical outcomes, utilization, and costs showed minimal impact by PPS. Panel size was primarily associated with patient age, sex, comorbidities, and practice type and structure. Community-based centers typically managed smaller panels, often staffed by female clinicians and serving socioeconomically disadvantaged populations with greater health needs than hospital-based practices. Female clinicians were also independently associated with managing smaller panels, higher quality care indicators, fewer emergency department visits, and improved patient satisfaction. Determining the ideal PPS is a multifaceted process influenced by practice setting, patient demographics, and clinician characteristics. While practice-related factors showed limited association with PPS, patient-reported outcomes were more closely linked to it. Primary care practices should tailor panel sizes to their patient populations, emphasizing a patient-centered approach and ensuring adequate infrastructure support to optimize care delivery.

PURPOSE Allogeneic hematopoietic cell transplantation (HCT) improves outcomes for patients with AML harboring an internal tandem duplication mutation of FLT3 ( FLT3-ITD) AML. These patients are routinely treated with a FLT3 inhibitor after HCT, but there is limited evidence to support this. Accordingly, we conducted a randomized trial of post-HCT maintenance with the FLT3 inhibitor gilteritinib (ClinicalTrials.gov identifier: NCT02997202 ) to determine if all such patients benefit or if detection of measurable residual disease (MRD) could identify those who might benefit. METHODS Adults with FLT3-ITD AML in first remission underwent HCT and were randomly assigned to placebo or 120 mg once daily gilteritinib for 24 months after HCT. The primary end point was relapse-free survival (RFS). Secondary end points included overall survival (OS) and the effect of MRD pre- and post-HCT on RFS and OS. RESULTS Three hundred fifty-six participants were randomly assigned post-HCT to receive gilteritinib or placebo. Although RFS was higher in the gilteritinib arm, the difference was not statistically significant (hazard ratio [HR], 0.679 [95% CI, 0.459 to 1.005]; two-sided P = .0518). However, 50.5% of participants had MRD detectable pre- or post-HCT, and, in a prespecified subgroup analysis, gilteritinib was beneficial in this population (HR, 0.515 [95% CI, 0.316 to 0.838]; P = .0065). Those without detectable MRD showed no benefit (HR, 1.213 [95% CI, 0.616 to 2.387]; P = .575). CONCLUSION Although the overall improvement in RFS was not statistically significant, RFS was higher for participants with detectable FLT3-ITD MRD pre- or post-HCT who received gilteritinib treatment. To our knowledge, these data are among the first to support the effectiveness of MRD-based post-HCT therapy.

Background: Physicians’ professional networks are an important source of new medical information and have been shown to influence the adoption of new treatments, but it is unknown how physician networks impact the de-adoption of harmful practices. Methods: We analyzed changes in physicians’ use of dronedarone after the PALLAS trial (Palbociclib Collaborative Adjuvant Study; November 2011) showed that dronedarone increased the risk of death from cardiovascular events among patients with permanent atrial fibrillation. Deidentified administrative claims from the OptumLabs Data Warehouse were combined with physicians’ demographic information from the Doximity database and publicly available data on physicians’ patient-sharing relationships compiled by the Centers for Medicare and Medicaid Services. We used a linear probability model with an interrupted linear time trend specification to model the impact of the PALLAS trial on physicians’ dronedarone usage between 2009 and 2014. Results: Before the PALLAS trial, the use of dronedarone was increasing by 0.22 percentage points per quarter (95% CI, 0.19–0.25) in our Medicare Advantage sample (N=343 429 patient-quarter observations) and 0.63 percentage points per quarter (95% CI, 0.52–0.75) in our commercially insured sample (N=44 402 patient-quarter observations). After the PALLAS trial and subsequent United States Food and Drug Administration black box warning, physicians in the Medicare Advantage sample with an above-median number of network connections to other physicians decreased their quarterly usage of dronedarone by 0.12 percentage points more per quarter (95% CI, −0.20 to −0.04; P =0.031) than physicians with equal to or below the median number of network connections. Similar patterns existed in the commercially insured sample ( P =0.0318). Conclusions: After controlling for a wide range of patient, physician, and geographic characteristics, physicians with a greater number of network connections were faster de-adopters of dronedarone for patients with permanent atrial fibrillation after the PALLAS trial and subsequent United States Food and Drug Administration black box warning detailed the harmfulness of dronedarone for these patients. Policies for improving physicians’ responsiveness to new medical information should consider utilizing the influence of these important professional network relationships.

Background: This paper assesses obesity- and smoking-related incremental healthcare costs for the employees and dependents of a large U.S. employer. Objectives: Unlike previous studies, this study evaluates the distributional effects of obesity and smoking on healthcare cost distribution using a recently developed econometric framework: the unconditional quantile regression (UQR). Methods: Results were compared with the traditional conditional quantile regression (CQR), and the generalized linear modeling (GLM) framework that is commonly used for modeling healthcare cost. Results: The study found strong evidence of association of healthcare costs with obesity and smoking. More importantly, the study found that these effects are substantially higher in the upper quantiles of the healthcare cost distribution than in the lower quantiles. The insights on the heterogeneity of impacts of obesity and smoking on healthcare costs would not have been captured by traditional mean-based approaches. The study also found that UQR impact estimates were substantially different from CQR impact estimates in the upper quantiles of the cost distribution. Conclusions: These results suggest the potential role that smoking cessation and weight management programs can play in arresting the growth in healthcare costs. Specifically, given the finding that obesity and smoking have markedly higher impacts on high-cost patients, such programs appear to have significant cost saving potential if targeted toward high-cost patients.

AbstractBackground and AimOptimal rectal cancer (RC) outcomes depend on accurate locoregional staging. The study sought to describe the impact of endoscopic ultrasound (EUS) on RC treatment patterns and survival.MethodsUsing the Surveillance, Epidemiology, and End Results‐Medicare database, the study identified patients with RC between 2005 and 2007. The study excluded patients with stage IV disease, those not enrolled in Medicare parts A and B, those enrolled in managed care, and those staged with pelvic magnetic resonance imaging (because of low numbers). The study then compared outcomes between patients who received EUS and computed tomography of the abdomen and pelvis (CTAP) to those staged with CTAP alone after propensity score matching.ResultsBetween 2005 and 2007, we identified 3,408 nonmetastatic RC patients. Compared with patients staged with CTAP alone, those who received EUS and CTAP were younger (median age: 75 vs 76 years, P < 0.0001), more likely men (57.6% vs 48.7%, P < 0.0001), with a lower Charlson comorbidity index (P < 0.0001). Predictors of EUS included socioeconomic status (highest vs lowest) (odds ratio [OR] 1.87, 95% confidence interval [CI] 1.4–2.5), care by a gastroenterologist (OR 1.713, 95% CI 1.38–2.13), and care in a teaching hospital (OR 1.68, 95% CI 1.35–2.08). Receipt of neoadjuvant chemoradiation was higher in EUS‐staged patients (50.3% vs 16.0%, P < 0.0001). EUS‐staged patients had longer overall survival compared with those staged with CTAP alone (60 vs 57 months), but this was not statistically significant (P = 0.24).ConclusionEndoscopic ultrasound in RC staging is associated with higher utilization of neoadjuvant chemoradiation without a significant difference in overall survival.

Aim: Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. Methods: This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. Results: The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. Conclusion: The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.