Background: Neoadjuvant chemoradiation and chemotherapy are recommended for the treatment of nonmetastatic esophageal cancer. The benefit of neoadjuvant treatment is mostly limited to patients who exhibit pathologic complete response (pCR). Existing estimates of pCR rates among patients receiving neoadjuvant therapy have not been synthesized and lack precision.Methods: We conducted an independently funded systematic review and meta‐analysis (PROSPERO CRD42023397402) of pCR rates among patients diagnosed with esophageal cancer treated with neoadjuvant chemo(radiation). Studies were identified from Medline, EMBASE, and CENTRAL database searches. Eligible studies included trials published from 1992 to 2022 that focused on nonmetastatic esophageal cancer, including the gastroesophageal junction. Histology‐specific pooled pCR prevalence was determined using the Freeman–Tukey transformation and a random effects model.Results: After eligibility assessment, 84 studies with 6451 patients were included. The pooled prevalence of pCR after neoadjuvant chemotherapy in squamous cell carcinomas was 9% (95% CI: 6%–14%), ranging from 0% to 32%. The pooled prevalence of pCR after neoadjuvant chemoradiation in squamous cell carcinomas was 32% (95% CI: 26%–39%), ranging from 8% to 66%. For adenocarcinoma, the pooled prevalence of pCR was 6% (95% CI: 1%–12%) after neoadjuvant chemotherapy, and 22% (18%–26%) after neoadjuvant chemoradiation.Conclusions: Under one‐third of patients with esophageal cancer who receive neoadjuvant chemo(radiation) experience pCR. Patients diagnosed with squamous cell carcinomas had higher rates of pCR than those with adenocarcinomas. As pCR represents an increasingly utilized endpoint in neoadjuvant trials, these estimates of pooled pCR rates may serve as an important benchmark for future trial design.

Antibiotic misuse, either by patients or healthcare professionals, is one of the major contributing factors to antimicrobial resistance. In many Middle Eastern countries including Egypt, there are no strict regulations regarding antibiotic dispensing by community pharmacies. In this study, we examined antibiotic dispensing patterns in Egyptian community pharmacies. About 150 community pharmacies were randomly chosen using convenience sampling from the five most populous urban districts of Minia Governorate in Egypt. Two simulated patient (SP) scenarios of viral respiratory tract infection requiring no antibiotic treatment were used to assess the actual antibiotics dispensing practice of. Face-to-face interviews were then conducted to assess the intended dispensing practice. Descriptive statistics were calculated to report the main study outcomes. In 238 visits of both scenarios, 98.3% of service providers dispensed amoxicillin. Although stated otherwise in interviews, most pharmacy providers (63%) dispensed amoxicillin without collecting relevant information from presenting SPs. Findings showed high rates of antibiotic misuse in community pharmacies. Discrepancies between interviews and patient simulation results also suggest a practice‒knowledge gap. Corrective actions, whether legislation, enforcement, education, or awareness campaigns about antibiotic misuse, are urgently needed to improve antibiotic dispensing practices in Egyptian community pharmacies.

Purpose: The use of open‐source programming languages can facilitate open science practices in real‐world evidence (RWE) studies. Real‐world studies often rely on using big data, which makes using such languages complicated. We demonstrate an efficient approach that enables RWE researchers to use R to undertake RWE analysis tasks from cohort building to reporting.Methods: Using the Merative Marketscan data (2017–2019), we developed an R function to transform the data into parquet format to be used in R. Then, we compared the differences in data size before and after transformation. We compared the performance of the transformed data in R to the original data in terms of numerical consistency and running times required to complete simple exploratory tasks. To show how the transformed databases can be used in practice, we conducted a simplified replication of an active comparator new user study from the literature. All codes are available on GitHub.Results: Our approach exhibited high efficiency in data storage, as evidenced by the converted data size, which ranged from 10% to 43% of that of the original data files. The runtime of the exploratory tasks in R generally outperformed that of the original data with SAS. We showed, through example, how the converted data can be efficiently used to implement an RWE study.Conclusion: We demonstrate a free and efficient solution to facilitate the use of open‐source programming languages with big real‐world databases, which can facilitate the adoption of open science practices.

Background: Roflumilast is an add‐on therapy for COPD following exacerbations, but real‐world safety data in the United States are limited. Objective: This study aimed to identify safety signals associated with roflumilast initiation through a high‐throughput signal detection algorithm. Methods: Using sequence symmetry analysis (SSA), we analysed Marketscan databases for new roflumilast users (2011–2021). We screened for adverse effects across 211 therapeutic classes within 365 days of initiation. Sensitivity analyses were conducted by sex, age and observation period. Crude and adjusted sequence ratios (cSR and aSR) were reported with 95% confidence intervals (CIs). Results: Among 11 091 patients (53% aged 65+, 52% female), 32 safety signals were identified. Strong associations were observed with antithyroid agents (aSR, 4.18; 95% CI: 1.66–11.95), parathyroid hormones (aSR, 3.09; 95% CI: 1.56–6.44), haematopoietic agents (aSR, 2.55; 95% CI: 1.07–6.49) and meglitinides (aSR, 2.37; 95% CI: 1.15–5.35). While many signals aligned with prior clinical trial data, novel associations with antithyroid and parathyroid agents were discovered. Conclusion: In our study, we detected 32 safety signals for roflumilast, including notable associations with antithyroid agents and parathyroid hormones. Future investigations using more robust study designs are warranted to evaluate those signals.

Objective To estimate the association between the billing (profit) margin and clinical benefit of cancer treatments and use by oncologists. Design Retrospective population based cohort study Setting Population based sample using fee-for-service Medicare claims data. Participants Medicare beneficiaries with an incident cancer diagnosis from 2015 to 2020; included all patients with cancer treatment indications for which the available treatment options varied in clinical benefit and billing margin. Main outcomes and measures The primary outcome was the cancer treatment each patient received among treatment options recommended by the National Comprehensive Cancer Network (NCCN). The characteristics of interest were provider billing margin (defined at the patient treatment level, using Medicare reimbursement rates corresponding to the patient’s diagnosis date) and a proxy measure of clinical benefit (rank order of treatments based on Evidence Blocks scores developed by the NCCN, corresponding to the patient’s diagnosis date). The association between treatment received, billing margin, and clinical benefit was modeled using a conditional logit model with inverse probability-of-treatment weights applied at the patient treatment level to control for patient and provider characteristics. Results Twelve cancer indications were examined comprising 19 397 individual patients. Provider billing margin ranged from $0 to $12 692 (£9440; €10 800) for each course of treatment. No association was found between a $100 increase in provider billing margin and the likelihood of treatment use (odds ratio 0.97, 95% confidence interval 0.91 to 1.03). Higher clinical benefit was associated with greater treatment use (1.62, 1.15 to 2.29). Conclusions In this observational study of Medicare beneficiaries, selection of cancer treatments was associated with the treatment’s clinical benefit but not billing margin. Therefore, it is unlikely that policy and price changes that affect the billing margin of cancer treatments would shift patterns of use.

Introduction: In the United States, clinical guidelines recommend daily use of proton pump inhibitors (PPIs) amongst individuals diagnosed with Barrett's esophagus to decrease the risk of progression to dysplasia and neoplasia. Prior studies documenting adherence to PPIs in this population have not characterized heterogeneity in adherence patterns. Factors that may relate to adherence are incompletely described.Methods: We used administrative claims data from the Merative MarketScan Commercial Claims and Encounters database to conduct a retrospective study of adherence to prescription PPIs. A cohort of individuals diagnosed with incident Barrett's esophagus between 2010 and 2019 was identified. Group‐based trajectory models were generated to detect longitudinal adherence subgroups.Results: 79 701 individuals with a new diagnosis of Barrett's esophagus were identified. The best fitting model detected five distinct adherence trajectory groups: consistently high (44% of the population), moderate decline (18%), slow decline (12%), rapid decline (10%), and decline‐then‐increase (16%). Compared to individuals starting PPIs, those already using PPIs were less likely to have a declining adherence pattern. Other factors associated with membership in a declining adherence group included (but were not limited to): female sex, having a past diagnosis of anxiety or depression, and having one or more emergency department visits in the past year.Discussion: Using an exploratory method, we detected heterogeneity in adherence to prescription PPIs. Less than half of individuals were classified into the consistently high adherence group, suggesting that many individuals with Barrett's esophagus receive inadequate pharmacologic therapy.