Analysis Of Real-world Data Research Articles

Neuromodulation for Neuropathic Pain Syndromes

ABSTRACT OBJECTIVE This article reviews the principles, applications, and emerging trends of neuromodulation as a therapeutic approach for managing painful neuropathic diseases. By parsing evidence for possible mechanisms of action and clinical trial outcomes for various diseases, this article focuses on five common therapy modalities: cutaneous, peripheral nerve, spinal cord, and brain stimulation, and intrathecal drug delivery. LATEST DEVELOPMENTS Recent advances in both invasive and noninvasive neuromodulation for pain have introduced personalized and closed-loop techniques, integrating real-time feedback mechanisms and combining therapies to improve physical and psychosocial function. Novel stimulation waveforms may influence distinct neural tissues to rectify pathologic pain signaling. ESSENTIAL POINTS With appropriate patient selection, peripheral nerve stimulation or epidural stimulation of the spinal cord can provide enduring relief for a variety of chronic pain syndromes. Newer technology using high frequencies, unique waveforms, or closed-loop stimulation may have selective advantages, but our current understanding of therapy mechanisms is very poor. For certain diagnoses and patients who meet clinical criteria, neuromodulation can provide profound, long-lasting relief that significantly improves quality of life. While many therapies are supported by data from large clinical trials, there is a risk of bias as most clinical studies were funded by device manufacturers or insurance companies, which increases the importance of real-world data analysis. Emerging methods like invasive or noninvasive brain stimulation may help us dissect basic mechanisms of pain processing and hold promise for personalized therapies for refractory pain syndromes. Finally, intrathecal delivery of drugs directly to segments of the spinal cord can also modify pain signaling to provide therapy for severe pain syndromes.

Comparison of the Risk of Diabetic Retinopathy Between Sodium-Glucose Cotransporter-2 Inhibitors and Dipeptidyl Peptidase-4 Inhibitors in Patients with Type 2 Diabetes Mellitus in Japan: A Retrospective Analysis of Real-World Data.

Diabetic retinopathy (DR), a microvascular complication of type 2 diabetes mellitus (T2DM), is a leading cause of blindness and has detrimental effects on patients' quality of life. We compared the risk of DR diagnosis with sodium-glucose cotransporter-2 inhibitors (SGLT2i) versus dipeptidyl peptidase-4 inhibitors (DPP-4i) in patients with T2DM in Japan. This Japanese retrospective cohort study used the JMDC Claims Database (data collected from January 2015 to September 2022). Patients with T2DM and no record of microvascular or macrovascular diseases who were newly treated with an SGLT2i (23,061 patients) or a DPP-4i (53,986 patients) were matched 1:1 using propensity score (10,166 per matched group). Incidence rates (IRs) and cumulative IRs of DR diagnosis were calculated for each treatment group; hazard ratio (HR) and its 95% confidence interval (CI) were calculated using Cox proportional hazard models to compare the risk between the groups. The IR of DR diagnosis was 46.23 and 57.12 per 1000 person-years in the SGLT2i and DPP-4i groups, respectively, with a significantly lower risk in the SGLT2i group than in the DPP-4i group (HR 0.83, 95% CI 0.75-0.92, P = 0.0003). In this study, the risk of DR diagnosis was lower with SGLT2i compared with DPP-4i in patients with T2DM without microvascular and macrovascular diseases in Japan. Findings suggest that early SGLT2i treatment may be beneficial in preventing DR development in early-stage T2DM. Graphical abstract available for this article.

Eligibility for Adjuvant Cyclin-Dependent Kinase 4/6 Inhibitors in Endocrine Receptor-Positive and HER2-Negative Early Breast Cancer by Age and Type of Surgery

Background: Despite early diagnosis, approximately 20% of patients with ER-positive and HER2-negative breast cancer (BC) will experience disease recurrence. Improved survival has been reported with adjuvant treatment combining cyclin-dependent kinase 4/6 inhibitors with endocrine therapy, in high-risk patients with ER-positive and HER2-negative BC, regardless of age. Older patients have higher rates of ER-positive/HER2-negative BC than younger patients. Methods: In this real-world data analysis, MonarchE and NataLEE high-risk patients accounted for 9.5% and 33% of patients undergoing upfront surgery, respectively. Significantly higher eligibility rates were observed in patients who underwent a mastectomy, >70 years and ≤40 years for adjuvant abemaciclib and ribociclib, and in patients >80 years for ribociclib. Results: Eligibility rates in patients ≤40 years and >80 years who underwent mastectomy were 27.8% and 24.7% for abemaciclib, respectively, and 56.6% and 65.2% for ribociclib, respectively. A higher discontinuation rate for abemaciclib was reported in patients aged ≥65 years and it can be assumed that discontinuation rates may increase in even older patients. Conclusions: If the results of the NataLEE trial translate into clinical practice, the number of patients potentially eligible for adjuvant CDK4/6 inhibitors may increase, especially in the elderly population.

Unveiling change-point detection with ARMA-GARCH models

This paper delves into the asymptotic theory of a Cumulative Sum (CUSUM)-type test designed for detecting change points in the variance of AutoRegressive Moving-Average models, incorporating Generalized Autoregressive Conditional Heteroscedasticity innovations. We demonstrate that, under the null hypothesis (no change), the CUSUM test statistic converges to the supremum of a standard Brownian bridge. Using a Monte Carlo simulation, we highlight the strong performance of our proposed test when compared to the methods by Song and Kang. Furthermore, we provide a real-world data analysis to showcase the practical application of our test.

A real-world data analysis of distribution and inconsistency between total serum IgE and allergen-specific IgE results in clinical practice.

The inconsistency between serum total IgE (tIgE) and allergen-specific IgE (sIgE) results is often encountered in clinical practice, but the distribution and influencing factors of the inconsistent results have not been fully understood. The aim of this study was to analyze the distribution and inconsistency between tIgE and sIgE test results. A retrospective study, from the electronic medical records of 2139 patients who underwent both tIgE and sIgE tests, from January to December 2023 was reviewed. The tIgE and sIgE results and their distribution, as well as their inconsistency, were analyzed based on sex, age, and disease subgroups. 36.2% of the patients had a positive sIgE, and 43.7% had an elevated tIgE level. sIgE and tIgE results were discordant in nearly 30% of patients, with no difference between genders, while individuals aged over 60 exhibited a significantly higher inconsistency rate than the other age groups, and the inconsistency rate between tIgE and sIgE results was significantly different among different tIgE levels, sIgE grades, positive allergen count and positive allergen types. In addition, patients with chronic urticaria (CU) had a higher inconsistency rate than those with other allergic diseases, but the difference was not statistically significant. The overall inconsistency rate between tIgE and sIgE results was about 30%. The elderly group older than 60 years old is more likely to have inconsistent results, and tIgE level, sIgE level, the number and type of positive allergens also affected the consistency of tIgE and sIgE results.

Glucocorticoid replacement therapy in congenital adrenal hyperplasia and its associations with growth outcomes - real world data analysis from an international cohort of 1500 patients

Glucocorticoid replacement therapy in congenital adrenal hyperplasia and its associations with growth outcomes - real world data analysis from an international cohort of 1500 patients

Long-Term Evaluation of Allopurinol Effectiveness in the Thai Population: Insights from 10 Years of Real-World Big Data Analysis

Objective: This study aimed to evaluate the effectiveness and safety profile of allopurinol in Songklanagarind hospital, Thailand. Material and Methods: Electronic medical records (EMRs) of patients having undergone allopurinol treatment for gouty arthritis, or other pertinent indications, were retrospectively reviewed. The primary outcome of this study was the longitudinal measurement of uric acid levels. A linear mixed model (LMM) analysis assessed the statistical significance of uric acid reduction across hospital visits. The safety profile regarding allopurinol-related adverse drug reactions was assessed.Results: A total of 11,277 EMRs were extracted, of which 8,801 EMRs were eligible for further analyses. These records pertain to a cohort of 3,219 unique patients whose visits were arranged chronologically from the earliest to the fifth recorded visit. Overall, uric acid level decreased after allopurinol treatment in all patients. Across subsequent visits, the analysis, using LMM, found a significant reduction in uric acid levels (χ²=1465.4, df=4, p-value<0.001), with the early reduction observed as early as the second visit. The incidence of allopurinol-related adverse reactions was 4.37% (385/8801 cases). Conclusion: The current dosing regimen of allopurinol at Songklanagarind Hospital has demonstrated favorable treatment outcomes and continues to be effective. This data provides insights into pharmacological management and its real-world outcomes.

Real-world data to support post-market safety and performance of embolization coils: evidence generation from a medical device manufacturer and data institute partnership

BackgroundRecognizing the limitations of pre-market clinical data, regulatory authorities have embraced total product lifecycle management with post-market surveillance (PMS) data to assess medical device safety and performance. One method of proactive PMS involves the analysis of real-world data (RWD) through retrospective review of electronic health records (EHR). Because EHRs are patient-centered and focused on providing tools that clinicians use to determine care rather than collecting information on individual medical products, the process of transforming RWD into real-world evidence (RWE) can be laborious, particularly for medical devices with broad clinical use and extended clinical follow-up. This study describes a method to extract RWD from EHR to generate RWE on the safety and performance of embolization coils.MethodsThrough a partnership between a non-profit data institute and a medical device manufacturer, information on implantable embolization coils’ use was extracted, linked, and analyzed from clinical data housed in an electronic data warehouse from the state of Indiana’s largest health system. To evaluate the performance and safety of the embolization coils, technical success and safety were defined as per the Society of Interventional Radiology guidelines. A multi-prong strategy including electronic and manual review of unstructured (clinical chart notes) and structured data (International Classification of Disease codes), was developed to identify patients with relevant devices and extract data related to the endpoints.ResultsA total of 323 patients were identified as treated using Cook Medical Tornado, Nester, or MReye embolization coils between 1 January 2014 and 31 December 2018. Available clinical follow-up for these patients was 1127 ± 719 days. Indications for use, adverse events, and procedural success rates were identified via automated extraction of structured data along with review of available unstructured data. The overall technical success rate was 96.7%, and the safety events rate was 5.3% with 18 major adverse events in 17 patients. The calculated technical success and safety rates met pre-established performance goals (≥ 85% for technical success and ≤ 12% for safety), highlighting the relevance of this surveillance method.ConclusionsGenerating RWE from RWD requires careful planning and execution. The process described herein provided valuable longitudinal data for PMS of real-world device safety and performance. This cost-effective approach can be translated to other medical devices and similar RWD database systems.

ASO Author Reflections: The Gustave Roussy Immune Score May Be a Useful Biomarker for Conversion Surgery After Chemotherapy Plus Nivolumab as the First-Line Treatment for Gastric Cancer.

PAST: There are no reports of promising biomarkers that predict which cases can be transferred to conversion surgery (CS) after chemotherapy plus nivolumab as first-line treatment for unresectable advanced or recurrent gastric cancer (GC). The purpose of this multicenter retrospective study was to conduct an analysis of real-world data on CS after chemotherapy plus nivolumab as a first-line treatment and to identify predictive biomarkers. PRESENT: We showed the CS transition rate was 11.5%. All CS cases had R0 resection, and the postoperative short-term outcome was acceptable. There were no high-risk Gustave Roussy Immune Score (GRIm-s) cases among those who underwent CS. FUTURE: Although this study was a multicenter study, the number of patients was small. A randomized controlled trial should be conducted for a more detailed study of the significance of CS.

Induction of Labor Using Castor Oil Cocktail - an Analysis of Real-world Data.

Induction of labor is indicated when benefits of delivery outweigh benefits of prolonged pregnancy, which is not always welcomed by women. Castor oil is accepted as an "old household remedy" for labor induction but is not yet part of the official guidelines. Nevertheless, it is often used, mostly even before the women are admitted to the hospital. Data on its actual benefits and safety are missing. Upon accepting the real-world practice of applying castor oil cocktail for labor induction we added castor oil as one option of labor induction in our clinical routine for multiparous women at term, with a history of at least one vaginal delivery. Here we aimed to generate data on the effectivity and safety of castor oil in labor induction by analyzing the real-world data generated in our cohort. In our retrospective analysis we included data of a cohort of 148 multiparous women induced by castor oil cocktail and of 286 matched controls receiving established methods according to the current guidelines for labor induction. The castor oil cocktail was prepared following a standardized recipe with quality-tested castor oil. Statistical analysis was performed with SPSS27.0. Perinatal outcome data including the rate of vaginal deliveries did not differ between groups, except significantly more neonates were admitted to the neonatal intensive care unit in the group receiving established methods for induction of labor (p=0.01). In 39 women (26%), administration of castor oil cocktail alone failed to induce labor. The time from initiation of labor induction until delivery was significantly shorter in the castor oil cocktail group (p=0.04). Our study demonstrates the safety and effectivity of a castor oil cocktail induction in multiparous women at term in a hospital-based setting using quality-controlled castor oil in a standardized recipe.

Safety of Options to "Boost" (Enhancing Insulin Infusion Rates) and "Ease-Off" (Reducing Insulin Infusion Rates) in CamAPS FX Hybrid Closed-Loop System: A Real-World Analysis.

The usage and safety of the Boost and Ease-off features in the CamAPS FX hybrid closed-loop system were analyzed in a retrospective analysis of real-world data from 7,464 users over a 12-month period. Boost was used more frequently than Ease-off, but for a shorter duration per use. Mean starting glucose was above range for Boost (229 ± 51 mg/dL), and within range for Ease-off (114 ± 29 mg/dL). Time spent below 70 mg/dL was low during Boost periods [median (interquartile range; IQR) 0.0% (0.0, 0.5%)], and lower than during no Boost periods [2.1% (1.2, 3.4%)], while time spent above 180 mg/dL was lower during Ease-off periods (15 ± 14%) compared with no Ease-off periods (25 ± 12%). There were no episodes of severe hypoglycemia or diabetic ketoacidosis attributed to Boost or Ease-off use. Boost and Ease-off allow users to engage safely with CamAPS FX to manage their glucose levels during periods of more-than-usual and less-than-usual insulin needs.

Semaglutide use in people with obesity and type 2 diabetes from real-world utilization data: An analysis of the All of US Program.

To analyse data from the All of Us Research Program to evaluate the real-world application and long-term effectiveness of semaglutide in treating type 2 diabetes and obesity patients in a large population. We identified patients prescribed semaglutide and analysed differences in route of administration and the time on semaglutide. For individuals diagnosed with obesity, we measured changes in body mass index (BMI) and weight from baseline, while measured changes in HbA1c for those patients with type 2 diabetes. We also examined the occurrence of newly diagnosed common adverse events from taking semaglutide. For 3739 semaglutide patients, those on injectable semaglutide (3364 patients) averaged 301.54 days on the medication, with 20.36% having no end date, while those on oral semaglutide (435 patients) averaged 172.48 days, with 24.60% having no end date. We found average decreases of 1.54 kg/m2 in BMI, 4.65 kg in weight and 0.75% in HbA1c for semaglutide users. The decreases were larger in participants taking injectable formulation, probably because of higher starting values. Over time, improvements in these outcomes diminished, but the values remained significantly lower than baseline levels. Approximately only 1.0% of patients reported newly diagnosed common adverse events. Consistent with clinical trial findings, this real-world data analysis showed that semaglutide was well tolerated and that, for a large population, it effectively reduced BMI, body weight and HbA1c, albeit to smaller magnitudes than observed in clinical trials. These findings provide valuable insights into real-world experience and the long-term effectiveness of semaglutide.

Adopting a Framework for Rapid Real-World Data Analyses in Safety Signal Assessment

The expanding availability of real-world data (RWD) has led to an increase in both the interest and possibilities for using this information in postmarketing safety analyses and signal management. While there is enormous potential value from the safety insights generated through RWD, the analysis preparation, execution, and communication required to reliably deliver the evidence can be time consuming. Since the safety signal assessment process is a regulated and timebound process, any supporting RWD analyses require a rapid turnaround of well-designed and informative results. To address this challenge, a TransCelerate BioPharma working group was formed and developed a framework to help teams responsible for safety signal assessment overcome the challenges of working with RWD rapidly to deliver analyses within regulatory timelines. Here, a previously performed safety assessment was evaluated within the context of the developed framework to illustrate how the framework may be adopted in practice.

Real-world data analysis of next-generation sequencing and corresponding clinical characteristics in thyroid tumor.

Next-generation sequencing (NGS) is of great benefit to clinical practice in terms of identifying genetic alterations. This study aims to clarify the gene background and its influence on thyroid tumors in the Chinese population. NGS data and corresponding clinicopathological features (sex, age, tumor size, extrathyroidal invasion, metastasis, multifocality, and TNM stage) were collected and analyzed retrospectively from 2844 individual thyroid tumor samples from July 2021 to August 2022. Among the cohort, 2337 (82%) cases possess genetic alterations, including BRAF (71%), RAS (4%), RET/PTC (4%), TERT (3%), RET (2.2%), and TP53 (1.4%). Diagnostic sensitivity before surgery can be significantly increased from 0.76 to 0.91 when cytology is supplemented by NGS. Our results show that BRAF-positive papillary thyroid cancer (PTC) patients tend to have older age, smaller tumor size, less vascular invasion, more frequent tumor multifocality, and a significantly higher cervical lymph node metastatic rate. Mutation at RET gene codons 918 and 634 is strongly correlated with medullary thyroid cancer. However, it did not display more invasive clinical characteristics. TERT-positive patients are more likely to have older age, and have larger tumor size, more tumor invasiveness, and more advanced TNM stage, indicating a poor prognosis. Patients with TERT, RET/PTC1, and CHEK2 mutations are more susceptible to lateral lymph node metastasis. In conclusion, NGS can be a useful tool that provides practical gene evidence in the process of diagnosis and treatment in thyroid tumors.

Sulfonylurea prescription patterns in elderly patients with type 2 diabetes mellitus: Acomprehensive analysis of real-world data from pharmacies in Japan.

The study aim was to investigate sulfonylurea prescription patterns in elderly patients (age ≥65 years) with type 2 diabetes mellitus in Japan. Sulfonylurea use among older adults has been insufficiently examined, despite the associated risks of hypoglycemia. This retrospective cross-sectional survey entailed analysis of Japanese pharmacy data, extracted from the Musubi database, for patients (age 20-100 years) prescribed sulfonylureas between November 2022 and October 2023. Dose distribution, adherence to the Diabetes Treatment Guidelines for the Elderly 2023 and coprescription of other diabetes medications were investigated. Of the total 91,229 patients, 80.1% were prescribed glimepiride, 16.3% gliclazide and 3.6% glibenclamide. In patients aged ≥65 years, exceeding the recommended dose (>1 mg/day for glimepiride, >40 mg/day for gliclazide) was numerically higher for glimepiride (25.0%) than for gliclazide (7.8%). The most common prescribing patterns were quadruple therapy with a sulfonylurea, a dipeptidyl peptidase-4 inhibitor, an sodium-glucose transporter 2 inhibitor and a biguanide in patients aged 65 to <75 years, and dual therapy with a sulfonylurea and a dipeptidyl peptidase-4 inhibitor in patients aged ≥75 years. Unfortunately, glinide was coprescribed for 338 (0.5%) of elderly patients. Insulin was coprescribed for 3,682 (5.6%) of elderly patients. Analysis of real-world sulfonylurea prescription data found guideline non-adherence, namely, excessive prescription of glimepiride, use of glibenclamide in elderly patients, and common coprescription with dipeptidyl peptidase-4 inhibitors. These findings might provide an opportunity to reconsider the treatment of patients with type 2 diabetes mellitus who are over-prescribed sulfonylureas to reduce residual risks, such as hypoglycemia.

Generalizing Treatment Effect to a Target Population Without Individual Patient Data in a Real-World Setting.

The innovative use of real-world data (RWD) can answer questions that cannot be addressed using data from randomized clinical trials (RCTs). While the sponsors of RCTs have a central database containing all individual patient data (IPD) collected from trials, analysts of RWD face a challenge: regulations on patient privacy make access to IPD from all regions logistically prohibitive. In this research, we propose a double inverse probability weighting (DIPW) approach for the analysis sponsor to estimate the population average treatment effect (PATE) for a target population without the need to access IPD. One probability weighting is for achieving comparable distributions in confounders across treatment groups; another probability weighting is for generalizing the result from a subpopulation of patients who have data on the endpoint to the whole target population. The likelihood expressions for propensity scores and the DIPW estimator of the PATE can be written to only rely on regional summary statistics that do not require IPD. Our approach hinges upon the positivity and conditional independency assumptions, prerequisites to most RWD analysis approaches. Simulations are conducted to compare the performances of the proposed method against a modified meta-analysis and a regular meta-analysis.

Online updating Huber robust regression for big data streams

ABSTRACT Big data streams have garnered significant attention in multiple industries. However, the immense volume and the presence of outliers in high-velocity streaming data pose great challenges to its analysis. To address these concerns, this paper introduces a novel Online Updating Huber Robust Regression algorithm. By efficiently capturing the salient features of new data subsets, a computationally efficient online updating estimator is proposed without the need for storing historical data. Furthermore, by incorporating Huber regression into its framework, the estimator exhibits robustness to heavy-tailed, heterogeneous as well as outlier-contaminated data. Theoretically, the proposed online updating estimator is asymptotically equivalent to an Oracle estimator derived from the entire dataset. Extensive numerical simulations and a real-world data analysis have been conducted to demonstrate the effectiveness and practicality of the proposed method.

1540MO The patient voice: An analysis of real-world data using the recurrent respiratory papillomatosis foundation/CoRDS patient registry (RRPF/CoRDS)

1540MO The patient voice: An analysis of real-world data using the recurrent respiratory papillomatosis foundation/CoRDS patient registry (RRPF/CoRDS)

Artificial Intelligence in Medical Affairs: A New Paradigm with Novel Opportunities.

The advent of artificial intelligence (AI) revolutionizes the ways of working in many areas of business and life science. In Medical Affairs (MA) departments of the pharmaceutical industry AI holds great potential for positively influencing the medical mission of identifying and addressing unmet medical needs and care gaps, and fostering solutions that improve the egalitarian and unbiased access of patients to treatments worldwide. Given the essential position of MA in corporate interactions with various healthcare stakeholders, AI offers broad possibilities to support strategic decision-making and to pioneer novel approaches in medical stakeholder interactions. By analyzing data derived from the healthcare environment and by streamlining operations in medical content generation, AI advances data-based prioritization and strategy execution. In this review, we discuss promising AI-based solutions in MA that support the effective use of heterogenous information from observations of the healthcare environment, the enhancement of medical education, and the analysis of real-world data. For a successful implementation of such solutions, specific considerations partly unique to healthcare must be taken care of, for example, transparency, data privacy, healthcare regulations, and in predictive applications, explainability.

Safety and efficacy of first-line nivolumab plus chemotherapy for HER2-negative advanced gastric or gastroesophageal junction adenocarcinoma: real-world data analysis

Safety and efficacy of first-line nivolumab plus chemotherapy for HER2-negative advanced gastric or gastroesophageal junction adenocarcinoma: real-world data analysis