Real-world Data Study Research Articles

Genomic Profiling of Small Intestine Cancers From a Real-World Data Set Identifies Subgroups With Actionable Alterations.

Panel-based comprehensive genomic profiling (CGP) is used in clinical practice worldwide; however, large real-world data (RWD) of patients with advanced small intestine cancer have not been characterized. We investigated differences in the prevalence of clinically relevant alterations across molecularly defined or age-stratified subgroups. This was a collaborative biomarker study of RWD from CGP testing (Foundation Medicine, Inc). Hybrid capture was conducted on at least 324 cancer-related genes and select introns from up to 31 genes frequently rearranged in cancer. Overall, 1,364 patients with advanced small intestine cancer were available for analyses and were stratified by age (≥40 years/<40 years), microsatellite instability (MSI) status, tumor mutational burden (TMB) status (high ≥10/low <10 Muts/Mb), and select gene alterations. The frequency of alterations was analyzed using a chi-square test with Yate's correction. Genes with frequent alterations included TP53 (59.8%), KRAS (54.8%), APC (27.7%), and CDKN2A (22.4%). Frequent genes with amplifications were MYC (6.7%), MDM2 (5.9%), GATA6 (5.5%), and CCND1 (3.4%). Patients younger than 40 years had significantly lower frequency of APC mutations than those 40 years and older (10.4% v 28.7%; P = .0008). Druggable genomic alterations were detected in 22.3% of patients: BRAF V600E (1.2%), BRCA1 (1.8%), BRCA2 (3.2%), ERBB2 amplification (3.2%), KRAS G12C (3.3%), NTRK1/2/3 fusion (0.07%), MSI-high (7.0%), and TMB-high (12.2%), with no significant differences in the frequency according to age (<40 years v ≥40 years; 22.1% v 22.3%). TMB of 10-20 Mut/Mb was observed in 4.8% of patients, and TMB ≥20 Mut/Mb was seen in 7.3% of the cohort. RWD from clinical panel testing revealed the genomic landscape in small intestine cancer by subgroup. These findings provide insights for the future development of treatments in advanced small intestine cancer.

Effectiveness of R-CHOP versus R-CHOEP for treatment of young patients with high-risk diffuse large B-cell lymphoma: A Danish observational population-based study.

Etoposide to standard R-CHOP is used for high-risk diffuse large B-cell lymphoma (DLBCL) in some countries. Due to the lack of randomized trials, a real-world data study using matching methods was used to test the potential effectiveness of R-CHOEP over R-CHOP. This study included patients from the Danish Lymphoma Register diagnosed between 2006 and 2020 at the age of 18-60 years with de novo DLBCL and age-adjusted IPI ≥2. R-CHOEP treated patients were matched 1:1 without replacement to R-CHOP treated patients using a hybrid exact and genetic matching technique. Primary endpoints were progression-free survival (PFS) and overall survival (OS). In total, 396 patients were included; 213 received R-CHOEP and 183 received R-CHOP. Unadjusted 5-year PFS and OS for R-CHOEP were 69% (95% Confidence intervals [CI]; 63%-76%) and 79% (CI;73%-85%) versus 62% (CI;55%-70%) and 76% (CI;69%-82%) for R-CHOP (log-rank test, PFS p = .25 and OS p = .31). A total of 127 patients treated with R-CHOEP were matched to 127 patients treated with R-CHOP. Matching-adjusted 5-year PFS and OS were 65% (CI; 57%-74%) and 79% (CI; 72%-84%) for R-CHOEP versus 63% (CI; 55%-73%) and 79% (CI;72%-87%) for R-CHOP (log-rank test, PFS p = .90 and OS p = .63). The present study did not confirm superiority of R-CHOEP over R-CHOP for young patients with high-risk DLBCL.

Efficacy and safety of pyrotinib-based regimens in HER2 positive metastatic breast cancer: A retrospective real-world data study

ObjectivePyrotinib is a novel irreversible tyrosine kinase inhibitor that has shown efficacy for human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC). This study explored the efficacy and safety of pyrotinib in the treatment of HER2-positive MBC patients in the real world. MethodsFrom September 2018 to February 2022, 137 female patients with HER2-positive MBC treated in this center were enrolled in this study. The follow-up period ended on January 12, 2023. The primary endpoint of this study was progression-free survival (PFS). Overall survival (OS), objective response rate (ORR), disease control rate (DCR), clinical benefit rate (CBR), central nervous system (CNS)-PFS, CNS-ORR, CNS-CBR, CNS-DCR, and adverse event (AE) were the secondary endpoints. ResultsThe ORR, DCR and CBR were 41.98 % (55/131), 87.79 % (115/131) and 44.27 % (58/131) in this cohort, respectively. The median PFS for this cohort was 10.37 months [95 % confidence interval (CI): 9.205-11.535] and the median OS was 37.53 months (not reached). Univariate and multivariate analyses showed that trastuzumab sensitivity was an independent predictor of improved PFS [hazard ratio (HR): 0.579 (0.371-0.904, p=0.016)] and improved OS [0.410 (0.213-0.790, p=0.008)]. Patients treated with a pyrotinib-based regimen as second-line and third-or-post-line therapy had poorer PFS [second-line: 3.315 (1.832-6.000, p<0.001); third-or-post-line: 3.304 (1.749-6.243, p<0.001)] and OS [second-line: 4.631 (1.033-20.771, p=0.045); third-or-post-line: 5.738 (1.212-27.174, p=0.028)]. There were 38 brain metastases (BM) patients in this study, the CNS-mPFS [14.37 months (7.815-20.925) vs. 7.83 months (7.047-8.613), p=0.375] and mOS [not reached vs. 36.40 months (18.551-54.249), p=0.034] were better in brain radiotherapy (BRT) group than NBRT group. 18.98 % (26/137) of patients experienced grade 3 or higher diarrhea. No AE-related death was reported. ConclusionThis study confirms the promising antitumor activity and acceptable safety of real-world pyrotinib-based regimens for the treatment of HER2-positive MBC patients, particularly those who are trastuzumab-sensitive and who are receiving pyrotinib-based regimens as advanced first-line therapy. It has also been demonstrated that these regimens combined with BRT, provide better intracranial responses and long-term survival benefits for these patients with BM.

Prevalence and characteristics of chronic kidney disease in people with type 2 diabetes mellitus in the Autonomous Community of Aragon

AimsThe main objective in this study was to determine the prevalence of Chronic Kidney Disease (CKD) in people with Type 2 Diabetes Mellitus (T2DM) in the Autonomous Community (AC) of Aragon (Spain) and to detect whether or not there is under-registration in the patient's history. As a secundary objetive, it was proposed to study the most relevant demographic and clinical characteristics of people with CKD. MethodsObservational and retrospective real world data study of the population over 18 years of age with a diagnosis of T2DM, between January 2017 and December 2021. A descriptive analysis of qualitative and quantitative variables, and a comparison using the parametric Student's t-test or the non-parametric Mann-Whitney U-test between both groups was performed. ResultsThe prevalence of T2DM was 8.07 % and that of CKD 31.4 %, with an under-reporting of 47 %. The main risk factor associated with CKD was arterial hypertension (p<0.001), followed by dyslipidemia (p<0.001). The main treatment used for diabetes control was metformin, both in patients with and without CKD (p<0.001). A total of 56.81 % of people with T2DM and CKD did not undergo annual monitoring of their renal function (glomerular filtration rate) or determination of albuminuria. ConclusionsThe prevalence of CKD increases in patients with T2DM (31.4 %), and in almost half of patients the diagnosis is not registered (47 %). This under-reporting delays the implementation of measures needed to prevent CKD progression.

Methods to advance health equity and social justice in healthcare: Protocol for a scoping review on the utilisation of routinely collected data.

Many areas of healthcare are impacted by a paucity of research that is translatable to clinical practice. Research utilising real-world data, such as routinely collected patient data, may be one option to efficiently create evidence to inform practice and service delivery. Such studies are also valuable for exploring (in)equity of services and outcomes, and benefit from using non-selected samples representing the diversity of the populations served in the 'real world'. This scoping review aims to identify and map the published research which utilises routinely collected clinical healthcare data. A secondary aim is to explore the extent to which this literature supports the pursuit of social justice in health, including health inequities and intersectional approaches. This review utilises Arksey and O'Malley's methodological framework for scoping reviews and draws on the recommended enhancements of this framework to promote a team-based and mixed methods approach. This includes searching electronic databases and screening papers based on a pre-specified inclusion and exclusion criteria. Data relevant to the research aims will be extracted from included papers, including the clinical/professional area of the topic, the source of data that was used, and whether it addresses elements of social justice. All screening and reviewing will be collaborative and iterative, drawing on strengths of the research team and responsive changes to challenges will be made. Quantitative data will be analysed descriptively, and conceptual content analysis will be utilised to understand qualitative data. These will be collectively synthesised in alignment to the research aims. Our findings will highlight the extent to which such research is being conducted and published, including gaps and make recommendations for future endeavours for real-world data studies. The findings from this scoping review will be relevant for practitioners and researchers, as well as health service managers, commissioners, and research funders.

Real-World Evidence to Support EU Regulatory Decision Making-Results From a Pilot of Regulatory Use Cases.

Studies using real-world data (RWD) can complement evidence from clinical trials and fill evidence gaps during different stages of a medicine's lifecycle. This review presents the experience resulting from the European Medicines Agency (EMA) pilot to generate RWE to support evaluations by EU regulators and down-stream decision makers from September 2021 to February 2023. A total of 61 research topics were identified for RWE generation during this period, covering a wide range of research questions, primarily generating evidence on medicines safety (22, 36%), followed by questions on the design and feasibility of clinical trials (11, 18%), drug utilization (10, 16%), clinical management (10, 16%), and disease epidemiology. A significant number of questions were related to the pediatric population and/or rare diseases. A total of 27 regulatory-led RWD studies have been conducted. Most studies were descriptive and aimed at estimating incidence and prevalence rates of clinical outcomes including adverse events or to evaluate medicines utilization. The review highlights key learnings to guide further efforts to enable the use and establish the value of real-world evidence (RWE) for regulatory decisions. For instance, there is a need to access additional fit-for-purpose and representative data, and to explore further means to provide timely evidence that meets regulatory timelines. The need for early interactions and close collaboration with study requesters, e.g., from the Agency's scientific Committees, to better understand the research question is equally important. Finally, the review provides our perspective on the way forward to maximize the potential of regulatory-led RWE generation.

A Real-World Evidence Primer for Advanced Practice Providers: Integrating P-Reality X Into Shared Decision-Making for People With HR+/HER2− Metastatic Breast Cancer

Advanced practice providers in oncology are now likely to encounter real-world data (RWD) studies in addition to data from randomized controlled trials (RCTs) in their practice. Real-world evidence derived from RWD can provide important information about a therapeutic agent’s effectiveness outside of the confines of RCTs. It is important to understand how these studies are conducted and how data from these two types of studies can be interpreted and integrated for practical clinical use and shared decision-making. The goal of this manuscript is to provide an overview of the fundamental aspects of RWD studies and what is required to conduct a robust RWD study. Recently published studies are cited to demonstrate how RWD studies complement RCTs.

The prediagnostic general practitioner care of sarcoma patients: A real-world data study.

Limited understanding exists regarding early sarcoma symptoms presented during general practitioner(GP) consultations. The study explores GP visit patterns and recorded diagnoses in the 12 months preceding sarcoma diagnosis. Sarcoma cases diagnosed from 2010 to 2020 were identified through the Netherlands Cancer Registry alongside general practice data. Sarcoma cases were age and gender matched to cancer-free controls (2:1 or 1:1 ratio). A total of 787 individuals with soft-tissue sarcoma (STS)and 188 individuals with bone sarcoma (BS)were identified. There was a significant difference in monthly GP contacts from 4 months to the last month before STS diagnosis, and 2 months before BS diagnosis between cases and controls. Most prevalent diagnoses recorded by the GP for STS cases included musculoskeletal neoplasm (26.6%), uncomplicated hypertension (15.6%), and cystitis/other urinary infections (12.2%). For BS cases, musculoskeletal neoplasm (42.8%), knee symptoms/complaints (9.7%), and shoulder symptoms/complaints (9.7%) were most frequent. A significant difference in GP contacts between cases and controls preceding sarcoma diagnosis. STS cases were predominantly diagnosed with nonspecific symptoms, whereas BS cases with diagnoses more suggestive of BS. Better understanding of the prediagnostic trajectory could aid GPs in early identification of sarcoma.

Association of Baseline Magnetic Resonance Imaging Prostate Imaging Reporting and Data System Score With Prostate Cancer Active Surveillance Early Biopsy Reclassification: Data From the Michigan Urological Surgery Improvement Collaborative (MUSIC).

The purpose of our study was to evaluate the association of baseline MRI Prostate Imaging Reporting and Data System (PI-RADS) score with biopsy reclassification in a multicenter active surveillance (AS) cohort. We identified men in the Michigan Urological Surgery Improvement Collaborative registry (46 hospital-based/academic/private practice urology groups) with National Comprehensive Cancer Network (NCCN) low-risk and favorable intermediate-risk prostate cancer who underwent MRI within 6 months before or after initial biopsy and enrolled in AS from June 2016 to January 2021. The primary objective was to determine the association of baseline MRI PI-RADS score (≥4 lesion) with reclassification to high-grade prostate cancer (≥grade group 3) on surveillance biopsy. Multivariable Cox proportional hazards regression models were constructed and adjusted for pathologic, MRI, and clinical/biopsy factors, with landmark time of 6 months from diagnostic biopsy. We included an interaction term between PI-RADS score and NCCN group in the Cox model. A total of 1491 men were included with median age 64 years (IQR: 59-69) with median follow-up 11.0 months (IQR: 6.0-23.0) after landmark. Baseline PI-RADS ≥ 4 lesion was associated with an increased hazard of biopsy reclassification (HR: 2.3 [95% CI: 1.6-3.2], P < .001), along with grade group 2 vs 1 (HR: 2.5 [95% CI: 1.7-3.7], P < .001), and increasing age (per 10 years; HR: 1.8 [95% CI: 1.4-2.4], P < .001). The interaction between NCCN risk group with MRI findings was not significant (P = .7). In this multicenter cohort study of real-world data, baseline MRI PI-RADS score was significantly associated with early biopsy reclassification in men undergoing AS with NCCN low- or favorable intermediate-risk prostate cancer.

CO205 Impact of GLP-1A Treatment on Eating Disorder Incidence: A Comparative, Real World Data Study in Patients With and Without Pre-Existing Mental Health Conditions

CO205 Impact of GLP-1A Treatment on Eating Disorder Incidence: A Comparative, Real World Data Study in Patients With and Without Pre-Existing Mental Health Conditions

MT10 Higher SARS-CoV-2 Spike Antibody Levels Are Associated With Reduced Risk of Subsequent Symptomatic and Severe COVID-19: A Real-World Data Study

MT10 Higher SARS-CoV-2 Spike Antibody Levels Are Associated With Reduced Risk of Subsequent Symptomatic and Severe COVID-19: A Real-World Data Study

RWD1 To Investigate Gender and Racial Disparities in the Resource Utilization of Patients With Lung Diseases in the US: A Real-World Data Study

RWD1 To Investigate Gender and Racial Disparities in the Resource Utilization of Patients With Lung Diseases in the US: A Real-World Data Study

Use of machine learning approaches to predict transition of retention in care among people living with HIV in South Carolina: a real-world data study

ABSTRACT Maintaining retention in care (RIC) for people living with HIV (PLWH) helps achieve viral suppression and reduce onward transmission. This study aims to identify the best machine learning model that predicts the RIC transition over time. Extracting from the enhanced HIV/AIDS reporting system, this study included 9765 PLWH from 2005 to 2020 in South Carolina. Transition of RIC was defined as the change of RIC status in each two–year time window. We applied seven classifiers, such as Random Forest, Support Vector Machine, eXtreme Gradient Boosting and Long–short–term memory, for each lagged response to predict the subsequent year's RIC transition. Classification performance was assessed using balanced prediction accuracy, the area under the curve (AUC), recall, precision and F1 scores. The proportion of the four categories of RIC transition was 13.59%, 29.78%, 9.06% and 47.57%, respectively. Support Vector Machine was the best approach for every lag model based on both the F1 score (0.713, 0.717 and 0.719) and AUC (0.920, 0.925 and 0.928). The findings could facilitate the risk augment of PLWH who are prone to follow–up so that clinicians and policymakers could come up with more specific strategies and relocate resources for intervention to keep them sustained in HIV care.

A pharmacovigilance study of drug-reduced male semen quality based on the Food and Drug Administration adverse event reporting system database.

Real-world big data studies on drug-reduced male semen quality are few and far between, with most studies based on animal trials, small scale retrospective studies, or a limited number of pre-market clinical trials. This study aimed to identify culprit drugs that reduced male semen quality based on the United States Food and Drug Administration adverse event reporting system. The Medical Dictionary for Regulatory Activities preferred terms and standardized Medical Dictionary for Regulatory Activities queries were used to define reduced male semen quality. Adverse events related to drug-reduced male semen quality were then analyzed by disproportionality analysis using the United States Food and Drug Administration adverse event reporting system data between 2004 and 2023. At the preferred term level, 59 drugs with risk signals were detected to be associated with drug-reduced male semen quality, with the three most frequently reported second-level Anatomical Therapeutic Chemical groups being antineoplastic agents (n=16, 27.12%), psychoanaleptics (n=9, 15.25%), and psycholeptics (n=6, 10.17%). At the standardized Medical Dictionary for Regulatory Activities queries level, the five drugs with the greatest number of cases were finasteride (845 cases, IC025=7.72), dutasteride (163 cases, IC025=7.22), tamsulosin (148 cases, IC025=5.99), testosterone (101 cases, IC025=4.08), and valproic acid (54 cases, IC025=2.44). Additionally, clinical information about drug-reduced male semen quality is absent from the Summary of Product Characteristics of 41 drugs in our study. Using the United States Food and Drug Administration adverse event reporting system database, we offer a list of drugs with risk signals for reducing male semen quality. In the future, there is still a need for more studies on drugs whose effects on male semen quality are not fully understood.

Concordance between physician response assessment and a novel method per Lugano criteria in patients with lymphoma using real-world data.

e19082 Background: Clinical response assessment criteria, such as RECIST v1.1 and Lugano 2014, provide a standardized approach to assess treatment effectiveness in oncology clinical trials. Corresponding methodologies are needed for real-world data (RWD) to improve interpretability alongside clinical trial data and facilitate replication of results across RWD studies. We developed a RWD novel methodology, real-world Lugano (rwLugano), derived from Lugano 2014 criteria to classify lymphoma treatment response among patients with diffuse large B-cell lymphoma (DLBCL). Methods: A retrospective multisite RWD study identified adult patients with DLBCL treated with first line chemoimmunotherapy in US clinical practice (01JAN2015-31DEC2022). Participating sites abstracted clinical data via medical chart review and positron emission tomography-computed tomography (PET-CT) reports. Deidentified digital PET-CTs taken at treatment initiation and first response assessment were uploaded for BICR. Three distinct methods were used to assess treatment response: 1) physician-reported obtained from unstructured clinical notes in medical records, 2) rwLugano calculated using data (i.e., components of Lugano 2014) from PET-CT reports, and 3) BICR adjudication by two lymphoma radiologists using Lugano 2014 criteria. We compared the proportion of patients by response category: complete (CR), partial (PR), stable (SD) and progressive (PD) for each method. Analyses included agreement (%), concordance (Cohen’s kappa [κ]), and odds ratios with 95% confidence interval (OR; 95%CI) estimated using multivariable generalized linear mixed models (GLMM) adjusted for baseline characteristics. Results: The study identified 174 patients with DLBCL (female n=71 [41%]; white n=135 [78%]; Hispanic n=13 [7%]; mean age 66 years). Fewer patients were classified as CR at initial response via physician-reported response (n=111, 64%) compared to rwLugano (n=145, 83%), and BICR (n=142, 82%). Overall and CR agreement with BICR (see Table) was higher for rwLugano (overall: 83%, κ=0.49; CR: 86%, κ=0.50) than physician-charted response (overall: 72%, κ=0.45; CR: 76%, κ=0.43). In GLMM models, physician-charted response underestimated CR compared to BICR (OR=0.22, 95%CI:0.12-0.43), whereas rwLugano was statistically similar to BICR (OR=1.2, 95%CI:0.6-2.4). Conclusions: This study found that physician-reported response may underestimate CR at initial response, and rwLugano may be more consistent with BICR for treatment response assessment. Use of rwLugano warrants further evaluation as a methodology to assess treatment response in RWD lymphoma research. [Table: see text]

Risk of new-onset hypertension in patients (pts) with newly diagnosed chronic lymphocytic leukemia (CLL) treated with Bruton tyrosine kinase inhibitors (BTKi): A real-world data study using the Symphony Health Solution database.

e19014 Background: BTKis provide an important therapeutic option for pts diagnosed with CLL. Concerns have arisen about a potential association with the risk of cardiovascular events with BTKi. Using the Symphony Health Solutions database, this study describes the risk of new-onset hypertension in CLL pts treated with and without BTKis. Methods: Newly diagnosed CLL pts who started ibrutinib or acalabrutinib and those not treated with an approved BTKi between 2019 and 2022 were included in the analysis. The prevalence of hypertension prior to and risk of new-onset hypertension after treatment initiation were defined by use of antihypertensive medication. Pt demographics and comorbidities were described. Multivariate regression and inverse probability treatment weight based on propensity score were used to account for bias due to differences in pt characteristics between groups. Results: In CLL pts treated with (n=7,114) and without BTKis (n=34,571), demographics and clinical characteristics included age at the index date (mean: 70.2 yrs, BTKi; 69.0 yrs, without BTKi), sex (male: 59.8%, BTKi; 55.7%, without BTKi), and Charlson comorbidity scores (mean: 3.3, BTKi; 3.1, without BTKi). At baseline, the prevalence of hypertension defined by the use of antihypertensive medication was 67.8% with BTKi and 67.6% without BTKi. Among pts without any antihypertensive medication use at baseline, the rates of new-onset hypertension within 1 yr after treatment initiation were greater in pts with BTKis than without BTKis (Table). Conclusions: In this real-world analysis, CLL pts treated with BTKis had a higher burden of comorbidities, and use of antihypertensive medication was common. The risk of new-onset hypertension was higher in pts initiated on BTKis than those on non-BTKi treatments. These data suggest that development of hypertension is an important consideration in the long-term management of CLL pts undergoing BTKi treatment. [Table: see text]

Cost-effectiveness study of atezolizumab (ATZ) vs. durvalumab (DUR): Real-world data (RWD) on first-line chemotherapy combined with immune-checkpoint inhibitors (Chemo-ICIs) for extensive disease small-cell lung cancer (ED-SCLC).

8097 Background: Chemo-ICI is the standard of care in first-line therapy for ED-SCLC. Although there is no comparative data on ATZ vs. DUR, their efficacies appear to be equivalent based on results from IMpower133 and CASPIAN trials. On the other hand, the drug price of DUR is higher than that of ATZ, suggesting a different cost-effectiveness. Methods: This is a multicenter retrospective study of RWD. Clinical outcomes and safety information of ED-SCLC patients (pts) who had received Chemo-ICIs were collected from electronic medical records, and the total cost incurred during ICIs was obtained from the receipts of each hospital. Propensity score matching (PSM) was performed to adjust difference of pts' backgrounds of two groups (ATZ-G vs. DUR-G). The total monthly medical costs incurred during ICI administration for both groups were compared by cost minimization analysis to evaluate cost-effectiveness. Results: From August 2018 to December 2022, 274 pts (ATZ/DUR: 176/98) were extracted from 8 hospitals in Japan. After PSM and exclusion of cisplatin-treated pts, total 128 pts: 64 pts in each group were evaluated. The mean total medical costs per month during ICIs were 1,003,922 (±310,192) JPY (6,783 USD) in the ATZ-G and 1,596,511 (±371,405) JPY (10,787 USD) in the DUR-G (Wilcoxon rank sum test: p &lt; 0.001). Mean ICI drug costs per month during ICIs were 799,079 (±89,555) JPY (5,399 USD) in the ATZ-G and 1,570,744 (±371,405) JPY (10,163 USD) in the DUR-G (p &lt; 0.001). Response rate was 73.4% for ATZ-G and 75.0% for DUR-G. Median overall survivals (OSs) of ATZ-G vs. DUR-G were 13.9 (95% confidence interval [CI]: 11.7-17.5) vs. 13.6 (95% CI: 11.0-20.0) months, respectively (p = 0.919). Median progression-free survivals of ATZ-G vs. DUR-G were 4.9 (95% CI: 4.4-5.6) vs. 5.6 (95% CI: 5.0-6.7) months, respectively (p = 0.060). Cox-proportional hazard model identified poor performance status (hazard ratio [HR]: 5.5, p &lt; 0.001) and bone metastases (HR: 1.8, p = 0.029) as significant factors for shorter OS, while ATZ vs. DUR was not significant. ATZ-G revealed lower incidences of immune-related adverse events (irAEs) ≥grade 2 (10.9 vs. 31.3%, p = 0.009) and any grade interstitial lung disease (ILD) (3.1 vs. 20.3%, p = 0.004) than DUR-G. Number of hospitalizations in ATZ-G (median 1, range 0-6) was lower than that in DUR-G (median 2, range 0-7) (p = 0.005). Conclusions: Our RWD demonstrated a superior cost-effectiveness of ATZ to that of DUR. Total efficacies were similar, whereas the safety profiles, including irAE and ILD were more favorable in ATZ-G. Further discussion is required regarding not only cost-effectiveness but also clinical practicality such as: dose schedule of 3 weeks vs. 4 weeks; regimen flexibility of carboplatin vs. cisplatin; and etoposide dose adjustment of 100 mg/m2 vs. 80 mg/m2. Clinical trial information: 000053483.

AI-based approach to enable proactive identification of early lung cancer: A retrospective population health study and economic model.

10536 Background: Approximately 48,500 new cases of lung cancer are diagnosed each year in the UK with a five-year survival rate which lags behind other European countries. Most patients are diagnosed at stage III or IV disease, which has a significantly worse prognosis. The integration of real-world data and AI techniques presents a promising avenue for improvement, using novel solutions not achievable through traditional care models. This study explores proactive patient identification at scale, aligning with the "left shift" paradigm in population health. The approach uses innovative technologies and novel data sources to identify patients with early-stage disease, enhancing both clinical and economic outcomes. Importantly, these interventions should be feasible on a large scale without overburdening already stretched clinical services. Methods: A retrospective study of real-world data for an urban population with high socioeconomic disadvantage and health needs was undertaken. Two endpoints were determined: detection potential and health economic impact. For detection potential (DP), patients aged 40 and above who underwent chest X-rays (CXR) at a large academic medical centre between 2016-2022 were included. Natural Language Processing (NLP) analysed unstructured free-text data from Electronic Health Records, combined with ICD-10 codes, for predictive model (PM) development using Machine Learning (ML) classification techniques. The PM's performance was assessed using the area under the receiver operating characteristic curve (AUCROC). Health economic impact was evaluated through a theoretical extrapolation of DP. Assuming a 9% left shift from late (stage III or IV) to early (stage I or II) disease, a health economic model (HEM) compared the impact of the current care model to a potential future state facilitated by the digital medicine care model (DMCM). Results: 75,342 patients were included, with 755 lung cancer diagnoses occurring within 6 months of CXR. The PM achieved a peak AUROC of 0.75, exceeding the performance of currently used risk prediction models (Q Cancer Risk, Risk Assessment Tools). A 9% left shift equated to 4.5 years mean increase in survival. The DMCM was associated with a net healthcare cost benefit of £6k per patient diagnosed with lung cancer, improved quality-adjusted life years of £21M for the year 1 cohort over 10 years and increased economic productivity (from additional years in workforce) of £2.4M. Conclusions: The study demonstrates the practical utility of AI-supported early lung cancer detection at population scale. Real-world evidence is needed to prospectively validate the model as cost-effective, scalable, and efficient. Future work will seek to improve the model's performance against a broader at-risk patient population and explore its applicability to other late-presenting tumours.

Pancreatitis with use of new diabetic medications: a real-world data study using the post-marketing FDA adverse event reporting system (FAERS) database.

Background: Pancreatitis is characterized by inflammation of the pancreas and significantly affects quality of life. Less than 5% of pancreatitis cases are drug-induced, but recent evidence suggests a substantial risk associated with glucagon-like peptide-1 receptor agonists (GLP-1 RAs). The aim of this study was to compare the risk of developing pancreatitis between those using GLP-1 RAs and those using sodium-glucose transport protein 2 (SGLT2) inhibitors and dipeptidyl peptidase 4 (DPP-4) inhibitors. Methods: This study was done using the FDA Adverse Event Reporting System (FAERS) database from 2019 to 2021. This database contains information from diverse submissions from healthcare providers, patients, and manufacturers. To ensure fairness and accuracy, the risk of pancreatitis associated with other hypoglycemic agents (SGLT2 inhibitors and DPP-4 inhibitors) was also investigated. Traditional and Bayesian statistical analysis methods were used to identify disproportionate statistics and included the reporting odds ratio (ROR), proportional reporting ratio (PRR), empirical Bayes geometric mean (EBGM), and information component (IC). A drug-adverse-event combination that met the criteria of all four indices was deemed a signal. Results: The analysis of 2,313 pancreatitis reports linked to hypoglycemic agents revealed a predominant association with GLP-1 RA (70.2%) compared to DPP-4 inhibitors (15%) and SGLT2 (14.7%). Most of these reports involved female patients (50.4%), and the highest incidence occurred in those over 50 years old (38.4%). Additionally, 17.7% of the reports were associated with serious events. The ROR was significant for the risk of pancreatitis when using DPP-4 (13.2, 95% confidence interval (CI) 11.84-14.70), while the ROR for GLP-1 was 9.65 (95% CI 9.17-10.16). The EBGM was highest with DPP-4 (12.25), followed by GLP-1 (8.64), while IC was highest with DPP-4 inhibitors (3.61). Liraglutide had the greatest association with pancreatitis among the GLP-1 RAs (ROR: 6.83, 95% CI 6.60-7.07). Conclusion: The findings show that pancreatitis has a strong link with DPP-4 inhibitors and GPL1 agonists, which pose a greater risk. Among the GLP-1 agonist medications, liraglutide has been found to have an association with pancreatitis.

In-hospital survival of critically ill COVID-19 patients treated with glucocorticoids: a multicenter real-world data study

The COVID-19 pandemic has posed a major challenge to healthcare systems globally. Millions of people have been infected, and millions of deaths have been reported worldwide. Glucocorticoids have attracted worldwide attention for their potential efficacy in the treatment of COVID-19. Various glucocorticoids with different dosages and treatment durations have been studied in patients with different severities, with a suitable dosage and treatment duration not yet defined. This study aimed to investigate whether in-hospital survival differs between critically ill patients treated with low-dose glucocorticoids, high-dose glucocorticoids or no glucocorticoids. All critically ill patients admitted to the intensive care unit of the Charité Hospital—Universitätsmedizin Berlin between February 2020 and December 2021 with COVID-19 pneumonia receiving supplemental oxygen were eligible to participate in this multicenter real-world data study. Patients were retrospectively assigned to one of three groups: the high corticosteroid dose (HighC) group (receiving 6 mg parenteral dexamethasone or an equivalent corticosteroid dosage for ten days), the low corticosteroid dose (LowC) group (receiving less than 6 mg parenteral dexamethasone or an equivalent corticosteroid dosage for ten days), or the no corticosteroid (NoC) group. Overall survival and risk effects were compared among groups within the total observation period, as well as at 35 days after the onset of COVID-19 symptoms. Adjusted multivariable Cox proportional hazard regression analysis was performed to compare the risk of death between the treatment groups. Out of 1561 critically ill COVID-19 patients, 1014 were included in the baseline analysis. In the survival study, 1009 patients were assigned to the NoC (n = 346), HighC (n = 552), or LowC group (n = 111). The baseline characteristics were balanced between groups, except for age, BMI, APACHE II score, SOFA and SAPS II. While the 35-day survival did not show any differences, a landmark analysis of the patients surviving beyond 35 days revealed differences between groups. The restricted mean survival time was 112 days in the LowC group [95% CI: 97 – 128], 133 days in the HighC group [95% CI: 124 – 141] and 144 days in the NoC group [95% CI: 121 – 167]. The multivariable-adjusted Cox proportional hazard analysis indicated that, regardless of age, sex, health status or invasive oxygenation, a low-dose treatment increased the hazard of death of critically ill COVID-19 patients by a factor of 2.09 ([95% CI: 0.99, 4.4], p = 0.05) and a high-dose corticosteroid treatment increased the risk by a factor of 1.07 ([95% CI: 0.53, 2.15], p = 0.85) compared to no treatment with glucocorticoids. The analysis reveals that corticosteroid treatment does not influence the survival of critically ill COVID-19 patients in the intensive care unit within 35 days. Our evaluations further suggest that regardless of ventilation status, the decision-making process for administering corticosteroid therapy should account for the individual severity of the illness.