A brief introduction to research based on real-world evidence: Considering the Korean National Health Insurance Service database

Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective Observational Study by Using the Common Data Model

Background/Objectives: Earlier detection of severe immune-related hematological adverse events (irHAEs) in cancer patients treated with a PD-1 or PD-L1 inhibitor is critical to improving treatment outcomes. The study aimed to develop a simple machine learning (ML) model for predicting irHAEs associated with PD-1/PD-L1 inhibitors. Methods: We utilized the Observational Medical Outcomes Partnership-Common Data Model based on electronic medical records from a tertiary (KHMC) and a secondary (KHNMC) hospital in South Korea. Severe irHAEs were defined as Grades 3-5 by the Common Terminology Criteria for Adverse Events (version 5.0). The predictive model was developed using the KHMC dataset, and then cross-validated against an independent cohort (KHNMC). The full ML models were then simplified by selecting critical features based on the feature importance values (FIVs). Results: Overall, 397 and 255 patients were included in the primary (KHMC) and cross-validation (KHNMC) cohort, respectively. Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). Parsimonious models reduced to 50% FIVs of the full models showed comparable performance to the full models (AUROC 0.83-0.86, p > 0.05). The KHMC and KHNMC parsimonious models shared common predictive features including furosemide, oxygen gas, piperacillin/tazobactam, and acetylcysteine. Conclusions: Considering the simplicity and adequate predictive performance, our simplified ML models might be easily implemented in clinical practice with broad applicability. Our model might enhance early diagnostic screening of irHAEs induced by PD-1/PD-L1 inhibitors, contributing to minimizing the risk of severe irHAEs and improving the effectiveness of cancer immunotherapy.

The association between inflammatory bowel disease and risk of prostate cancer: a population-based retrospective study based on Korean National Health Insurance Service database

Background

The aim of this study was to determine whether inflammatory bowel disease (IBD) is associated with the risk of developing prostate cancer (PCa) through a population-based study.

Materials and methods

Male patients aged ≥40 years, diagnosed with IBD from 2010 to 2013 and without IBD were identified and followed-up till 2019. A matched cohort of male patients with and without IBD in a ratio of 1:4 was created based on age, income level, and Charlson comorbidity index. Multivariate Cox regression analysis was conducted to evaluate the association of IBD with the prescence of PCa and PCa requiring definitive treatment within 1 year of diagnosis. The hazard ratio (HR) and 95% confidence interval (CI) were stratified by Crohn's disease, ulcerative colitis (UC), and subtypes.

Results

After matching, 15,751 IBD patients and 62,346 controls were analyzed. Over a median follow-up period of 96 months, the HR for PCa was significantly increased in patients with IBD (HR: 2.44; 95% CI: 2.08-2.86, P < 0.001). IBD was also associated with PCa requiring definitive treatment within 1 year (HR: 2.67; 95% CI: 2.09-3.42, P < 0.001). In subgroup analysis, UC (HR: 2.83; 95% CI: 2.18-3.69, P < 0.001) showed higher risk of PCa requiring definitive treatment than for Crohn's disease (HR: 2.21; 95% CI: 1.43-3.43, P = 0.0004). All-cause death in patient-diagnosed PCa was the highest in UC of pancolitis (HR: 2.26; 95% CI: 0.99-5.16, P = 0.054), and the lowest in ulcerative proctitis (HR: 0.35; 95% CI: 0.21-0.60, P = 0.0001).

Conclusion

IBD was associated with an increased incidence of PCa in our matched analysis.

Integrated Real-World Data Warehouses Across 7 Evolving Asian Health Care Systems: Scoping Review

BACKGROUND

Asia consists of diverse nations with extremely variable health care systems. Integrated real-world data (RWD) research warehouses provide vast interconnected data sets that uphold statistical rigor. Yet, their intricate details remain underexplored, restricting their broader applications.

OBJECTIVE

Building on our previous research that analyzed integrated RWD warehouses in India, Thailand, and Taiwan, this study extends the research to 7 distinct health care systems: Hong Kong, Indonesia, Malaysia, Pakistan, the Philippines, Singapore, and Vietnam. We aimed to map the evolving landscape of RWD, preferences for methodologies, and database use and archetype the health systems based on existing intrinsic capability for RWD generation.

METHODS

A systematic scoping review methodology was used, centering on contemporary English literature on PubMed (search date: May 9, 2023). Rigorous screening as defined by eligibility criteria identified RWD studies from multiple health care facilities in at least 1 of the 7 target Asian nations. Point estimates and their associated errors were determined for the data collected from eligible studies.

RESULTS

Of the 1483 real-world evidence citations identified on May 9, 2023, a total of 369 (24.9%) fulfilled the requirements for data extraction and subsequent analysis. Singapore, Hong Kong, and Malaysia contributed to ≥100 publications, with each country marked by a higher proportion of single-country studies at 51% (80/157), 66.2% (86/130), and 50% (50/100), respectively, and were classified as solo scholars. Indonesia, Pakistan, Vietnam, and the Philippines had fewer publications and a higher proportion of cross-country collaboration studies (CCCSs) at 79% (26/33), 58% (18/31), 74% (20/27), and 86% (19/22), respectively, and were classified as global collaborators. Collaboration with countries outside the 7 target nations appeared in 84.2% to 97.7% of the CCCSs of each nation. Among target nations, Singapore and Malaysia emerged as preferred research partners for other nations. From 2018 to 2023, most nations showed an increasing trend in study numbers, with Vietnam (24.5%) and Pakistan (21.2%) leading the growth; the only exception was the Philippines, which declined by -14.5%. Clinical registry databases were predominant across all CCCSs from every target nation. For single-country studies, Indonesia, Malaysia, and the Philippines favored clinical registries; Singapore had a balanced use of clinical registries and electronic medical or health records, whereas Hong Kong, Pakistan, and Vietnam leaned toward electronic medical or health records. Overall, 89.9% (310/345) of the studies took >2 years from completion to publication.

CONCLUSIONS

The observed variations in contemporary RWD publications across the 7 nations in Asia exemplify distinct research landscapes across nations that are partially explained by their diverse economic, clinical, and research settings. Nevertheless, recognizing these variations is pivotal for fostering tailored, synergistic strategies that amplify RWD's potential in guiding future health care research and policy decisions.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/43741.

Deliberative process of health technology reassessment by health technology assessment agency in Korea

In 2019, the National Evidence-based Healthcare Collaborating Agency (NECA) in Korea established a health technology reassessment (HTR) system to manage the life cycle of health technologies and develop operational measures promoting the efficient use of healthcare resources. The purpose of this study is to introduce the detailed implementation process and practical functional methods of the HTR implemented by NECA.The HTR is a structured multidisciplinary method for analyzing health technologies currently used in the healthcare system based on the latest information on parameters, such as clinical safety, effectiveness, and cost-effectiveness of optimizing the use of healthcare resources as well as social and ethical issues. All decision-making stages of the HTR are carefully reviewed and transparently managed. The HTR committee makes significant decisions, and the subcommittee decides the details related to the assessment process.Since the pilot began in 2018, 262 cases have been reassessed, of which, 126 cases (48.1 percent) were health services not covered by the National Health Insurance (NHI). Over the past 5 years, approximately 130 recommendations for the in-use technologies were determined by the HTR committee. In the near future, it will be necessary to officially develop and establish a Korean HTR system and a legal foundation to optimize the NHI system.

Real-world data analysis on effectiveness of integrative therapies: A practical guide to study design and data analysis using healthcare databases

Real world data (RWD) is increasingly used to investigate health outcomes and treatment efficacy in the field of integrative medicine. Due to the fact that the majority of RWDs are not intended for research, their secondary use in research necessitates complex study designs to account for bias and confounding. To conduct a robust analysis of RWD in integrative medicine, a comprehensive study design process that reflects the characteristics of integrative therapies is necessary. In this paper, we present a guide for designing comparative effectiveness RWE research in integrative medicine. We discuss key factors to consider when selecting RWDs for research on integrative medicine. We provide practical steps for developing a research question, formulating the PICOT objectives (population, intervention, comparator, outcome, and time horizon), and selecting and defining covariates with a summary table. Specific study designs are depicted with corresponding diagrams. Finally, data analysis procedures are introduced. We hope this article clarifies the importance of RWE research design and related processes in order to improve the rigor of RWD studies in the field of integrative medicine research.

Comparative analysis of mortality and progression to end-stage renal disease between surgically induced and medical chronic kidney disease: A study using the National Health Insurance customized database

PURPOSE

We aimed to compare the mortality rate and the risk for progression to end-stage renal disease (ESRD) and cardiovascular disease (CVD) between patients who underwent surgery for localized renal cell carcinoma (RCC) and those with chronic kidney disease (CKD) without surgery by investigating the National Health Insurance Service.

MATERIALS AND METHODS

The surgical group (CKD-S) included patients who underwent radical or partial nephrectomy for RCC from 2007 to 2009. Grades of surgical CKD were classified according to the estimated glomerular filtration rate (eGFR) measured at a health screening within 2 years after surgery. The nonsurgical group (CKD-M) was graded according to the eGFR in the 2009-2010 health screenings. We performed 1:5 propensity score matching for age, gender, diabetes, hypertension, Charlson comorbidity index, smoking, alcohol consumption, baseline eGFR, and body mass index.

RESULTS

A total of 8,698 patients (CKD-S, n=1,521; CKD-M, n=7,177) were analyzed. The CKD-M group was at higher risk for progression to ESRD (hazard ratio [HR] 1.90, 95% confidence interval [CI] 1.04-3.44, p=0.036) and CVD (HR 1.17, 95% CI 1.06-1.29, p=0.002) than the CKD-S group. In the group of patients with grade 3 disease or higher, the CKD-M group was at significantly higher risk for progression to ESRD (HR 2.21, 95% CI 1.47-3.31, p<0.001), CVD (HR 1.32, 95% CI 1.20-1.45, p<0.001), and overall mortality (HR 1.50, 95% CI 1.21-1.86, p<0.001).

CONCLUSIONS

The risk for progression to ESRD, CVD, or mortality in patients with CKD-S may be lower than in patients with CKD-M.

The association between prostatitis and risk of prostate cancer: a National Health Insurance Database study

PURPOSE

Inflammation is thought to affect the development of prostate cancer (PCa). By retrospectively investigating the database of the National Health Insurance Service, this study attempted to perform a relevant analysis of patients with prostatitis and PCa.

METHODS

Participants were aged ≥ 50 years. Patients diagnosed with prostatitis between 2010 and 2013 and matched controls were followed up until 2019. We selected controls with matched propensity scores for age, diabetes, hypertension, and the Charlson comorbidity index. Multivariate Cox regression analysis was conducted to determine the hazard ratio (HR) and 95% confidence interval (CI) of the association between prostatitis and PCa. The HR for PCa according to the presence of prostatitis was classified as acute, chronic, or other prostatitis.

RESULTS

A total of 746,176 patients from each group were analyzed. The incidence of PCa was significantly higher in the group with prostatitis (1.8% vs 0.6%, p < 0.001). The HR for PCa was significantly higher in patients with prostatitis (HR 2.99; 95% CI 2.89-3.09, p < 0.001). The HR for PCa was significantly higher in acute prostatitis than in chronic prostatitis (3.82; 95% CI 3.58-4.08; p < 0.001; HR 2.77; 95% CI 2.67-2.87, p < 0.001). The incidence of all-cause death in patients diagnosed PCa was significantly lower in prostatitis group (HR 0.58, 95% CI 0.53-0.63, p < 0.001).

CONCLUSION

Prostatitis is associated with an increased incidence of PCa. Acute prostatitis is associated with higher risk of PCa than chronic prostatitis. Clinicians should inform patients with prostatitis that they may have an increased risk of diagnosing PCa, and follow-up is needed.

Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers

Real world data (RWD) and real-world evidence (RWE) plays an increasingly important role in clinical research since scientific knowledge is obtained during routine clinical large-scale practice and not experimentally as occurs in the highly controlled traditional clinical trials. Particularly, the electronic health records (EHRs) are a relevant source of data. Nevertheless, there are also significant challenges in the correct use and interpretation of EHRs data, such as bias, heterogeneity of the population, and missing or non-standardized data formats. Despite the RWD and RWE recognized difficulties, these are easily outweighed by the benefits of ensuring the efficacy, safety, and cost-effectiveness in complement to the gold standards of the randomized controlled trial (RCT), namely by providing a complete picture regarding factors and variables that can guide robust clinical decisions. Their relevance can be even further evident as healthcare units develop more accurate EHRs always in the respect for the privacy of patient data. This editorial is an overview of the RWD and RWE major aspects of the state of the art and supports the Special Issue on "Digital Health and Big Data Analytics: Implications of Real-World Evidence for Clinicians and Policymakers" aimed to explore all the potential and the utility of RWD and RWE in offering insights on diseases in a broad spectrum.