When and How Can Real World Data Analyses Substitute for Randomized Controlled Trials?

Real world data on digital remote refraction in a healthy population of 14,680 eyes

Refractive errors are the leading cause of preventable visual impairment, to which web-based remote refraction could contribute. We report real-world 2021-2022 data of the underlying algorithm and validated these to conventional prescriptions among healthy individuals (high visual acuity and satisfactied current refraction). Participants were 18-45 years with a spherical (S) error between -3.50 + 2.00S to -2.00 Diopter Cylinder (DC), reported as Spherical Equivalent (SEQ) in mean differences and 95% Limits of agreement. Consecutive measurements (n = 14,680) were assessed of which n = 6386 selected for validation. The mean difference was 0.01D(SD 0.69) and -0.73D(SD 0.92) for myopes and hyperopes respectively. This algorithm shows variation, nonetheless, 67% and 82% of myopes were within ±0.5 and ±0.75D. The test underestimates hyperopes (34% and 50% within ±0.5D and ±0.75D) and had inconsistencies distinguishing hyperopia. This proof-of-concept shows home testing has the potency to increase accessibility to care by delivering a valuable alternative for uncomplicated refractive assessments.

Efficacy and Safety of Bispecific T-Cell Engagers in Relapsed/Refractory Multiple Myeloma: A Real-World Data-Based Case-Controlled Study

Although bispecific T-cell engager (BiTE) is a promising treatment for relapsed/refractory multiple myeloma (RRMM), it needs to be evaluated in a real-world setting. This study aimed to evaluate the efficacy and safety of BiTEs compared with a synthetic standard of care (SOC). From a multicenter registry database of 474 patients with RRMM who received third- or more advanced-line treatments between January 2021 and October 2023, 1:1 propensity score-matched BiTE cohort (n = 71) and SOC cohort (n = 71) were established. Matching was based on age, sex, number of prior therapies, international staging system at diagnosis, and baseline biochemical characteristics. Compared with the matched SOC cohort, the matched BiTE cohort demonstrated a significant improvement in median progression-free survival (PFS, 19.2 vs 5.4 months, hazard ratio (HR) = .50 [95% CI, .33 to .78], p < .01). However, the overall survival (OS) was not significantly different between the two cohorts. Safety profiles showed that 37 (52%) patients in the matched BiTE cohort experienced cytokine release syndrome, mostly grade 1 (n = 29, 41%), with rare occurrences of neurotoxicity (n = 4, 5.6%). Infections were significantly more common in the matched BiTE cohort compared with the matched SOC cohort (81% vs. 49%, p < .01). Non-B-cell mutation antigen (BCMA)-targeted BiTEs improved 6-month OS rates compared with BCMA-targeted BiTEs in monotherapy (94% [95% CI, 84 to 100] vs. 65% [95% CI, 45 to 95], p = .04) and combination with daratumumab (100% [95% CI, 100 to 100] vs. 77% [95% CI, 57 to 100], p = .20). Non-BCMA-targeted BiTEs also provided benefit for 6-month PFS rate compared with the BCMA-targeted BiTE cohort in monotherapy (76% [95% CI, 59 to 100] vs. 50% [95% CI, 31 to 82], p = .11) and combination with daratumumab (100% [95% CI, 100 to 100] vs. 69% [95% CI, 48 to 99], p = .10). Quantitative bias and sensitivity analyses confirmed the robustness of these results. This real-world data-based study underscores the potential of BiTEs to significantly enhance survival outcomes in patients with heavily treated RRMM and manageable safety profiles. The difference in clinical outcomes by BiTE targets warrants further investigation in larger clinical trials (ClinicalTrials.gov identifier: NCT06205823).

Operationalising routinely collected patient data in research to further the pursuit of social justice and health equity: a team-based scoping review

BACKGROUND

Vast volumes of routinely collected data (RCD) about patients are collated by health professionals. Leveraging this data - a form of real-world data - can be valuable for quality improvement and contributing to the evidence-base to inform practice. Examining routine data may be especially useful for examining issues related to social justice such as health inequities. However, little is known about the extent to which RCD is utilised in health fields and published for wider dissemination.

OBJECTIVES

The objective of this scoping review is to document the peer-reviewed published research in allied health fields which utilise RCD and evaluate the extent to which these studies have addressed issues pertaining to social justice.

METHODS

An enhanced version of the Arksey and O'Malley's framework, put forth by Westphalm et al. guided the scoping review. A comprehensive literature search of three databases identified 1584 articles. Application of inclusion and exclusion criteria was piloted on 5% of the papers by three researchers. All titles and abstracts were screened independently by 2 team members, as were full texts. A data charting framework, developed to address the research questions, was piloted by three researchers with data extraction being completed by the lead researcher. A sample of papers were independently charted by a second researcher for reliability checking.

RESULTS

One hundred and ninety papers were included in the review. The literature was diverse in terms of the professions that were represented: physiotherapy (33.7%) and psychology/mental health professions (15.8%) predominated. Many studies were first authored by clinicians (44.2%), often with clinical-academic teams. Some (33.25%) directly referenced the use of their studies to examine translation of research to practice. Few studies (14.2%) specifically tackled issues pertaining to social justice, though many collected variables that could have been utilised for this purpose.

CONCLUSION

Studies operationalising RCD can meaningfully address research to practice gaps and provide new evidence about issues related to social justice. However, RCD is underutilised for these purposes. Given that vast volumes of relevant data are routinely collected, more needs to be done to leverage it, which would be supported by greater acknowledgement of the value of RCD studies.

Methodological challenges using routine clinical care data for real-world evidence: a rapid review utilizing a systematic literature search and focus group discussion

BACKGROUND

The integration of real-world evidence (RWE) from real-world data (RWD) in clinical research is crucial for bridging the gap between clinical trial results and real-world outcomes. Analyzing routinely collected data to generate clinical evidence faces methodological concerns like confounding and bias, similar to prospectively documented observational studies. This study focuses on additional limitations frequently reported in the literature, providing an overview of the challenges and biases inherent to analyzing routine clinical care data, including health claims data (hereafter: routine data).

METHODS

We conducted a literature search on routine data studies in four high-impact journals based on the Journal Citation Reports (JCR) category "Medicine, General & Internal" as of 2022 and three oncology journals, covering articles published from January 2018 to October 2023. Articles were screened and categorized into three scenarios based on their potential to provide meaningful RWE: (1) Burden of Disease, (2) Safety and Risk Group Analysis, and (3) Treatment Comparison. Limitations of this type of data cited in the discussion sections were extracted and classified according to different bias types: main bias categories in non-randomized studies (information bias, reporting bias, selection bias, confounding) and additional routine data-specific challenges (i.e., operationalization, coding, follow-up, missing data, validation, and data quality). These classifications were then ranked by relevance in a focus group meeting of methodological experts. The search was pre-specified and registered in PROSPERO (CRD42023477616).

RESULTS

In October 2023, 227 articles were identified, 69 were assessed for eligibility, and 39 were included in the review: 11 on the burden of disease, 17 on safety and risk group analysis, and 11 on treatment comparison. Besides typical biases in observational studies, we identified additional challenges specific to RWE frequently mentioned in the discussion sections. The focus group had varied opinions on the limitations of Safety and Risk Group Analysis and Treatment Comparison but agreed on the essential limitations for the Burden of Disease category.

CONCLUSION

This review provides a comprehensive overview of potential limitations and biases in analyzing routine data reported in recent high-impact journals. We highlighted key challenges that have high potential to impact analysis results, emphasizing the need for thorough consideration and discussion for meaningful inferences.

Real-World Evidence on the Effectiveness of Pembrolizumab in Patients With Recurrent/Metastatic/Unresectable Head and Neck Squamous Cell Cancer: A Systematic Review and Meta-Analysis

The aim of the review was to systematically review real-world data on the effectiveness and safety of pembrolizumab in recurrent/metastatic/unresectable head and neck squamous cell cancer (HNSCC) patients. Two independent reviewers retrieved the studies separately and simultaneously. PubMed, Embase, Scopus, Web of Science, and Cochrane Central were searched for prospective and retrospective studies on recurrent/metastatic/unresectable HNSCC patients treated with either pembrolizumab monotherapy or pembrolizumab combination therapy published till November 2024. Studies published in the English language and available as full-text articles were included while studies with patients treated with additional chemotherapeutic agents that do not include chemotherapy with fluorouracil, platinum, cetuximab, or radiotherapy were excluded. Outcomes were overall response rate, progression-free survival, overall survival, and adverse events. Forest plots were generated using RevMan software version 5.4 (2020; The Cochrane Collaboration, London, United Kingdom). The ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool was used for the assessment of the potential risk of bias and the quality of evidence was synthesized using GRADEpro (Evidence Prime Inc., Hamilton, Canada). We identified 5884 records, removed 2784 duplicate records, and screened 3100 studies. A total of 2931 records were excluded based on title/abstract. Of the remaining 169 articles, nine studies satisfied eligibility criteria and were included for final review. Pooled data suggested that 1006 patients were administered with pembrolizumab monotherapy while 448 patients received pembrolizumab combination therapy. Monotherapy improved the overall response rate compared to combination therapy. No significant difference in progression-free survival and overall survival was found between the two groups. Adverse events were reported less in pembrolizumab monotherapy compared to pembrolizumab combination therapy. The studies were assessed at high risk of bias and graded at low to very low quality of evidence. The study showed some beneficial effects of pembrolizumab monotherapy in recurrent/metastatic/unresectable HNSCC patients in real-world scenarios. However, more studies are required to generate robust evidence.

Sociodemographics and clinical factors associated with depression treatment outcomes in 65,741 first-time users of selective serotonin reuptake inhibitors: A Danish cohort study in older adults

OBJECTIVE

To investigate a wide range of sociodemographic and clinical factors associated with treatment outcomes in older adults who initiated an SSRI for depression treatment in a real-world setting.

METHODS

This cohort study used Danish registry data covering all older adults (aged ≥65) who initiated SSRIs for depression from 2006 to 2017, first-time (since 1995). We followed the individuals for one year after their SSRI prescription. Six different outcomes were analyzed, including treatment discontinuation, switching, augmentation, psychiatric hospital contacts for depression, psychiatric hospital admission, and suicide attempt/self-harm. Association analyses employed Poisson regression, estimating incidence rate ratios with 95 % confidence intervals.

RESULTS

The study included 65,741 individuals with a mean age of 78.23 years, and 55.6 % were females. During follow-up, 40.1 % discontinued, 4.8 % switched, 20.3 % received augmentation, 3.0 % had psychiatric hospital contacts for depression, 3.2 % had psychiatric admission, and 0.1 % had suicide attempt/self-harm records. Differential treatment outcomes were observed based on sociodemographic and clinical factors. For example, being female, residing predominantly in rural areas, having psychiatric or somatic diagnoses, and using medications acting on blood/blood-forming organs, the cardiovascular system, or musculo-skeletal systems were linked to fewer unfavorable clinical outcomes. Conversely, marital status as being single or separated and the use of nervous system drugs were associated with a higher risk of unfavorable outcomes.

LIMITATIONS

Confounding by indication might remain a problem, and depression severity data was not unavailable.

CONCLUSIONS

Our findings emphasize considering patient characteristics in clinical decisions, as they can influence the clinical course of those undergoing depression treatment.

Machine learning approach for detection of MACE events within clinical trial data

Randomized controlled trials (RCTs) are the gold standard for clinical research but may not accurately reflect the impact of medicines in real-world settings. Supplementing RCTs with insights from real-world data (RWD) can address known limitations by including more diverse patient populations, additional types of sites-of-care, and practices more representative of the care most people receive. One current challenge in using RWD is the lack of an algorithmic approach to identifying outcomes. To address this, machine learning models for identifying a frequently used outcome, Major Adverse Cardiovascular Events (MACE), were developed in Clinical Trial Data (CTD). Anonymized CTD sourced from the Medidata Enterprise Data Store were used to develop model features on the condition that they would be useful for labelling MACE events and that they could also be found in RWD. These features were used to train three random forest models to identify each component of 3-point MACE in a patient's clinical trial journey. Performance metrics for the models are presented (recall = 0.72 [0.07], precision = 0.68 [0.12] - mean, [SD]) along with the top contributing features. We show that the models can be tuned specifically to replicate the adjudication panels' results and present a cost-benefit analysis for deploying such models in clinical trial settings. We demonstrate the viability of using advanced algorithms for identifying clinical outcomes in prospective clinical trials. Deployment of such models could reduce the resources required to conduct RCTs. Extending such models to RWD would facilitate approval of pragmatic clinical trials for regulatory submissions.

Characteristics of non-randomised studies of drug treatments: cross sectional study

ABSTRACT

Objective

To examine the characteristics of comparative non-randomised studies that assess the effectiveness or safety, or both, of drug treatments.

Design

Cross sectional study.

Data sources

Medline (Ovid), for reports published from 1 June 2022 to 31 August 2022.

Eligibility criteria for selecting studies

Reports of comparative non-randomised studies that assessed the effectiveness or safety, or both, of drug treatments were included. A randomly ordered sample was screened until 200 eligible reports were found. Data on general characteristics, reporting characteristics, and time point alignment were extracted, and possible related biases, with a piloted form inspired by reporting guidelines and the target trial emulation framework.

Results

Of 462 reports of non-randomised studies identified, 262 studies were excluded (32% had no comparator and 25% did not account for confounding factors). To assess time point alignment and possible related biases, three study time points were considered: eligibility, treatment assignment, and start of follow-up. Of the 200 included reports, 70% had one possible bias, related to: inclusion of prevalent users in 24%, post-treatment eligibility criteria in 32%, immortal time periods in 42%, and classification of treatment in 23%. Reporting was incomplete, and only 2% reported all six of the key elements considered: eligibility criteria (87%), description of treatment (46%), deviations in treatment (27%), causal contrast (11%), primary outcomes (90%), and confounding factors (88%). Most studies used routinely collected data (67%), but only 7% reported using validation studies of the codes or algorithms applied to select the population. Only 7% of reports mentioned registration on a trial registry and 3% had an available protocol.

Conclusions

The findings of the study suggest that although access to real world evidence could be valuable, the robustness and transparency of non-randomised studies need to be improved.

Hysterectomy versus uterine preservation for pelvic organ prolapse surgery: a prospective cohort study

BACKGROUND

One in 5 females will have surgery to treat pelvic organ prolapse in their lifetime. Uterine-preserving surgery involving suspension of the uterus is an increasingly popular alternative to the traditional use of hysterectomy with vaginal vault suspension to treat pelvic organ prolapse; however, comparative evidence with native tissue repairs remains limited in scope and quality.

OBJECTIVE

To compare 1-year outcomes between hysterectomy-based and uterine-preserving native tissue prolapse surgeries performed through minimally invasive approaches.

STUDY DESIGN

We used a nonrandomized design with patients self-selecting their surgical group to integrate a pragmatic, patient-centered, and autonomy-focused approach. Participants chose between uterine-preserving surgery or hysterectomy-based surgery, guided by neutral evidence-based discussions and individualized decision-making, with support from fellowship-trained urogynecologists. Inverse probability of treatment weighting based on high-dimensional propensity scores was used to balance baseline differences across surgical groups in an effort to resemble a randomized clinical trial. A prospective cohort study of 321 participants with stage ≥2 prolapse involving the uterus who desired surgical treatment were recruited between 2020 and 2022 and followed to 1 year (retention >90%). Patients chose to receive uterine-preserving pelvic organ prolapse surgery through hysteropexy (n=151) or hysterectomy with vaginal vault suspension (n=170; reference group), with repair of anterior and/or posterior prolapse if indicated. The primary outcome was anatomic prolapse recurrence within 1 year, defined as apical descent ≥50% of the total vaginal length. Secondary outcomes were perioperative, functional, clinical, and healthcare outcomes measured at 6 weeks and 1 year. Inverse probability of treatment weighted linear regression and modified Poisson regression were used to estimate adjusted mean differences and relative risks, respectively.

RESULTS

Apical anatomic recurrence rates at 1 year were 17.2% following hysterectomy and 7.5% following uterine-preservation, resulting in an adjusted relative risk of 0.35 (95% CI 0.15, 0.83). Uterine-preserving surgery was associated with shorter length of surgery (adjusted mean difference -0.68 hours [-0.80, -0.55]) and hospitalization (adjusted mean difference -4.34 hours [-7.91, -0.77]), less use of any opioids within 24 hours (adjusted relative risk 0.79 [0.65, 0.97]), and fewer procedural complications (adjusted relative risk 0.19 [0.04, 0.83]) than hysterectomy. Up to 1 year, uterine-preserving surgery was associated with lower risk of composite recurrence (stage ≥2 prolapse in any compartment or retreatment; adjusted relative risk 0.47 [0.32, 0.69]) than hysterectomy, driven by anatomic outcomes. There were no clinically meaningful differences in functional or healthcare outcomes between surgical groups.

CONCLUSION

This study adds real-world evidence to the growing body of research supportive of uterine-preserving surgery as a safe, efficient, and effective alternative to hysterectomy during native tissue prolapse repair. Given mounting evidence on safety, efficiency, and effectiveness of uterine-preserving surgery and its alignment with the preferences of approximately half of patients to keep their uterus, the standard of care should include routine offering and patient choice between uterine-preserving and hysterectomy-based surgery for pelvic organ prolapse.

On the use of RWD in support of regulatory submission in drug development

For the approval of a drug product, the United States Food and Drug Administration requires substantial evidence (SE) regarding effectiveness and safety of the test drug to be provided. In recent years, the use of real-world data in support of regulatory submission of pharmaceutical development has received much attention, and real-world evidence (RWE) is treated as complementary to SE by evaluating the real-world performance of the test treatment. In this article, we start by summarizing current regulatory perspectives on drug evaluation and some potential challenges in using RWE. To test for superiority in co-primary endpoints, a two-stage hybrid RCT/RWS adaptive design that combines randomized control trial for providing SE and real-world study for generating RWE is proposed. We use superiority in effectiveness and non-inferiority in safety as an example to illustrate how to implement this design. Numerical studies have shown that the proposed design has merits in reducing the required sample size compared with traditional co-primary endpoint tests while maintaining statistical power and controlling type I error inflation. The proposed design can be implemented in drug development considering co-primary endpoints, especially for oncology and rare disease drug development.

A Two-Step Framework for Validating Causal Effect Estimates

BACKGROUND

Comparing causal effect estimates obtained using observational data to those obtained from the gold standard (i.e., randomized controlled trials [RCTs]) helps assess the validity of these estimates. However, comparisons are challenging due to differences between observational data and RCT generated data. The unknown treatment assignment mechanism in the observational data and varying sampling mechanisms between the RCT and the observational data can lead to confounding and sampling bias, respectively.

AIMS

The objective of this study is to propose a two-step framework to validate causal effect estimates obtained from observational data by adjusting for both mechanisms.

MATERIALS AND METHODS

An estimator of causal effects related to the two mechanisms is constructed. A two-step framework for comparing causal effect estimates is derived from the estimator. An R package RCTrep is developed to implement the framework in practice.

RESULTS

A simulation study is conducted to show that using our framework observational data can produce causal effect estimates similar to those of an RCT. A real-world application of the framework to validate treatment effects of adjuvant chemotherapy obtained from registry data is demonstrated.

CONCLUSION

This  study constructs a framework for comparing causal effect estimates between observational data and RCT data, facilitating the assessment of the validity of causal effect estimates obtained from observational data.

Comparative risk of opioid overdose in patients who initiated antibiotics for urinary tract infection while on long-term opioid therapy

Sulfamethoxazole/trimethoprim, a commonly used antibiotic, has been associated with opioid overdose in patients with long-term opioid use, based on a prior drug-drug interaction screening study. To evaluate whether this finding represents a false-positive signal due to potential confounding, we assessed the safety of sulfamethoxazole/trimethoprim relative to 2 comparable antibiotic treatments in patients receiving long-term opioid therapy. We used data from 4 large administrative claims databases spanning 2000-2019. The study population was restricted to patients aged 18 years or older with urinary tract infection and at least 90 days of continuous prescription opioid use who initiated sulfamethoxazole/trimethoprim, nitrofurantoin, or fluoroquinolone therapy. We used propensity score matching weights to adjust for confounding and Cox proportional hazards models to estimate weighted hazard ratios (HRs) and 95% CIs in a 30-day intention-to-treat analysis. Cumulative 30-day opioid overdose risk ranged between 0.04% and 0.12% across databases and did not differ between antibiotics. Relative to sulfamethoxazole/trimethoprim, the weighted HR of opioid overdose was 1.09 (95% CI, 0.79-1.50) for nitrofurantoin and 0.94 (95% CI, 0.68-1.31) for fluoroquinolones. Potential safety signals identified in high-throughput screening studies, especially for medication combinations with limited biologic plausibility of drug-drug interaction and high frequency of use, should be interpreted with caution.

This article is part of a Special Collection on Pharmacoepidemiology.

Exploring the discrepancies between clinical trials and real-world data: A small-cell lung cancer study

The potential of real-world data to inform clinical trial design and supplement control arms has gained much interest in recent years. The most common approach relies on reproducing control arm outcomes by matching real-world patient cohorts to clinical trial baseline populations. However, recent studies pointed out that there is a lack of replicability, generalisability, and consensus. In this article, we propose a novel approach that aims to explore and examine these discrepancies by concomitantly investigating the impact of selection criteria and operations on the measurements of outcomes from the patient data. We tested the approach on a dataset consisting of small-cell lung cancer patients receiving platinum-based chemotherapy regimens from a real-world data cohort (n = 223) and six clinical trial control arms (n = 1224). The results showed that the discrepancy between real-world and clinical trial data potentially depends on differences in both patient populations and operational conditions (e.g., frequency of assessments, and censoring), for which further investigation is required. Discovering and accounting for confounders, including hidden effects of differences in operations related to the treatment process and clinical trial study protocol, would potentially allow for improved translation between clinical trials and real-world data. Continued development of the method presented here to systematically explore and account for these differences could pave the way for transferring learning across clinical studies and developing mutual translation between the real-world and clinical trials to inform clinical study design.

Application of cultured epidermal autograft, JACE®, improves survival rate in extensive burns: A propensity score matching study using Tokyo registry data

Cultured epidermal autograft, JACE®, was introduced into the Japanese national health insurance system in 2009 and has been used in more than 1000 cases of extensive burns. The aim of this study was to investigate whether the use of JACE® contributes to survival rate in extensive burns. In this study, 119 cases were selected from 3990 cases in Tokyo Burn Unit Association registry data from 2009 to 2023, excluding cases with less than 40% total body surface area, cases of deaths within 4 weeks and cases with unknown length of hospital stay. In total, 25 patients treated with JACE® were selected and matched with another 25 patients who did not receive JACE® using propensity score matching. The results showed that patients treated with JACE® had a significantly higher survival rate than did those who were not treated with JACE® at all time points between 6 and 9 weeks post-injury. In addition, there was no significant difference in length of hospital stay between the groups. These results suggest that the use of JACE® in patients with extensive burns contributes to patient survival and does not prolong hospital stay.

From the Randomized AMBORA Trial to Clinical Practice: Comparison of Medication Errors in Oral Antitumor Therapy

The randomized AMBORA trial showed that medication errors are frequent in patients treated with oral antitumor therapeutics and that they can be substantially reduced by an intensified clinical pharmacological/pharmaceutical care program. While randomized controlled trials are essential to generate clinical evidence, their generalizability in real-world is not always given. The AMBORA care program was implemented in clinical routine within the AMBORA Competence and Consultation Center (AMBORA Center) at the Comprehensive Cancer Center Erlangen-EMN, allowing a thorough comparison of medication error frequencies and characteristics. Our primary analysis compared data at therapy initiation of new oral antitumor therapeutics from the AMBORA trial intervention group (n = 98) and the AMBORA Center (n = 142). Medication errors involving the oral antitumor therapeutics were twofold higher in real-world compared to the randomized controlled trial (mean 0.83 ± 0.80 per patient vs. 0.41 ± 0.53, P < 0.001). We observed more complex oral antitumor therapeutic regimens, a higher median number of medications, and a higher ECOG status in clinical routine vs. the randomized trial. A high percentage of medication errors was completely solved in both groups (85.7% vs. 88.3%, ns). Medication error characteristics within the complete medication (oral antitumor therapeutics and concomitant medication) were similar in both groups (e.g., patient-related causes, drug-drug/drug-food interactions). Taken together, medication errors were even more frequent in clinical routine than in the randomized controlled trial and a high rate was solved in clinical routine by a clinical pharmacological/pharmaceutical care program.

Appropriate Relevancy and Reliability of Real-World Data for the Utilization of Regulatory Submission

The extraction of data that contribute to regulatory approval from real-world data (RWD) is difficult because of the lack of a standardized data format and extraction methodology. Additionally, when real-world evidence (RWE) is used as an external control group, the similarity between internal and external control data is not evaluated. To investigate the data extraction methodology for the external control data of rare molecular subtypes, we have initiated the "REALISE" study. In this study, we aim to elucidate the "relevance" and "reliability" of RWD/RWE necessary for regulatory approval. As most databases are not designed for regulatory use in the creation phase, we will investigate retrospective methodologies to ensure RWD/RWE reliability. This study will compare the "relevance" and "reliability" of the ARCAD global database, SCRUM-Japan Registry, SCRUM-Japan observational study, and Flatiron Health RWD, and statistically analyze the differences and similarities among the four databases. We will also examine the methodology for extracting sufficiently relevant data from the SCRUM-Japan observational study. Additionally, if the reliability of the RWD/RWE does not reach the required level for regulatory approval, we will examine the methodologies to ensure the "reliability" of the SCRUM-Japan observational study for regulatory approval. The obtained results will be submitted to the "Consultation for Development of Registry" in the Pharmaceuticals and Medical Devices Agency, and we will discuss the standard methodology. The procedures and findings identified in the REALISE study will be organized from the perspectives of "database construction," "data analysis," and "outcome evaluation" and will be issued as "the draft guidelines."

The individualized delineation of clinical target volume for primary nasopharyngeal carcinoma based on invasion risk of substructures: A prospective, real-world study with a large population

BACKGROUND AND PURPOSE

The delineation of clinical target volume (CTV) for primary nasopharyngeal carcinoma (NPC) is currently controversial and the international guideline still recommend a uniform border for CTV regardless of the tumor extent. We conducted this prospective, real-world study to evaluate the clinical outcomes of our individualized CTV delineation method based on distance plus substructures.

MATERIALS AND METHODS

We preliminarily investigated the local extension patterns of NPC on 354 newly diagnosed patients and defined the structures surrounding the nasopharynx as Level-1 to Level-4 substructures stratified by the risk of invasion. We then enrolled patients with newly diagnosed NPC without distant metastasis to investigate our individualized CTV delineation protocol. All patients received intensity modulated radiotherapy. CTV1 and CTV2 were prescribed doses of 60 Gy and 54 Gy in 30 ∼ 33 fractions. The primary endpoint was local recurrence-free survival (LRFS); secondary endpoints included regional control and survival, estimated using the Kaplan-Meier method. The local failure patterns were also analyzed.

RESULTS

From January 2008 to December 2012 and from January 2013 to September 2019, 356 and 648 patients were enrolled, named as training set and validation set, respectively. With a median follow-up of 104.6 (interquartile, 73.1-126.9) and 51.4 (39.5-78.5) months, 31 (8.7 %) and 38 (5.9 %) patients in training and validation sets experienced local recurrence, and the 5-year LRFS was 93.0 % and 93.2 %, respectively; 63 (17.7 %) and 39 (6 %) patients died in training and validation sets, and the 5-year overall survival (OS) was 88.5 % and 93.4 %, respectively. For the whole study cohort (N = 1004) with a median follow-up of 66.6 (41.5-98.0) months, the 5-year LRFS and OS was 93.2 % and 91.5 %. The grade 3 late toxicities included xerostomia, subcutaneous fibrosis, hearing impairment, trismus, visuality impairment and skin atrophy, with a total incidence of 1.5 %. Sixty-seven of 69 (97.1 %) local recurrence was in high-dose area.

CONCLUSION

Our individualized CTV delineation method can achieve favorable local tumor control and long-term survival outcomes with acceptable late toxicities.

Chiropractic spinal manipulation and likelihood of tramadol prescription in adults with radicular low back pain: a retrospective cohort study using US data

OBJECTIVES

Patients receiving chiropractic spinal manipulation (CSM) for low back pain (LBP) are less likely to receive any opioid prescription for subsequent pain management. However, the likelihood of specifically being prescribed tramadol, a less potent opioid, has not been explored. We hypothesised that adults receiving CSM for newly diagnosed radicular LBP would be less likely to receive a tramadol prescription over 1-year follow-up, compared with those receiving usual medical care.

DESIGN

Retrospective cohort study.

SETTING

US medical records-based dataset including >115 million patients attending academic health centres (TriNetX, Inc), queried 9 November 2023.

PARTICIPANTS

Opioid-naive adults aged 18-50 with a new diagnosis of radicular LBP were included. Patients with serious pathology and tramadol use contraindications were excluded. Variables associated with tramadol prescription were controlled via propensity matching.

INTERVENTIONS

Patients were divided into two cohorts dependent on treatment received on the index date of radicular LBP diagnosis (CSM or usual medical care).

PRIMARY AND SECONDARY OUTCOME MEASURES

Risk ratio (RR) for tramadol prescription (primary); markers of usual medical care utilisation (secondary).

RESULTS

After propensity matching, there were 1171 patients per cohort (mean age 35 years). Tramadol prescription was significantly lower in the CSM cohort compared with the usual medical care cohort, with an RR (95% CI) of 0.32 (0.18 to 0.57; p<0.0001). A cumulative incidence graph demonstrated that the reduced incidence of tramadol prescription in the CSM cohort relative to the usual medical care cohort was maintained throughout 1-year follow-up. Utilisation of NSAIDs, physical therapy evaluation and lumbar imaging was similar between cohorts.

CONCLUSIONS

This study found that US adults initially receiving CSM for radicular LBP had a reduced likelihood of receiving a tramadol prescription over 1-year follow-up. These findings should be corroborated by a prospective study to minimise residual confounding.

Expert survey on real-world data utilization and real-world evidence generation for regulatory decision-making in drug lifecycle in Korea

As the importance of utilizing real-world data (RWD)/real-world evidence (RWE) for supporting regulatory scientific decision-making continues to grow, experiences and inputs from experts become crucial for developing a systematic and practice-oriented plan for the use of fit-for-purpose RWD/RWE. This study aimed to survey relevant experts from government agencies, industries, and academia to identify prerequisites for the drug life cycle in Korea. The questionnaire comprised the following: (A) the definition and categories of RWD/RWE, (B) the suitability and feasibility of using RWD/RWE at each authorization stage by the types of RWD, and (C) the challenges and solutions for the use of RWD/RWE. A total of 46 respondents completed the online survey, with 89.1% of them having prior experience with RWD/RWE usage. A majority of respondents agreed that RWD can be obtained from various sources. Among these sources, the registry was the most suitable source. It is suitable to compensate for the limitations of randomized control trials and ensure quality in data collection. Though there was consensus among the respondents for the use of RWD/RWE in post-marketing surveillance, the use of such data in new drug application (NDA) was disagreeable. Respondents considered it necessary to write a protocol in advance for RWD collection and RWE generation, for all RWD types. In conclusion, this study examined the perceptions of experts for RWD/RWE use at each approval stage of drugs. The results suggest that guidelines for the fit-for-purpose use of RWD/RWE should be developed via careful deliberation among experts in the future.

Facilitated subcutaneous immunoglobulin treatment patterns in pediatric patients with primary immunodeficiency diseases

Aim: This retrospective study investigated real-world hyaluronidase-facilitated subcutaneous immunoglobulin (fSCIG) treatment patterns in pediatric patients with primary immunodeficiency diseases (PIDs) in Poland. Methods: Clinical and demographic information, fSCIG treatment parameters and clinical outcomes were extracted from medical records of 28 participants (aged ≤18 years) with PIDs who received fSCIG. Results: 18 participants (64.3%) started fSCIG with a ramp-up (median duration: 35.5 days). 27 patients (96.4%) were administered fSCIG every 4 weeks and one patient every 3 weeks. 25 patients (89.3%) used one infusion site. No serious bacterial infections occurred. Conclusion: Data support the feasibility of administering fSCIG to children and adolescents with PIDs every 3-4 weeks using a single infusion site and indicate flexibility in modifying fSCIG infusion parameters. Clinical Trial Registration: NCT04636502 (ClinicalTrials.gov).

Generating and using real-world data: A worthwhile uphill battle

The precision oncology paradigm challenges the feasibility and data generalizability of traditional clinical trials. Consequently, an unmet need exists for practical approaches to test many subgroups, evaluate real-world drug value, and gather comprehensive, accessible datasets to validate novel biomarkers. Real-world data (RWD) are increasingly recognized to have the potential to fill this gap in research methodology. Established applications of RWD include informing disease epidemiology, pharmacovigilance, and healthcare quality assessment. Currently, concerns regarding RWD quality and comprehensiveness, privacy, and biases hamper their broader application. Nonetheless, RWD may play a pivotal role in supplementing clinical trials, enabling conditional reimbursement and accelerated drug access, and innovating trial conduct. Moreover, purpose-built RWD repositories may support the extension or refinement of drug indications and facilitate the discovery and validation of new biomarkers. This perspective explores the potential of leveraging RWD to advance oncology, highlights its benefits and challenges, and suggests a path forward in this evolving field.

Efficacy and acceptability of adjunctive n-acetylcysteine for psychotic disorders: Systematic review and meta-analysis

INTRODUCTION

N-acetylcysteine (NAC) augmentation of antipsychotic medication has been studied in psychotic disorders but the results are inconsistent. This meta-analysis aimed to evaluate the efficacy and acceptability of NAC as an augmentation strategy for psychotic disorders.

METHODS

PubMed, Web of Science, EMBASE, PsycINFO, Cochrane Library, and ClinicalTrials.gov were searched until the date of November 28, 2022. The inclusion criteria were randomized controlled trials (RCTs) comparing NAC and placebo in patients with psychotic disorders. The outcomes were the psychotic symptoms measured by the Positive and Negative Syndrome Scale (PANSS) and drop-out rates.

RESULTS

A total of 594 patients from eight trials were included. The results showed that no difference was found in score changes of PANSS total, positive, negative, or general psychopathology scale scores between the NAC group and placebo group in both time points (≤24 weeks and >24 weeks). There was also no statistical difference in drop-out rates between the two groups.

CONCLUSION

For the moment, it is not appropriate to recommend NAC as an augmentation of antipsychotic medication to treat psychotic disorders in routine clinical practice.

The Effectiveness of GenerationPMTO During Sustained Implementation in the Public Mental Health System: A Single-Arm Open Trial Evaluation

To support families and reduce the burden of child mental, emotional, and behavioral problems, evidence-based parenting interventions must remain effective in real-world service delivery contexts. The purpose of the current study was to evaluate the effectiveness of the GenerationPMTO (GenPMTO) intervention during sustained implementation in the Michigan public mental health system using a single-arm open trial (pre-post) design. We also examined potential predictors of treatment response. A multilevel analysis framework was utilized to evaluate data from 365 caregivers who completed GenPMTO treatment. Results revealed significant positive improvements from pretest to posttest in all four outcome domains (i.e., parenting confidence, parenting practices, caregiver depressive symptoms, child behavior problems). When compared to group-based GenPMTO delivery, the individual delivery format was associated with significantly greater improvements in overall effective parenting practices, as well as in the subdomain of skill encouragement. Caregiver gender, caregiver educational level, and child age were all implicated as predictors of GenPMTO outcomes. These findings add to the literature by supporting the effectiveness of the GenPMTO intervention when fully integrated into mental health care practice and can inform continued efforts to provide families with evidence-based services in community settings.

Considerations for master protocols using external controls

There has been an increasing use of master protocols in oncology clinical trials because of its efficiency to accelerate cancer drug development and flexibility to accommodate multiple substudies. Depending on the study objective and design, a master protocol trial can be a basket trial, an umbrella trial, a platform trial, or any other form of trials in which multiple investigational products and/or subpopulations are studied under a single protocol. Master protocols can use external data and evidence (e.g. external controls) for treatment effect estimation, which can further improve efficiency of master protocol trials. This paper provides an overview of different types of external controls and their unique features when used in master protocols. Some key considerations in master protocols with external controls are discussed including construction of estimands, assessment of fit-for-use real-world data, and considerations for different types of master protocols. Similarities and differences between regular randomized controlled trials and master protocols when using external controls are discussed. A targeted learning-based causal roadmap is presented which constitutes three key steps: (1) define a target statistical estimand that aligns with the causal estimand for the study objective, (2) use an efficient estimator to estimate the target statistical estimand and its uncertainty, and (3) evaluate the impact of causal assumptions on the study conclusion by performing sensitivity analyses. Two illustrative examples for master protocols using external controls are discussed for their merits and possible improvement in causal effect estimation.

Design differences and variation in results between randomised trials and non-randomised emulations: meta-analysis of RCT-DUPLICATE data

Objective

To explore how design emulation and population differences relate to variation in results between randomised controlled trials (RCT) and non-randomised real world evidence (RWE) studies, based on the RCT-DUPLICATE initiative (Randomised, Controlled Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology).

Design

Meta-analysis of RCT-DUPLICATE data.

Data sources

Trials included in RCT-DUPLICATE, a demonstration project that emulated 32 randomised controlled trials using three real world data sources: Optum Clinformatics Data Mart, 2004-19; IBM MarketScan, 2003-17; and subsets of Medicare parts A, B, and D, 2009-17.

Eligibility criteria for selecting studies

Trials where the primary analysis resulted in a hazard ratio; 29 RCT-RWE study pairs from RCT-DUPLICATE.

Results

Differences and variation in effect sizes between the results from randomised controlled trials and real world evidence studies were investigated. Most of the heterogeneity in effect estimates between the RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: treatment started in hospital (which does not appear in health insurance claims data), discontinuation of some baseline treatments at randomisation (which would have been an unusual care decision in clinical practice), and delayed onset of drug effects (which would be under-reported in real world clinical practice because of the relatively short persistence of the treatment). Adding the three emulation differences to the meta-regression reduced heterogeneity from 1.9 to almost 1 (absence of heterogeneity).

Conclusions

This analysis suggests that a substantial proportion of the observed variation between results from randomised controlled trials and real world evidence studies can be attributed to differences in design emulation.

Advances in methodologies of negative controls: a scoping review

OBJECTIVES

Negative controls are considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]).

STUDY DESIGN AND SETTING

We searched PubMed, Web of Science, Embase, and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers selected eligible studies and collected relevant data independently and in duplicate. We reported total numbers and percentages, and summarized methodologies narratively.

RESULTS

A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n = 11, 29.8%), NCO (n = 13, 35.1%), or both (n = 13, 35.1%), with most focused on bias detection (n = 14, 37.8%), bias correction (n = 16, 43.3%), and P value or confidence interval (CI) calibration (n = 5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity, and linearity.

CONCLUSION

Negative controls can be leveraged for bias detection, P value or CI calibration, and bias correction, among which bias correction has been the most studied methodologically. The current available methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

A comparative study of clinical trial and real-world data in patients with diabetic kidney disease

A growing body of research is focusing on real-world data (RWD) to supplement or replace randomized controlled trials (RCTs). However, due to the disparities in data generation mechanisms, differences are likely and necessitate scrutiny to validate the merging of these datasets. We compared the characteristics of RCT data from 5734 diabetic kidney disease patients with corresponding RWD from electronic health records (EHRs) of 23,523 patients. Demographics, diagnoses, medications, laboratory measurements, and vital signs were analyzed using visualization, statistical comparison, and cluster analysis. RCT and RWD sets exhibited significant differences in prevalence, longitudinality, completeness, and sampling density. The cluster analysis revealed distinct patient subgroups within both RCT and RWD sets, as well as clusters containing patients from both sets. We stress the importance of validation to verify the feasibility of combining RCT and RWD, for instance, in building an external control arm. Our results highlight general differences between RCT and RWD sets, which should be considered during the planning stages of an RCT-RWD study. If they are, RWD has the potential to enrich RCT data by providing first-hand baseline data, filling in missing data or by subgrouping or matching individuals, which calls for advanced methods to mitigate the differences between datasets.

Validation of diagnoses of liver disorders in users of systemic azole antifungal medication in Sweden

BACKGROUND

Liver disorders are important adverse effects associated with antifungal drug treatment. However, the accuracy of Clinical International Classification of Diseases (ICD)-10 codes in identifying liver disorders for register based research is not well-established. This study aimed to determine the positive predictive value (PPV) of the ICD-10 codes for identifying patients with toxic liver disease, hepatic failure, and jaundice among patients with systemic antifungal treatment.

METHODS

Data from the Swedish Prescribed Drug Register and the National Patient Register were utilized to identify adult patients who received systemic azole antifungal drugs and had a recorded diagnosis of toxic liver disease (K71.0, K71.1, K71.2, K71.6, K71.8, K71.9), hepatic failure (K72.0, K72.9), or jaundice (R17) between 2005 and 2016. The medical records of all included patients were reviewed. Prespecified criteria were used to re-evaluate and confirm each diagnosis, serving as the gold standard to calculate PPVs with 95% confidence intervals (95% CI) for each diagnostic group.

RESULTS

Among the 115 included patients, 26 were diagnosed with toxic liver disease, 58 with hepatic failure, and 31 with jaundice. Toxic liver disease was confirmed in 14 out of 26 patients, yielding a PPV of 53.8% (95% CI 33.4-73.4%). Hepatic failure was confirmed in 26 out of 38 patients, resulting in a PPV of 62.1% (95% CI 48.4-74.5%). The highest PPV was found in jaundice, with 30 confirmed diagnoses out of 31, yielding a PPV of 96.8% (95% CI 83.3-99.9%).

CONCLUSION

Among patients who received azole antifungal treatment and were subsequently diagnosed with a liver disorder, the PPV for the diagnosis of jaundice was high, while the PPVs for toxic liver disease and hepatic failure were lower.

Using an artificial intelligence tool incorporating natural language processing to identify patients with a diagnosis of ANCA-associated vasculitis in electronic health records

BACKGROUND

Because anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis (AAV) is a rare, life-threatening, auto-immune disease, conducting research is difficult but essential. A long-lasting challenge is to identify rare AAV patients within the electronic-health-record (EHR)-system to facilitate real-world research. Artificial intelligence (AI)-search tools using natural language processing (NLP) for text-mining are increasingly postulated as a solution.

METHODS

We employed an AI-tool that combined text-mining with NLP-based exclusion, to accurately identify rare AAV patients within large EHR-systems (>2.000.000 records). We developed an identification method in an academic center with an established AAV-training set (n = 203) and validated the method in a non-academic center with an AAV-validation set (n = 84). To assess accuracy anonymized patient records were manually reviewed.

RESULTS

Based on an iterative process, a text-mining search was developed on disease description, laboratory measurements, medication and specialisms. In the training center, 608 patients were identified with a sensitivity of 97.0 % (95%CI [93.7, 98.9]) and positive predictive value (PPV) of 56.9 % (95%CI [52.9, 60.1]). NLP-based exclusion resulted in 444 patients increasing PPV to 77.9 % (95%CI [73.7, 81.7]) while sensitivity remained 96.3 % (95%CI [93.8, 98.0]). In the validation center, text-mining identified 333 patients (sensitivity 97.6 % (95%CI [91.6, 99.7]), PPV 58.2 % (95%CI [52.8, 63.6])) and NLP-based exclusion resulted in 223 patients, increasing PPV to 86.1 % (95%CI [80.9, 90.4]) with 98.0 % (95%CI [94.9, 99.4]) sensitivity. Our identification method outperformed ICD-10-coding predominantly in identifying MPO+ and organ-limited AAV patients.

CONCLUSIONS

Our study highlights the advantages of implementing AI, notably NLP, to accurately identify rare AAV patients within large EHR-systems and demonstrates the applicability and transportability. Therefore, this method can reduce efforts to identify AAV patients and accelerate real-world research, while avoiding bias by ICD-10-coding.

Assessing the use of observational methods and real-world data to emulate ongoing randomized controlled trials

BACKGROUND/AIMS

There has been growing interest in better understanding the potential of observational research methods in medical product evaluation and regulatory decision-making. Previously, we used linked claims and electronic health record data to emulate two ongoing randomized controlled trials, characterizing the populations and results of each randomized controlled trial prior to publication of its results. Here, our objective was to compare the populations and results from the emulated trials with those of the now-published randomized controlled trials.

METHODS

This study compared participants' demographic and clinical characteristics and study results between the emulated trials, which used structured data from OptumLabs Data Warehouse, and the published PRONOUNCE and GRADE trials. First, we examined the feasibility of implementing the baseline participant characteristics included in the published PRONOUNCE and GRADE trials' using real-world data and classified each variable as ascertainable, partially ascertainable, or not ascertainable. Second, we compared the emulated trials and published randomized controlled trials for baseline patient characteristics (concordance determined using standardized mean differences <0.20) and results of the primary and secondary endpoints (concordance determined by direction of effect estimates and statistical significance).

RESULTS

The PRONOUNCE trial enrolled 544 participants, and the emulated trial included 2226 propensity score-matched participants. In the PRONOUNCE trial publication, one of the 32 baseline participant characteristics was listed as an exclusion criterion on ClinicalTrials.gov but was ultimately not used. Among the remaining 31 characteristics, 9 (29.0%) were ascertainable, 11 (35.5%) were partially ascertainable, and 10 (32.2%) were not ascertainable using structured data from OptumLabs. For one additional variable, the PRONOUNCE trial did not provide sufficient detail to allow its ascertainment. Of the nine variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 6 (66.7%). The primary endpoint of time from randomization to the first major adverse cardiovascular event and secondary endpoints of nonfatal myocardial infarction and stroke were concordant between the emulated trial and published randomized controlled trial. The GRADE trial enrolled 5047 participants, and the emulated trial included 7540 participants. In the GRADE trial publication, 8 of 34 (23.5%) baseline participant characteristics were ascertainable, 14 (41.2%) were partially ascertainable, and 11 (32.4%) were not ascertainable using structured data from OptumLabs. For one variable, the GRADE trial did not provide sufficient detail to allow for ascertainment. Of the eight variables that were ascertainable, values in the emulated trial and published randomized controlled trial were discordant for 4 (50.0%). The primary endpoint of time to hemoglobin A1c ≥7.0% was mostly concordant between the emulated trial and the published randomized controlled trial.

CONCLUSION

Despite challenges, observational methods and real-world data can be leveraged in certain important situations for a more timely evaluation of drug effectiveness and safety in more diverse and representative patient populations.

Real-World Evidence Studies in Oncology Therapeutics: Hope or Hype?

Randomized controlled trial (RCT) remains a gold standard in evidence-based medicine for assessing the efficacy and safety of cancer therapies. However, due to some inherent methodological limitations of RCT, such as stringent inclusion criteria, highly specific treatment, ethical and scientific compromise in rare cancer, and inability to adequately assess safety, real-world evidence (RWE) has been adjudged as a suitable option to complement data obtained from RCT. Moreover, in the context of cancer therapeutics, few notable merits pertain to developing a novel product for rare cancer subtypes, establishing new indications for already approved drugs, optimization of treatment regimen and sequence, a better description of long-term safety, and supporting the reimbursement-related decision. However, the implementation of RWE for the aforementioned purposes will be limited by various challenges, especially in the context of developing economies such as India. Special attention should be given to the availability of data, maintaining the quality standard, and establishing stringent regulations for privacy and security along with active regulatory engagement with relevant stakeholders. Such activities will be key to facilitating the use of RWE in cancer therapeutics.

Improving Food and Drug Administration-Centers for Medicare and Medicaid Services Coordination for Drugs Granted Accelerated Approval

Policy Points The increasing number of drugs granted accelerated approval by the Food and Drug Administration (FDA) has challenged the Medicare program, which often pays for expensive therapies despite substantial uncertainty about benefits and risks to Medicare beneficiaries. We recommend several administrative and legislative approaches for improving FDA-Centers for Medicare and Medicaid Services (CMS) coordination around accelerated-approval drugs, including promoting earlier discussions among the FDA, the CMS, and drug companies; strengthening Medicare's coverage with evidence development program; linking Medicare payment to evidence generation milestones; and ensuring that the CMS has adequate staffing and resources to evaluate new therapies. These activities can help improve the integrity; transparency; and efficiency of approval, coverage, and payment processes for drugs granted accelerated approval.

CONTEXT

The Food and Drug Administration (FDA)'s accelerated-approval pathway expedites patient access to promising treatments. However, increasing use of this pathway has challenged the Medicare program, which often pays for expensive therapies despite substantial uncertainty about benefits and risks to Medicare beneficiaries. We examined approaches to improve coordination between the FDA and Centers for Medicare and Medicaid Services (CMS) for drugs granted accelerated approval.

METHODS

We argue that policymakers have focused on expedited pathways at the FDA without sufficient attention to complementary policies at the CMS. Although differences between the FDA and CMS decisions are to be expected given the agencies' different missions and statutory obligations, procedural improvements can ensure that Medicare beneficiaries have timely access to novel therapies that are likely to improve health outcomes. To inform policy options and recommendations, we conducted semistructured interviews with stakeholders to capture diverse perspectives on the topic.

FINDINGS

We recommend ten areas for consideration: clarifying the FDA's evidentiary standards; strengthening FDA authorities; promoting earlier discussions among the FDA, the CMS, and drug companies; improving Medicare's coverage with evidence development program; tying Medicare payment for accelerated-approval drugs to evidence generation milestones; issuing CMS guidance on real-world evidence; clarifying Medicare's "reasonable and necessary" criteria; adopting lessons from international regulatory-reimbursement harmonization efforts; ensuring that the CMS has adequate staffing and expertise; and emphasizing equity.

CONCLUSIONS

Better coordination between the FDA and CMS could improve the transparency and predictability of drug approval and coverage around accelerated-approval drugs, with important implications for patient outcomes, health spending, and evidence generation processes. Improved coordination will require reforms at both the FDA and CMS, with special attention to honoring the agencies' distinct authorities. It will require administrative and legislative actions, new resources, and strong leadership at both agencies.

Real-world data emulating randomized controlled trials of non-vitamin K antagonist oral anticoagulants in patients with venous thromboembolism

BACKGROUND

Emulating randomized controlled trials (RCTs) by real-world evidence (RWE) studies would benefit future clinical and regulatory decision-making by balancing the limitations of RCT. We aimed to evaluate whether the findings from RWE studies can support regulatory decisions derived from RCTs of non-vitamin K antagonist oral anticoagulants (NOACs) in patients with venous thromboembolism (VTE).

METHODS

Five landmark trials (AMPLIFY, RE-COVER II, Hokusai-VTE, EINSTEIN-DVT, and EINSTEIN-PE) of NOACs were emulated using the South Korean nationwide claims database (January 2012 to August 2020). We applied an active comparator and new-user design to include patients who initiated oral anticoagulants within 28 days from their VTE diagnoses. The prespecified eligibility criteria, exposure (each NOAC, such as apixaban, rivaroxaban, dabigatran, and edoxaban), comparator (conventional therapy, defined as subcutaneous heparin followed by warfarin), and the definition of outcomes from RCTs were emulated as closely as possible in each separate emulation cohort. The primary outcome was identical to each trial, which was defined as recurrent VTE or VTE-related death. The safety outcome was major bleeding. Propensity score matching was conducted to balance 69 covariates between the exposure groups. Effect estimates for outcomes were estimated using the Mantel-Haenszel method and Cox proportional hazards model and subsequently compared with the corresponding RCT estimates.

RESULTS

Compared to trial populations, real-world study populations were older (range: 63-69 years [RWE] vs. 54-59 years [RCT]), with more females (55-60.5% vs. 39-48.3%) and had a higher prevalence of active cancer (4.2-15.4% vs. 2.5-9.5%). The emulated estimates for effectiveness outcomes showed superior effectiveness of NOAC (AMPLIFY: relative risk 0.81, 95% confidence interval 0.70-0.94; RE-COVER II: hazard ratio [HR] 0.60, 0.37-0.96; Hokusai-VTE: 0.49, 0.31-0.78; EINSTEIN-DVT: 0.54, 0.33-0.89; EINSTEIN-PE: 0.50, 0.34-0.74), when contrasted with trials that showed non-inferiority. For safety outcomes, all emulations except for AMPLIFY and EINSTEIN-DVT yielded results consistent with their corresponding RCTs.

CONCLUSIONS

This study revealed the feasibility of complementing RCTs with RWE studies by using claims data in patients with VTE. Future studies to consider the different demographic characteristics between RCT and RWE populations are needed.

Real-world outcomes of pembrolizumab for platinum-refractory advanced urothelial carcinoma: Efficacy, safety, and evidence for trial-unfit patients

Pembrolizumab, monoclonal antibody targeting programmed cell death 1, is widely used for platinum-refractory urothelial carcinoma (UC) patients. Although the survival benefit of pembrolizumab was proven in the well-designed phase III trial, these data represent only a part of patients due to strictly defined eligibility criteria. The patients' characteristics in the clinical practice are much more heterogenous than those of trial participants. The real-world experience is useful to validate the trial result and find suitable candidates for the treatment. Similarly, real-world data plays a significant role in addressing the efficacy and safety of special populations, such as poor performance status or older patients. This review summarizes the real-world evidence on pembrolizumab for platinum-refractory UCs and discusses the clinical risk factors and efficacy for trial-ineligible patients.

Evaluation of randomized controlled trials: a primer and tutorial for mental health researchers

BACKGROUND

Considered one of the highest levels of evidence, results of randomized controlled trials (RCTs) remain an essential building block in mental health research. They are frequently used to confirm that an intervention "works" and to guide treatment decisions. Given their importance in the field, it is concerning that the quality of many RCT evaluations in mental health research remains poor. Common errors range from inadequate missing data handling and inappropriate analyses (e.g., baseline randomization tests or analyses of within-group changes) to unduly interpretations of trial results and insufficient reporting. These deficiencies pose a threat to the robustness of mental health research and its impact on patient care. Many of these issues may be avoided in the future if mental health researchers are provided with a better understanding of what constitutes a high-quality RCT evaluation.

METHODS

In this primer article, we give an introduction to core concepts and caveats of clinical trial evaluations in mental health research. We also show how to implement current best practices using open-source statistical software.

RESULTS

Drawing on Rubin's potential outcome framework, we describe that RCTs put us in a privileged position to study causality by ensuring that the potential outcomes of the randomized groups become exchangeable. We discuss how missing data can threaten the validity of our results if dropouts systematically differ from non-dropouts, introduce trial estimands as a way to co-align analyses with the goals of the evaluation, and explain how to set up an appropriate analysis model to test the treatment effect at one or several assessment points. A novice-friendly tutorial is provided alongside this primer. It lays out concepts in greater detail and showcases how to implement techniques using the statistical software R, based on a real-world RCT dataset.

DISCUSSION

Many problems of RCTs already arise at the design stage, and we examine some avoidable and unavoidable "weak spots" of this design in mental health research. For instance, we discuss how lack of prospective registration can give way to issues like outcome switching and selective reporting, how allegiance biases can inflate effect estimates, review recommendations and challenges in blinding patients in mental health RCTs, and describe problems arising from underpowered trials. Lastly, we discuss why not all randomized trials necessarily have a limited external validity and examine how RCTs relate to ongoing efforts to personalize mental health care.

Tell me what you want, what you really really want: Estimands in observational pharmacoepidemiologic comparative effectiveness and safety studies

PURPOSE

Ideally, the objectives of a pharmacoepidemiologic comparative effectiveness or safety study should dictate its design and data analysis. This paper discusses how defining an estimand is instrumental to this process.

METHODS

We applied the ICH-E9 (Statistical Principles for Clinical Trials) R1 addendum on estimands - which originally focused on randomized trials - to three examples of observational pharmacoepidemiologic comparative effectiveness and safety studies. Five key elements specify the estimand: the population, contrasted treatments, endpoint, intercurrent events, and population-level summary measure.

RESULTS

Different estimands were defined for case studies representing three types of pharmacological treatments: (1) single-dose treatments using a case study about the effect of influenza vaccination versus no vaccination on mortality risk in an adult population of ≥60 years of age; (2) sustained-treatments using a case study about the effect of dipeptidyl peptidase 4 inhibitor versus glucagon-like peptide-1 agonist on hypoglycemia risk in treatment of uncontrolled diabetes; and (3) as needed treatments using a case study on the effect of nitroglycerin spray as-needed versus no nitroglycerin on syncope risk in treatment of stabile angina pectoris.

CONCLUSIONS

The case studies illustrated that a seemingly clear research question can still be open to multiple interpretations. Defining an estimand ensures that the study targets a treatment effect that aligns with the treatment decision the study aims to inform. Estimand definitions further help to inform choices regarding study design and data-analysis and clarify how to interpret study findings.

Association between chiropractic spinal manipulation and gabapentin prescription in adults with radicular low back pain: retrospective cohort study using US data

OBJECTIVES

Radicular low back pain (rLBP) is often treated off-label with gabapentin or by chiropractors using chiropractic spinal manipulative therapy (CSMT). To date, no studies have examined the association between these interventions. We hypothesised that adults under 50 years of age receiving CSMT for newly diagnosed rLBP would have reduced odds of receiving a gabapentin prescription over 1 year-follow-up.

DESIGN

Retrospective cohort study.

SETTING

US network including linked medical records, medical claims and pharmacy claims of >122 million patients attending large healthcare organisations (TriNetX), queried 15 June 2023, yielding data from 2017 to 2023.

PARTICIPANTS

Adults aged 18-49 were included at their first occurrence of rLBP diagnosis. Exclusions were severe pathology, other spinal conditions, on-label gabapentin indications and gabapentin contraindications. Propensity score matching controlled for variables associated with gabapentin use and receipt of prescription medication over the preceding year.

INTERVENTIONS

Patients were divided into CSMT or usual medical care cohorts based on the care received on the index date of rLBP diagnosis.

PRIMARY AND SECONDARY OUTCOME MEASURES

OR for gabapentin prescription.

RESULTS

After propensity matching, there were 1635 patients per cohort (mean age 36.3±8.6 years, 60% women). Gabapentin prescription over 1-year follow-up was significantly lower in the CSMT cohort compared with the usual medical care cohort, with an OR (95% CI) of 0.53 (0.40 to 0.71; p<0.0001). Sensitivity analyses revealed early divergence in cumulative incidence of prescription; and no significant between-cohort difference in a negative control outcome (gastrointestinal medication) suggesting adequate control for pharmacological care preference.

CONCLUSIONS

Our findings suggest that US adults receiving CSMT for newly diagnosed rLBP have significantly reduced odds of receiving a gabapentin prescription over 1-year follow-up compared with those receiving usual medical care. Results may not be generalisable and should be replicated in other healthcare settings and corroborated by a prospective study to reduce confounding.

DESIGN DIFFERENCES EXPLAIN VARIATION IN RESULTS BETWEEN RANDOMIZED TRIALS AND THEIR NON-RANDOMIZED EMULATIONS

Objectives

While randomized controlled trials (RCTs) are considered a standard for evidence on the efficacy of medical treatments, non-randomized real-world evidence (RWE) studies using data from health insurance claims or electronic health records can provide important complementary evidence. The use of RWE to inform decision-making has been questioned because of concerns regarding confounding in non-randomized studies and the use of secondary data. RCT-DUPLICATE was a demonstration project that emulated the design of 32 RCTs with non-randomized RWE studies. We sought to explore how emulation differences relate to variation in results between the RCT-RWE study pairs.

Methods

We include all RCT-RWE study pairs from RCT-DUPLICATE where the measure of effect was a hazard ratio and use exploratory meta-regression methods to explain differences and variation in the effect sizes between the results from the RCT and the RWE study. The considered explanatory variables are related to design and population differences.

Results

Most of the observed variation in effect estimates between RCT-RWE study pairs in this sample could be explained by three emulation differences in the meta-regression model: (i) in-hospital start of treatment (not observed in claims data), (ii) discontinuation of certain baseline therapies at randomization (not part of clinical practice), (iii) delayed onset of drug effects (missed by short medication persistence in clinical practice).

Conclusions

This analysis suggests that a substantial proportion of the observed variation between results from RCTs and RWE studies can be attributed to design emulation differences. (238 words).

Complementary evidence on the performance of coronary stents generated by a randomized controlled trial and a worldwide registry

BACKGROUND

Large-scale registries can provide valuable complementary data to randomized controlled trials (RCT) for the postmarketing evaluation of coronary stents, but their scientific relevance remains debated.

METHODS

We sought to compare the evidence on the performance of a single coronary stent platform generated by the RCT for its regulatory approval and a well-conducted international registry. Patients treated with the Ultimaster coronary stent in the CENTURY II (CII-UM) trial (n = 551) were compared to patients in the real-world e-ULTIMASTER (e-UM) registry (n = 35,389). All major events were adjudicated by an independent clinical event committee in both studies. Propensity weighted analysis was used to balance baseline and procedural differences between the 2 populations.

RESULTS

Coronary artery disease was more complex in e-UM compared to CII-UM, including more acute coronary syndromes, multivessel disease, left main, arterial, or venous grafts, and chronic total occlusions (P < .005 for all). At one-year follow-up and after excluding periprocedural myocardial infarction (MI) there was no statistically significant difference between CII-UM and e-UM regarding all-cause death (hazard ratio [HR] 0.55, 95% confidence interval [CI] 0.26-1.20, P = .14), cardiac death (HR 0.71, 95% CI 0.29-1.72, P = .45), target lesion failure (HR 1.18, 95% CI 0.78-1.78, P = .44), and target vessel MI (HR 0.76, 95% CI 0.24-2.38, P = .63). However, target vessel revascularization rate was significantly higher in CII-UM than in e-UM, HR 1.78, 95% CI 1.23-2.56, P = .002.

CONCLUSIONS

A well-conducted large-scale registry can provide valuable complementary evidence to RCTs on the postmarket performance of new coronary stents, across a wider range of uses and various geographic areas.

Statistical Considerations on the Use of RWD/RWE for Oncology Drug Approvals: Overview and Lessons Learned

Despite increasing utilization of real-world data (RWD)/real-world evidence (RWE) in regulatory submissions, their application to oncology drug approvals has seen limited success. Real-world data is most commonly summarized as a benchmark control for a single arm study or used to augment the concurrent control in a randomized clinical trial (RCT). While there has been substantial research on usage of RWD/RWE, our goal is to provide a comprehensive overview of their use in oncology drug approval submissions to inform future RWD/RWE study design. We will review examples of applications and summarize the strengths and weaknesses of each example identified by regulatory agencies. A few noteworthy case studies will be reviewed in detail. Operational aspects of RWD/RWE study design/analysis will be also discussed.

Machine learning in predicting outcomes for stroke patients following rehabilitation treatment: A systematic review

OBJECTIVE

This review aimed to summarize the use of machine learning for predicting the potential benefits of stroke rehabilitation treatments, to evaluate the risk of bias of predictive models, and to provide recommendations for future models.

MATERIALS AND METHODS

This systematic review was conducted in accordance with the PRISMA statement and the CHARMS checklist. The PubMed, Embase, Cochrane Library, Scopus, and CNKI databases were searched up to April 08, 2023. The PROBAST tool was used to assess the risk of bias of the included models.

RESULTS

Ten studies within 32 models met our inclusion criteria. The optimal AUC value of the included models ranged from 0.63 to 0.91, and the optimal R2 value ranged from 0.64 to 0.91. All of the included models were rated as having a high or unclear risk of bias, and most of them were downgraded due to inappropriate data sources or analysis processes.

DISCUSSION AND CONCLUSION

There remains much room for improvement in future modeling studies, such as high-quality data sources and model analysis. Reliable predictive models should be developed to improve the efficacy of rehabilitation treatment by clinicians.

Defining the role of real-world data in cancer clinical research: The position of the European Organisation for Research and Treatment of Cancer

The emergence of the precision medicine paradigm in oncology has led to increasing interest in the integration of real-world data (RWD) into cancer clinical research. As sources of real-world evidence (RWE), such data could potentially help address the uncertainties that surround the adoption of novel anticancer therapies into the clinic following their investigation in clinical trials. At present, RWE-generating studies which investigate antitumour interventions seem to primarily focus on collecting and analysing observational RWD, typically forgoing the use of randomisation despite its methodological benefits. This is appropriate in situations where randomised controlled trials (RCTs) are not feasible and non-randomised RWD analyses can offer valuable insights. Nevertheless, depending on how they are designed, RCTs have the potential to produce strong and actionable RWE themselves. The choice of which methodology to employ for RWD studies should be guided by the nature of the research question they are intended to answer. Here, we attempt to define some of the questions that do not necessarily require the conduct of RCTs. Moreover, we outline the strategy of the European Organisation for Research and Treatment of Cancer (EORTC) to contribute to the generation of robust and high-quality RWE by prioritising the execution of pragmatic trials and studies set up according to the trials-within-cohorts approach. If treatment allocation cannot be left up to random chance due to practical or ethical concerns, the EORTC will consider undertaking observational RWD research based on the target trial principle. New EORTC-sponsored RCTs may also feature concurrent prospective cohorts composed of off-trial patients.

Emulation of Randomized Clinical Trials With Nonrandomized Database Analyses: Results of 32 Clinical Trials

Importance

Nonrandomized studies using insurance claims databases can be analyzed to produce real-world evidence on the effectiveness of medical products. Given the lack of baseline randomization and measurement issues, concerns exist about whether such studies produce unbiased treatment effect estimates.

Objective

To emulate the design of 30 completed and 2 ongoing randomized clinical trials (RCTs) of medications with database studies using observational analogues of the RCT design parameters (population, intervention, comparator, outcome, time [PICOT]) and to quantify agreement in RCT-database study pairs.

Design, Setting, and Participants

New-user cohort studies with propensity score matching using 3 US claims databases (Optum Clinformatics, MarketScan, and Medicare). Inclusion-exclusion criteria for each database study were prespecified to emulate the corresponding RCT. RCTs were explicitly selected based on feasibility, including power, key confounders, and end points more likely to be emulated with real-world data. All 32 protocols were registered on ClinicalTrials.gov before conducting analyses. Emulations were conducted from 2017 through 2022.

Exposures

Therapies for multiple clinical conditions were included.

Main Outcomes and Measures

Database study emulations focused on the primary outcome of the corresponding RCT. Findings of database studies were compared with RCTs using predefined metrics, including Pearson correlation coefficients and binary metrics based on statistical significance agreement, estimate agreement, and standardized difference.

Results

In these highly selected RCTs, the overall observed agreement between the RCT and the database emulation results was a Pearson correlation of 0.82 (95% CI, 0.64-0.91), with 75% meeting statistical significance, 66% estimate agreement, and 75% standardized difference agreement. In a post hoc analysis limited to 16 RCTs with closer emulation of trial design and measurements, concordance was higher (Pearson r, 0.93; 95% CI, 0.79-0.97; 94% meeting statistical significance, 88% estimate agreement, 88% standardized difference agreement). Weaker concordance occurred among 16 RCTs for which close emulation of certain design elements that define the research question (PICOT) with data from insurance claims was not possible (Pearson r, 0.53; 95% CI, 0.00-0.83; 56% meeting statistical significance, 50% estimate agreement, 69% standardized difference agreement).

Conclusions and Relevance

Real-world evidence studies can reach similar conclusions as RCTs when design and measurements can be closely emulated, but this may be difficult to achieve. Concordance in results varied depending on the agreement metric. Emulation differences, chance, and residual confounding can contribute to divergence in results and are difficult to disentangle.

Haefeli W, M. Seidling H. Mortality and Hospitalizations Among Patients Enrolled in an Interprofessional Medication Management Program

BACKGROUND

Measures for improving medication safety in outpatient care are often complex and involve medication reviews. Over the period 2016-2022 (with a preceeding one-year pilot phase), an interprofessional medication management program- the Medicines Initiative Saxony-Thuringia (Arzneimittelinitiative Sachsen-Thüringen, ARMIN)-was implemented in two German federal states. More than 5000 patients received a medication review by the end of 2019 by a team composed of physicians and pharmacists and were provided with joint, continuous care thereafter.

METHODS

In the framework of a retrospectively registered cohort study, the mortality and hospitalizations of this population (5033 patients) were studied using routine data from a statutory health insurer (observation period 2015-2019) and compared with those of a control group (10 039 patients) determined from the routine data by propensity score matching. Mortality was compared by survival analysis (Cox regression), and hospitalization rates were compared in terms of event probabilities within two years of enrollment in the medication management program. Robustness was tested in multiple sensitivity analyses.

RESULTS

Over the observation period, 9.3% of the ARMIN participants and 12.9% of persons in the control group died (hazard ratio of the adjusted Cox regression, 0.84; 95% confidence interval [0.76; 0.94], P = 0.001). In the first two years after inclusion, the ARMIN participants were hospitalized just as often as the persons in the control group (52.4% versus 53.4%; odds ratio from the adjusted model, 1.04 [0.96; 1.11], P = 0.347). The effects were consistent in sensitivity analyses.

CONCLUSION

In this retrospective cohort study, participation in the ARMIN program was associated with a lower risk of death. Exploratory analyses provide clues to the potential origin of this association.

Machine Learning Methods in Real-World Studies of Cardiovascular Disease

Objective:Cardiovascular disease (CVD) is one of the leading causes of death worldwide, and answers are urgently needed regarding many aspects, particularly risk identification and prognosis prediction. Real-world studies with large numbers of observations provide an important basis for CVD research but are constrained by high dimensionality, and missing or unstructured data. Machine learning (ML) methods, including a variety of supervised and unsupervised algorithms, are useful for data governance, and are effective for high dimensional data analysis and imputation in real-world studies. This article reviews the theory, strengths and limitations, and applications of several commonly used ML methods in the CVD field, to provide a reference for further application.

Methods:This article introduces the origin, purpose, theory, advantages and limitations, and applications of multiple commonly used ML algorithms, including hierarchical and k-means clustering, principal component analysis, random forest, support vector machine, and neural networks. An example uses a random forest on the Systolic Blood Pressure Intervention Trial (SPRINT) data to demonstrate the process and main results of ML application in CVD.

Conclusion:ML methods are effective tools for producing real-world evidence to support clinical decisions and meet clinical needs. This review explains the principles of multiple ML methods in plain language, to provide a reference for further application. Future research is warranted to develop accurate ensemble learning methods for wide application in the medical field.

Preliminary Attainability Assessment of Real-World Data for Answering Major Clinical Research Questions in Breast Cancer Brain Metastasis: Framework Development and Validation Study

BACKGROUND

In recent decades, real-world evidence (RWE) in oncology has rapidly gained traction for its potential to answer clinical questions that cannot be directly addressed by randomized clinical trials. Integrating real-world data (RWD) into clinical research promises to contribute to more sustainable research designs, including extension, augmentation, enrichment, and pragmatic designs. Nevertheless, clinical research using RWD is still limited because of concerns regarding the shortage of best practices for extracting, harmonizing, and analyzing RWD. In particular, pragmatic screening methods to determine whether the content of a data source is sufficient to answer the research questions before conducting the research with RWD have not yet been established.

OBJECTIVE

We examined the PAR (Preliminary Attainability Assessment of Real-World Data) framework and assessed its utility in breast cancer brain metastasis (BCBM), which has an unmet medical need for data attainability screening at the preliminary step of observational studies that use RWD.

METHODS

The PAR framework was proposed to assess data attainability from a particular data source during the early research process. The PAR framework has four sequential stages, starting with clinical question clarification: (1) operational definition of variables, (2) data matching (structural/semantic), (3) data screening and extraction, and (4) data attainability diagramming. We identified 5 clinical questions to be used for PAR framework evaluation through interviews and validated them with a survey of breast cancer experts. We used the Samsung Medical Center Breast Cancer Registry, a hospital-based real-time registry implemented in March 2021, leveraging the institution's anonymized and deidentified clinical data warehouse platform. The number of breast cancer patients in the registry was 45,129; it covered the period from June 1995 to December 2021. The registry consists of 24 base data marts that represent disease-specific breast cancer characteristics and care pathways. The outcomes included screening results of the clinical questions via the PAR framework and a procedural diagram of data attainability for each research question.

RESULTS

Data attainability was tested for study feasibility according to the PAR framework with 5 clinical questions for BCBM. We obtained data sets that were sufficient to conduct studies with 4 of 5 clinical questions. The research questions stratified into 3 types when we developed data fields for clearly defined research variables. In the first, only 1 question could be answered using direct data variables. In the second, the other 3 questions required surrogate definitions that combined data variables. In the third, the question turned out to be not feasible for conducting further analysis.

CONCLUSIONS

The adoption of the PAR framework was associated with more efficient preliminary clinical research using RWD from BCBM. Furthermore, this framework helped accelerate RWE generation through clinical research by enhancing transparency and reproducibility and lowering the entry barrier for clinical researchers.

Trajectory for the Regulatory Approval of a Combination of Pertuzumab Plus Trastuzumab for Pre-treated HER2-positive Metastatic Colorectal Cancer Using Real-world Data

Utilizing real-world data (RWD) for effective clinical implementation is becoming more and more appealing as the cost of drug development rises, especially for patients with rare diseases and rare molecular subtypes for whom conducting randomized controlled trials is challenging. If a regulatory approval methodology based on RWD as an external control group can be established, drug development for rarer fractions can be accelerated by lowering costs and time, as well as reducing physical and emotional burdens on both patients and healthcare professionals. Since 2017, we have been prospectively collecting the clinical data of standard therapies in patients with rare molecular fractions under the SCRUM-Japan Registry platform, which is a qualified registry utilized as external control data for regulatory submission. Based on the results of the phase II TRIUMPH study (UMIN000027887) and the extracted data from the SCRUM-Japan Registry, the pharmaceutical company submitted an application for pertuzumab and trastuzumab in patients with HER2-positive metastatic colorectal cancer in April 2021. Pertuzumab and trastuzumab were approved as expanded indications on March 28, 2022, as 6 cases out of 14 extracted from the SCRUM-Japan Registry were classified and utilized as "evaluation material" under the review process of the Pharmaceuticals and Medical Devices Agency (PMDA). Through the TRIUMPH study and the SCRUM-Japan Registry, we have paved the way for regulatory approval of RWD in Japan. In future, we must define the steps for constructing regulatory-grade registries and the method/process for utilizing RWD by accumulating case experiences.

Trends in the Use of Oral Anticoagulants for Adults With Venous Thromboembolism in the US, 2010-2020

Importance

The introduction of direct oral anticoagulants (DOACs) has transformed the treatment of venous thromboembolism (VTE). Large health care databases offer valuable insight into how oral anticoagulants (OACs) are used in clinical practice and may aid in understanding reasons for changes in therapy.

Objectives

To evaluate prescribing patterns of OACs for patients with VTE and identify clinical events that precede treatment changes.

Design, Setting, and Participants

This retrospective cohort study used data from a public (Medicare fee-for-service) and a commercial (IBM MarketScan) health insurance database on 298 609 patients initiating OACs within 90 days of index VTE hospitalization from January 1, 2009, to December 31, 2020. Statistical analysis was conducted from April to August 2022.

Exposures

Warfarin and the DOACs rivaroxaban, apixaban, dabigatran, and edoxaban.

Main Outcomes and Measures

Characteristics of patients initiating different OACs, along with trends over time of patients initiating OACs, were compared. Time receiving continuous anticoagulant therapy, patterns of anticoagulant discontinuation (treatment gap of ≥30 days), and treatment switches were assessed. Clinical events in the 30 days preceding treatment modifications were identified.

Results

A total of 203 378 individuals with Medicare (mean [SD] age, 76.9 [7.6] years; 122 554 women [60.3%]) and 95 231 with commercial insurance (mean [SD] age, 57.6 [15.8] years; 47 139 women [49.5%]) were included (N = 298 609). Warfarin was the most frequent OAC prescribed (163 044 [54.6%]), followed by rivaroxaban (66 882 [22.3%]) and apixaban (65 997 [22.1%]). The proportion of patients initiating DOACs increased from 0% in 2010 to 86.8% (22 420 of 25 817) in 2019 for patients with Medicare and 92.1% (4012 of 4357) in 2020 for commercially insured patients. Patients with chronic kidney disease were more likely to initiate warfarin (35 561 [11.9%]) or apixaban (16 294 [5.5%]) than rivaroxaban (10 136 [3.4%]), and those with a history of bleeding were more likely to initiate apixaban (5424 [1.8%]) than rivaroxaban (3007 [1.0%]). Overall, patients received persistent OAC treatment for approximately 6 months (Medicare: median, 175 days [IQR, 76-327 days]; commercial insurance: median, 168 days [IQR, 83-279 days]). A total of 33 011 patients (11.1%) switched anticoagulant therapy within a year. Switching to another anticoagulant was preceded most frequently by codes for a VTE diagnostic procedure (27.2% of all switchers [8983 of 33 011]).

Conclusions and Relevance

This cohort study using data from 2 US health insurance databases suggests that most patients with VTE continued oral anticoagulant treatment for approximately 6 months. Clinical reasons for modifying anticoagulant therapy were identified in one-third of patients. Identifying reasons for treatment modification is crucial for generating valid evidence on drug safety and effectiveness.

Channeling of New Neuropsychiatric Drugs-Impact on Safety and Effectiveness Studies

This study aimed to examine differential prescribing due to channeling and propensity score non-overlap over time in new versus established treatments for common neurological conditions. We conducted cross-sectional analyses on a national sample of US commercially insured adults using 2005-2019 data. We compared new users of recently approved versus established medications for management of diabetic peripheral neuropathy (pregabalin versus gabapentin), Parkinson disease psychosis (pimavanserin versus quetiapine), and epilepsy (brivaracetam versus levetiracetam). Within these drug pairs, we compared demographic, clinical, and healthcare utilization characteristics of recipients of each drug. In addition, we fit yearly propensity score models for each condition and assessed propensity score non-overlap over time. For all three drug pairs, users of the more recently approved medications more frequently had prior treatment (pregabalin = 73.9%, gabapentin = 38.7%; pimavanserin = 41.1%, quetiapine = 14.0%; brivaracetam = 93.4%, levetiracetam = 32.1%). Propensity score non-overlap and its resulting sample loss after trimming were the greatest in the first year that the more recently approved medication was available (diabetic peripheral neuropathy, 12.4% non-overlap; Parkinson disease psychosis, 6.1%; epilepsy, 43.2%) and subsequently improved. Newer neuropsychiatric therapies appear to be channeled to individuals with refractory disease or intolerance to other treatments, leading to potential confounding and biased comparative effectiveness and safety study findings when compared to established treatments. Propensity score non-overlap should be reported in comparative studies that include newer medications. When studies comparing newer and established treatments are critically needed as soon as new treatments enter the market, investigators should recognize the potential for channeling bias and implement methodological approaches like those demonstrated in this study to understand and improve this issue in such studies.