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IDELVION: A Comprehensive Review of Clinical Trial and Real-World Data.

ABSTRACT: Hemophilia B is a bleeding disorder caused by a deficiency of coagulation factor IX (FIX). Treatment with FIX replacement products can increase FIX activity levels to minimize or prevent bleeding events. However, frequent dosing with standard-acting FIX products can create a high treatment burden. Long-acting products have been developed to maintain bleed protection with extended dosing intervals. Recombinant factor IX-albumin fusion protein (rIX-FP) is a long-acting product indicated for the treatment and prophylaxis of bleeding events and perioperative management in adult and pediatric patients. This review outlines data from all previously treated patients in the Prophylaxis and On-Demand Treatment using Longer Half-Life rIX-FP (PROLONG-9FP) clinical trial program and summarizes real-world data evaluating the use of rIX-FP in routine clinical practice. In the PROLONG-9FP program, rIX-FP demonstrated effective hemostasis in all patients at dose regimens of up to 21 days in patients aged ≥ 18 years and up to 14 days in patients aged < 12 years. rIX-FP has a favorable pharmacokinetic profile and an excellent safety and tolerability profile. Extended dosing intervals with rIX-FP led to high levels of adherence and reduced consumption compared with other FIX therapies. Data from real-world practice are encouraging and reflect the results of the clinical trials.

SUBMITTER: Escobar M

PROVIDER: S-EPMC8875492 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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IDELVION: A Comprehensive Review of Clinical Trial and Real-World Data.

Escobar Miguel M Mancuso Maria Elisa ME Hermans Cedric C Leissinger Cindy C Seifert Wilfried W Li Yanyan Y McKeand William W Oldenburg Johannes J

Journal of clinical medicine 20220218 4

Hemophilia B is a bleeding disorder caused by a deficiency of coagulation factor IX (FIX). Treatment with FIX replacement products can increase FIX activity levels to minimize or prevent bleeding events. However, frequent dosing with standard-acting FIX products can create a high treatment burden. Long-acting products have been developed to maintain bleed protection with extended dosing intervals. Recombinant factor IX-albumin fusion protein (rIX-FP) is a long-acting product indicated for the tr ...[more]

PMID: 35207344

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Project description:ImportanceAlthough randomized clinical trials are considered to be the criterion standard for generating clinical evidence, the use of real-world evidence to evaluate the efficacy and safety of medical interventions is gaining interest. Whether observational data can be used to address the same clinical questions being answered by traditional clinical trials is still unclear.ObjectiveTo identify the number of clinical trials published in high-impact journals in 2017 that could be feasibly replicated using observational data from insurance claims and/or electronic health records (EHRs).Design, setting, and participantsIn this cross-sectional analysis, PubMed was searched to identify all US-based clinical trials, regardless of randomization, published between January 1, 2017, and December 31, 2017, in the top 7 highest-impact general medical journals of 2017. Trials were excluded if they did not involve human participants, did not use end points that represented clinical outcomes among patients, were not characterized as clinical trials, and had no recruitment sites in the United States.Main outcomes and measuresThe primary outcomes were the number and percentage of trials for which the intervention, indication, trial inclusion and exclusion criteria, and primary end points could be ascertained from insurance claims and/or EHR data.ResultsOf the 220 US-based trials analyzed, 33 (15.0%) could be replicated using observational data because their intervention, indication, inclusion and exclusion criteria, and primary end points could be routinely ascertained from insurance claims and/or EHR data. Of the 220 trials, 86 (39.1%) had an intervention that could be ascertained from insurance claims and/or EHR data. Among the 86 trials, 62 (72.1%) had an indication that could be ascertained. Forty-five (72.6%) of 62 trials had at least 80% of inclusion and exclusion criteria data that could be ascertained. Of these 45 studies, 33 (73.3%) had at least 1 primary end point that could be ascertained.Conclusions and relevanceThis study found that only 15% of the US-based clinical trials published in high-impact journals in 2017 could be feasibly replicated through analysis of administrative claims or EHR data. This finding suggests the potential for real-world evidence to complement clinical trials, both by examining the concordance between randomized experiments and observational studies and by comparing the generalizability of the trial population with the real-world population of interest.

Project description:IntroductionIn this literature review we evaluated the real-world clinical effectiveness of switching Japanese diabetic patients from their current insulin regimen to insulin degludec (IDeg).MethodsStudies were identified from Japanese Diabetes Society (JDS) abstracts (2014-2015) and PubMed (2012 onwards). Inclusion criteria were: Japanese population, >15 participants, and studies switching patients from basal or basal-bolus insulin regimens to IDeg. Randomized controlled trials and case reports were excluded. Weighted mean changes in safety and effectiveness endpoints were calculated using the number of patients in each study.ResultsIn total, 81 JDS abstracts and seven manuscripts met the search criteria, representing 4238 patients [1028 with type 1 diabetes (T1D), 602 with type 2 diabetes (T2D), 2608 with unspecified or mixed diabetes]. Glycated hemoglobin (HbA1c) was reported in 93% of studies, with an improvement in 84% of these (51% significant, 33% numerical), no change in 12%, and worsening in 4% (3% numerical, 1% significant). Across all studies, the weighted mean absolute change in HbA1c was -0.3% (-2.7 mmol/mol). Basal insulin dose was reported in 58% of studies and was lower in 60% of these (30% significant, 30% numerical), numerically unchanged in 26%, and higher in 14% (2% significant, 12% numerical). The weighted mean change in basal insulin dose was -4.8% and -3.0% for all studies and for studies with only significant results, respectively. The weighted mean change in basal dose based on all studies was -8.9, -5.5, and -2.9% for the T1D, T2D, and unspecified patient populations, respectively. Hypoglycemia was recorded in 31% of the studies. After switching treatment to IDeg, 55% of studies reported decreased hypoglycemia, 29% no change, and 16% an increase. Quality of life (QoL) was measured in 11% of studies, of which 82% reported improved QoL after switching, and 18% reported no change in QoL.ConclusionSwitching from a conventional basal insulin to IDeg has the potential to improve HbA1c with a lower insulin dose. Switching to IDeg may also provide a reduced risk of hypoglycemia and improvement in QoL.FundingNovo Nordisk.

Project description:Overly restrictive eligibility criteria for clinical trials may limit the generalizability of the trial results to their target real-world patient populations. We developed a novel machine learning approach using large collections of real-world data (RWD) to better inform clinical trial eligibility criteria design. We extracted patients' clinical events from electronic health records (EHRs), which include demographics, diagnoses, and drugs, and assumed certain compositions of these clinical events within an individual's EHRs can determine the subphenotypes-homogeneous clusters of patients, where patients within each subgroup share similar clinical characteristics. We introduced an outcome-guided probabilistic model to identify those subphenotypes, such that the patients within the same subgroup not only share similar clinical characteristics but also at similar risk levels of encountering severe adverse events (SAEs). We evaluated our algorithm on two previously conducted clinical trials with EHRs from the OneFlorida+ Clinical Research Consortium. Our model can clearly identify the patient subgroups who are more likely to suffer or not suffer from SAEs as subphenotypes in a transparent and interpretable way. Our approach identified a set of clinical topics and derived novel patient representations based on them. Each clinical topic represents a certain clinical event composition pattern learned from the patient EHRs. Tested on both trials, patient subgroup (#SAE=0) and patient subgroup (#SAE>0) can be well-separated by k-means clustering using the inferred topics. The inferred topics characterized as likely to align with the patient subgroup (#SAE>0) revealed meaningful combinations of clinical features and can provide data-driven recommendations for refining the exclusion criteria of clinical trials. The proposed supervised topic modeling approach can infer the clinical topics from the subphenotypes with or without SAEs. The potential rules for describing the patient subgroups with SAEs can be further derived to inform the design of clinical trial eligibility criteria.

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IDELVION: A Comprehensive Review of Clinical Trial and Real-World Data.

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IDELVION: A Comprehensive Review of Clinical Trial and Real-World Data.

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