Claims-based Algorithm for Amyloidosis
Recruiting in Palo Alto (17 mi)
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Yale University
Disqualifiers: Opted out of research, Pregnancy
No Placebo Group
Approved in 4 Jurisdictions
Trial Summary
What is the purpose of this trial?
The primary objective of this study is to evaluate the diagnostic performance of an algorithm in identifying patients with ATTR amyloidosis.
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications.
What data supports the effectiveness of the drug tafamidis for treating amyloidosis?
Tafamidis has been shown to slow the progression of neurological symptoms and maintain quality of life in patients with early-stage transthyretin amyloidosis with polyneuropathy (ATTR-PN) in clinical studies, including an 18-month trial and long-term studies up to 10 years. It is approved in over 40 countries for treating this condition.12345
Is the treatment for amyloidosis safe for humans?
What makes the drug tafamidis (Vyndaqel, Vyndamax) unique for treating amyloidosis?
Eligibility Criteria
This trial is for patients within the YNHHS claims dataset who are flagged by a computer algorithm as potentially having ATTR amyloidosis, which includes both hereditary and non-hereditary forms. They must be willing to undergo further clinical evaluation. Pregnant individuals or those opting out of research in the Epic system cannot participate.Inclusion Criteria
I have been identified as having ATTR amyloidosis by a specific diagnostic algorithm.
I need further tests to confirm if I have ATTR amyloidosis.
I am at risk for ATTR and am being treated within the YNHHS system.
Exclusion Criteria
Patients who are pregnant or who may become pregnant
I have not opted out of research in the Epic system.
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Evaluation
Participants are evaluated for the identification of ATTR Amyloidosis through a claims-based algorithm
2 years
Follow-up
Participants are monitored for safety and effectiveness after evaluation
4 weeks
Treatment Details
Interventions
- ATTR diagnostic algorithm (Computer Algorithm)
Trial OverviewThe study is testing the effectiveness of a computer algorithm designed to identify patients at risk of ATTR amyloidosis using medical records data. The goal is to see how well this algorithm predicts actual cases when compared with Yale's list of potential subjects.
Participant Groups
1Treatment groups
Experimental Treatment
Group I: Computer algorithm for ATTRExperimental Treatment1 Intervention
Patients will be evaluated for the identification of ATTR Amyloidosis through a claims-based algorithm
ATTR diagnostic algorithm is already approved in United States, United States, United States for the following indications:
🇺🇸 Approved in United States as Vyndaqel / Vyndamax for:
- Transthyretin amyloidosis cardiomyopathy (ATTR-CM)
🇺🇸 Approved in United States as Attruby for:
- Transthyretin amyloidosis (ATTR) with heart involvement (cardiomyopathy)
🇺🇸 Approved in United States as diflunisal for:
- Hereditary ATTR amyloidosis
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Yale New Haven HospitalNew Haven, CT
Loading ...
Who Is Running the Clinical Trial?
Yale UniversityLead Sponsor
Alnylam Pharmaceuticals IncCollaborator
References
Diflunisal tolerability in transthyretin cardiac amyloidosis: a single center's experience. [2019]Transthyretin (ATTR) amyloidosis is an under-recognized, progressive disease manifesting as cardiomyopathy and/or polyneuropathy. Diflunisal, a nonsteroidal anti-inflammatory drug (NSAID), has demonstrated transthyretin stabilization in vitro and slowing of polyneuropathy progression in the hereditary ATTR subtype (ATTRm). However, the use of diflunisal has only been described in a small cohort of patients with ATTR cardiac amyloidosis (CA). We hypothesized that selected patients with ATTR-CA, both hereditary and wild-type (ATTRwt), would tolerate diflunisal with limited adverse events.
Safety and efficacy of long-term diflunisal administration in hereditary transthyretin (ATTR) amyloidosis. [2015]A recent 2-year randomized controlled trial indicated that the transthyretin (TTR) tetramer stabilizer, diflunisal, inhibits polyneuropathy progression and preserves quality of life in hereditary ATTR amyloidosis. However, its long-term outcomes are unknown. Here, we report tolerance and efficacy of long-term diflunisal administration in hereditary ATTR amyloidosis.
Tafamidis: A Review in Transthyretin Amyloidosis with Polyneuropathy. [2020]Transthyretin amyloidosis with polyneuropathy (ATTR-PN), a rare and progressive hereditary disorder, results from mutations in the gene coding for the transthyretin (TTR) protein that destabilize the protein's tetrameric structure. In over 40 countries worldwide, tafamidis (Vyndaqel®) is approved for the treatment of TTR amyloidosis in adults with stage 1 symptomatic polyneuropathy, to delay peripheral neurological impairment. Tafamidis is administered orally once daily, as a soft capsule. Evidence from clinical studies, including an 18-month placebo-controlled trial and subsequent long-term, open-label extension studies (providing data from ≤ 6 years of treatment), indicate that tafamidis slowed deterioration of neurological function and maintained health-related quality of life in patients with early-stage ATTR-PN and the Val30Met mutation. TTR tetramers were stabilized in nearly all patients, and nutritional status was generally maintained or improved. Similar benefit was seen with tafamidis over 12 months in a noncomparative trial in patients with non-Val30Met ATTR-PN, although disease progression in this population (which was older and had had ATTR-PN for longer than Val30Met patients) became more notable with continued therapy in an extension study. Data for up to 10 years from large registry and referral centre studies support the long-term effectiveness and safety of tafamidis in delaying disease progression and conferring survival benefits in patients with stage 1 ATTR-PN. Tafamidis was generally well tolerated, with no new safety signals detected during the long-term trial or real-world experience. Thus, based on up to 10 years' experience, tafamidis continues to be a valuable option in the treatment of early-stage ATTR-PN.
Advances in Diagnosis and Treatment of Cardiac and Renal Amyloidosis. [2022]Diagnoses of amyloidosis are increasing annually, and advances in bone scintigraphy and cardiac MRI accompanied by development of nonbiopsy diagnostic criteria have specifically led to a huge increase in transthyretin amyloidosis cardiomyopathy (ATTR-CM) diagnoses worldwide. Tafamidis use is increasing, and there are several ongoing phase III clinical trials of novel agents that promise to transform the treatment landscape for patients with ATTR-CM. In systemic light chain (AL) amyloidosis, more effective chemotherapeutic agents continue to improve patient outcomes. Accelerating the removal of amyloid deposits to accompany these therapies remains the holy grail. However, in the meantime, early diagnosis is undoubtedly key in improving patient outcomes.
A Review of Novel Agents and Clinical Considerations in Patients With ATTR Cardiac Amyloidosis. [2023]Transthyretin (ATTR) amyloidosis is a multisystem disease caused by organ deposition of amyloid fibrils derived from the misfolded transthyretin (TTR) protein. The purpose of this article is to provide an overview of current treatment regimens and summarize important considerations for each agent. A literature search was performed with the PubMed database for articles published through October 2020. Search criteria included therapies available on the market and investigational therapies used for ATTR amyloidosis treatment. Both prospective clinical trials and retrospective studies have been included in this review. Available therapies discussed in this review article are tafamidis, diflunisal, patisiran, and inotersen. Tafamidis is FDA approved for treatment of wild-type ATTR (ATTRwt) and hereditary ATTR (ATTRv) cardiomyopathy, and patisiran and inotersen are FDA approved for ATTRv polyneuropathy. Diflunisal does not have an FDA-labeled indication for amyloidosis but has been studied in ATTRv polyneuropathy and ATTRwt cardiomyopathy. Investigational therapies include a TTR stabilizer, AG10; 2 antifibril agents, PRX004 and doxycycline/tauroursodeoxycholic acid; and 2 gene silencers, vutrisiran and AKCEA-TTR-LRx; and clinical trials are ongoing. ATTR amyloidosis treatment selection is based on subtype and presence of cardiac or neurological manifestations. Additional considerations such as side effects, monitoring, and administration are outlined in this review.
Evaluation of Mortality During Long-Term Treatment with Tafamidis for Transthyretin Amyloidosis with Polyneuropathy: Clinical Trial Results up to 8.5 Years. [2020]The effects of tafamidis on mortality in Val30Met and non-Val30Met patients with transthyretin amyloidosis with polyneuropathy (ATTR-PN) were evaluated.
Natural history and impact of treatment with tafamidis on major cardiovascular outcome-free survival time in a cohort of patients with transthyretin amyloidosis. [2021]Hereditary (ATTRv) and wild-type (ATTRwt) transthyretin amyloidosis are severe and fatal systemic diseases, characterised by amyloid fibrillar accumulation principally in the heart or peripheral nerves (or both). Since 2012, tafamidis has been used in France to treat patients with ATTRv with neuropathy (alone or combined with cardiomyopathy). Recently, the Phase III ATTR-ACT trial showed that tafamidis decreased the relative risk of mortality in ATTR amyloidosis with cardiomyopathy. The aims of this study were to assess the clinical characteristics of ATTR amyloidosis in a real-life population in comparison to the population included in the ATTR-ACT trial and to assess the impact of tafamidis treatment on major cardiovascular outcome (MCO)-free survival time without cardiac decompensation, heart transplant, or death.
Identification of rheumatoid arthritis in German claims data using different algorithms: Validation by cross-sectional patient-reported survey data. [2023]To evaluate different algorithms for the identification of rheumatoid arthritis (RA) in claims data using patient-reported diagnosis as reference.
Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study. [2023]Label="Introduction" NlmCategory="UNASSIGNED">Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics.
Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods. [2023]Identification of medical conditions using claims data is generally conducted with algorithms based on subject-matter knowledge. However, these claims-based algorithms (CBAs) are highly dependent on the knowledge level and not necessarily optimized for target conditions. We investigated whether machine learning methods can supplement researchers' knowledge of target conditions in building CBAs. Retrospective cohort study using a claims database combined with annual health check-up results of employees' health insurance programs for fiscal year 2016-17 in Japan (study population for hypertension, N = 631,289; diabetes, N = 152,368; dyslipidemia, N = 614,434). We constructed CBAs with logistic regression, k-nearest neighbor, support vector machine, penalized logistic regression, tree-based model, and neural network for identifying patients with three common chronic conditions: hypertension, diabetes, and dyslipidemia. We then compared their association measures using a completely hold-out test set (25% of the study population). Among the test cohorts of 157,822, 38,092, and 153,608 enrollees for hypertension, diabetes, and dyslipidemia, 25.4%, 8.4%, and 38.7% of them had a diagnosis of the corresponding condition. The areas under the receiver operating characteristic curve (AUCs) of the logistic regression with/without subject-matter knowledge about the target condition were .923/.921 for hypertension, .957/.938 for diabetes, and .739/.747 for dyslipidemia. The logistic lasso, logistic elastic-net, and tree-based methods yielded AUCs comparable to those of the logistic regression with subject-matter knowledge: .923-.931 for hypertension; .958-.966 for diabetes; .747-.773 for dyslipidemia. We found that machine learning methods can attain AUCs comparable to the conventional knowledge-based method in building CBAs.
Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis. [2022]Ankylosing spondylitis (AS) is a chronic progressive inflammatory disease of the spine and its affiliated tissues. AS mainly affects the axial bone, sacroiliac joint, hip joint, spinal facet, and adjacent ligaments. We used machine learning (ML) methods to construct diagnostic models based on blood routine examination, liver function test, and kidney function test of patients with AS. This method will help clinicians enhance diagnostic efficiency and allow patients to receive systematic treatment as soon as possible.
Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions. [2018]To examine the effects of varying diagnostic and pharmaceutical criteria on the performance of claims-based algorithms for identifying beneficiaries with hypertension, heart failure, chronic lung disease, arthritis, glaucoma, and diabetes.