Claims-based Algorithm for Amyloidosis

Overseen By Cinthia S De Freitas, RN, BSN

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Yale University

Disqualifiers: Opted out of research, Pregnancy

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Approved in 2 Jurisdictions This treatment is already approved in other countries

Compensation: Varies

Number of Visits: Unknown

100 Participants Needed

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. ^{1 2 3 4 5}

Is the treatment for amyloidosis safe for humans?

Tafamidis has been used for up to 10 years in patients with transthyretin amyloidosis and is generally well tolerated, with no new safety concerns reported. Diflunisal has also been used in patients with hereditary transthyretin amyloidosis and is tolerated with limited adverse events. ^{1 2 3 6 7}

What makes the drug tafamidis (Vyndaqel, Vyndamax) unique for treating amyloidosis?

Tafamidis is unique because it stabilizes the transthyretin protein, preventing it from breaking apart and forming amyloid deposits, which is different from other treatments that may focus on managing symptoms rather than addressing the underlying cause. ^{8 9 10 11 12}

Research Team

Edward Miller, MD

Principal Investigator

Yale University

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.

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

Trial Overview The 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

Group I: Computer algorithm for ATTR Experimental Treatment 1 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 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

Who Is Running the Clinical Trial?

Yale University

Lead Sponsor

Trials

1,963

Recruited

3,046,000+

Alnylam Pharmaceuticals Inc

Collaborator

Trials

1

Recruited

100+

Findings from Research

In a study of 23 patients with transthyretin amyloid cardiomyopathy (ATTR-CA), diflunisal was found to be well-tolerated, with only 13% of patients withdrawing due to gastrointestinal side effects, indicating its potential safety in this population.

The treatment did not lead to significant adverse events, such as clinically significant bleeding or hospitalizations for heart failure, suggesting that diflunisal can be safely administered with proper monitoring in patients with both hereditary and wild-type ATTR-CA.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Diflunisal tolerability in transthyretin cardiac amyloidosis: a single center's experience. Ikram, A., Donnelly, JP., Sperry, BW., et al.[2019]

In a long-term study of 40 Japanese patients with hereditary ATTR amyloidosis, diflunisal was found to be well-tolerated, with most patients experiencing sustained clinical benefits over an average of 38 months, although some experienced renal function deterioration and thrombocytopenia.

Diflunisal significantly increased serum TTR concentration and stabilized the TTR tetramer structure, with no deterioration in neurological and cardiac functions observed after 24 months of treatment, indicating its efficacy in managing the disease.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Safety and efficacy of long-term diflunisal administration in hereditary transthyretin (ATTR) amyloidosis. Sekijima, Y., Tojo, K., Morita, H., et al.[2015]

Tafamidis (Vyndaqel®) is an effective oral treatment for transthyretin amyloidosis with polyneuropathy (ATTR-PN), significantly slowing neurological deterioration and maintaining quality of life in patients with early-stage disease, based on evidence from an 18-month placebo-controlled trial and long-term studies of up to 6 years.

Long-term data from registry studies indicate that tafamidis is safe and well-tolerated, with no new safety concerns, and it provides survival benefits while stabilizing the TTR protein structure in nearly all patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Tafamidis: A Review in Transthyretin Amyloidosis with Polyneuropathy. Lamb, YN., Deeks, ED.[2020]

The diagnosis of transthyretin amyloidosis cardiomyopathy (ATTR-CM) is on the rise due to advancements in imaging techniques and nonbiopsy diagnostic criteria, highlighting the importance of early detection for better patient outcomes.

Tafamidis is increasingly used for treating ATTR-CM, and ongoing phase III trials for new therapies may significantly change treatment options, while in systemic light chain (AL) amyloidosis, improved chemotherapy is enhancing patient outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Advances in Diagnosis and Treatment of Cardiac and Renal Amyloidosis. Law, S., Fontana, M., Gillmore, JD.[2022]

Tafamidis is FDA approved for treating both wild-type and hereditary transthyretin (ATTR) amyloidosis, specifically for cardiomyopathy, while patisiran and inotersen are approved for hereditary ATTR polyneuropathy, highlighting the efficacy of these treatments in managing different forms of the disease.

The review also discusses investigational therapies, such as AG10 and gene silencers like vutrisiran, indicating ongoing research aimed at improving treatment options for ATTR amyloidosis, which is crucial given the disease's complexity and the need for tailored therapies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Review of Novel Agents and Clinical Considerations in Patients With ATTR Cardiac Amyloidosis. Benbrahim, M., Norman, K., Sanchorawala, V., et al.[2023]

In patients with transthyretin amyloidosis with polyneuropathy (ATTR-PN), long-term treatment with tafamidis showed a significant survival benefit, with 85.9% of Val30Met patients alive after 9 years when treated continuously with tafamidis.

For non-Val30Met patients, 75.9% were alive after 8 years, indicating that tafamidis may also be beneficial for this group, although survival rates were lower compared to Val30Met patients.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of Mortality During Long-Term Treatment with Tafamidis for Transthyretin Amyloidosis with Polyneuropathy: Clinical Trial Results up to 8.5 Years. Merlini, G., Coelho, T., Waddington Cruz, M., et al.[2020]

In a study of 648 patients with hereditary (ATTRv) and wild-type (ATTRwt) transthyretin amyloidosis, tafamidis treatment was linked to a significantly longer median survival time without major cardiovascular outcomes, showing its efficacy in a real-life setting.

The results indicated that tafamidis treatment reduced the risk of cardiac decompensation, heart transplant, or death, with a hazard ratio of 0.546, confirming its beneficial impact on patients with cardiomyopathy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Natural history and impact of treatment with tafamidis on major cardiovascular outcome-free survival time in a cohort of patients with transthyretin amyloidosis. Bézard, M., Kharoubi, M., Galat, A., et al.[2021]

The study evaluated algorithms for identifying rheumatoid arthritis (RA) in claims data, finding that the ICD-10 codes M05 and M06 have high positive predictive values (PPVs) of 81%, making them reliable for RA identification in a large German health insurance database.

Using additional criteria such as inflammatory markers, rheumatologist visits, or specific medications improved the accuracy of RA identification, with specific medication showing the highest discriminative properties (diagnostic odds ratio of 3.0).

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Identification of rheumatoid arthritis in German claims data using different algorithms: Validation by cross-sectional patient-reported survey data. Callhoff, J., Albrecht, K., Marschall, U., et al.[2023]

The Rheumatic? tool effectively differentiates between individuals developing arthritis and those who do not, with a significant median score difference and an AUC-ROC of 75.3, indicating good predictive ability.

It also distinguishes patients with immune-mediated rheumatic diseases from other conditions, achieving an AUC-ROC of 79.0, although the tool's scoring system requires further optimization for improved sensitivity.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study. Knevel, R., Knitza, J., Hensvold, A., et al.[2023]

Machine learning methods can effectively supplement traditional knowledge-based algorithms for identifying chronic conditions like hypertension, diabetes, and dyslipidemia, achieving comparable accuracy in a study of over 631,000 individuals.

The study demonstrated that various machine learning techniques, including logistic regression and tree-based models, produced area under the curve (AUC) scores similar to those of conventional methods, indicating their potential for optimizing claims-based algorithms in healthcare.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods. Hara, K., Kobayashi, Y., Tomio, J., et al.[2023]

A machine learning model was developed using data from 348 patients with ankylosing spondylitis (AS) to enhance diagnostic efficiency, identifying seven key blood test factors that can predict AS with high accuracy (AUC values of 0.878 in training and 0.823 in validation cohorts).

The nomogram created from this model can assist orthopedic surgeons in making more personalized treatment decisions for AS patients, potentially leading to earlier and more systematic interventions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis. Zhu, J., Lu, Q., Liang, T., et al.[2022]

Using stricter diagnostic criteria, such as requiring two medical claims or a claim for a face-to-face encounter, significantly improved the specificity of algorithms for identifying chronic conditions like hypertension and diabetes, increasing it by 0.03 to 0.11.

Incorporating both medical claims and pharmacy claims for relevant medications enhanced the specificity by 0.03 to 0.17 and improved sensitivity by 0.01 to 0.20, demonstrating that more comprehensive data can lead to better identification of beneficiaries with chronic diseases.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions. Rector, TS., Wickstrom, SL., Shah, M., et al.[2018]

References

1. England pubmed.ncbi.nlm.nih.gov

Diflunisal tolerability in transthyretin cardiac amyloidosis: a single center's experience. [2019]

2. England pubmed.ncbi.nlm.nih.gov

Safety and efficacy of long-term diflunisal administration in hereditary transthyretin (ATTR) amyloidosis. [2015]

3. New Zealand pubmed.ncbi.nlm.nih.gov

Tafamidis: A Review in Transthyretin Amyloidosis with Polyneuropathy. [2020]

4. Netherlands pubmed.ncbi.nlm.nih.gov

Advances in Diagnosis and Treatment of Cardiac and Renal Amyloidosis. [2022]

5. United States pubmed.ncbi.nlm.nih.gov

A Review of Novel Agents and Clinical Considerations in Patients With ATTR Cardiac Amyloidosis. [2023]

6. New Zealand pubmed.ncbi.nlm.nih.gov

Evaluation of Mortality During Long-Term Treatment with Tafamidis for Transthyretin Amyloidosis with Polyneuropathy: Clinical Trial Results up to 8.5 Years. [2020]

7. England pubmed.ncbi.nlm.nih.gov

Natural history and impact of treatment with tafamidis on major cardiovascular outcome-free survival time in a cohort of patients with transthyretin amyloidosis. [2021]

8. England pubmed.ncbi.nlm.nih.gov

Identification of rheumatoid arthritis in German claims data using different algorithms: Validation by cross-sectional patient-reported survey data. [2023]

9. Switzerland pubmed.ncbi.nlm.nih.gov

Rheumatic?-A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study. [2023]

10. United States pubmed.ncbi.nlm.nih.gov

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods. [2023]

11. England pubmed.ncbi.nlm.nih.gov

Development and Validation of a Machine Learning-Based Nomogram for Prediction of Ankylosing Spondylitis. [2022]

12. United States pubmed.ncbi.nlm.nih.gov

Specificity and sensitivity of claims-based algorithms for identifying members of Medicare+Choice health plans that have chronic medical conditions. [2018]