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2024-09-10
2027-09-26
2027-09-26
419
NCT06549725
Lipidica, a.s.
Lipidica, a.s.
INTERVENTIONAL
Clinical Performance of Medical Device Software "Lipidica 1.0" for Processing Data Generated by Lipidomic Analysis in Pancreatic Cancer Screening
Software "Lipidica" is intended to be used for processing data generated by the in-house in vitro diagnostic medical device for lipidomic testing for the purpose of screening Pancreatic cancer (PaC) in the population at high risk of this cancer due to familial risk, selected gene mutations or hereditary pancreatic diseases. The primary objective is to verify that the investigational IVDSW can discriminate between results of patients with Pancreatic cancer and persons without Pancreatic cancer but at higher risk of this cancer disease due to their predispositions. Participants will: * come to baseline and end of study visit for blood sampling and medical imaging * some participant will undertake one more visit depending on their results on baseline
Pancreatic cancer (PaC) is one of the cancer diseases with the worst prognosis, as mortality almost equals the incidence. In the Czech Republic, the incidence of pancreatic ductal adenocarcinoma (PDAC) has had a clear upward trend since the late 1970s, and in 2018, 21.9 new cases per 100,000 persons were reported. PDAC is associated with a poor prognosis for several reasons. Due to the usual asymptomatic course or occurrence of only non-specific symptoms, it is usually detected in an advanced stage. Moreover, the diagnosis by standard methods can be difficult in the early stages, and investigators lack sensitive and specific tumor markers. The disease forms distant metastases rapidly, which creates a very short time interval for effective curative interventions. So far, PaC screening possibilities in the Czech Republic are limited to several academic research screening cohorts. Five-year survival, regardless of clinical stage, is 7-9%. The resectable disease is detected in 10% of patients with a 5-year survival of 42%. Locally advanced unresectable disease is found in about 30% of patients with a 5-year survival of 12%, and metastatic disease is diagnosed in about 60% of patients with a 5-year survival of only approx. 3%. PaC screening is not suitable for an unselected population. By contrast, it is vital for individuals with a high risk of developing this disease due to family history and/or genetic predispositions. Early diagnosis resulted in more curative resections and longer survival in this population thanks to the screening programs. First economic evaluations described the possible cost-effectiveness of screening high-risk individuals. Changes in plasma lipid concentrations were reported in various cancer types (bladder, breast, colorectal, gastric, liver, kidney, lung, oesophageal, ovarian, prostate, thyroid, and pancreas). The altered plasma lipid profile may originate not only from tumor cells, tumor stroma, and apoptotic cells but also from an immune response. Previous study robustly proved a specific lipidomic phenotype in patients with PDAC across stages, age, treatments, or the presence of diabetes. Multiple lipid species were significantly downregulated in the plasma of PDAC patients, such as very long-chain monounsaturated sphingomyelins, ceramides and (lyso)phosphatidylcholines. The study showed that lipid profiling can discriminate between patients with PDAC and healthy controls or patients with pancreatitis. This clinical performance study (CPS) follows on from the previous study by Wolrab et al.
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
| Study Registration Dates | Results Reporting Dates | Study Record Updates |
|---|---|---|
2024-08-05 | N/A | 2025-07-29 |
2024-08-08 | N/A | 2025-08-01 |
2024-08-12 | N/A | 2025-07 |
This section provides details of the study plan, including how the study is designed and what the study is measuring.
Primary Purpose:
Screening
Allocation:
Randomized
Interventional Model:
Parallel
Masking:
Single
Arms and Interventions
| Participant Group/Arm | Intervention/Treatment |
|---|---|
| ACTIVE_COMPARATOR: Patients with Pancreatic cancer Participants with histologically confirmed diagnosis of resectable Pancreatic cancer. Arm 1 will undertake one visit (baseline) for blood sampling - lipidomics, CA 19-9 and CEA, HbA1c. At baseline their participation ends. | DEVICE: software Lipidica
DIAGNOSTIC_TEST: laboratory examination
|
| EXPERIMENTAL: Patient at risk of Pancreatic cancer Participants without Pancreatic cancer but at higher risk of this cancer disease due to their predispositions. Arm 2 will come for two or three visits depending on results at baseline. On each visit blood sampling (lipidomics, CA 19-9 and CEA, HbA1c, hCG | DEVICE: software Lipidica
PROCEDURE: endoscopic ultrasonography
PROCEDURE: magnetic resonance
DIAGNOSTIC_TEST: laboratory examination
PROCEDURE: computed tomography
|
| Primary Outcome Measures | Measure Description | Time Frame |
|---|---|---|
| The primary objective is to verify that the investigational IVDSW can discriminate between results of patients with PaC and persons without PaC but at higher risk of this cancer disease due to their predispositions. | The primary objective will be assessed using the following parameters: Diagnostic sensitivity The sensitivity is defined as the capacity to correctly detect confirmed positive samples of plasma from patient with PaC diagnosed with standard diagnostic methods. Diagnostic specificity The specificity is the ability to correctly classify samples of plasma from patient without PaC but at higher risk of the disease. The diagnosis of PaC will be excluded using standard diagnostic methods. Positive predictive value It is the ratio of patients with PaC truly diagnosed as positive to all those who had positive results (including healthy subjects who were incorrectly diagnosed as patients with PaC). Negative predictive value It is the ratio of subjects truly diagnosed as negative to all those who had negative results (including patients with PaC who were incorrectly diagnosed as healthy). Likelihood ratio and Expected values in normal and affected populations | Interim analysis 1 year from first subject enrolled and through study completion (an average of 3 years) |
| Secondary Outcome Measures | Measure Description | Time Frame |
|---|
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
|
Study Contact Name: Karolina Kasparova Phone Number: +420723 242 544 Email: karolina.kasparova@lipidica.cz |
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person’s general health condition or prior treatments.
Ages Eligible for Study:
ALL
Sexes Eligible for Study:
18 Years
Accepts Healthy Volunteers:
1
This is where you will find people and organizations involved with this study.
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
No publications available
