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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:
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with Pancreatic cancer | Active Comparator | 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. |
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| Patient at risk of Pancreatic cancer | Experimental | 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) and medical imaging by EUS, MR or CT will be performed. Their participation ends with the diagnosis of Pancreatic cancer or after 12 months of follow-up. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| software Lipidica | Device | The investigational in vitro diagnostic medical device-software (IVDSW) "Lipidica" processes and analyses data inputs from the analysis of lipid profile in human plasma using an in-house in vitro diagnostic medical device. |
| 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) |
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| Measure | Description | Time Frame |
|---|---|---|
| Glycosylated haemoglobin (HbA1c) levels with PaC diagnosis status | The association of glycosylated haemoglobin (HbA1c) levels with PaC diagnosis status. Measured in both arms. | Through study completion (an average of 3 years) |
| Effect of CA 19-9 and CEA tumor markers on sensitivity and specificity |
Inclusion Criteria Arm1:
Exclusion Criteria Arm 1:
Inclusion Criteria Arm2:
Age ≥ 18 years
Signed informed consent
High risk of PaC due to the presence of one of the following risk factors:
Age:
Exclusion Criteria Arm 2:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Karolina Kasparova | Contact | +420723 242 544 | karolina.kasparova@lipidica.cz |
| Name | Affiliation | Role |
|---|---|---|
| Karolina Kasparova | Lipidica, a.s. | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ustredni vojenska nemocnice | Recruiting | Prague | Czechia | Czechia |
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Arm 1: Histologically confirmed diagnosis of resectable Pancreatic cancer Arm 2: Participants without PaC but at higher risk of Pancreatic cancer disease due to their predispositions
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The laboratory personnel performing the lipidomic testing and using the investigated medical device software will be blinded to the allocation of the participants/ samples.
| endoscopic ultrasonography | Procedure | Endoscopic ultrasonography - maximum frequency: 3 times during the participation |
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| magnetic resonance | Procedure | Magnetic resonance - maximum frequency: 3 times during the participation |
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| laboratory examination | Diagnostic Test | Lipidomic analysis, CA 19-9, CEA, HbA1c and hCG levels assessment (hCG only in women of childbearing potential in Arm 2) |
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| computed tomography | Procedure | computed tomography - maximum frequency: 3 times during the participation |
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The effect of CA 19-9 and CEA tumor markers input into the mathematical model as an integral part of MDSW used for processing data derived from lipidomic testing on sensitivity and specificity. Measured in both arms. |
| Through study completion (an average of 3 years) |
| Several predefined cut-off values | Sensitivity and specificity will be assessed for several predefined cut-off values to explore the impact of the results within the range of diagnostic uncertainty. The impact of subgroups within different ranges of results based on IVDSW processing on sensitivity and specificity will be assessed. Measured in both arms. | Through study completion (an average of 3 years) |
| The effect of the normalization step on the calculation of lipid concentrations and its impact on the clinical performance of IVDSW. | The effect of the normalization step on the calculation of lipid concentrations and its impact on the clinical performance of IVDSW. Sponsor will assess the impact of normalization which automatically eliminates the effect of mass spectrometer aging on key diagnostic parameters of the method in alignment with the primary outcome of the study: Diagnostic sensitivity, Diagnostic specificity, Positive predictive value, Negative predictive value, Likelihood ratio, Expected values in normal and affected populations. The expected value of the result from IVDSW "Lipidica" is ≤ 0.5 for the healthy population. The expected value for patients with PaC is > 0.5. | Through study completion (an average of 3 years) |
| Verification of the clinical performance of next version(s) of IVDSW "Lipidica" | Verification of the clinical performance of next version(s) of IVDSW "Lipidica" in alignment with the intended purpose using the laboratory and clinical data obtained in this CPS (i.e. to verify that new version(s) can still discriminate between samples of patients with PaC and persons without PaC but at higher risk of this cancer disease). Sponsor will assess the clinical function of the next version of IVDSW "Lipidica" on key diagnostic parameters of the method in alignment with the primary outcome of the study and in comparison to the previous version which is the studied device: Diagnostic sensitivity, Diagnostic specificity, Positive predictive value, Negative predictive value, Likelihood ratio, Expected values in normal and affected populations. The expected value of the result from IVDSW "Lipidica" is ≤ 0.5 for the healthy population. The expected value for patients with PaC is > 0.5. | Through study completion (an average of 3 years) |
| Fakultni nemocnice Brno | Recruiting | Brno | Czechia |
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| Fakultni nemocnice u sv. Anny | Recruiting | Brno | Czechia |
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| Masarykuv onkologicky ustav | Recruiting | Brno | Czechia |
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| Nemocnice Ceske Budejovice | Recruiting | České Budějovice | Czechia |
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| Fakultni nemocnice Hradec Kralove | Recruiting | Hradec Králové | Czechia |
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| Nemocnice Jablonec nad Nisou | Not yet recruiting | Jablonec nad Nisou | Czechia |
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| Fakultni nemocnice Olomouc | Recruiting | Olomouc | Czechia |
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| Nemocnice Pardubickeho kraje | Recruiting | Pardubice | Czechia |
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| Fakultni nemocnice Plzen | Recruiting | Pilsen | Czechia |
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| Fakultni nemocnice Bulovka | Recruiting | Prague | Czechia |
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| Fakultni nemocnice Kralovske Vinohrady | Recruiting | Prague | Czechia |
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| Fakultni Thomayerova nemocnice | Recruiting | Prague | Czechia |
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| Institut klinicke a experimentalni mediciny | Recruiting | Prague | Czechia |
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| Vseobecna fakultni nemocnice | Recruiting | Prague | Czechia |
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| Masarykova nemocnice v Usti nad Labem | Recruiting | Ústí nad Labem | Czechia |
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| ID | Term |
|---|---|
| D010190 | Pancreatic Neoplasms |
| D030342 | Genetic Diseases, Inborn |
| D050500 | Pancreatitis, Chronic |
| ID | Term |
|---|---|
| D004067 | Digestive System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D004701 | Endocrine Gland Neoplasms |
| D004066 | Digestive System Diseases |
| D010182 | Pancreatic Diseases |
| D004700 | Endocrine System Diseases |
| D009358 | Congenital, Hereditary, and Neonatal Diseases and Abnormalities |
| D010195 | Pancreatitis |
| D002908 | Chronic Disease |
| D020969 | Disease Attributes |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D009682 | Magnetic Resonance Spectroscopy |
| ID | Term |
|---|---|
| D013057 | Spectrum Analysis |
| D002623 | Chemistry Techniques, Analytical |
| D008919 | Investigative Techniques |
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