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This is a retrospective, open label study to establish and validate a prediction technology for advanced melanoma patients under the 1st, 2nd and later treatment lines, with the immunotherapeutic drugs Ipilimumab, Pembrolizumab & Nivolumab, in order to predict response rate and disease progression
The aim of this project is to develop a technology application (termed ML-PrediCare), which is meant to be a predictive stand-alone software device, to support clinicians' decision-making, by predicting the individual patient's response to immunotherapy treatments, e.g., in terms of time-to-progression (TTP).
In Stage I of the study, data will be collected for establishing a training set and assess the predictive potential of the modelling technology for the response of melanoma patients to immunotherapy. In Stage II of the study, data will be collected in order to establish a validation set and test the predictive power of the modelling technology in an independent set of patients diagnosed with melanoma.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Training Set | The objective of the Training stage is to assess the predictive potential of ML-PrediCare for melanoma patients' response to Ipilimumab, Pembrolizumab and Nivolumab. |
| |
| Validation Set | The objective of the Validation stage is to test the predictive power of ML -PrediCare in an independent set of patients diagnosed with melanoma. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ML-PrediCare | Device |
|
| Measure | Description | Time Frame |
|---|---|---|
| The primary endpoint in this study stage is Time to Progression of disease | 1 year |
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Inclusion Criteria:
Patients who meet all of the following criteria are eligible for this study:
Exclusion Criteria:
Patients meeting one or more of the following criteria are ineligible for this study:
History of another malignancy within the previous 2 years except for:
• Adequately treated Stage I or II cancer currently in complete remission, or any other cancer that has been in complete remission for at least 2 years
Ocular melanoma
Active brain metastases or leptomeningeal metastases.
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Data from up to about 500 melanoma patients will be screened for collection, depending on data availability and completeness of the files
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Marina Kleiman, PhD | Contact | 972-7519226 | 112 | marina@optimata.com |
| Name | Affiliation | Role |
|---|---|---|
| Marina Kleiman, PhD | Optimata Ltd. | Study Director |
| Michal Lotem, MD | Hadassah Medical Organization | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Optimata Ltd. | Recruiting | Bne ‘Atarot | 60991 | Israel |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31590677 | Derived | Tsur N, Kogan Y, Avizov-Khodak E, Vaeth D, Vogler N, Utikal J, Lotem M, Agur Z. Predicting response to pembrolizumab in metastatic melanoma by a new personalization algorithm. J Transl Med. 2019 Oct 7;17(1):338. doi: 10.1186/s12967-019-2081-2. |
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| ID | Term |
|---|---|
| D008545 | Melanoma |
| ID | Term |
|---|---|
| D018358 | Neuroendocrine Tumors |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
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Tumor tissue from an unresectable or metastatic site of disease will be collected for biomarker analyses. Paraffin-embedded tissue samples from patients treated with the immunotherapy drugs (with the previously obtained inform consent form) will be collected from the tissue bank of the hospital and according to the European Commission regulations.
| D009369 | Neoplasms |
| D009380 | Neoplasms, Nerve Tissue |
| D018326 | Nevi and Melanomas |
| D012878 | Skin Neoplasms |
| D009371 | Neoplasms by Site |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |