An observational study in Melanoma (Skin Cancer), sponsored by Vastra Gotaland Region. Not yet recruiting at 1 site in Sweden. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-01-23.
Sponsored by Vastra Gotaland Region · Observational
In Sweden, approximately 9,000 Swedes are affected by melanoma annually, and each year, 500 individuals die from metastatic melanoma. The prognosis for melanoma primarily depends on the thickness of the tumor at diagnosis. Melanomas that only grow in the epidermis and have not yet grown into the dermis are called melanoma in situ or pre-melanoma. These melanomas lack the potential to spread in the body. Melanomas that grow into the dermis, on the other hand, are called invasive or malignant melanomas. Invasive melanomas have the potential to spread in the body.
To improve melanoma diagnostics, a dermatoscope is used. A dermatoscope is a type of magnifying glass equipped with a strong light. Using a dermatoscope makes the structures in the epidermis and dermis clearer. Although most melanomas are relatively easy to detect, it is often difficult to determine whether melanomas are invasive or in situ based on the dermatoscopic image. Despite the fact that all suspected melanomas (regardless of melanoma depth) should be operated on, it is important to form an opinion on whether the melanoma is invasive or in situ. This decision is important because it:
In recent years, several applications of machine learning have shown great potential in research contexts within dermatology and venereology. However, these tools have been evaluated to a very limited extent in clinical trials, which is naturally a prerequisite before they can be safely implemented in routine healthcare.
3,006 studies on the registry are indexed under Melanoma; 520 are open to participants now.
This study's planned enrollment of 900 is above the median of 182 across 438 observational studies indexed under Melanoma.
Browse Melanoma studies →Vastra Gotaland Region is the lead sponsor of 267 studies on the registry; 107 are open to participants now.
Counted across the registry records on this site, refreshed daily.
The investigational population are patients ≥18 years with suspected cutaneous melanoma with Fitzpatrick skin phototypes I, II, III and IV. We aim to include 300 melanomas with histopathological verification. Importantly, we will include only suspected melanomas, meaning that some lesions will end up being either dysplastic nevi (DN) or other skin tumours. This implies that we need to include up to 600-900 lesions. Considering the non-invasive nature of the investigational product pregnant and breastfeeding women, immune-compromised and elderly subjects will be eligible for inclusion if they fulfil all inclusion criteria.
Exclusion Criteria:
As per judgement by the investigator, to exclude when there are factors that may affect the quality of the photo such as when:
Device: Medical Device Dermalyser
Dermalyser is an Artificial Intelligence (AI) application (app) that allows medical professionals to take pictures of cutaneous lesions with the help of a smartphone camera. A dermatoscope is connected to the smartphone camera and is used to take the digital image of cutaneous lesions with suspicion of melanoma. Based on image processing algorithms, the app does a detailed analysis of the captured cutaneous lesion. In this clinical investigation, the objective is to test the device performance in a prospective setting in patients with a suspicion of primary cutaneous melanoma, to validate the added AI component. The intended purpose of the device is not to replace the physician's assessment, but rather to assist physicians in their assessment. Consequently, the final device should be regarded as a second opinion to augment clinical decision-making. The ultimate aim is to develop a tool that may augment clinical decision-making.
Area under the curve (AUC) for discrimination between invansive and in situ melanoma for the "in distribution data set".
Please note that preoperatively there will still be uncertainty if an included lesion will be histopathologically verified as a melanoma. After histopathological analysis all lesions will be separated into an "in distrubution data set", i.e. lesions that were confirmed as melanomas and an "out-of distribution set", i.e., lesions that proved to have an alternative diagnosis. Please note that the primary outcome measure will be limited the "in distrubution data set", i.e., lesions that turned out to be a melanoma. Image analysis with the help of AI tool Dermalyser in a prospective setting.
Time frame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Sensitivity and Specificity
Please note that preoperatively there will still be uncertainty if an included lesion will be histopathologically verified as a melanoma. After histopathological analysis all lesions will be separated into an "in distrubution data set", i.e. lesions that were confirmed as melanomas and an "out-of distribution set", i.e., lesions that proved to have an alternative diagnosis. Please note that the sensitivity and specificity measure will be limited the "in distrubution data set", i.e., lesions that turned out to be a melanoma. Image analysis with the help of AI tool Dermalyser in a prospective setting.
Time frame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Algorithmic and physicians assessment of the "out of distribution set"
Please note that preoperatively there will still be uncertainty if an included lesion will be histopathologically verified as a melanoma. After histopathological analysis all lesions will be separated into an "in distrubution data set", i.e. lesions that were confirmed as melanomas and an "out-of distribution set", i.e., lesions that proved to have an alternative diagnosis. Please note that this pre-specified outcome will be limited the "out of distrubution data set", i.e., lesions that turned out not to be a melanoma. Image analysis with the help of AI tool Dermalyser in a prospective setting.
Time frame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Plan to share: Undecided
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Vastra Gotaland Region