MelanomaNNCDNCT03362138
Artificial Intelligence-assisted Evaluation of Pigmented Skin Lesions
An observational study of Melanoma and Pigmented Skin Lesion, run by Assuta Hospital Systems at 1 site in Israel.
Trial summary
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths at a 1:28 lifetime incidence (2016). The golden standard, dermoscopy, enables Dermatologists to diagnose with a sensitivity of 40%, and a 8-12% specificity, approximately. Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Melanoma, Pigmented Skin Lesion, Dysplastic Nevi
- What is being tested?
- dermoscopy
- Type of treatment
- Medical device
- How many people
- 80 participants
- Where
- 1 siteIsrael
- Study dates
- 6 Dec 2017to 31 Mar 2019
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- Adult, Older adult
Study population: Subjects examined at a Dermatologic speciality clinic.
Who may be able to join
- Patient aged 18-90 years
- A pigmented lesion by dermoscopy.
- Clinical management by the examining dermatologist results in biopsy
- The diameter of the pigmented area is between 1 and 40 millimeters
- The patient has consented to participate in the study and has signed the Informed Consent Form
Who cannot join
- Non intact skin (ulcers, bleeding)
- The lesion is located within 1 cm of the eye
- The lesion is located on mucosal surfaces
- The lesion is on or under nails
Trial locations and contacts
1 site in 1 country.
Israel1 site, 1 recruiting
- Recruiting
Maccabi Healthcare Clinic
Tel Aviv, 59485
Avi Dascalu, MD, 97236099005, dasc17@gmail.com
About this study
Official title: Dermoscopy Evaluation of Pigmented Skin Lesions by a Neuronal Network Clinical Decision Support: an Open Prospective Non Interventional Study
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths at a 1:28 lifetime incidence (2016).
The golden standard, dermoscopy, enables Dermatologists to diagnose with a sensitivity of 40%, and a 8-12% specificity, approximately. Additional diagnostic abilities are restricted to devices which are either unproved or experimental.
Read more
A new technology of Neuronal Network Clinical Decision Support (NNCD) was developed. It uses a dermoscopic imaging device and a camera able to capture an image. The photo is transferred to a Cloud Server and further analyzed by a trained classifier. Classifier training is aimed at a high accuracy diagnosis of Dysplastic Nevi (DN), Spitz Nevi and Malignant Melanoma detection with assistance from a Deep Neuronal Learning network (DLN). Diagnosis output is an excise or do not excise recommendation for pigmented skin lesions.
A total of 80 subjects already referred to biopsy pigmented skin lesions will be examined by dermoscopy imaging in a non interventional study. Artificial Intelligence output results, as measured by 2 different dermoscopes, to be compared to ground truth biopsies, by either classifier decisions or a novel Modified Classifier Technology output decisions.
Primary endpoints are sensitivity and specificity detection of the NNCD techniques. Secondary endpoints are the positive and negative prediction ratios of NNCD techniques.
Read the detailed description
Background
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths [1]. The incidence rate for MM ascended between 1950 and 2007 more than 17-fold in men (1.9 to 33.5 per 100,000) and more than 9-fold in women (2.6 to 25.3 per 100,000) [2]. It is estimated that 76000 new cases and 9000 deaths are diagnosed/ year (US, only, 2017) [3]. European Countries yield 22000/yr. stage 4 melanomas.
MM starts de novo in about 70% of subjects, with a small 2 millimeters or more superficial skin lesion which, if left undiagnosed, might develop into a more advanced stage cancer, followed by silent lymph node spreading and invasion of vital organs such as liver and brain. MM is staged by either direct invasion into the skin, the Breslow scale in mm, or by its skin level involvement, a Clark 1-5 structural skin level of involvement. Both methods of assessment are predictors of long term survival, which is almost unchanged at a Breslow depth beneath 1 mm and much decreased beyond Clark III stage. Therefore early detection of melanoma, generally tagged as small melanoma, is critical.
Present Methodologies of MM detection
The following different methods and diagnostic means for detection of the cutaneous melanoma are currently employed as a means of diagnosis:
- Visual recognition by an Asymmetry, Border, Color, Diameter and Evolvement (ABCDE rule). A 30 year old methodology and still running, assessing: ABCDE. It is used by part of US dermatologists who trust their clinical skills and instincts [4]. Due to its innate complexity and myriad of recognition patterns, dermoscopy by epiluminescence microscopy is considered as ineffective by 60% of the non users dermatologists and 30% report it as time consuming, rendering it impracticable. The abovementioned rule was reviewed in 2015 [5] and teaches the use of a diameter greater than 6 mm as a criteria for melanoma recognition. Consequently, it does not contribute to early detection of a melanoma, which might be life saving, since 70-80% of melanomas start de novo as small melanomas. An attempt to change the Diameter criteria, i.e. a decrease in the postulated 6 mm Diameter, leads to a major decrease in sensitivity and specificity, rendering the ABCDE ineffective for early melanoma detection. It is concluded that these basic visual criteria, although widely used, are a non effective prevention method due to their innate criteria which misses the evolving melanomas, since all melanomas start as small melanomas.
- Epiluminescence microscopy is a 65 years old art, which is considered the golden standard of evaluation. It is highly dependent on the skills and knowledge of the diagnostician. Epiluminescence microscopy is a the bridge between clinical observation and histopathological diagnosis. It allows visualization of skin pigments up to the papillary dermis and improves detection sensitivity and specificity. Analysis is made by a clinician based on dermoscopy rules [6], which are based on a complicated dermoscopic pattern analysis. Complete dermoscopic pattern analysis of a lesion is the mainstream of diagnosis. Each of the dermoscopic patterns can diverge in extent, diameter, general or local appearance, or evolve as multi patterns with various area of expression on the same lesion and rendering the diagnosis beyond an encyclopedic task. Due to the complexity of the dermoscopic pattern analysis method, different modifications were proposed, such as a simplified ABCD rule, an intermediate 7 rules assessment and a 11 rules checklist. The myriad of data and its interpretation render even experts in dermoscopy to identify melanomas with a relative low ratio from 5:1 to 15:1, i.e. the number of biopsies of benign lesions performed in order to make the diagnosis of one skin melanoma. Furthermore, there are claims that one diagnostic sign might be more sensitive that other signs, alike the criteria of a light brown structureless area. Dermatologists commonly fail in diagnosing early small melanoma which is the critical period of growth of the tumor and most efficacious prevention.
- Visual recognition by temporal total body photography is yet non standardized methodology, a time consuming and patient expensive procedure. It uses the human comparison assessment and is subjected to biases of pixel photo during performance of the measurement, due to lighting, background and camera position. Addition of patient assessment by artificial intelligence, an analysis based on computer evaluation of different colorimetric and geometric parameters of a lesion in real time, confer a limited advantage only, yielding sometimes more false positives compared to inexperienced or even experienced clinicians.
- Multi Spectrometry devices, which provide measurements of melanin, collagen and hemoglobin with further use of image analysis, do not confer any advantage to epiluminescence microscopy. Although displaying a higher sensitivity, these methodologies specificity are considerably below that of simple epiluminescence microscopy in melanoma identification rate .
- Confocal scanning microscopy, a procedure which uses a low power laser for a 3D imaging. An effective means of diagnosis. However, the use of this methodology is limited by its high cost, a prolonged (6 mo) learning curve of 2000-4000 images, and the requirement for a highly specialized and trained personal, since this methodology is highly subjected to artifacts.
- Experimental under development methods: alike Electrical impedance spectroscopy, Optical coherence tomography, High frequency ultrasound, Laser doppler perfusion imaging, Dynamic thermal imaging, Photoacoustic microscopy, to be further developed and proved.
Clinical Requirements
It is desirable to identify a new non invasive methodology which will
- Improve Sensitivity of diagnosis of pigmented skin lesions, alike dysplastic nevi, Spitz nevi and MM
- Identify small MM,
- Increase Specificity of lesions to be biopsied
- Non invasive fast technology.
Common Practice
Commonly, a patient is evaluated by a physician due to either a skin lesion complaint or, with high risk patients, a summon to visit on a regular basis.
Only some of the dermatologists employ dermoscopy or are skilled to use it since it may seem to be time consuming. There is no international standard of degree of skill. Even a golden standard textbook of dermoscopy is not existent.
Upon recognition of suspicious lesion, patient is referred to a surgeon for biopsy.
As recently reviewed and in view of the above-mentioned, the incidence of melanoma is continuing to increase. All present methods commonly do not diagnose melanoma at an early stage and epiluminescence microscopy is highly user dependant and commonly misses the diagnosis . Early excision is the only strategy to reduce the death toll associated with melanoma. Unnecessary excision of benign lesions increases morbidity and raise healthcare costs associated with melanoma screening, resulting in recommended restrictions to a total body screening by Surgeon General (2016) and questioning the efficacy of such a screening.
The requirement for a more systemized methodology and system is obvious in view of the expected increase in melanoma incidence to a 1:15 within the next 15 years. A new device able to capture the window of opportunity of Dysplastic Nevus to small melanoma is highly useful for today healthcare systems.
Primary Study Objectives
- A Sensitivity of at least 75% for Classifier results as compared to biopsy Sensitivity is the percentage of correctly diagnosed dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ].
- A Sensitivity of at least 85% for an Modified Classifier Technology (MCT) results as compared to biopsy. Sensitivity is the percentage of correctly diagnosed dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
- A Specificity of at least 33% for Classifier results as compared to biopsy. Specificity is the percentage of correctly identified dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
- A Specificity of at least 33% for MCT results as compared to biopsy. Specificity is the percentage of correctly identified dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
Secondary Study Objectives
- The positive predictive value of MCT, compared to the biopsy result [ Designated as safety issue: No ]
- The negative predictive value of MCT, [ Designated as safety issue: No ]
- The false positive rate of MCT, [ Designated as safety issue: No ]
- The false negative rate of MCT, [ Designated as safety issue: No ]
- The difference between two dermoscopes, [ Designated as safety issue: No ]
- The positive predictive value of Classifier, compared to the biopsy result [ Designated as safety issue: No ]
- The negative predictive value of Classifier, [ Designated as safety issue: No ]
- The false positive rate of Classifier, [ Designated as safety issue: No ]
- The false negative rate of Classifier, [ Designated as safety issue: No ]
- Clinical decision Sensitivity and Specificity rates.
- Conditions
- Melanoma, Pigmented Skin Lesion, Dysplastic Nevi
- Being tested
- dermoscopy
- Keywords
- melanoma, dysplastic nevus, artificial intelligence, early diagnosis
- Medical subject headings
- Melanoma, Dysplastic Nevus Syndrome, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
dermoscopyDevice
Solely after the dermatologist has decided to biopsy a lesion and sent the patient to biopsy, a dermoscopic image is captured by a camera attached to a dermoscope.
| Study group | Role | What they receive |
|---|---|---|
| Dermoscopy | Dermoscopic imaging of a lesion decided to be biopsied Receives: Device: dermoscopy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Sensitivity for Classifier results as compared to biopsy
A Sensitivity of at least 75% for Classifier results as compared to biopsy
Measured: 15 months
Sensitivity for MCT results as compared to biopsy
A Sensitivity of at least 85% for Classifier results as compared to biopsy
Measured: 15 months
Secondary outcomes (2)
The positive predictive value of MCT
The positive predictive value of MCT, compared to the biopsy result
Measured: 15 months
The negative predictive value of MCT
The negative predictive value of MCT, compared to the biopsy result
Measured: 15 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Dec 2017
- Study start6 Dec 2017
- Primary completion31 Dec 2018 (estimated)
- Study completion31 Mar 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (8)Papers the sponsor has linked to this study.
- Other trials for MelanomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Enrolment
- 80 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Assuta Hospital Systems
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Avi Dascalu, MD. Ph.D., Principal investigator, Bostel LLC
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03362138
- Sponsor's protocol ID
- AQ16842
- Acronym
- NNCD
- Status last verified
- Nov 2017
- First submitted
- 27 Nov 2017
- Last updated
- 13 Sep 2018
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Eggermont AM, Spatz A, Robert C. Cutaneous melanoma. Lancet. 2014 Mar 1;383(9919):816-27. doi: 10.1016/S0140-6736(13)60802-8. Epub 2013 Sep 19.
PubMed 24054424Mayer JE, Swetter SM, Fu T, Geller AC. Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part I. Epidemiology, high-risk groups, clinical strategies, and diagnostic technology. J Am Acad Dermatol. 2014 Oct;71(4):599.e1-599.e12; quiz 610, 599.e12. doi: 10.1016/j.jaad.2014.05.046.
PubMed 25219716Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012 Jan-Feb;62(1):10-29. doi: 10.3322/caac.20138. Epub 2012 Jan 4.
PubMed 22237781Noor O 2nd, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009 Sep;48(9):951-2. doi: 10.1111/j.1365-4632.2009.04095.x.
PubMed 19702978American Academy of Dermatology Ad Hoc Task Force for the ABCDEs of Melanoma; Tsao H, Olazagasti JM, Cordoro KM, Brewer JD, Taylor SC, Bordeaux JS, Chren MM, Sober AJ, Tegeler C, Bhushan R, Begolka WS. Early detection of melanoma: reviewing the ABCDEs. J Am Acad Dermatol. 2015 Apr;72(4):717-23. doi: 10.1016/j.jaad.2015.01.025. Epub 2015 Feb 16.
PubMed 25698455Campos-do-Carmo G, Ramos-e-Silva M. Dermoscopy: basic concepts. Int J Dermatol. 2008 Jul;47(7):712-9. doi: 10.1111/j.1365-4632.2008.03556.x.
PubMed 18613881Dascalu A, David EO. Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope. EBioMedicine. 2019 May;43:107-113. doi: 10.1016/j.ebiom.2019.04.055. Epub 2019 May 14.
PubMed 31101596Walker BN, Rehg JM, Kalra A, Winters RM, Drews P, Dascalu J, David EO, Dascalu A. Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies. EBioMedicine. 2019 Feb;40:176-183. doi: 10.1016/j.ebiom.2019.01.028. Epub 2019 Jan 20.
PubMed 30674442
Study at a glance
From the registry record, last updated by the sponsor on 13 Sep 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Dermoscopy Evaluation of Pigmented Skin Lesions by a Neuronal Network Clinical Decision Support: an Open Prospective Non Interventional Study
- ClinicalTrials.gov ID
- NCT03362138
- Acronym / sponsor ID
- NNCD / AQ16842
- Conditions
- Melanoma, Pigmented Skin Lesion, Dysplastic Nevi
- Keywords
- melanoma, dysplastic nevus, artificial intelligence, early diagnosis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 80 participants (estimated)
- Lead sponsor
- Assuta Hospital SystemsUniversity, hospital or other
- Study start
- 6 Dec 2017 (actual)
- Primary completion
- 31 Dec 2018 (estimated)
- Study completion
- 31 Mar 2019 (estimated)
- First posted
- 5 Dec 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths at a 1:28 lifetime incidence (2016).
The golden standard, dermoscopy, enables Dermatologists to diagnose with a sensitivity of 40%, and a 8-12% specificity, approximately. Additional diagnostic abilities are restricted to devices which are either unproved or experimental.
A new technology of Neuronal Network Clinical Decision Support (NNCD) was developed. It uses a dermoscopic imaging device and a camera able to capture an image. The photo is transferred to a Cloud Server and further analyzed by a trained classifier. Classifier training is aimed at a high accuracy diagnosis of Dysplastic Nevi (DN), Spitz Nevi and Malignant Melanoma detection with assistance from a Deep Neuronal Learning network (DLN). Diagnosis output is an excise or do not excise recommendation for pigmented skin lesions.
A total of 80 subjects already referred to biopsy pigmented skin lesions will be examined by dermoscopy imaging in a non interventional study. Artificial Intelligence output results, as measured by 2 different dermoscopes, to be compared to ground truth biopsies, by either classifier decisions or a novel Modified Classifier Technology output decisions.
Primary endpoints are sensitivity and specificity detection of the NNCD techniques. Secondary endpoints are the positive and negative prediction ratios of NNCD techniques.
Detailed description
Background
Malignant melanoma (MM) is a deadly cancer, claiming globally about 160000 new cases per year and 48000 deaths [1]. The incidence rate for MM ascended between 1950 and 2007 more than 17-fold in men (1.9 to 33.5 per 100,000) and more than 9-fold in women (2.6 to 25.3 per 100,000) [2]. It is estimated that 76000 new cases and 9000 deaths are diagnosed/ year (US, only, 2017) [3]. European Countries yield 22000/yr. stage 4 melanomas.
MM starts de novo in about 70% of subjects, with a small 2 millimeters or more superficial skin lesion which, if left undiagnosed, might develop into a more advanced stage cancer, followed by silent lymph node spreading and invasion of vital organs such as liver and brain. MM is staged by either direct invasion into the skin, the Breslow scale in mm, or by its skin level involvement, a Clark 1-5 structural skin level of involvement. Both methods of assessment are predictors of long term survival, which is almost unchanged at a Breslow depth beneath 1 mm and much decreased beyond Clark III stage. Therefore early detection of melanoma, generally tagged as small melanoma, is critical.
Present Methodologies of MM detection
The following different methods and diagnostic means for detection of the cutaneous melanoma are currently employed as a means of diagnosis:
- Visual recognition by an Asymmetry, Border, Color, Diameter and Evolvement (ABCDE rule). A 30 year old methodology and still running, assessing: ABCDE. It is used by part of US dermatologists who trust their clinical skills and instincts [4]. Due to its innate complexity and myriad of recognition patterns, dermoscopy by epiluminescence microscopy is considered as ineffective by 60% of the non users dermatologists and 30% report it as time consuming, rendering it impracticable. The abovementioned rule was reviewed in 2015 [5] and teaches the use of a diameter greater than 6 mm as a criteria for melanoma recognition. Consequently, it does not contribute to early detection of a melanoma, which might be life saving, since 70-80% of melanomas start de novo as small melanomas. An attempt to change the Diameter criteria, i.e. a decrease in the postulated 6 mm Diameter, leads to a major decrease in sensitivity and specificity, rendering the ABCDE ineffective for early melanoma detection. It is concluded that these basic visual criteria, although widely used, are a non effective prevention method due to their innate criteria which misses the evolving melanomas, since all melanomas start as small melanomas.
- Epiluminescence microscopy is a 65 years old art, which is considered the golden standard of evaluation. It is highly dependent on the skills and knowledge of the diagnostician. Epiluminescence microscopy is a the bridge between clinical observation and histopathological diagnosis. It allows visualization of skin pigments up to the papillary dermis and improves detection sensitivity and specificity. Analysis is made by a clinician based on dermoscopy rules [6], which are based on a complicated dermoscopic pattern analysis. Complete dermoscopic pattern analysis of a lesion is the mainstream of diagnosis. Each of the dermoscopic patterns can diverge in extent, diameter, general or local appearance, or evolve as multi patterns with various area of expression on the same lesion and rendering the diagnosis beyond an encyclopedic task. Due to the complexity of the dermoscopic pattern analysis method, different modifications were proposed, such as a simplified ABCD rule, an intermediate 7 rules assessment and a 11 rules checklist. The myriad of data and its interpretation render even experts in dermoscopy to identify melanomas with a relative low ratio from 5:1 to 15:1, i.e. the number of biopsies of benign lesions performed in order to make the diagnosis of one skin melanoma. Furthermore, there are claims that one diagnostic sign might be more sensitive that other signs, alike the criteria of a light brown structureless area. Dermatologists commonly fail in diagnosing early small melanoma which is the critical period of growth of the tumor and most efficacious prevention.
- Visual recognition by temporal total body photography is yet non standardized methodology, a time consuming and patient expensive procedure. It uses the human comparison assessment and is subjected to biases of pixel photo during performance of the measurement, due to lighting, background and camera position. Addition of patient assessment by artificial intelligence, an analysis based on computer evaluation of different colorimetric and geometric parameters of a lesion in real time, confer a limited advantage only, yielding sometimes more false positives compared to inexperienced or even experienced clinicians.
- Multi Spectrometry devices, which provide measurements of melanin, collagen and hemoglobin with further use of image analysis, do not confer any advantage to epiluminescence microscopy. Although displaying a higher sensitivity, these methodologies specificity are considerably below that of simple epiluminescence microscopy in melanoma identification rate .
- Confocal scanning microscopy, a procedure which uses a low power laser for a 3D imaging. An effective means of diagnosis. However, the use of this methodology is limited by its high cost, a prolonged (6 mo) learning curve of 2000-4000 images, and the requirement for a highly specialized and trained personal, since this methodology is highly subjected to artifacts.
- Experimental under development methods: alike Electrical impedance spectroscopy, Optical coherence tomography, High frequency ultrasound, Laser doppler perfusion imaging, Dynamic thermal imaging, Photoacoustic microscopy, to be further developed and proved.
Clinical Requirements
It is desirable to identify a new non invasive methodology which will
- Improve Sensitivity of diagnosis of pigmented skin lesions, alike dysplastic nevi, Spitz nevi and MM
- Identify small MM,
- Increase Specificity of lesions to be biopsied
- Non invasive fast technology.
Common Practice
Commonly, a patient is evaluated by a physician due to either a skin lesion complaint or, with high risk patients, a summon to visit on a regular basis.
Only some of the dermatologists employ dermoscopy or are skilled to use it since it may seem to be time consuming. There is no international standard of degree of skill. Even a golden standard textbook of dermoscopy is not existent.
Upon recognition of suspicious lesion, patient is referred to a surgeon for biopsy.
As recently reviewed and in view of the above-mentioned, the incidence of melanoma is continuing to increase. All present methods commonly do not diagnose melanoma at an early stage and epiluminescence microscopy is highly user dependant and commonly misses the diagnosis . Early excision is the only strategy to reduce the death toll associated with melanoma. Unnecessary excision of benign lesions increases morbidity and raise healthcare costs associated with melanoma screening, resulting in recommended restrictions to a total body screening by Surgeon General (2016) and questioning the efficacy of such a screening.
The requirement for a more systemized methodology and system is obvious in view of the expected increase in melanoma incidence to a 1:15 within the next 15 years. A new device able to capture the window of opportunity of Dysplastic Nevus to small melanoma is highly useful for today healthcare systems.
Primary Study Objectives
- A Sensitivity of at least 75% for Classifier results as compared to biopsy Sensitivity is the percentage of correctly diagnosed dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ].
- A Sensitivity of at least 85% for an Modified Classifier Technology (MCT) results as compared to biopsy. Sensitivity is the percentage of correctly diagnosed dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
- A Specificity of at least 33% for Classifier results as compared to biopsy. Specificity is the percentage of correctly identified dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
- A Specificity of at least 33% for MCT results as compared to biopsy. Specificity is the percentage of correctly identified dysplastic nevi, Spitz nevi or melanomas. [ Designated as safety issue: No ]
Secondary Study Objectives
- The positive predictive value of MCT, compared to the biopsy result [ Designated as safety issue: No ]
- The negative predictive value of MCT, [ Designated as safety issue: No ]
- The false positive rate of MCT, [ Designated as safety issue: No ]
- The false negative rate of MCT, [ Designated as safety issue: No ]
- The difference between two dermoscopes, [ Designated as safety issue: No ]
- The positive predictive value of Classifier, compared to the biopsy result [ Designated as safety issue: No ]
- The negative predictive value of Classifier, [ Designated as safety issue: No ]
- The false positive rate of Classifier, [ Designated as safety issue: No ]
- The false negative rate of Classifier, [ Designated as safety issue: No ]
- Clinical decision Sensitivity and Specificity rates.
Study design
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Dermoscopy | – | Device: dermoscopyDermoscopic imaging of a lesion decided to be biopsied |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Age groups
- Adult, Older adult
- Study population
- Subjects examined at a Dermatologic speciality clinic.
Key inclusion criteria (5 listed)
- Patient aged 18-90 years
- A pigmented lesion by dermoscopy.
- Clinical management by the examining dermatologist results in biopsy
- The diameter of the pigmented area is between 1 and 40 millimeters
- The patient has consented to participate in the study and has signed the Informed Consent Form
Key exclusion criteria (4 listed)
- Non intact skin (ulcers, bleeding)
- The lesion is located within 1 cm of the eye
- The lesion is located on mucosal surfaces
- The lesion is on or under nails
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| dermoscopySolely after the dermatologist has decided to biopsy a lesion and sent the patient to biopsy, a dermoscopic image is captured by a camera attached to a dermoscope. | Device | Dermoscopy |
Primary outcome
Sensitivity for Classifier results as compared to biopsy
Time frame: 15 months
A Sensitivity of at least 75% for Classifier results as compared to biopsy
Sensitivity for MCT results as compared to biopsy
Time frame: 15 months
A Sensitivity of at least 85% for Classifier results as compared to biopsy
2 secondary outcomes
The positive predictive value of MCT
Time frame: 15 months
The negative predictive value of MCT
Time frame: 15 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Sep 2018.
- Background: PubMed 24054424Eggermont AM, Spatz A, Robert C. Cutaneous melanoma. Lancet. 2014 Mar 1;383(9919):816-27. doi: 10.1016/S0140-6736(13)60802-8. Epub 2013 Sep 19.
- Background: PubMed 25219716Mayer JE, Swetter SM, Fu T, Geller AC. Screening, early detection, education, and trends for melanoma: current status (2007-2013) and future directions: Part I. Epidemiology, high-risk groups, clinical strategies, and diagnostic technology. J Am Acad Dermatol. 2014 Oct;71(4):599.e1-599.e12; quiz 610, 599.e12. doi: 10.1016/j.jaad.2014.05.046.
- Background: PubMed 22237781Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012 Jan-Feb;62(1):10-29. doi: 10.3322/caac.20138. Epub 2012 Jan 4.
- Background: PubMed 19702978Noor O 2nd, Nanda A, Rao BK. A dermoscopy survey to assess who is using it and why it is or is not being used. Int J Dermatol. 2009 Sep;48(9):951-2. doi: 10.1111/j.1365-4632.2009.04095.x.
- Background: PubMed 25698455American Academy of Dermatology Ad Hoc Task Force for the ABCDEs of Melanoma; Tsao H, Olazagasti JM, Cordoro KM, Brewer JD, Taylor SC, Bordeaux JS, Chren MM, Sober AJ, Tegeler C, Bhushan R, Begolka WS. Early detection of melanoma: reviewing the ABCDEs. J Am Acad Dermatol. 2015 Apr;72(4):717-23. doi: 10.1016/j.jaad.2015.01.025. Epub 2015 Feb 16.
- Background: PubMed 18613881Campos-do-Carmo G, Ramos-e-Silva M. Dermoscopy: basic concepts. Int J Dermatol. 2008 Jul;47(7):712-9. doi: 10.1111/j.1365-4632.2008.03556.x.
- Derived from this study: PubMed 31101596Dascalu A, David EO. Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope. EBioMedicine. 2019 May;43:107-113. doi: 10.1016/j.ebiom.2019.04.055. Epub 2019 May 14.
- Derived from this study: PubMed 30674442Walker BN, Rehg JM, Kalra A, Winters RM, Drews P, Dascalu J, David EO, Dascalu A. Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies. EBioMedicine. 2019 Feb;40:176-183. doi: 10.1016/j.ebiom.2019.01.028. Epub 2019 Jan 20.
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A Feasibility Study Utilizing Immune Recall to Increase Response to Checkpoint Therapy
Melanoma
Active, not recruitingPhase 1/2
A Study of Dapansutrile Plus Pembrolizumab in Patients With PD-1 Refractory Advanced Melanoma
Melanoma
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Avi Dascalu, MD. Ph.D. principal investigator
Bostel LLC
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Melanoma and Pigmented Skin Lesion, run by Assuta Hospital Systems at 1 site in Israel.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 13 Sep 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Israel. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Avi Dascalu, MD, Ph.D. (+972544306331, dasc17@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Sensitivity for Classifier results as compared to biopsy (time frame: 15 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03362138, which also lists 8 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Sep 2018.