The study has 2 parts. Part 1 will investigate the effects of introducing teledermoscopy in clinical practice, more specifically the change in referral patterns, the risk of undetected skin cancers and the effect on diagnostic accuracy in general practitioners.
Part 2 will investigate how to introduce artificial intelligence (AI) within teledermocsopy. In this study the investigators will measure the effect of displaying the results of artificial intelligence in different ways and at different time points.
Data will be collcted through teledermoscopic referrals, patient records, national registries and questionnairs.
Study objective:
Material and methods:
4.2. In part 2, different ways of displaying the results of the artificial intelligence as well as feeding the results at different time points will be compared using analyses of sensitivity, specificity, and Area under ROC-curve (AUROC). The study will also report the impact the results of the artificial intelligence has on the willingness to change a diagnosis or a management plan.
5. Power set to 0.8 and significance to 0.05. 10% censures. 5.1. Patients recruited to this study can be used in several of the sub-studies. The aim of the study is to collect 8000 patients in total in this study.
5.2. To detect a difference in "unimaged skin cancers" between teledermoscopy and conventional care of patients 1200 cases and 2400 controls need to be included.
5.3. To detect a 10% difference in sensitivity/ specificity of diagnostic ability in PCPs before and after working with teledermoscopy 3400 patients need to be included.
5.4. To investigate how artificial intelligence should be implemented in clinical care the investigators have calculated that 6000 patients are needed to detect a 10% difference in sensitivity and specificity in the subgroups.
Ethical considerations and data management:
Data will be collected using Dermicus, a CE-certified digital platform and mobile application. With the application downloaded on iPhones, locked for any other uses, the history of the patients are registered. Then, by connecting the iPhone to a dermoscope, macroscopic and dermoscopic images are captured. All data will be stored on the servers of the health care region of Skne, where the studies are conducted. Patients participating in the studies will be tagged with a study code enabling the investigators to extract the data from the patients that has agreed to participate in our study. Once a case has been created and sent to the data base all information will be deleted from the iPhone. Additional data will also be retrieved from relevant medical records, e.g. histopathological diagnosis, and manually registered in an electronic database at a highly secure location (LUSEC/ REDCap provided by Lund University) . Data collected from PCP and dermatologists by questionnaires will also be registered in this data base by means of electronic surveys (REDCap). Information from primary care on total number of visits, referrals to dermatologists and referrals to pathology regarding skin lesions will be extracted from patient administrative systems. Age- and sex matched controls will be used for the study investigating missed skin cancer. These controls will be randomly selected from patients that was referred to a skin clinic by paper referral during the same period as the teledermoscopically referred patients were gathered. Algorithms for skin cancer diagnosis will be implemented in the web platform of Dermicus for the studies of introduction of artificial intelligence. Teledermoscopic assessors will be instructed on when and how to use these different tools.
Every week the newly entered data will be checked for completeness, and in the case of missing data, reminders to participating investigators will be send.
Then the data sets are complete, identifiers (such as personal identification number) will be replaced by a code kept secure at a different location than the data set. Data will thereafter be extracted from the data base to perform statistical analysis.
The study is approved by the Swedish Ethical Review Authority and all relevant approvals for data extraction and data storage has been obtained.
Condition | Metastatic Melanoma, skin cancers, Melanoma, Skin Cancer, Malignant Melanoma, skin cancer, melanoma |
---|---|
Treatment | Diagnostic algorithms |
Clinical Study Identifier | NCT05033678 |
Sponsor | Region Skane |
Last Modified on | 22 September 2021 |
,
You have contacted , on
Your message has been sent to the study team at ,
You are contacting
Primary Contact
Additional screening procedures may be conducted by the study team before you can be confirmed eligible to participate.
Learn moreIf you are confirmed eligible after full screening, you will be required to understand and sign the informed consent if you decide to enroll in the study. Once enrolled you may be asked to make scheduled visits over a period of time.
Learn moreComplete your scheduled study participation activities and then you are done. You may receive summary of study results if provided by the sponsor.
Learn moreEvery year hundreds of thousands of volunteers step forward to participate in research. Sign up as a volunteer and receive email notifications when clinical trials are posted in the medical category of interest to you.
Sign up as volunteer
Lorem ipsum dolor sit amet consectetur, adipisicing elit. Ipsa vel nobis alias. Quae eveniet velit voluptate quo doloribus maxime et dicta in sequi, corporis quod. Ea, dolor eius? Dolore, vel!
No annotations made yet
Congrats! You have your own personal workspace now.