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In this study, various health care professionals will follow an E-learning module in which BCC detection on OCT is explained. Thereafter, the participants will test their skill by assessing OCT-scans. Their performance will be monitored using cumulative-sum analysis. After completion, newly trained OCT assessors will test their diagnostic accuracy for BCC detection on OCT in a exploratory study. The trainability, amount of required training and diagnostic accuracy will be compared between dermatologist and non-dermatologists.
Accurate detection of BCC on OCT requires substantial training and for future implementation of OCT, many OCT assessors need to be trained. Cumulative-sum analysis (CUSUM-analysis) can be used to objectify the competence of OCT assessors and has been previously used to monitor the competence of OCT assessors. Hence CUSUM-analysis may be valuable in training new assessors. A consensus statement from 2021 states that OCT scans should be acquired and interpreted by dermatologists. But this consensus is challenged by various studies in which OCT assessors were non-dermatologists. All non-dermatologist OCT assessors achieved high diagnostic accuracy. In addition, as diagnosis, treatment and follow-up of BCC patients constitute a substantial proportion of the workload of dermatologists, the question arises whether the acquisition of OCT scans and the subsequent assessment thereof could be outsourced to non-dermatologists. This could reduce the workload of the dermatologist, shorten waiting lists and potentially reduce costs.
In an E-learning dermatologists and non-dermatologists will learn about BCC features on OCT as described by Hussain et al. In this E-learning they will learn how to systematically examine an OCT-scan and detect BCC features. They will also be informed on common pitfalls in BCC detection. Thereafter they will start a CUSUM-module containing 400 OCT-scans (50% BCC vs. 50% non-BCC) to monitor cumulative successes and failures in diagnostic assessments. The competence of OCT assessors can be objectified using preset acceptable (16%) and unacceptable error rates (25%). The error rate is defined as the sum of false negative and false positive diagnoses divided by the total number of assessed OCT scans. For all OCT scans, the histologically verified diagnosis based on punch or excision biopsy is available. The OCT assessor will practice until an acceptable performance rate is achieved and maintained (over 50 scans). A secondary objective will be to explore the diagnostic accuracy in terms of sensitivity and specificity. Once an acceptable performance rate is achieved and maintained, assessors will assess a new cohort of 100 OCT scans (50% BCC and 50% non-BCC). Their level of suspicion for BCC will be expressed on a 5-point Likert-Scale. Diagnostic parameters will be compared between dermatologists and non-dermatologists.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Dermatologists | Dermatologists who have no experience with OCT. |
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| Residents | Residents who have no experience with OCT |
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| Medical students | Medical students who have no experience with OCT |
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| Nurses | Nurses who have no experience with OCT |
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| Research physicians |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| E-learning | Other | The E-learning is under development at the department of Dermatology from MUMC+. |
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| Measure | Description | Time Frame |
|---|---|---|
| Achieving and maintaining an acceptable error rate (16%) for BCC detection on OCT | Measured before december 31st 2023 | |
| Number of practice scans needed in order to achieve an acceptable error rate | Measured before december 31st 2023 | |
| Median time that dermatologists and non-dermatologists need to assess OCT scans | Measured before december 31st 2023 | |
| Diagnostic accuracy of newly trained dermatologists and non-dermatologists expressed as sensitivity, specificity, PPV, NPV and DOR. | Measured before december 31st 2023 |
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Inclusion Criteria:
Exclusion Criteria:
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The study population will consist of various health care provides; dermatologists, residents/clinical researchers, nurses and medical students. We aim to include at least 5 participants per category of healthcare providers.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Maastricht UMC+ | Maastricht | Limburg | 6229HX | Netherlands |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40579737 | Derived | Wolswijk T, Nelemans PJ, Adan F, van Leersum F, Kreiter D, Adams T, van Dorsten S, Mosterd K. Cumulative Sum Analysis-Integrated E-Learning for Differentiation Between Basal Cell Carcinoma and Non-Basal Cell Carcinoma on Optical Coherence Tomography: An Observational Cohort Study. Int J Dermatol. 2025 Oct;64(10):1870-1878. doi: 10.1111/ijd.17918. Epub 2025 Jun 27. |
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To be decided
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| ID | Term |
|---|---|
| D002280 | Carcinoma, Basal Cell |
| ID | Term |
|---|---|
| D002277 | Carcinoma |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009370 | Neoplasms by Histologic Type |
| D009369 | Neoplasms |
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| D018295 |
| Neoplasms, Basal Cell |