Melanoma risk prediction models

Nikolić, Jelena; Lončar-Turukalo, Tatjana; Sladojević, Srđan; Marinković, Mirjana Marković; Janjić, Zlata

doi:10.2298/vsp130722045n

Cited by 5 publications

(5 citation statements)

References 32 publications

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“…We included 42 studies in our TRIPOD rating. Forty studies [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 ] were adopted from the systematic review about risk prediction models for melanoma published in 2020, whereas the remaining two studies [ 60 , 61 ] arose from the updated literature search. Details on the information extracted from the studies are summarized in Table A1 .…”

Section: Resultsmentioning

confidence: 99%

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

et al. 2022

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Transparent and accurate reporting is essential to evaluate the validity and applicability of risk prediction models. Our aim was to evaluate the reporting quality of studies developing and validating risk prediction models for melanoma according to the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis) checklist. We included studies that were identified by a recent systematic review and updated the literature search to ensure that our TRIPOD rating included all relevant studies. Six reviewers assessed compliance with all 37 TRIPOD components for each study using the published “TRIPOD Adherence Assessment Form”. We further examined a potential temporal effect of the reporting quality. Altogether 42 studies were assessed including 35 studies reporting the development of a prediction model and seven studies reporting both development and validation. The median adherence to TRIPOD was 57% (range 29% to 78%). Study components that were least likely to be fully reported were related to model specification, title and abstract. Although the reporting quality has slightly increased over the past 35 years, there is still much room for improvement. Adherence to reporting guidelines such as TRIPOD in the publication of study results must be adopted as a matter of course to achieve a sufficient level of reporting quality necessary to foster the use of the prediction models in applications.

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Section: Resultsmentioning

confidence: 99%

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

et al. 2022

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“…In total, we included 42 studies in our PROBAST rating. Forty studies [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ] were adopted from the most recent systematic review about risk prediction models for melanoma that was published in 2020. The remaining two recent studies [ 62 , 63 ] were identified through the updated literature search.…”

Section: Resultsmentioning

confidence: 99%

“… + - - Stefanaki et al [ 56 ] D 2013 Case-control - ? + - - Nikolic et al [ 49 ] D 2014 Case-control - ? + ?…”

Section: Table A1mentioning

confidence: 99%

Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies

Kaiser

Mathes

Pfahlberg

et al. 2022

Cancers

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Rising incidences of cutaneous melanoma have fueled the development of statistical models that predict individual melanoma risk. Our aim was to assess the validity of published prediction models for incident cutaneous melanoma using a standardized procedure based on PROBAST (Prediction model Risk Of Bias ASsessment Tool). We included studies that were identified by a recent systematic review and updated the literature search to ensure that our PROBAST rating included all relevant studies. Six reviewers assessed the risk of bias (ROB) for each study using the published “PROBAST Assessment Form” that consists of four domains and an overall ROB rating. We further examined a temporal effect regarding changes in overall and domain-specific ROB rating distributions. Altogether, 42 studies were assessed, of which the vast majority (n = 34; 81%) was rated as having high ROB. Only one study was judged as having low ROB. The main reasons for high ROB ratings were the use of hospital controls in case-control studies and the omission of any validation of prediction models. However, our temporal analysis results showed a significant reduction in the number of studies with high ROB for the domain “analysis”. Nevertheless, the evidence base of high-quality studies that can be used to draw conclusions on the prediction of incident cutaneous melanoma is currently much weaker than the high number of studies on this topic would suggest.

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“…Demographic Information of the Participants use, wearing sleeved clothing, being in the shade, skin color, skin assessment in terms of cancer, age, sex and ethnicity were investigated as data elements about melanoma [15]. Also, another study conducted by Nikolic and et al, to identify the most important factors affecting on melanoma in the population showed that factors such as Sex, age, education level, medical history, melanoma in the family (first degree relatives), exposure to ultraviolet rays, use of sunscreens, sunburn, hormonal contraceptive treatment (HCT) and immunosuppressive treatment have been identified as important data elements in this regard [16]. In the study of Green et al, with the aim of investigating the effect of sunscreen cream in dealing with melanoma, elements such as gender, age, observation of skin cancer, reaction to sunlight, color, occupation, number of sunburn and birthmark observation were considered as data elements [17].…”

Section: Discussionmentioning

confidence: 99%

Determining the Content of a Melanoma Prevention and Care Mobile Application for Melanoma Patients: A Survey Study

Ataee,

Shirkhoda,

Nahvijou

et al. 2024

Asian Pac J Cancer Prev

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Objects: Skin cancer is one of the most common cancers and melanoma is the deadliest type of skin cancer. Since the Mobile based health interventions have significant effects in the management of diseases. This study aimed to determining the content of melanoma prevention and care application. Methods: This is a descriptive study that was conducted in three stages. at first, in order to identify the features of the application, search was conducted based on PubMed, Google Scholar ، Scopus databases. In the second step, in order to determine the content of information, articles and guidelines related to melanoma were searched. In the third stage, in order to ensure the validity of researcher-made questionnaire, a survey was conducted by 51 experts based on targeted sampling. The collected data were analyzed. Results: demographic and clinical information and melanoma prevention training was common in 14 reviewed applications; The possibility of sending reminders for patients was less considered. Most of the articles have paid attention to the data elements: age, gender, history of sunburn, skin color and history of cancer, exposure to ultraviolet rays, how to care for the skin. The content of the melanoma prevention and care application consists of three general sections: 1- Demographic, clinical information and melanoma risk factors; 2- Educational needs; 3- Features and capabilities of the application for prevention and care were formed. The results of the expert survey showed that 81% of the section1, 80% of the section2, and 91% of the section3 were approved. Conclusions: Mobile applications has an effective role in disease management and accelerating the provision of health services and reducing the costs of providing services. Melanoma prevention and care application can be an aid in patient education and ultimately better disease management in the field of prevention and care during the current crisis.

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Melanoma risk prediction models

Cited by 5 publications

References 32 publications

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

Reporting Quality of Studies Developing and Validating Melanoma Prediction Models: An Assessment Based on the TRIPOD Statement

Using the Prediction Model Risk of Bias Assessment Tool (PROBAST) to Evaluate Melanoma Prediction Studies

Determining the Content of a Melanoma Prevention and Care Mobile Application for Melanoma Patients: A Survey Study

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