Observational studyJournal of the American Academy of Dermatology2018
Estimating the cost of skin cancer detection by dermatology providers in a large health care system.
Observational study in Journal of the American Academy of Dermatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Comparative Analysis of Diagnostic Techniques for Melanoma Detection: A Systematic Review of Diagnostic Test Accuracy Studies and Meta-Analysis.Frontiers in medicine · 2021Pooled it
- An Intelligent System for Monitoring Skin Diseases.Sensors (Basel, Switzerland) · 2018Trial
- AI-Assisted Basal Cell Carcinoma Analysis in Line-Field Confocal OCT: Exploring Diagnostic Metrics.Journal of biophotonics · 2026Article
- Clinical and Dermoscopic Determinants of Surgical Decision-Making in Skin Cancer Screening: A Retrospective Analysis.Medicina (Kaunas, Lithuania) · 2026Article
- Emerging Artificial Intelligence Models for Estimating Breslow Thickness from Dermoscopic Images.Biomedicines · 2026Review
- Ex Vivo Assessment of Keratinocytic Carcinomas Using a Fast Mid-Infrared Probe.Journal of biophotonics · 2026Article
- Line-Field Confocal Optical Coherence Tomography for the Diagnosis of Skin Tumors: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2024Review
- Anastrozole for the prevention of breast cancer in high-risk postmenopausal women: cost-effectiveness analysis in the UK and the USA.BMC health services research · 2024Article
- AI-based skin cancer detection: the balance between access and overutilization.NPJ digital medicine · 2023Article
- Patterns and cost of care according to keratinocyte cancer risk stratification in a volunteer population screening clinic: Real-world data from the TRoPICS study.The Australasian journal of dermatology · 2023Article
- An artificial intelligence based app for skin cancer detection evaluated in a population based setting.NPJ digital medicine · 2023Article
- A Deep CNN Transformer Hybrid Model for Skin Lesion Classification of Dermoscopic Images Using Focal Loss.Diagnostics (Basel, Switzerland) · 2022Article
- Augmenting pigmented lesion assay results with the three-point dermoscopy checklist to improve pigmented lesion triage.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2022Article
- From P4 medicine to P5 medicine: transitional times for a more human-centric approach to AI-based tools for hospitals of tomorrow.Open research Europe · 2022Article
- Second Primary Malignancies in Patients With Melanoma Subtypes: Analysis of 120,299 Patients From the SEER Database (2000-2016).Frontiers in oncology · 2022Article
- Low accuracy of self-reported family history of melanoma in high-risk patients.Familial cancer · 2021Review
- Melanoma Biomarkers and Their Potential Application for In Vivo Diagnostic Imaging Modalities.International journal of molecular sciences · 2020Review
- Analyzing Controversies in Management and Surveillance of Early-Stage Melanoma.Oncology and therapy · 2020Article
- Identification of skin cancer screening visits by using claims data.Journal of the American Academy of Dermatology · 2020Article
- Skin cancer detection by deep learning and sound analysis algorithms: A prospective clinical study of an elementary dermoscope.EBioMedicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundData on the cost and efficiency of skin cancer detection through total body skin examination are scarce.
objectiveTo determine the number needed to screen (NNS) and biopsy (NNB) and cost per skin cancer diagnosed in a large dermatology practice in patients undergoing total body skin examination.
methodsThis is a retrospective observational study.
resultsDuring 2011-2015, a total of 20,270 patients underwent 33,647 visits for total body skin examination; 9956 lesion biopsies were performed yielding 2763 skin cancers, including 155 melanomas. The NNS to detect 1 skin cancer was 12.2 (95% confidence interval [CI] 11.7-12.6) and 1 melanoma was 215 (95% CI 185-252). The NNB to detect 1 skin cancer was 3.0 (95% CI 2.9-3.1) and 1 melanoma was 27.8 (95% CI 23.3-33.3). In a multivariable model for NNS, age and personal history of melanoma were significant factors. Age switched from a protective factor to a risk factor at 51 years of age. The estimated cost per melanoma detected was $32,594 (95% CI $27,326-$37,475). LIMITATIONS: Data are from a single health care system and based on physician coding.
conclusionMelanoma detection through total body skin examination is most efficient in patients ≥50 years of age and those with a personal history of melanoma. Our findings will be helpful in modeling the cost effectiveness of melanoma screening by dermatologists.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.