ArticleJMIR cancer2017
Rotterdam Prostate Cancer Risk Calculator: Development and Usability Testing of the Mobile Phone App.
Article in JMIR cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Development and Validation of a Machine Learning-Based Model of Mortality Risk in First-Episode Psychosis.JAMA network open · 2024Article
- Article
- [Systematic or targeted fusion-guided biopsy].Urologie (Heidelberg, Germany) · 2023Review
- Obesity and "obesity-related" cancers: are there body mass index cut-points?International journal of obesity (2005) · 2022Article
- Iterative Development of a Mobile Phone App to Support Community Health Volunteers During Cervical Cancer Screening in Western Kenya: Qualitative Study.JMIR formative research · 2022Article
- Review
- Prostate Cancer Risk Calculator Apps in a Taiwanese Population Cohort: Validation Study.Journal of medical Internet research · 2020Article
- Personalized strategies in population screening for prostate cancer.International journal of cancer · 2020Review
- Current use of telehealth in urology: a review.World journal of urology · 2020Review
- Smartphone technology and its applications in urology: a review of the literature.World journal of urology · 2020Review
- Biomarkers That Differentiate Benign Prostatic Hyperplasia from Prostate Cancer: A Literature Review.Cancer management and research · 2020Review
- Designing a health referral mobile application for high-mobility end users in Indonesia.Heliyon · 2020Article
- The Impact of Mobile Health on Cancer Screening: A Systematic Review.Cancer informatics · 2020Review
- Prediction Medicine: Biomarkers, Risk Calculators and Magnetic Resonance Imaging as Risk Stratification Tools in Prostate Cancer Diagnosis.International journal of molecular sciences · 2019Review
- Spectrophotometric photodynamic diagnosis of prostate cancer cells excreted in voided urine using 5-aminolevulinic acid.Lasers in medical science · 2018Article
- eHealth and mHealth in prostate cancer detection and active surveillance.Translational andrology and urology · 2018Review
- Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App.JMIR formative research · 2017Article
- A narrative review of biparametric MRI (bpMRI) implementation on screening, detection, and the overall accuracy for prostate cancer.Therapeutic advances in urologyReview
- Development and professional validation of an App to support Oral Cancer Screening.Brazilian dental journalArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe use of prostate cancer screening tools that take into account relevant prebiopsy information (ie, risk calculators) is recommended as a way of determining the risk of cancer and the subsequent need for a prostate biopsy. This has the potential to limit prostate cancer overdiagnosis and subsequent overtreatment. mHealth apps are gaining traction in urological practice and are used by both practitioners and patients for a variety of purposes.
objectiveThe impetus of the study was to design, develop, and assess a smartphone app for prostate cancer screening, based on the Rotterdam Prostate Cancer Risk Calculator (RPCRC).
methodsThe results of the Rotterdam arm of the European Randomized Study of Screening for Prostate Cancer (ERSPC) study were used to elaborate several algorithms that allowed the risk of prostate cancer to be estimated. A step-by-step workflow was established to ensure that depending on the available clinical information the most complete risk model of the RPCRC was used. The user interface was designed and then the app was developed as a native app for iOS. The usability of the app was assessed using the Post-Study System Usability Questionnaire (PSSUQ) developed by IBM, in a group of 92 participants comprising urologists, general practitioners, and medical students.
resultsA total of 11 questions were built into the app, and, depending on the answers, one of the different algorithms of the RPCRC could be used to predict the risk of prostate cancer and of clinically significant prostate cancer (Gleason score ≥7 and clinical stage >T2b). The system usefulness, information quality, and interface quality scores were high-92% (27.7/30), 87% (26.2/30), and 89% (13.4/15), respectively. No usability problems were identified.
conclusionsThe RPCRC app is helpful in predicting the risk of prostate cancer and, even more importantly, clinically significant prostate cancer. Its algorithms have been externally validated before and the usability score shows the app's interface is well designed. Further usability testing is required in different populations to verify these results and ensure that it is easy to use, to warrant a broad appeal, and to provide better patient care.
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