Large language models have demonstrated impressive capabilities, but application to medicine remains unclear. We seek to evaluate the use of ChatGPT on the American Urological Association Self-assessment Study Program as an educational adjunct for urology trainees and practicing physicians. One hundred fifty questions from the 2022 Self-assessment Study Program exam were screened, and those containing visual assets (n=15) were removed. The remaining items were encoded as open ended or multiple choice. ChatGPT's output was coded as correct, incorrect, or indeterminate; if indeterminate, responses were regenerated up to 2 times. Concordance, quality, and accuracy were ascertained by 3 independent researchers and reviewed by 2 physician adjudicators. A new session was started for each entry to avoid crossover learning. ChatGPT was correct on 36/135 (26.7%) open-ended and 38/135 (28.2%) multiple-choice questions. Indeterminate responses were generated in 40 (29.6%) and 4 (3.0%), respectively. Of the correct responses, 24/36 (66.7%) and 36/38 (94.7%) were on initial output, 8 (22.2%) and 1 (2.6%) on second output, and 4 (11.1%) and 1 (2.6%) on final output, respectively. Although regeneration decreased indeterminate responses, proportion of correct responses did not increase. For open-ended and multiple-choice questions, ChatGPT provided consistent justifications for incorrect answers and remained concordant between correct and incorrect answers. ChatGPT previously demonstrated promise on medical licensing exams; however, application to the 2022 Self-assessment Study Program was not demonstrated. Performance improved with multiple-choice over open-ended questions. More importantly were the persistent justifications for incorrect responses-left unchecked, utilization of ChatGPT in medicine may facilitate medical misinformation.

Background: In recent years, the assessment of erectile dysfunction (ED) has experienced a paradigm shift from objective, quantitative methods to subjective, qualitative patient-reported outcomes. Facilitated by this shift is the ongoing debate on questionnaire selection and need for standardization, particularly among sexual medicine specialists. Aim: To review current literature on assessment of erectile function via patient-reported outcomes and discuss the context, advantages, and limitations of currently available questionnaires. Methods: A thorough literature search of erectile function questionnaires developed from 1990 through 2019 was carried out using 3 methods: a search of the MedLine databases; hand-search of peer-reviewed urologic, sexual medicine, and health policy journals; and expert review. The following keywords were used: [assessment of], [inventory], [questionnaire], or [validated measure]; in combination with: [sexual function] or [erectile function]. Measures were stratified into one of the following 3 groups: screening, outcome, or disease-specific. 3 screening measures (International Index of Erectile Function, the Male Sexual Health Questionnaire, and Brief Male Sexual Inventory); 5 outcome measures (Sexual Health Inventory for Men, Erection Hardness Score, Erectile Dysfunction Inventory for Treatment and Satisfaction, and Treatment Satisfaction Scale); and 3 categories of disease-specific measures (cancer, Peyronie's disease, and spinal cord injury) were included. Outcomes: Strengths, limitations, and valid uses of each erectile function questionnaire. Results: There currently exists a wide variety of screening, outcome, and disease-specific measures for ED diagnosis, assessment, and treatment. Rigor of psychometric validation varies greatly across studies. However, depending on purpose of use, all abovementioned questionnaires have merit for use in clinical practice, are nonredundant, and can complement and supplement one another. Clinical Implications: Before choosing a specific measure for ED diagnosis, assessment, or treatment, there must be careful consideration of the questionnaire's psychometric properties, context of validation, and its possible limitations. Strengths & Limitations: The patient reported outcome measures highlighted in this article complement and supplement one another, as each emphasizes a related yet distinct central theme. During selection for use in clinical practice and research studies, special attention needs to be paid to the context, strengths, and weaknesses of each measure. Conclusion: When used conscientiously, patient-reported questionnaires can significantly optimize patient management.

The use of multiparametric magnetic resonance imaging (mpMRI)-derived radiomics has the potential to offer noninvasive, imaging-based biomarkers for the identification of subvisual characteristics indicative of a poor oncologic outcome. The present study, therefore, seeks to develop, validate, and assess the performance of an MRI-derived radiomic model for the prediction of prostate cancer (PC) recurrence following radical prostatectomy (RP) with curative intent. mpMRI imaging was obtained from 251 patients who had undergone an RP for the treatment of localized prostate cancer across two institutions and three surgeons. All patients had a minimum of 2 years follow-up via prostate-specific antigen serum testing. Each prostate mpMRI was individually reviewed, and the prostate was delineated as a single slice (ROI) on axial T2 high-resolution image sets. A total of 924 radiomic features were extracted and tested for stability via intraclass correlation coefficient (ICC) following image normalization via histogram matching. Fourteen important and nonredundant features were found to be predictors of PC recurrence at a mean ± SD of 3.2 ± 2.2 years post-RP. Five-fold, ten-run cross-validation of the model containing these fourteen features yielded an area under the curve (AUC) of 0.89 ± 0.04 in the training set (n = 225). In comparison, the University of California San Fransisco Cancer of the Prostate Risk Assessment score (UCSF-CAPRA) and Memorial Sloan Kettering Cancer Center (MSKCC) Pre-Radical prostatectomy nomograms yielded AUC of 0.66 ± 0.05 and 0.67 ± 0.05, respectively (p < 0.01). When the radiomic model was applied to the test set (n = 26), AUC was 0.78; sensitivity, specificity, positive predictive value, and negative predictive value were 60%, 86%, 52%, and 89%, respectively. Accuracy in predicting PC recurrence was 81%.

The development of precise medical imaging has facilitated the establishment of radiomics, a computer-based method of quantitatively analyzing subvisual imaging characteristics. The present review summarizes the current literature on the use of diagnostic magnetic resonance imaging (MRI)-derived radiomics in prostate cancer (PCa) risk stratification. A stepwise literature search of publications from 2017 to 2022 was performed. Of 218 articles on MRI-derived prostate radiomics, 33 (15.1%) generated models for PCa risk stratification. Prediction of Gleason score (GS), adverse pathology, postsurgical recurrence, and postradiation failure were the primary endpoints in 15 (45.5%), 11 (33.3%), 4 (12.1%), and 3 (9.1%) studies. In predicting GS and adverse pathology, radiomic models differentiated well, with receiver operator characteristic area under the curve (ROC-AUC) values of 0.50–0.92 and 0.60–0.92, respectively. For studies predicting post-treatment recurrence or failure, ROC-AUC for radiomic models ranged from 0.73 to 0.99 in postsurgical and radiation cohorts. Finally, of the 33 studies, 7 (21.2%) included external validation. Overall, most investigations showed good to excellent prediction of GS and adverse pathology with MRI-derived radiomic features. Direct prediction of treatment outcomes, however, is an ongoing investigation. As these studies mature and reach potential for clinical integration, concerted effort to validate these radiomic models must be undertaken.

Rationale: Concern for immune-related adverse events from immunotherapy and radiation therapy are well-documented; however, side effects are mostly mild to moderate. However, high-grade, potentially life-threatening adverse events are increasing. While case reports regarding immunotherapy-related bullous pemphigoid (BP) have been rising, only 1 has described BP following concomitant use of both nivolumab and radiation therapy (RT). For that patient, nivolumab was used for 10 weeks prior to RT and development of PB followed 7 weeks later. This case presents a patient who tolerated nivolumab well for 38 months prior to developing BP less than 2 weeks after completing RT. Patient concerns: We present the case of DH, a 67-year-old gentleman on nivolumab for metastatic renal cell carcinoma to the lung since May of 2017. Following progressing lung nodules, the patient had his nivolumab paused and completed a course of short-beam radiation therapy. After restarting nivolumab post-radiation, the patient presented with itchy rash and blisters on his arm, legs, and trunk. Diagnosis: DH consulted dermatology following development of rash and was diagnosed with bullous dermatosis, likely bullous pemphigoid. Bullous pemphigoid following concomitant nivolumab (OPDIVO), despite prior tolerance and no history of autoimmune disease, was confirmed by biopsy a month later. Interventions: Initial treatment was betamethasone 0.05% cream mixed 1:1 with powder to form paste applied twice daily. Given progressive symptoms and confirmatory biopsy of BP, nivolumab was held and 100 mg doxycycline and 80 mg prednisone daily was prescribed for a week, reduced to 60 mg during the second week. Outcomes: A week following discontinuation of nivolumab and beginning of doxycycline and prednisone, the blistering and rash was almost entirely resolved. Four months later, nivolumab was restarted and the patient continued low-dose tapering of prednisone until December. Since completing prednisone, the patient has shown no recurrence of bullous pemphigoid and has not developed any other immune-related adverse events to nivolumab upon rechallenge. Follow-up through October 2021 demonstrates the patient's sites of disease, both in- and out-field, have remained responsive to treatment. Lessons: Treating physicians should be aware of off-target effects of radiotherapy for oligoprogressive disease, which may include abscopal toxicities and the development of new immune-related adverse effects.