Evaluation of American Urological Association Renal Cell Carcinoma Risk Groups for Chromophobe Renal Cell Carcinoma.

OBJECTIVE: To develop and compare various models for risk stratification in chromophobe renal cell carcinoma (chrRCC). Models have been developed to predict progression-free (PFS) and cancer-specific survival (CSS) following surgery for localized renal cell carcinoma (RCC). Notably, chromophobe RCC (chrRCC) is not included in American Urological Association (AUA) risk stratification, as nuclear grading is not recommended. METHODS: We queried our institutional registry to identify patients managed surgically for unilateral, sporadic, M0, chrRCC from 1970-2012. AUA risk groups were defined using reported criteria, excluding grade, and were compared to the Mayo system incorporating nodal involvement, perinephric/renal sinus fat invasion, and sarcomatoid differentiation. PFS and CSS were estimated using the Kaplan-Meier method. Predictive ability was summarized using c-indexes from Cox proportional hazard regression models. RESULTS: A total of 257 patients were identified. Thirty-nine patients experienced disease progression at a median 30 months (IQR 5.0-84) and 25 died from chrRCC at a median 34 months (IQR 15-79) following surgery. PFS and CSS rates at 10 years after surgery were 84% and 90%, respectively. C-indexes for modified AUA and Mayo risk groups were similar at 0.76 and 0.75, respectively, for PFS, and 0.77 and 0.76, respectively for CSS. CONCLUSION: The modified AUA and Mayo risk stratification systems have similarly robust c-indexes for PFS and CSS in chrRCC. These models can be used to counsel patients based on pathologic features, inform clinicians on appropriate follow-up pathways, and identify patients at risk of disease progression for enrollment in adjuvant systemic therapy trials.

Artificial intelligence model for automated surgical instrument detection and counting: an experimental proof-of-concept study.

BACKGROUND: Retained surgical items (RSI) are preventable events that pose a significant risk to patient safety. Current strategies for preventing RSIs rely heavily on manual instrument counting methods, which are prone to human error. This study evaluates the feasibility and performance of a deep learning-based computer vision model for automated surgical tool detection and counting. METHODS: A novel dataset of 1,004 images containing 13,213 surgical tools across 11 categories was developed. The dataset was split into training, validation, and test sets at a 60:20:20 ratio. An artificial intelligence (AI) model was trained on the dataset, and the model's performance was evaluated using standard object detection metrics, including precision and recall. To simulate a real-world surgical setting, model performance was also evaluated in a dynamic surgical video of instruments being moved in real-time. RESULTS: The model demonstrated high precision (98.5%) and recall (99.9%) in distinguishing surgical tools from the background. It also exhibited excellent performance in differentiating between various surgical tools, with precision ranging from 94.0 to 100% and recall ranging from 97.1 to 100% across 11 tool categories. The model maintained strong performance on a subset of test images containing overlapping tools (precision range: 89.6-100%, and recall range 97.2-98.2%). In a real-time surgical video analysis, the model maintained a correct surgical tool count in all non-transition frames, with a median inference speed of 40.4 frames per second (interquartile range: 4.9). CONCLUSION: This study demonstrates that using a deep learning-based computer vision model for automated surgical tool detection and counting is feasible. The model's high precision and real-time inference capabilities highlight its potential to serve as an AI safeguard to potentially improve patient safety and reduce manual burden on surgical staff. Further validation in clinical settings is warranted.

Evaluating Large Language Model (LLM) Performance on Established Breast Classification Systems.

Medical researchers are increasingly utilizing advanced LLMs like ChatGPT-4 and Gemini to enhance diagnostic processes in the medical field. This research focuses on their ability to comprehend and apply complex medical classification systems for breast conditions, which can significantly aid plastic surgeons in making informed decisions for diagnosis and treatment, ultimately leading to improved patient outcomes. Fifty clinical scenarios were created to evaluate the classification accuracy of each LLM across five established breast-related classification systems. Scores from 0 to 2 were assigned to LLM responses to denote incorrect, partially correct, or completely correct classifications. Descriptive statistics were employed to compare the performances of ChatGPT-4 and Gemini. Gemini exhibited superior overall performance, achieving 98% accuracy compared to ChatGPT-4's 71%. While both models performed well in the Baker classification for capsular contracture and UTSW classification for gynecomastia, Gemini consistently outperformed ChatGPT-4 in other systems, such as the Fischer Grade Classification for gender-affirming mastectomy, Kajava Classification for ectopic breast tissue, and Regnault Classification for breast ptosis. With further development, integrating LLMs into plastic surgery practice will likely enhance diagnostic support and decision making.

Perioperative nivolumab versus observation in patients with renal cell carcinoma undergoing nephrectomy (PROSPER ECOG-ACRIN EA8143): an open-label, randomised, phase 3 study.

BACKGROUND: The standard of care for patients with intermediate-to-high risk renal cell carcinoma is partial or radical nephrectomy followed by surveillance. We aimed to investigate use of nivolumab before nephrectomy followed by adjuvant nivolumab in patients with high-risk renal cell carcinoma to determine recurrence-free survival compared with surgery only. METHODS: In this open-label, randomised, phase 3 trial (PROSPER EA8143), patients were recruited from 183 community and academic sites across the USA and Canada. Eligible patients were aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0-1, with previously untreated clinical stage T2 or greater or Tany N+ renal cell carcinoma of clear cell or non-clear cell histology planned for partial or radical nephrectomy. Selected patients with oligometastatic disease, who were disease free at other disease sites within 12 weeks of surgery, were eligible for inclusion. We randomly assigned (1:1) patients using permuted blocks (block size of 4) within stratum (clinical TNM stage) to either nivolumab plus surgery, or surgery only followed by surveillance. In the nivolumab group, nivolumab 480 mg was administered before surgery, followed by nine adjuvant doses. The primary endpoint was investigator-reviewed recurrence-free survival in patients with renal cell carcinoma assessed in all randomly assigned patients regardless of histology. Safety was assessed in all randomly assigned patients who started the assigned protocol treatment. This trial is registered with ClinicalTrials.gov, NCT03055013, and is closed to accrual. FINDINGS: Between Feb 2, 2017, and June 2, 2021, 819 patients were randomly assigned to nivolumab plus surgery (404 [49%]) or surgery only (415 [51%]). 366 (91%) of 404 patients assigned to nivolumab plus surgery and 387 (93%) of 415 patients assigned to surgery only group started treatment. Median age was 61 years (IQR 53-69), 248 (30%) of 819 patients were female, 571 (70%) were male, 672 (88%) were White, and 77 (10%) were Hispanic or Latino. The Data and Safety Monitoring Committee stopped the trial at a planned interim analysis (March 25, 2022) because of futility. Median follow-up was 30·4 months (IQR 21·5-42·4) in the nivolumab group and 30·1 months (21·9-41·8) in the surgery only group. 381 (94%) of 404 patients in the nivolumab plus surgery group and 399 (96%) of 415 in the surgery only group had renal cell carcinoma and were included in the recurrence-free survival analysis. As of data cutoff (May 24, 2023), recurrence-free survival was not significantly different between nivolumab (125 [33%] of 381 had recurrence-free survival events) versus surgery only (133 [33%] of 399; hazard ratio 0·94 [95% CI 0·74-1·21]; one-sided p=0·32). The most common treatment-related grade 3-4 adverse events were elevated lipase (17 [5%] of 366 patients in the nivolumab plus surgery group vs none in the surgery only group), anaemia (seven [2%] vs nine [2%]), increased alanine aminotransferase (ten [3%] vs one [<1%]), abdominal pain (four [1%] vs six [2%]), and increased serum amylase (nine [2%] vs none). 177 (48%) patients in the nivolumab plus surgery group and 93 (24%) in the surgery only group had grade 3-5 adverse events due to any cause, the most common of which were anaemia (23 [6%] vs 19 [5%]), hypertension (27 [7%] vs nine [2%]), and elevated lipase (18 [5%] vs six [2%]). 48 (12%) of 404 patients in the nivolumab group and 40 (10%) of 415 in the surgery only group died, of which eight (2%) and three (1%), respectively, were determined to be treatment-related. INTERPRETATION: Perioperative nivolumab before nephrectomy followed by adjuvant nivolumab did not improve recurrence-free survival versus surgery only followed by surveillance in patients with high-risk renal cell carcinoma. FUNDING: US National Institutes of Health National Cancer Institute and Bristol Myers Squibb.

End-Stage Kidney Disease After Partial and Radical Nephrectomy Among Patients With Severe Chronic Kidney Disease.

PURPOSE: AUA guidelines prioritize nephron sparing in patients with preexisting chronic kidney disease (CKD). However, few studies analyze long-term renal function in patients with preoperative severe CKD who undergo extirpative renal surgery. Herein, we compare the hazard of progression to end-stage kidney disease (ESKD) following partial nephrectomy (PN) and radical nephrectomy (RN) among patients with preoperative severe CKD. MATERIALS AND METHODS: Patients with stage 4 CKD who underwent PN or RN from 1970 to 2018 were identified. A multivariable Fine-Gray subdistribution hazard model was employed to assess associations with progression to ESKD accounting for the competing risk of death. RESULTS: A total of 186 patients with stage 4 CKD underwent PN (n = 71; 38%) or RN (n = 115; 62%) for renal neoplasms with median follow-up of 6.9 years (interquartile range 3.8-14.1). On multivariable analyses adjusting for competing risk of death, the subdistribution hazard ratio (SHR) for older age at surgery (SHR for 5-year increase 0.81; 95% CI 0.73-0.91; P < .001) and higher preoperative estimated glomerular filtration rate (SHR for 5-unit increase 0.63; 95% CI 0.47-0.84; P = .002) was associated with lower hazard of progression to ESKD. There was no significant difference in hazard of ESKD between PN and RN (SHR 0.82; 95% CI 0.50-1.33; P = .4). CONCLUSIONS: Among patients with preoperative severe CKD, higher preoperative estimated glomerular filtration rate was associated with lower hazard of progression to ESKD after extirpative surgery for renal neoplasms. We did not observe a significant difference in overall hazard for developing ESKD between PN and RN.

Incidence and predictors of ipsilateral local recurrence following partial nephrectomy.

PURPOSE: Ipsilateral local recurrence (LR) after partial nephrectomy (PN) for renal cell carcinoma (RCC) may result from a metachronous tumor or PN bed recurrence. To date, literature has predominantly reported ipsilateral LRs collectively, although the pathophysiology and prognostic implications of these event may be distinct. We sought to assess variables associated with LR and evaluated associations of LR with metastasis and death from RCC. MATERIALS AND METHODS: We identified adults undergoing PN for unilateral, sporadic, localized RCC from 2000 to 2019 using a prospectively maintained, single institution registry. LR was defined as new, enhancing tumor within/near the PN bed on MRI/CT. Cox proportional hazards models were used to create a preoperative risk score for LR and to examine the association of LR with metastasis and CSS following PN among patients with clear cell RCC. RESULTS: In a cohort of 2,164 PNs, 106 true LRs were identified, for a 10-year incidence of 6.2%. A preoperative risk score for LR based on age, symptoms, solitary kidney, complex tumor necessitating open partial nephrectomy, and cT stage was created (c-index = 0.73). Postoperatively, positive margins, pT stage, and clear cell subtype were associated with LR. Notably, 21% (23/106) of patients with LR presented with synchronous metastases. Following LR, 5-year metastasis-free and cancer-specific survival were 64% and 71%, respectively. LR remained associated with metastasis (HR 6.25; P < 0.001) and death from RCC (HR 1.93; P = 0.03) on multivariable analysis. CONCLUSIONS: We developed a preoperative risk score to identify patients at risk for LR following PN. LR was an independent risk factor for metastasis and death from RCC. Further study is warranted to determine whether treatment of LR improves oncologic outcomes.

High-risk human papilloma virus status & outcomes for penile squamous cell carcinoma: A single institution experience.

OBJECTIVES: There is a paucity of data on North American cohorts of patients with penile squamous cell carcinoma (pSCC). Herein, we aimed to assess the sensitivity of various modalities to identify human papillomavirus (HPV) status, determine the prevalence of high-risk HPV-positivity, and evaluate the prognostic impact of relevant clinicopathologic variables. METHODS: Patients with pSCC (n = 121) consecutively treated with partial/total penectomy (2000-2022) at a single institution were included. HPV status (based on immunohistochemistry [IHC], in situ hybridization [ISH], and panviral metagenomic sequencing [PMS]), histologic features, and outcomes were reviewed. Outcome events included death due to disease and progression. RESULTS: The majority of patients were white (105/121, 86.8%). Thirty-seven (30.6%) were high-risk HPV-positive, and morphologic evaluation had a sensitivity of 97.3% (95% confidence interval [CI], 86.2-99.5) for predicting high-risk HPV status compared to IHC/ISH/PMS. Disease progression was more common among high-risk HPV-negative compared to high-risk HPV-positive patients (HR 2.74, CI 1.12-8.23, P = 0.03). Moreover, among high-risk HPV-negative patients, those with moderate-poorly differentiated tumors had increased disease-specific mortality (32.6%, CI 17.1-48.1) compared to those with well-differentiated tumors (0%). Among high-risk HPV-positive patients, those with basaloid morphology had lower disease-specific mortality (0% vs 14.4%, CI 0.0-33.1). CONCLUSIONS: We demonstrate high-risk HPV-positivity in approximately one-third of patients with pSCC. Morphologic evaluation alone had a high sensitivity in correctly determining HPV status. Our results suggest that high-risk HPV status and morphologic features (differentiation in high-risk HPV-negative, and basaloid subtype in high-risk HPV-positive pSCC) may have prognostic value.

Artificial Intelligence in Postoperative Care: Assessing Large Language Models for Patient Recommendations in Plastic Surgery.

Since their release, the medical community has been actively exploring large language models' (LLMs) capabilities, which show promise in providing accurate medical knowledge. One potential application is as a patient resource. This study analyzes and compares the ability of the currently available LLMs, ChatGPT-3.5, GPT-4, and Gemini, to provide postoperative care recommendations to plastic surgery patients. We presented each model with 32 questions addressing common patient concerns after surgical cosmetic procedures and evaluated the medical accuracy, readability, understandability, and actionability of the models' responses. The three LLMs provided equally accurate information, with GPT-3.5 averaging the highest on the Likert scale (LS) (4.18 ± 0.93) (p = 0.849), while Gemini provided significantly more readable (p = 0.001) and understandable responses (p = 0.014; p = 0.001). There was no difference in the actionability of the models' responses (p = 0.830). Although LLMs have shown their potential as adjunctive tools in postoperative patient care, further refinement and research are imperative to enable their evolution into comprehensive standalone resources.

Comparison of a modified staging system with 8th edition AJCC criteria in a North American cohort of pT2/pT3 HPV-negative penile squamous cell carcinoma.

The staging for pT2/pT3 penile squamous cell carcinoma (pSCC) has undergone major changes. Some authors proposed criteria wherein the distinction between pT2/pT3 was made using the same histopathological variables that are currently utilized to differentiate pT1a/pT1b. In this single-institution, North American study, we focused on (HPV-negative) pT2/3 pSCCs (i.e., tumors invading corpus spongiosum/corpus cavernosum), and compared the prognostic ability of the following systems: (i) AJCC (8th edition) criteria; (ii) modified staging criteria proposed by Sali et al. (Am J Surg Pathol. 2020; 44:1112-7). In the proposed system, pT2 tumors were defined as those devoid of lymphovascular invasion (LVI) or perineural invasion (PNI), and were not poorly differentiated; whereas pT3 showed one or more of the following: LVI, PNI, and/or grade 3. 48 pT2/pT3 cases were included (AJCC, pT2: 27 and pT3: 21; Proposed, pT2: 22 and pT3: 26). The disease-free survival (DFS) and progression-free survival (PFS) did not differ between pT2 and pT3, following the current AJCC definitions (p = 0.19 and p = 0.10, respectively). When the pT2/3 stages were reconstructed using the modified criteria, however, a statistically significant difference was present in both DFS and PFS between pT2 and pT3 (p = 0.004 and p = 0.003, respectively). The proposed staging system has the potential to improve the prognostication of pT2/pT3 tumors in pSCC. Each of these histopathologic variables has been shown to have a significant association with outcomes in pSCC, which is an advantage. Further studies are needed to demonstrate the utility of this modified staging system in patient populations from other geographic regions.

Artificial Intelligence Algorithms for Expert Identification in Medical Domains: A Scoping Review.

With abundant information and interconnectedness among people, identifying knowledgeable individuals in specific domains has become crucial for organizations. Artificial intelligence (AI) algorithms have been employed to evaluate the knowledge and locate experts in specific areas, alleviating the manual burden of expert profiling and identification. However, there is a limited body of research exploring the application of AI algorithms for expert finding in the medical and biomedical fields. This study aims to conduct a scoping review of existing literature on utilizing AI algorithms for expert identification in medical domains. We systematically searched five platforms using a customized search string, and 21 studies were identified through other sources. The search spanned studies up to 2023, and study eligibility and selection adhered to the PRISMA 2020 statement. A total of 571 studies were assessed from the search. Out of these, we included six studies conducted between 2014 and 2020 that met our review criteria. Four studies used a machine learning algorithm as their model, while two utilized natural language processing. One study combined both approaches. All six studies demonstrated significant success in expert retrieval compared to baseline algorithms, as measured by various scoring metrics. AI enhances expert finding accuracy and effectiveness. However, more work is needed in intelligent medical expert retrieval.

Comparative Analysis of Artificial Intelligence Virtual Assistant and Large Language Models in Post-Operative Care.

In postoperative care, patient education and follow-up are pivotal for enhancing the quality of care and satisfaction. Artificial intelligence virtual assistants (AIVA) and large language models (LLMs) like Google BARD and ChatGPT-4 offer avenues for addressing patient queries using natural language processing (NLP) techniques. However, the accuracy and appropriateness of the information vary across these platforms, necessitating a comparative study to evaluate their efficacy in this domain. We conducted a study comparing AIVA (using Google Dialogflow) with ChatGPT-4 and Google BARD, assessing the accuracy, knowledge gap, and response appropriateness. AIVA demonstrated superior performance, with significantly higher accuracy (mean: 0.9) and lower knowledge gap (mean: 0.1) compared to BARD and ChatGPT-4. Additionally, AIVA's responses received higher Likert scores for appropriateness. Our findings suggest that specialized AI tools like AIVA are more effective in delivering precise and contextually relevant information for postoperative care compared to general-purpose LLMs. While ChatGPT-4 shows promise, its performance varies, particularly in verbal interactions. This underscores the importance of tailored AI solutions in healthcare, where accuracy and clarity are paramount. Our study highlights the necessity for further research and the development of customized AI solutions to address specific medical contexts and improve patient outcomes.

Mayo Clinic Validation of the AUA Risk Groups for Localized Renal Cell Carcinoma.

PURPOSE: The AUA guidelines introduced a new risk group stratification system based primarily on tumor stage and grade to guide surveillance for patients treated surgically for localized renal cell carcinoma (RCC). We sought to evaluate the predictive ability of these risk groups using progression-free survival (PFS) and cancer-specific survival (CSS), and to compare their performance to that of our published institutional risk models. MATERIALS AND METHODS: We queried our Nephrectomy Registry to identify adults treated with radical or partial nephrectomy for unilateral, M0, clear cell RCC, or papillary RCC from 1980 to 2012. The AUA stratification does not apply to other RCC subtypes as tumor grading for other RCC, such as chromophobe, is not routinely performed. PFS and CSS were estimated using the Kaplan-Meier method. Predictive abilities were evaluated using C indexes from Cox proportional hazards regression models. RESULTS: A total of 3191 patients with clear cell RCC and 633 patients with papillary RCC were included. For patients with clear cell RCC, C indexes for the AUA risk groups and our model were 0.780 and 0.815, respectively (P < .001) for PFS, and 0.811 and 0.857, respectively (P < .001), for CSS. For patients with papillary RCC, C indexes for the AUA risk groups and our model were 0.775 and 0.751, respectively (P = .002) for PFS, and 0.830 and 0.803, respectively (P = .2) for CSS. CONCLUSIONS: The AUA stratification is a parsimonious system for categorizing RCC that provides C indexes of about 0.80 for PFS and CSS following surgery for localized clear cell and papillary RCC.

Evaluation of tumor response to immune checkpoint inhibitors by a 3D immunotumoroid model.

Background: Only 20 percent of renal and bladder cancer patients will show a significant response to immune checkpoint inhibitor (ICI) therapy, and no test currently available accurately predicts ICI response. Methods: We developed an "immunotumoroid" cell model system that recapitulates the tumor, its microenvironment, and necessary immune system components in patient-derived spheroids to enable ex vivo assessment of tumor response to ICI therapy. Immunotumoroids were developed from surgically resected renal cell carcinomas and bladder carcinomas selected for high tumor-infiltrating lymphocytes (TILs) and survived more than a month without media exchange. Immunohistochemistry was used to detect immune and non-immune cells in cryopreserved source tumors and the resulting immunotumoroids. Immunotumoroid response to ICIs (nivolumab, pembrolizumab, and durvalumab) and chemotherapy (cisplatin, gemcitabine, and paclitaxel) was monitored in real-time with Cytotox Red staining in an Incucyte device, and the immunotumoroid response was compared to retrospective clinical drug responses. Results: Six of the 13 cases tested grew viable immunotumoroid models, with failed cases attributed to extensive tumor tissue necrosis or excess lymphocytes preventing spheroid formation. One successfully cultured case was excluded from the study due to low TIL infiltration (<5%) in the primary tumor sample. The five remaining models contained immune cells (CD4+ and CD8+ T cells, and macrophages), non-immune cells (fibroblasts), and tumor cells. Chemotherapy and ICI drugs were tested in immunotumoroids from 5 cases and compared to clinical outcomes where data was available. Four/five models showed cell killing in response to chemotherapy and two/five showed sensitivity to ICI. In three cases, the immunotumoroid model accurately predicted the patient's clinical response or non-response to ICIs or chemotherapy. Conclusion: Our immunotumoroid model replicated the multicellular nature of the tumor microenvironment sufficiently for preclinical ICI screening. This model could enable valuable insights into the complex interactions between cancer cells, the immune system, and the microenvironment. This is a feasibility study on a small number of cases, and additional studies with larger case numbers are required including correlation with clinical response.

Single nucleotide polymorphism (SNP) chromosomal microarray as a diagnostic tool for mucinous tubular and spindle cell carcinoma: A validation study.

Mucinous tubular and spindle cell carcinoma (MTSCC) shows significant overlap with papillary renal cell carcinoma (PRCC), and harbor recurrent copy-number alterations (CNA). We evaluated 16 RCC with features suggestive of MTSCC using chromosomal microarrays. The cohort was comprised of 8 females and males, each, with an age range of 33-79 years (median, 59), and a tumor size range of 3.4-15.5 cm (median, 5.0). Half the tumors were high-grade (8/16, 50%) with features such as necrosis, marked cytologic atypia, and sarcomatoid differentiation, and 5/16 (31%) were high stage (≥pT3a). Three (of 16, 19%) cases had a predominant (>95%) spindle cell component, whereas 5/16 (31%) were composed of a predominant (>95%) epithelial component. Most cases (12/16, 75%) exhibited a myxoid background and/or extravasated mucin, at least focally. Twelve (of 16, 75%) cases demonstrated CNA diagnostic of MTSCC (losses of chromosomes 1, 4, 6, 8, 9, 13, 14, 15, and 22). In addition, 2 high-grade tumors showed loss of CDKN2A/B, and gain of 1q, respectively, both of which are associated with aggressive behavior. Three (of 16, 19%) cases, demonstrated nonspecific CNA, and did not meet diagnostic criteria for established RCC subtypes. One (of 16, 6%) low-grade epithelial predominant tumor (biopsy) demonstrated characteristic gains of 7, 17, and loss of Y, diagnostic of PRCC. MTSCC can be a morphologically heterogenous tumor. Our study validates the detection of characteristic chromosomal CNA for diagnostic use that may be useful in challenging cases with unusual spindle cell or epithelial predominant features, as well as in high-grade tumors.

Genomic attributes of prostate cancer across primary and metastatic noncastrate and castrate resistant disease states: a next generation sequencing study of 183 patients.

Primary prostatic adenocarcinoma (pPC) undergoes genomic evolution secondary to therapy-related selection pressures as it transitions to metastatic noncastrate (mNC-PC) and castrate resistant (mCR-PC) disease. Next generation sequencing results were evaluated for pPC (n = 97), locally advanced disease (involving urinary bladder/rectum, n = 12), mNC-PC (n = 21), and mCR-PC (n = 54). We identified enrichment of TP53 alterations in high-grade pPC, TP53/RB1 alterations in HGNE disease, and AR alterations in metastatic and castrate resistant disease. Actionable alterations (MSI-H phenotype and HRR genes) were identified in approximately a fifth of all cases. These results help elucidate the landscape of genomic alterations across the clinical spectrum of prostate cancer.

Predictors of Excellent Urology Residents at the Time of the Urology Match.

OBJECTIVE: To update our experience and report on features predictive of high-quality urology residents at the time of the urology match, because data predicting which medical students will mature into excellent urology residents are sparse. METHODS: We reviewed our experience with 84 urology residents who graduated from 2006 to 2023. Residents were independently scored 1-10 based on overall quality by the current and former Program Director. Discrepant scoring by >2 was resolved by an independent review. Associations of features from the medical student application with an excellent score (defined as 8-10) were evaluated with logistic regression. RESULTS: Discrepant scoring >2 was noted in only 5 (6%) residents. Among the 84 residents, the median overall score was 7 (range 1-10) and 36 (43%) residents had an excellent score of 8-10. Univariably, higher USMLE step II score (P = .03), election to alpha omega alpha (P = .004), no negative interview comments (P = .002), honors in OB/Gyn (P = .048) and psychiatry clerkships (P = .04), and honors in all core clinical clerkships (P < .001) were significantly associated with an excellent score. In a multivariable model, no negative interview comments (P = .003) and honors in all core clinical clerkships (P = .001) were independently associated with an excellent score (c-index 0.76). There were several notable features (sex, letters of recommendation, USMLE step I, externship at our institution, surgery clerkship grade, and rank list) that were not significantly associated with excellent residents. CONCLUSION: We demonstrate features associated with excellent urology residents, most notably no negative interview comments and an honors grade in all core clinical clerkships.

Comparative cost-effectiveness of contemporary treatment strategies for stage IIA seminoma.

BACKGROUND: The Surgery in Early Metastatic Seminoma (SEMS) trial examined retroperitoneal lymph node dissection as first-line treatment for patients with isolated 1-3 cm retroperitoneal lymphadenopathy. To date, the standard of care for these patients has been either chemotherapy or radiotherapy. Herein, we evaluated the relative cost-effectiveness of these management strategies. METHODS: A microsimulation model assessed the cost-effectiveness of retroperitoneal lymph node dissection, chemotherapy, and radiotherapy for stage IIA seminoma. Sensitivity analyses were performed to evaluate model robustness. Retroperitoneal lymph node dissection recurrence probabilities were obtained from the SEMS trial. All other probability and utility values were obtained from published literature. Primary outcomes included costs from a commercial insurer's perspective, effectiveness (quality adjusted life-years [QALYs]), and incremental cost-effectiveness ratios using a willingness-to-pay threshold of $100 000/QALY. RESULTS: At a lifetime horizon, the mean costs per patient for retroperitoneal lymph node dissection, radiotherapy, and chemotherapy were $58 469, $98 783, and $104 096, and the mean QALYs were 40.61, 40.70, and 39.15, respectively. Retroperitoneal lymph node dissection was found to be the most cost-effective approach because of high costs and accrued disutility of chronic toxicities associated with radiotherapy (cost-effectiveness ratios = $433 845/QALY) and chemotherapy (dominated). On 1-way sensitivity analyses, retroperitoneal lymph node dissection was no longer cost-effective if the probabilities of infertility and cardiovascular toxicity after radiotherapy were less than 13% and 16%, respectively, or if the 2-year probability of progression after retroperitoneal lymph node dissection was more than 26%. CONCLUSIONS: Retroperitoneal lymph node dissection was the most cost-effective treatment approach for stage IIA seminoma. These findings support clinical guideline consideration of including retroperitoneal lymph node dissection as a treatment option for well-selected patients with stage IIA seminoma.