JU open plus最新文献

Purpose: To quantify population-specific differences in prostate cancer (PCa) presentation between African American (AA) and White (W) men on MRI using radiomics.

Materials and methods: We identified N = 149 men with PCa who underwent 3T MRI, a confirmatory biopsy and for whom self-reported race was available. Patient studies were partitioned into training (D_Tr) and hold-out test set (D_Te). Three hundred radiomic features quantifying textural patterns were extracted from radiologist delineated PCa regions of interest (ROI) on biparametric MRI. Features with significant differences (P < .05) between clinically significant (csPCa) and insignificant (ciPCa) PCa were identified. Machine learning models were trained separately for AA and W men (C_AA, C_W) on D_Tr to distinguish csPCa and ciPCa. Validation on D_Te was assessed for AUC and compared against a population agnostic model (C_PA) in combination with clinical parameters (age, PSA, Prostate Imaging Reporting and Diagnostic System and tumor volume).

Results: Radiomic features from PCa ROIs on biparametric MRI associated with csPCa were observed to be different in AA compared with W men, especially in the peritumoral region. Population-specific radiomic models outperformed similarly trained C_PA models (AUC = 0.84, 0.57 with C_AA, C_PA; P < .05) in AA men on D_Te. Similar findings were observed for W men (AUC = 0.71, 0.60 with C_W, C_PA; P < .05). Integrating clinical and radiomics further improved the risk stratification for AA men (AUC = 0.90) and W men (AUC = 0.75).

Conclusions: Accounting for population-specific differences in radiomics may enable improved PCa risk stratification at MRI among AA men compared with a population agnostic approach.

For our monthly editorial series, we are featuring highlights of key academic meetings as a potential review topic, and the editorial board is planning additional content that will feature and illustrate key AUA guidelines into presentation quality formats. For this month, we received this excellent write up of a recent collaborative symposium (basically all authors listed except me) and include it with minimal edits below.

Purpose: For patients with muscle-invasive bladder cancer (MIBC), time to cystectomy and receipt of neoadjuvant chemotherapy are associated with improved survival. Travel burden may be an important barrier to timely guideline-concordant treatment.

Materials and methods: We conducted a cross-sectional study of patients in Pennsylvania with a first lifetime cancer diagnosis of MIBC who underwent radical cystectomy at non-federal short-term general hospitals identified in 2010-2016 Pennsylvania Cancer Registry linked to Pennsylvania Healthcare Cost Containment Council (PHC4) inpatient data through 2018. Physician location came from the Centers for Medicare and Medicaid Services.

Results: Mean (standard deviation) drive time to nearest oncologist was 17.1 (11.4) minutes and to nearest urologist was 13.9 (9.2) minutes. A 30-minute increase in drive time to the urologist was associated with a 12.5 percentage point lower likelihood of undergoing cystectomy within 90 days (95% CI: -24.3 to -0.6), with greater effects for more socioeconomically disadvantaged areas (18.7 percentage point lower [95% CI: -33.1 to -4.3]). A 30-minute increase to the oncologist was associated with an 11.9 percentage point lower likelihood of receiving neoadjuvant chemotherapy (95% CI: -23.4 to -0.4). Drive time was not significantly associated with 90-day mortality or readmission.

Conclusions: Drive time to oncologists and urologists is associated with timely receipt of guideline-recommended care for patients with MIBC. Understanding the impact of geographic access on clinical outcomes for patients with cancer who require multispecialty care can inform providers and policymakers in efforts to improve cancer care access and outcomes.