INTRODUCTION AND OBJECTIVES: Compliance with 24hour urine collections for assessing stone risk is important for assigning appropriate preventive therapy. The objectives of this study were to determine factors associated with compliance and the impact of an intervention introduced to improve this outcome.METHODS: In 2015, the patients in our stone clinic in whom 24 hour urine testing was desired were instructed to contact the vendor (Litholink) and given an instructional sheet provided by this company to arrange for the collections. In 2016, a practice change was implemented and clinic staff sent all urine study requests to the vendor by FAX. During this 2-year period, 24-hour urine studies were ordered by the treating physician in 368 adult stoneformers (SF). Demographic data analyzed included age, gender, race, insurance status, partner status, income, and education. Statistical analysis methods included ANOVA, Fisher's exact test, Chi-squared, and t-test analyses. Compliance was determined based on completion of 24-hour urine collections. Data were analyzed for 2015, 2016, and both years combined (2015/2016).RESULTS: Average age of SF was 49.6 years at time of collection. 47.5% of SF were female. The majority were Caucasians (84.2%) and 15.8% were African Americans. Most patients were adequately insured (90.5%) and the majority had domestic partners (61.4%). Compliance increased after the intervention from 46.9% to 65.1% (p<0.001). Adequate insurance was associated with increased compliance for both years combined (58.3% vs 37.15%, p¼0.017). Partner status and older age were associated with increased compliance in 2015 (54.2% vs 32.8% p¼0.006; 52.9 years vs 47.1 years p¼0.014), but following intervention in 2016 were no longer contributing factors.CONCLUSIONS: A simple intervention increased compliance with performance of 24 hour urine testing by 18% and eliminated health disparities (age, partner status). Inadequate insurance status resulted in poor compliance despite this intervention.
INTRODUCTION AND OBJECTIVES:The utility of the Decipher biopsy test in magnetic resonance imaging (MRI)-targeted biopsies from men with favorable-risk prostate cancer has not been evaluated. We sought to assess the association between Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) score, the Decipher score and histologic grade of carcinoma in biopsy tissue among low-to intermediate-risk prostate cancer patients.METHODS: MRI-ultrasound targeted biopsy of regions of interest and concurrent 12-core systematic biopsy was performed on 291 men with Gleason grade group (GG) 1 and 2. We compared Decipher score with PI-RADS scores and biopsy Gleason GG. Subgroup analyses were performed to evaluate patients who underwent radical prostatectomy, and men with Decipher testing from a targeted biopsy core.RESULTS: One hundred three patients with GG1 and GG2 had biopsy Decipher testing. There was no significant difference in the median Decipher scores among the three mpMRI categories. Patients with GG2 vs. GG1 in the setting of PI-RADS 4 and 5 had higher genomic scores (p [ 0.01), but no significant difference was noted in patients with PI-RADS 3. The rate of genomic higher-risk disease on a targeted biopsy from PI-RADS 5 was higher in GG2 (75%) vs. GG1 (11.1%; p [ 0.01) (Figure 1). Among 14 patients who underwent radical prostatectomy, no downgrading was detected.CONCLUSIONS: High-risk genomic classification can be seen across all combinations of PI-RADS categories and Gleason GG1 and GG2, confirming a potential utility for Decipher testing in men with lowto favorable intermediate-risk prostate cancer. The Decipher biopsy genomic test related to Gleason GG independent of PI-RADSv2 score, which may be beneficial when incorporating this genomic marker into a nomogram or a clinical decision-making model.
performed 2x2 table analysis of relationships between the scores for each papillary feature at the level of the papillum and the level of the kidney. Finally, we calculated mean scores for each feature by kidney and used Pearson correlation coefficients to measure relationships between features at the kidney level.RESULTS: 85 patients were included with a total of 361 papillae graded. In table analysis of pitting scores by plaque scores, values deviated powerfully from chance (X 2 ¼63.997, p<0.00001). Increasing plaque scores were associated with decreasing percentage of pitting score zero. The presence of plaque without pitting is more often seen than pitting without plaque. A similar but less pronounced relationship was seen in the analysis of contour loss by pitting scores (X 2 ¼ 35.9461, p¼0.0029). Furthermore, contour loss and plaque scores showed a very strong relationship (X 2 ¼ 57.2033, p<0.00001). Results of the papillum-level analysis are summarized in Figure 2. At the level of the kidney, the strongest relationship exists between mean RP and mean contour scores (r p ¼0.4630, p¼0.0003).CONCLUSIONS: These data support our critical hypothesis that RP and attached calcium stone complex are shed from the papillum leaving behind a pitting defect on the papillary surface, which can then either heal over or, with repeated insult, progress to loss of papillary contour. We believe that understanding this sequence helps link renal physiology to a urologic endpoint.
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