Provider- and Facility-Level Variation in Precancerous Cervical Biopsy Diagnoses.

OBJECTIVES: Reproducibility of cervical biopsy diagnoses is low and may vary based on where the diagnostic test is performed and by whom. Our objective was to measure multilevel variation in diagnoses across colposcopists, pathologists, and laboratory facilities. METHODS: We cross-sectionally examined variation in cervical biopsy diagnoses within the 5 sites of the Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR I) consortium within levels defined by colposcopists, pathologists, and laboratory facilities. Patients aged 18 to 65 years with a colposcopy with biopsy performed were included, with diagnoses categorized as normal, cervical intraepithelial neoplasia grade 1 (CIN1), grade 2 (CIN2), and grade 3 (CIN3). Using Markov Chain Monte-Carlo methods, we fit mixed-effects logistic regression models for biopsy diagnoses and presented median odds ratios (MORs), which reflect the variability within each level. Median odds ratios can be interpreted as the average increased odds a patient would have for a given outcome (e.g., CIN2 or CIN3 vs normal or CIN1) when switching to a provider with higher odds of diagnosing that outcome. The MOR is always 1 or greater, and a value of 1 indicates no variation in outcome for that level, with higher values indicating greater variation. RESULTS: A total of 130,110 patients were included who received care across 82 laboratory facilities, 2,620 colposcopists, and 489 pathologists. Substantial variation in biopsy diagnoses was found at each level, with the most occurring between laboratory facilities, followed by pathologists and colposcopists. Substantial variation in biopsy diagnoses of CIN2 or CIN3 (vs normal or CIN1) was present between laboratory facilities (MOR: 1.26; 95% credible interval = 1.19-1.36). CONCLUSIONS: Improving consistency in cervical biopsy diagnoses is needed to reduce underdiagnosis, overdiagnosis, and unnecessary treatment resulting from variation in cervical biopsy diagnoses.

Magnetic Resonance Imaging for the Detection of High Grade Cancer in the Canary Prostate Active Surveillance Study.

PURPOSE: We investigated the ability of prostate magnetic resonance imaging to detect Gleason Grade Group 2 or greater cancer in a standardized, multi-institutional active surveillance cohort. MATERIALS AND METHODS: We evaluated men enrolled in Canary Prostate Active Surveillance Study with Gleason Grade Group less than 2 and who underwent biopsy within 12 months of multiparametric magnetic resonance imaging. Our primary outcome was biopsy reclassification to Gleason Grade Group 2 or greater. We evaluated the performance of magnetic resonance imaging PI-RADS® score and clinical factors. Multivariable logistic regression models were fit with magnetic resonance imaging and clinical factors and used to perform receiver operating curve analyses. RESULTS: There were 361 participants with 395 prostate magnetic resonance imaging studies with a median followup of 4.1 (IQR 2.0-7.6) years. Overall 108 (27%) biopsies showed reclassification. Defining positive magnetic resonance imaging as PI-RADS 3-5, the negative predictive value and positive predictive value for detecting Gleason Grade Group 2 or greater cancer was 83% (95% CI 76-90) and 31% (95% CI 26-37), respectively. PI-RADS was significantly associated with reclassification (PI-RADS 5 vs 1 and 2 OR 2.71, 95% CI 1.21-6.17, p=0.016) in a multivariable model but did not improve upon a model with only clinical factors (AUC 0.768 vs 0.762). In 194 fusion biopsies higher grade cancer was found in targeted cores in 21 (11%) instances, while 25 (13%) had higher grade cancer in the systematic cores. CONCLUSIONS: This study adds the largest cohort data to the body of literature for magnetic resonance imaging in active surveillance, recommending systematic biopsy in patients with negative magnetic resonance imaging and the inclusion of systematic biopsy in patients with positive magnetic resonance imaging.

Racial/ethnic differences in obesity and comorbidities between safety-net- and non safety-net integrated health systems.

Previous research shows that patients in integrated health systems experience fewer racial disparities compared with more traditional healthcare systems. Little is known about patterns of racial/ethnic disparities between safety-net and non safety-net integrated health systems.We evaluated racial/ethnic differences in body mass index (BMI) and the Charlson comorbidity index from 3 non safety-net- and 1 safety-net integrated health systems in a cross-sectional study. Multinomial logistic regression modeled comorbidity and BMI on race/ethnicity and health care system type adjusting for age, sex, insurance, and zip-code-level incomeThe study included 1.38 million patients. Higher proportions of safety-net versus non safety-net patients had comorbidity score of 3+ (11.1% vs. 5.0%) and BMI ≥35 (27.7% vs. 15.8%). In both types of systems, blacks and Hispanics were more likely than whites to have higher BMIs. Whites were more likely than blacks or Hispanics to have higher comorbidity scores in a safety net system, but less likely to have higher scores in the non safety-nets. The odds of comorbidity score 3+ and BMI 35+ in blacks relative to whites were significantly lower in safety-net than in non safety-net settings.Racial/ethnic differences were present within both safety-net and non safety-net integrated health systems, but patterns differed. Understanding patterns of racial/ethnic differences in health outcomes in safety-net and non safety-net integrated health systems is important to tailor interventions to eliminate racial/ethnic disparities in health and health care.

Variation in Mammographic Breast Density Assessments Among Radiologists in Clinical Practice: A Multicenter Observational Study.

Background: About half of the United States has legislation requiring radiology facilities to disclose mammographic breast density information to women, often with language recommending discussion of supplemental screening options for women with dense breasts. Objective: To examine variation in breast density assessment across radiologists in clinical practice. Design: Cross-sectional and longitudinal analyses of prospectively collected observational data. Setting: 30 radiology facilities within the 3 breast cancer screening research centers of the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. Participants: Radiologists who interpreted at least 500 screening mammograms during 2011 to 2013 (n = 83). Data on 216 783 screening mammograms from 145 123 women aged 40 to 89 years were included. Measurements: Mammographic breast density, as clinically recorded using the 4 Breast Imaging Reporting and Data System categories (heterogeneously dense and extremely dense categories were considered "dense" for analyses), and patient age, race, and body mass index (BMI). Results: Overall, 36.9% of mammograms were rated as showing dense breasts. Across radiologists, this percentage ranged from 6.3% to 84.5% (median, 38.7% [interquartile range, 28.9% to 50.9%]), with multivariable adjustment for patient characteristics having little effect (interquartile range, 29.9% to 50.8%). Examination of patient subgroups revealed that variation in density assessment across radiologists was pervasive in all but the most extreme patient age and BMI combinations. Among women with consecutive mammograms interpreted by different radiologists, 17.2% (5909 of 34 271) had discordant assessments of dense versus nondense status. Limitation: Quantitative measures of mammographic breast density were not available for comparison. Conclusion: There is wide variation in density assessment across radiologists that should be carefully considered by providers and policymakers when considering supplemental screening strategies. The likelihood of a woman being told she has dense breasts varies substantially according to which radiologist interprets her mammogram. Primary Funding Source: National Institutes of Health.

Influence of Age and Comorbidity on Colorectal Cancer Screening in the Elderly.

INTRODUCTION: Expert recommendations differ for colorectal cancer screening in the elderly. Recent studies suggest that healthy adults aged >75 years may benefit from screening. This study examined screening use and follow-up, and how they varied by health status within age strata, among a large cohort of elderly individuals in community settings. METHODS: A population-based, longitudinal cohort study was conducted among health plan members aged 65-89 years enrolled during 2011-2012 in three integrated healthcare systems participating in the Population-Based Research Optimizing Screening through Personalized Regimens consortium. Comorbidity measurements used the Charlson index. Analyses, conducted in 2015, comprised descriptive statistics and multivariable modeling that estimated age by comorbidity-specific percentages of patients for two outcomes: colorectal cancer screening uptake and follow-up of abnormal fecal blood tests. RESULTS: Among 846,267 patients, 72% were up-to-date with colorectal cancer screening. Of patients with a positive fecal blood test, 65% received follow-up colonoscopy within 3 months. Likelihood of being up-to-date and receiving timely follow-up was significantly lower for patients aged ≥76 years than their younger counterparts (p<0.001). Comorbidity was less influential than age and more strongly related to timely follow-up than being up-to-date. In all age groups, considerable numbers of patients with no/low comorbidity were not up-to-date or did not receive timely follow-up. CONCLUSIONS: In three integrated healthcare systems, many older, relatively healthy patients were not screening up-to-date, and some relatively young, healthy patients did not receive timely follow-up. Findings suggest a need for re-evaluating age-based screening guidelines and improving screening completion among the elderly.

Time to Colonoscopy after Positive Fecal Blood Test in Four U.S. Health Care Systems.

BACKGROUND: To reduce colorectal cancer mortality, positive fecal blood tests must be followed by colonoscopy. METHODS: We identified 62,384 individuals ages 50 to 89 years with a positive fecal blood test between January 1, 2011 and December 31, 2012 in four health care systems within the Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR) consortium. We estimated the probability of follow-up colonoscopy and 95% confidence intervals (CI) using the Kaplan-Meier method. Overall differences in cumulative incidence of follow-up across health care systems were assessed with the log-rank test. HRs and 95% CIs were estimated from multivariate Cox proportional hazards models. RESULTS: Most patients who received a colonoscopy did so within 6 months of their positive fecal blood test, although follow-up rates varied across health care systems (P <0.001). Median days to colonoscopy ranged from 41 (95% CI, 40-41) to 174 (95% CI, 123-343); percent followed-up by 12 months ranged from 58.1% (95% CI, 51.6%-63.7%) to 83.8% (95% CI, 83.4%-84.3%) and differences across health care systems were also observed at 1, 2, 3, and 6 months. Increasing age and comorbidity score were associated with lower follow-up rates. CONCLUSION: Individual characteristics and health care system were associated with colonoscopy after positive fecal blood tests. Patterns were consistent across health care systems, but proportions of patients receiving follow-up varied. These findings suggest that there is room to improve follow-up of positive colorectal cancer screening tests. IMPACT: Understanding the timing of colonoscopy after positive fecal blood tests and characteristics associated with lack of follow-up may inform future efforts to improve follow-up.