A mixed-methods study of multi-level factors influencing mammography overuse among an older ethnically diverse screening population: implications for de-implementation

Background There is growing concern that routine mammography screening is overused among older women. Successful and equitable de-implementation of mammography will require a multi-level understanding of the factors contributing to mammography overuse. Methods This explanatory, sequential, mixed-methods study collected survey data (n= 52, 73.1% Hispanic, 73.1% Spanish-speaking) from women ≥70 years of age at the time of screening mammography, followed by semi-structured interviews with a subset of older women completing the survey (n=19, 63.2% Hispanic, 63.2% Spanish-speaking) and providers (n=5, 4 primary care, 1 obstetrics and gynecology) to better understand multi-level factors influencing mammography overuse and inform potential de-implementation strategies. We conducted a descriptive analysis of survey data and content analysis of qualitative interview data. Survey and interview data were examined separately, compared, integrated, and organized according to Norton and Chambers Continuum of Factors Influencing De-Implementation Process. Results Survey findings show that 87.2% of older women believe it is important to plan for an annual mammogram, 80.8% received a provider recommendation, and 78.9% received a reminder in the last 12 months to schedule a mammogram. Per interviews with older women, the majority were unaware of or did not perceive to have experienced overuse and intended to continue mammography screening. Findings from interviews with older women and providers suggest that there are multiple opportunities for older women to obtain a mammogram. Per provider interviews, almost all reported that reducing overuse was not viewed as a priority by the system or other providers. Providers also discussed that variation in mammography screening practices across providers, fear of malpractice, and monetary incentives may contribute to overscreening. Providers identified potential strategies to reduce overscreening including patient and provider education around harms of screening, leveraging the electronic health record to identify women who may receive less health benefit from screening, customizing system-generated reminder letters, and organizing workgroups to develop standard processes of care around mammography screening. Conclusions Multi-level factors contributing to mammography overuse are dynamic, interconnected, and reinforced. To ensure equitable de-implementation, there is a need for more refined and empirical testing of theories, models, and frameworks for de-implementation with a strong patient-level component that considers the interplay between multilevel factors and the larger care delivery process

Association between Class III Obesity (BMI of 40–59 kg/m2) and Mortality: A Pooled Analysis of 20 Prospective Studies

Background: The prevalence of class III obesity (body mass index [BMI]≥40 kg/m2) has increased dramatically in several countries and currently affects 6% of adults in the US, with uncertain impact on the risks of illness and death. Using data from a large pooled study, we evaluated the risk of death, overall and due to a wide range of causes, and years of life expectancy lost associated with class III obesity. Methods and Findings: In a pooled analysis of 20 prospective studies from the United States, Sweden, and Australia, we estimated sex- and age-adjusted total and cause-specific mortality rates (deaths per 100,000 persons per year) and multivariable-adjusted hazard ratios for adults, aged 19–83 y at baseline, classified as obese class III (BMI 40.0–59.9 kg/m2) compared with those classified as normal weight (BMI 18.5–24.9 kg/m2). Participants reporting ever smoking cigarettes or a history of chronic disease (heart disease, cancer, stroke, or emphysema) on baseline questionnaires were excluded. Among 9,564 class III obesity participants, mortality rates were 856.0 in men and 663.0 in women during the study period (1976–2009). Among 304,011 normal-weight participants, rates were 346.7 and 280.5 in men and women, respectively. Deaths from heart disease contributed largely to the excess rates in the class III obesity group (rate differences = 238.9 and 132.8 in men and women, respectively), followed by deaths from cancer (rate differences = 36.7 and 62.3 in men and women, respectively) and diabetes (rate differences = 51.2 and 29.2 in men and women, respectively). Within the class III obesity range, multivariable-adjusted hazard ratios for total deaths and deaths due to heart disease, cancer, diabetes, nephritis/nephrotic syndrome/nephrosis, chronic lower respiratory disease, and influenza/pneumonia increased with increasing BMI. Compared with normal-weight BMI, a BMI of 40–44.9, 45–49.9, 50–54.9, and 55–59.9 kg/m2 was associated with an estimated 6.5 (95% CI: 5.7–7.3), 8.9 (95% CI: 7.4–10.4), 9.8 (95% CI: 7.4–12.2), and 13.7 (95% CI: 10.5–16.9) y of life lost. A limitation was that BMI was mainly ascertained by self-report. Conclusions: Class III obesity is associated with substantially elevated rates of total mortality, with most of the excess deaths due to heart disease, cancer, and diabetes, and major reductions in life expectancy compared with normal weight. Please see later in the article for the Editors' Summar

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT, per-allele odds ratio (OR) = 0.79, 95% confidence interval (CI) 0.74-0.84, P = 3.0 x 10(-12)), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2, OR = 1.46, 95% CI 1.30-1.65, P = 1.1 x 10(-10)), rs9581943 at 13q12.2 (PDX1, OR = 1.15, 95% CI 1.10-1.20, P = 2.4 x 10(-9)) and rs16986825 at 22q12.1 (ZNRF3, OR = 1.18, 95% CI 1.12-1.25, P = 1.2 x 10(-8)). We identified an independent signal in exon 2 of TERT at the established region 5p15.33 (rs2736098, OR = 0.80, 95% CI 0.76-0.85, P = 9.8 x 10(-14)). We also identified a locus at 8q24.21 (rs1561927, P = 1.3 x 10(-7)) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study identified multiple new susceptibility alleles for pancreatic cancer that are worthy of follow-up studies

Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer

We performed a multistage genome-wide association study (GWAS) including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT; per-allele odds ratio [OR] = 0.79; 95% confidence interval [CI] = 0.74–0.84; P = 3.0×10−12), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2; OR = 1.46; 95% CI = 1.30–1.65; P = 1.1×10−10), rs9581943 at 13q12.2 (PDX1; OR = 1.15; 95% CI = 1.10–1.20; P = 2.4×10−9), and rs16986825 at 22q12.1 (ZNRF3; OR = 1.18; 95% CI = 1.12–1.25; P = 1.2×10−8). An independent signal was identified in exon 2 of TERT at the established region 5p15.33 (rs2736098; OR = 0.80; 95% CI = 0.76–0.85; P = 9.8×10−14). We also identified a locus at 8q24.21 (rs1561927; P = 1.3×10−7) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study has identified multiple new susceptibility alleles for pancreatic cancer worthy of follow-up studies

Vitamin D Metabolic Pathway Genes and Pancreatic Cancer Risk

Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN) totaling 213 single nucleotide polymorphisms (SNPs), and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (50 nmol/L) for the most significant SNPs using a subset of cohort cases (n = 713) and controls (n = 878). The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830). Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186), LRP2 (rs4668123), CYP24A1 (rs2762932), GC (rs2282679), and CUBN (rs1810205) genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037), but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk

Vitamin D metabolic pathway genes and pancreatic cancer risk

Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN) totaling 213 single nucleotide polymorphisms (SNPs), and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (≤50, >50 nmol/L) for the most significant SNPs using a subset of cohort cases (n = 713) and controls (n = 878). The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830). Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186), LRP2 (rs4668123), CYP24A1 (rs2762932), GC (rs2282679), and CUBN (rs1810205) genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037), but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk.This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E

Description of participants with BMI in the normal-weight (18.5–24.9 kg/m²) and class III obesity (40.0–59.0 kg/m²) range, by cohort.

<p>Description of participants with BMI in the normal-weight (18.5–24.9 kg/m²) and class III obesity (40.0–59.0 kg/m²) range, by cohort.</p

Hazard ratios and 95% confidence intervals for risk of death according to BMI category (40.0–59.9 versus 18.5–24.9 kg/m²) or continuous values of BMI between 40.0 and 59.9 kg/m² (per 5 kg/m²): subgroup analyses.

<p>*Calculated by including a cross-product term between the subgroup variable and BMI (40.0–59.9 versus 18.5–24.9 kg/m²); subgroup analyses for attained age and calendar year were stratified by follow-up period.</p>a<p>Models use attained age as the underlying time metric, and are adjusted for sex, race/ethnicity (white [all participants in the Swedish and Australian cohorts were coded as white], black, Asian/Pacific Islander, Hispanic, other/unknown), education (high school or less, post–high school, college, unknown), alcohol intake (grams of ethanol per day: 0, >0 to <10, ≥10, unknown), physical activity level (cohort-specific tertiles corresponding to low, medium, and high), and study.</p>b<p>Models excluded participants who entered the study at or after age 65 y; follow-up time was censored at age at study exit (due to loss to follow-up, death, or administrative end date) or age 65 y, whichever came first.</p>c<p>Models excluded participants who exited the study at or before age 65 y; follow-up began at age 65 y for those who entered the study before age 65 y.</p>d<p>Models excluded participants who entered the study on or after the year 2000; follow-up time was censored at study exit (due to loss to follow-up, death, or administrative end date) or the year 2000, whichever came first.</p>e<p>Models excluded participants who exited the study on or before the year 2000; follow-up began in the year 2000 for those who entered the study before the year 2000.</p