IMPORTANCE: After the US Food and Drug Administration (FDA) approved computer-aided detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid Services (CMS) provided ...increased payment in 2002, CAD technology disseminated rapidly. Despite sparse evidence that CAD improves accuracy of mammographic interpretations and costs over $400 million a year, CAD is currently used for most screening mammograms in the United States. OBJECTIVE: To measure performance of digital screening mammography with and without CAD in US community practice. DESIGN, SETTING, AND PARTICIPANTS: We compared the accuracy of digital screening mammography interpreted with (n = 495 818) vs without (n = 129 807) CAD from 2003 through 2009 in 323 973 women. Mammograms were interpreted by 271 radiologists from 66 facilities in the Breast Cancer Surveillance Consortium. Linkage with tumor registries identified 3159 breast cancers in 323 973 women within 1 year of the screening. MAIN OUTCOMES AND MEASURES: Mammography performance (sensitivity, specificity, and screen-detected and interval cancers per 1000 women) was modeled using logistic regression with radiologist-specific random effects to account for correlation among examinations interpreted by the same radiologist, adjusting for patient age, race/ethnicity, time since prior mammogram, examination year, and registry. Conditional logistic regression was used to compare performance among 107 radiologists who interpreted mammograms both with and without CAD. RESULTS: Screening performance was not improved with CAD on any metric assessed. Mammography sensitivity was 85.3% (95% CI, 83.6%-86.9%) with and 87.3% (95% CI, 84.5%-89.7%) without CAD. Specificity was 91.6% (95% CI, 91.0%-92.2%) with and 91.4% (95% CI, 90.6%-92.0%) without CAD. There was no difference in cancer detection rate (4.1 in 1000 women screened with and without CAD). Computer-aided detection did not improve intraradiologist performance. Sensitivity was significantly decreased for mammograms interpreted with vs without CAD in the subset of radiologists who interpreted both with and without CAD (odds ratio, 0.53; 95% CI, 0.29-0.97). CONCLUSIONS AND RELEVANCE: Computer-aided detection does not improve diagnostic accuracy of mammography. These results suggest that insurers pay more for CAD with no established benefit to women.
Cancer is the second leading cause of death in the United States.
To conduct systematic reviews of aspirin and 1) total cancer mortality and incidence in persons eligible for primary prevention of ...cardiovascular disease (CVD) and 2) colorectal cancer (CRC) mortality and incidence in persons at average CRC risk.
MEDLINE, PubMed, and the Cochrane Central Register of Controlled Trials through January 2015 and relevant references from other reviews.
Trials comparing oral aspirin versus placebo or no treatment in adults aged 40 years or older were included. Two investigators independently reviewed abstracts and articles against inclusion and quality criteria.
Data from 20 good- or fair-quality trials were abstracted by one reviewer and checked by another.
In CVD primary prevention trials, cancer mortality (relative risk RR, 0.96 95% CI, 0.87 to 1.06) (10 trials; n = 103 787) and incidence (RR, 0.98 CI, 0.93 to 1.04) (6 trials; n = 72 926) were similar in aspirin and control groups over 3.6 to 10.1 years. In CVD primary and secondary prevention trials, 20-year CRC mortality was reduced among persons assigned to aspirin therapy (RR, 0.67 CI, 0.52 to 0.86) (4 trials; n = 14 033). Aspirin appeared to reduce CRC incidence beginning 10 to 19 years after initiation (RR, 0.60 CI, 0.47 to 0.76) (3 trials; n = 47 464).
Most data were from clinically and methodologically heterogeneous CVD prevention trials. Outcome assessment and follow-up length varied across studies. Data on non-CRC cancer types and subgroups were limited.
In CVD primary prevention populations, aspirin's effect on total cancer mortality and incidence was not clearly established. Evidence from CVD primary and secondary prevention studies suggested that aspirin therapy reduces CRC incidence and perhaps mortality approximately 10 years after initiation.
Agency for Healthcare Research and Quality.
Abstract Objective To evaluate the effectiveness of methods that control for confounding by indication, we compared breast cancer recurrence rates among women receiving adjuvant chemotherapy with ...those who did not. Study Design and Setting In a medical record review-based study of breast cancer treatment in older women ( n = 1798) diagnosed between 1990 and 1994, our crude analysis suggested that adjuvant chemotherapy was positively associated with recurrence (hazard ratio HR = 2.6; 95% confidence interval CI = 1.9, 3.5). We expected a protective effect, so postulated that the crude association was confounded by indications for chemotherapy. We attempted to adjust for this confounding by restriction, multivariable regression, propensity scores (PSs), and instrumental variable (IV) methods. Results After restricting to women at high risk for recurrence ( n = 946), chemotherapy was not associated with recurrence (HR = 1.1; 95% CI = 0.7, 1.6) using multivariable regression. PS adjustment yielded similar results (HR = 1.3; 95% CI = 0.8, 2.0). The IV-like method yielded a protective estimate (HR = 0.9; 95% CI = 0.2, 4.3); however, imbalances of measured factors across levels of the IV suggested residual confounding. Conclusion Conventional methods do not control for unmeasured factors, which often remain important when addressing confounding by indication. PS and IV analysis methods can be useful under specific situations, but neither method adequately controlled confounding by indication in this study.
Accurate long-term breast cancer risk assessment for women attending routine screening could help reduce the disease burden and intervention-associated harms by personalizing screening ...recommendations and preventive interventions.
To report the accuracy of risk assessment for breast cancer during a period of 19 years.
This cohort study of the Kaiser Permanente Washington breast imaging registry included women without previous breast cancer, aged 40 to 73 years, who attended screening from January 1, 1996, through December 31, 2013. Follow-up was completed on December 31, 2014, and data were analyzed from March 2, 2016, through November 13, 2017.
Risk factors from a questionnaire and breast density from the Breast Imaging and Reporting Data System at entry; primary risk was assessed using the Tyrer-Cuzick model.
Incidence of invasive breast cancer was estimated with and without breast density. Follow-up began 6 months after the entry mammogram and extended to the earliest diagnosis of invasive breast cancer, censoring at 75 years of age, 2014, diagnosis of ductal carcinoma in situ, death, or health plan disenrollment. Observed divided by expected (O/E) numbers of cancer cases were compared using exact Poisson 95% CIs. Hazard ratios for the top decile of 10-year risk relative to the middle 80% of the study population were estimated. Constancy of relative risk calibration during follow-up was tested using a time-dependent proportional hazards effect.
In this cohort study of 132 139 women (median age at entry, 50 years; interquartile range, 44-58 years), 2699 invasive breast cancers were subsequently diagnosed after a median 5.2 years of follow-up (interquartile range, 2.4-11.1 years; maximum follow-up, 19 years; annual incidence rate IR per 1000 women, 2.9). Observed number of cancer diagnoses was close to the expected number (O/E for the Tyrer-Cuzick model, 1.02 95% CI, 0.98-1.06; O/E for the Tyrer-Cuzick model with density, 0.98 95% CI, 0.94-1.02). The Tyrer-Cuzick model estimated 2554 women (1.9%) to be at high risk (10-year risk of ≥8%), of whom 147 subsequently developed invasive breast cancer (O/E, 0.79; 95% CI, 0.67-0.93; IR per 1000 women, 8.7). The Tyrer-Cuzick model with density estimated more women to be at high risk (4645 3.5%; 273 cancers 10.1%; O/E, 0.78; 95% CI, 0.69-0.88; IR per 1000 women, 9.2). The hazard ratio for the highest risk decile compared with the middle 80% was 2.22 (95% CI, 2.02-2.45) for the Tyrer-Cuzick model and 2.55 (95% CI, 2.33-2.80) for the Tyrer-Cuzick model with density. Little evidence was found for a decrease in relative risk calibration throughout follow-up for the Tyrer-Cuzick model (age-adjusted slope, -0.003; 95% CI, -0.018 to 0.012) or the Tyrer-Cuzick model with density (age-adjusted slope, -0.008; 95% CI, -0.020 to 0.004).
Breast cancer risk assessment combining classic risk factors with mammographic density may provide useful data for 10 years or more and could be used to guide long-term, systematic, risk-adapted screening and prevention strategies.
Identifying risk factors for breast cancer specific to women in their 40s could inform screening decisions.
To determine what factors increase risk for breast cancer in women aged 40 to 49 years and ...the magnitude of risk for each factor.
MEDLINE (January 1996 to the second week of November 2011), Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (fourth quarter of 2011), Scopus, reference lists of published studies, and the Breast Cancer Surveillance Consortium.
English-language studies and systematic reviews of risk factors for breast cancer in women aged 40 to 49 years. Additional inclusion criteria were applied for each risk factor.
Data on participants, study design, analysis, follow-up, and outcomes were abstracted. Study quality was rated by using established criteria, and only studies rated as good or fair were included. Results were summarized by using meta-analysis when sufficient studies were available or from the best evidence based on study quality, size, and applicability when meta-analysis was not possible. Data from the Breast Cancer Surveillance Consortium were analyzed with proportional hazards models by using partly conditional Cox regression. Reference groups for comparisons were set at U.S. population means.
Sixty-six studies provided data for estimates. Extremely dense breasts on mammography or first-degree relatives with breast cancer were associated with at least a 2-fold increase in risk for breast cancer. Prior breast biopsy, second-degree relatives with breast cancer, or heterogeneously dense breasts were associated with a 1.5- to 2.0-fold increased risk; current use of oral contraceptives, nulliparity, and age 30 years or older at first birth were associated with a 1.0- to 1.5-fold increased risk.
Studies varied by measures, reference groups, and adjustment for confounders, which could bias combined estimates. Effects of multiple risk factors were not considered.
Extremely dense breasts and first-degree relatives with breast cancer were each associated with at least a 2-fold increase in risk for breast cancer in women aged 40 to 49 years. Identification of these risk factors may be useful for personalized mammography screening.
National Cancer Institute.
Purpose To establish performance benchmarks for modern screening digital mammography and assess performance trends over time in U.S. community practice. Materials and Methods This HIPAA-compliant, ...institutional review board-approved study measured the performance of digital screening mammography interpreted by 359 radiologists across 95 facilities in six Breast Cancer Surveillance Consortium (BCSC) registries. The study included 1 682 504 digital screening mammograms performed between 2007 and 2013 in 792 808 women. Performance measures were calculated according to the American College of Radiology Breast Imaging Reporting and Data System, 5th edition, and were compared with published benchmarks by the BCSC, the National Mammography Database, and performance recommendations by expert opinion. Benchmarks were derived from the distribution of performance metrics across radiologists and were presented as 50th (median), 10th, 25th, 75th, and 90th percentiles, with graphic presentations using smoothed curves. Results Mean screening performance measures were as follows: abnormal interpretation rate (AIR), 11.6 (95% confidence interval CI: 11.5, 11.6); cancers detected per 1000 screens, or cancer detection rate (CDR), 5.1 (95% CI: 5.0, 5.2); sensitivity, 86.9% (95% CI: 86.3%, 87.6%); specificity, 88.9% (95% CI: 88.8%, 88.9%); false-negative rate per 1000 screens, 0.8 (95% CI: 0.7, 0.8); positive predictive value (PPV) 1, 4.4% (95% CI: 4.3%, 4.5%); PPV2, 25.6% (95% CI: 25.1%, 26.1%); PPV3, 28.6% (95% CI: 28.0%, 29.3%); cancers stage 0 or 1, 76.9%; minimal cancers, 57.7%; and node-negative invasive cancers, 79.4%. Recommended CDRs were achieved by 92.1% of radiologists in community practice, and 97.1% achieved recommended ranges for sensitivity. Only 59.0% of radiologists achieved recommended AIRs, and only 63.0% achieved recommended levels of specificity. Conclusion The majority of radiologists in the BCSC surpass cancer detection recommendations for screening mammography; however, AIRs continue to be higher than the recommended rate for almost half of radiologists interpreting screening mammograms.
RSNA, 2016 Online supplemental material is available for this article.
The increasing availability of electronic health records (EHRs) creates opportunities for automated extraction of information from clinical text. We hypothesized that natural language processing ...(NLP) could substantially reduce the burden of manual abstraction in studies examining outcomes, like cancer recurrence, that are documented in unstructured clinical text, such as progress notes, radiology reports, and pathology reports. We developed an NLP-based system using open-source software to process electronic clinical notes from 1995 to 2012 for women with early-stage incident breast cancers to identify whether and when recurrences were diagnosed. We developed and evaluated the system using clinical notes from 1,472 patients receiving EHR-documented care in an integrated health care system in the Pacific Northwest. A separate study provided the patient-level reference standard for recurrence status and date. The NLP-based system correctly identified 92% of recurrences and estimated diagnosis dates within 30 days for 88% of these. Specificity was 96%. The NLP-based system overlooked 5 of 65 recurrences, 4 because electronic documents were unavailable. The NLP-based system identified 5 other recurrences incorrectly classified as nonrecurrent in the reference standard. If used in similar cohorts, NLP could reduce by 90% the number of EHR charts abstracted to identify confirmed breast cancer recurrence cases at a rate comparable to traditional abstraction.
Background: Risk prediction models for breast cancer can be improved by the addition of recently identified risk factors, including breast density and use of hormone therapy. We used prospective risk ...information to predict a diagnosis of breast cancer in a cohort of 1 million women undergoing screening mammography. Methods: There were 2 392 998 eligible screening mammograms from women without previously diagnosed breast cancer who had had a prior mammogram in the preceding 5 years. Within 1 year of the screening mammogram, 11 638 women were diagnosed with breast cancer. Separate logistic regression risk models were constructed for premenopausal and postmenopausal examinations by use of a stringent (P<.0001) criterion for the inclusion of risk factors. Risk models were constructed with 75% of the data and validated with the remaining 25%. Concordance of the predicted with the observed outcomes was assessed by a concordance (c) statistic after logistic regression model fit. All statistical tests were two-sided. Results: Statistically significant risk factors for breast cancer diagnosis among premenopausal women included age, breast density, family history of breast cancer, and a prior breast procedure. For postmenopausal women, the statistically significant factors included age, breast density, race, ethnicity, family history of breast cancer, a prior breast procedure, body mass index, natural menopause, hormone therapy, and a prior false-positive mammogram. The model may identify high-risk women better than the Gail model, although predictive accuracy was only moderate. The c statistics were 0.631 (95% confidence interval CI = 0.618 to 0.644) for premenopausal women and 0.624 (95% CI = 0.619 to 0.630) for postmenopausal women. Conclusion: Breast density is a strong additional risk factor for breast cancer, although it is unknown whether reduction in breast density would reduce risk. Our risk model may be able to identify women at high risk for breast cancer for preventive interventions or more intensive surveillance.
Low-dose computed tomography (LDCT) of the chest for lung cancer screening of heavy smokers was given a 'B' rating by the U.S. Preventive Services Task Force (USPSTF) in 2013, and gained widespread ...insurance coverage in the U.S. in 2015. Lung cancer screening has since had low uptake. However, for those that do choose to screen, little is known about patient motivations for completing screening in real-world practice.
To explore the motivations for screening-eligible patients to screen for lung cancer.
Semi-structured qualitative interviews were conducted with 20 LDCT screen-completed men and women who were members of an integrated mixed-model healthcare system in Washington State. From June to September 2015, participants were recruited and individual interviews performed about motivations to screen for lung cancer. Audio-recorded interviews were transcribed and analyzed using inductive content analysis by three investigators.
Four primary themes emerged as motivations for completing LDCT lung cancer screening: 1) trust in the referring clinician; 2) early-detection benefit; 3) low or limited harm perception; and 4) friends or family with advanced cancer.
Participants in our study were primarily motivated to screen for lung cancer based on perceived benefit of early-detection, absence of safety concerns, and personal relationships. Our findings provide new insights about patient motivations to screen, and can potentially be used to improve lung cancer screening uptake and shared decision-making processes.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Compared with film, digital mammography has superior sensitivity but lower specificity for women aged 40 to 49 years and women with dense breasts. Digital has replaced film in virtually all US ...facilities, but overall population health and cost from use of this technology are unclear.
Using five independent models, we compared digital screening strategies starting at age 40 or 50 years applied annually, biennially, or based on density with biennial film screening from ages 50 to 74 years and with no screening. Common data elements included cancer incidence and test performance, both modified by breast density. Lifetime outcomes included mortality, quality-adjusted life-years, and screening and treatment costs.
For every 1000 women screened biennially from age 50 to 74 years, switching to digital from film yielded a median within-model improvement of 2 life-years, 0.27 additional deaths averted, 220 additional false-positive results, and $0.35 million more in costs. For an individual woman, this translates to a health gain of 0.73 days. Extending biennial digital screening to women ages 40 to 49 years was cost-effective, although results were sensitive to quality-of-life decrements related to screening and false positives. Targeting annual screening by density yielded similar outcomes to targeting by age. Annual screening approaches could increase costs to $5.26 million per 1000 women, in part because of higher numbers of screens and false positives, and were not efficient or cost-effective.
The transition to digital breast cancer screening in the United States increased total costs for small added health benefits. The value of digital mammography screening among women aged 40 to 49 years depends on women's preferences regarding false positives.
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