Background
Women and their health care providers need a reliable answer to this important question: If a woman chooses to participate in regular mammography screening, then how much will this choice ...improve her chances of avoiding a death from breast cancer compared with women who choose not to participate?
Methods
To answer this question, we used comprehensive registries for population, screening history, breast cancer incidence, and disease‐specific death data in a defined population in Dalarna County, Sweden. The annual incidence of breast cancer was calculated along with the annual incidence of breast cancers that were fatal within 10 and within 11 to 20 years of diagnosis among women aged 40 to 69 years who either did or did not participate in mammography screening during a 39‐year period (1977‐2015). For an additional comparison, corresponding data are presented from 19 years of the prescreening period (1958‐1976). All patients received stage‐specific therapy according to the latest national guidelines, irrespective of the mode of detection.
Results
The benefit for women who chose to participate in an organized breast cancer screening program was a 60% lower risk of dying from breast cancer within 10 years after diagnosis (relative risk, 0.40; 95% confidence interval, 0.34‐0.48) and a 47% lower risk of dying from breast cancer within 20 years after diagnosis (relative risk, 0.53; 95% confidence interval, 0.44‐0.63) compared with the corresponding risks for nonparticipants.
Conclusions
Although all patients with breast cancer stand to benefit from advances in breast cancer therapy, the current results demonstrate that women who have participated in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than do those who have not participated.
After 20 years of follow‐up, women who participate in mammography screening have a 47% lower risk of dying from breast cancer. Although all patients with breast cancer potentially can benefit from advances in breast cancer therapy, women who participate in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than those who do not participate.
To estimate the long-term (29-year) effect of mammographic screening on breast cancer mortality in terms of both relative and absolute effects.
This study was carried out under the auspices of the ...Swedish National Board of Health and Welfare. The board determined that, because randomization was at a community level and was to invitation to screening, informed verbal consent could be given by the participants when they attended the screening examination. A total of 133 065 women aged 40-74 years residing in two Swedish counties were randomized into a group invited to mammographic screening and a control group receiving usual care. Case status and cause of death were determined by the local trial end point committees and, independently, by an external committee. Mortality analysis was performed by using negative binomial regression.
There was a highly significant reduction in breast cancer mortality in women invited to screening according to both local end point committee data (relative risk RR = 0.69; 95% confidence interval: 0.56, 0.84; P < .0001) and consensus data (RR = 0.73; 95% confidence interval: 0.59, 0.89; P = .002). At 29 years of follow-up, the number of women needed to undergo screening for 7 years to prevent one breast cancer death was 414 according to local data and 519 according to consensus data. Most prevented breast cancer deaths would have occurred (in the absence of screening) after the first 10 years of follow-up.
Invitation to mammographic screening results in a highly significant decrease in breast cancer-specific mortality. Evaluation of the full impact of screening, in particular estimates of absolute benefit and number needed to screen, requires follow-up times exceeding 20 years because the observed number of breast cancer deaths prevented increases with increasing time of follow-up.
Not only were social events and public facilities closed temporarily due to the coronavirus disease 2019 (COVID‐19) pandemic, but health services also were affected greatly. In this commentary, the ...authors discuss how the national program of mammography screening in Taiwan was affected, even without known community‐acquired transmission.
Background
It is of paramount importance to evaluate the impact of participation in organized mammography service screening independently from changes in breast cancer treatment. This can be done by ...measuring the incidence of fatal breast cancer, which is based on the date of diagnosis and not on the date of death.
Methods
Among 549,091 women, covering approximately 30% of the Swedish screening‐eligible population, the authors calculated the incidence rates of 2473 breast cancers that were fatal within 10 years after diagnosis and the incidence rates of 9737 advanced breast cancers. Data regarding each breast cancer diagnosis and the cause and date of death of each breast cancer case were gathered from national Swedish registries. Tumor characteristics were collected from regional cancer centers. Aggregated data concerning invitation and participation were provided by Sectra Medical Systems AB. Incidence rates were analyzed using Poisson regression.
Results
Women who participated in mammography screening had a statistically significant 41% reduction in their risk of dying of breast cancer within 10 years (relative risk, 0.59; 95% CI, 0.51‐0.68 P < .001) and a 25% reduction in the rate of advanced breast cancers (relative risk, 0.75; 95% CI, 0.66‐0.84 P < .001).
Conclusions
Substantial reductions in the incidence rate of breast cancers that were fatal within 10 years after diagnosis and in the advanced breast cancer rate were found in this contemporaneous comparison of women participating versus those not participating in screening. These benefits appeared to be independent of recent changes in treatment regimens.
Substantial and significant reductions in the incidence rates of fatal breast cancer and advanced breast cancer with 10 years of follow‐up are observed in this analysis of greater than one‐half million Swedish women participating and not participating in breast cancer screening. These comparisons are contemporaneous, and thus are not influenced by changes in therapeutic regimens.
Modeling overdetection resulting from screening often uses the conventional competing risk model. This model assigns screen‐detected cases dying from other causes as overdetection modeled by a ...one‐jump process, which may not be true for the censored overdetected cases. To relax this restrictive assumption, accommodate a finite Markov process for overdetection, and dispense with long‐term follow‐up until death, we propose a generalized Coxian phase‐type Markov process to distinguish the progressive latent multistate pathway from the nonprogressive (overdetected) latent multistate pathway. Various new likelihood functions were developed to estimate the transition parameters with the available data accrued at the time of diagnosis. The proportion of overdetected cancers by the cured model was further estimated by using parameters with and without distinguishing between the two latent pathways. While perturbation analyses were conducted by changing their parameters to assess their effects on overdetection, the results, including of asymptotic analyses, were very robust for an overdetection rate higher than 20% but not for low overdetection rates. These two scenarios were demonstrated by applying the Coxian phase‐type model to prostate cancer and breast cancer screening, yielding a substantial proportion of overdetected prostate cancer (60%) attributed to the prostate specific antigen test and a small fraction of overdetected breast cancer (3%) detected by mammography. This kind of variation in overdetection elucidated by the Coxian phase‐type Markov process provides new insights into the quantitative mechanisms producing overdetection, which is informative for evaluating the benefits and risks of various types of population‐based cancer screening programs.
Multistate Markov regression models used for quantifying the effect size of state‐specific covariates pertaining to the dynamics of multistate outcomes have gained popularity. However, the ...measurements of multistate outcome are prone to the errors of classification, particularly when a population‐based survey/research is involved with proxy measurements of outcome due to cost consideration. Such a misclassification may affect the effect size of relevant covariates such as odds ratio used in the field of epidemiology. We proposed a Bayesian measurement‐error‐driven hidden Markov regression model for calibrating these biased estimates with and without a 2‐stage validation design. A simulation algorithm was developed to assess various scenarios of underestimation and overestimation given nondifferential misclassification (independent of covariates) and differential misclassification (dependent on covariates). We applied our proposed method to the community‐based survey of androgenetic alopecia and found that the effect size of the majority of covariate was inflated after calibration regardless of which type of misclassification. Our proposed Bayesian measurement‐error‐driven hidden Markov regression model is practicable and effective in calibrating the effects of covariates on multistate outcome, but the prior distribution on measurement errors accrued from 2‐stage validation design is strongly recommended.
Emergency department (ED) crowding continues to be an important health care issue in modern countries. Among the many crucial quality indicators for monitoring the throughput process, a patient's ...length of stay (LOS) is considered the most important one since it is both the cause and the result of ED crowding. The aim of this study is to identify and quantify the influence of different patient-related or diagnostic activities-related factors on the ED LOS of discharged patients.
This is a retrospective electronic data analysis. All patients who were discharged from the ED of a tertiary teaching hospital in 2013 were included. A multivariate accelerated failure time model was used to analyze the influence of the collected covariates on patient LOS.
A total of 106,206 patients were included for analysis with an overall medium ED LOS of 1.46 (interquartile range = 2.03) hours. Among them, 96% were discharged by a physician, 3.5% discharged against medical advice, 0.5% left without notice, and only 0.02% left without being seen by a physician. In the multivariate analysis, increased age (>80 vs <20, time ratio (TR) = 1.408, p<0.0001), higher acuity level (triage level I vs. level V, TR = 1.343, p<0.0001), transferred patients (TR = 1.350, p<0.0001), X-rays obtained (TR = 1.181, p<0.0001), CT scans obtained (TR = 1.515, p<0.0001), laboratory tests (TR = 2.654, p<0.0001), consultation provided (TR = 1.631, p<0.0001), observation provided (TR = 8.435, p<0.0001), critical condition declared (TR = 1.205, p<0.0001), day-shift arrival (TR = 1.223, p<0.0001), and an increased ED daily census (TR = 1.057, p<0.0001) lengthened the ED LOS with various effect sizes. On the other hand, male sex (TR = 0.982, p = 0.002), weekend arrival (TR = 0.928, p<0.0001), and adult non-trauma patients (compared with pediatric non-trauma, TR = 0.687, p<0.0001) were associated with shortened ED LOS. A prediction diagram was made accordingly and compared with the actual LOS.
The influential factors on the ED LOS in discharged patients were identified and quantified in the current study. The model's predicted ED LOS may provide useful information for physicians or patients to better anticipate an individual's LOS and to help the administrative level plan its staffing policy.
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