Knowledge of the likelihood that a screening-detected case of cancer has been overdiagnosed is vitally important to make treatment decisions and develop screening policy. An overdiagnosed case is an ...excess case detected by screening. Estimates of the frequency of overdiagnosis in breast and prostate cancer screening vary greatly across studies. This article identifies features of overdiagnosis studies that influence results and shows their effect by using published research. First, different ways to define and measure overdiagnosis are considered. Second, contextual features and how they affect overdiagnosis estimates are examined. Third, the effect of estimation approach is discussed. Many studies use excess incidence under screening as a proxy for overdiagnosis. Others use statistical models to make inferences about lead time or natural history and then derive the corresponding fraction of cases that are overdiagnosed. This article concludes with questions that readers of overdiagnosis studies can use to evaluate the validity and relevance of published estimates and recommends that authors of studies quantifying overdiagnosis provide information about these features.
The number of patients with cancer who are age 65 years or older (hereinafter "older") is increasing dramatically. One obvious aspect of cancer care for this group is that they are experiencing ...age-related changes in multiple organ systems, including the brain, which complicates decisions about systemic therapy and assessments of survivorship outcomes. There is a consistent body of evidence from studies that use neuropsychological testing and neuroimaging that supports the existence of impairment following systemic therapy in selected cognitive domains among some older patients with cancer. Impairment in one or more cognitive domains could have important effects in the daily lives of older patients. However, an imperfect understanding of the precise biologic mechanisms underlying cognitive impairment after systemic treatment precludes development of validated methods for predicting which older patients are at risk. From what is known, risks may include lifestyle factors such as smoking, genetic predisposition, and specific comorbidities such as diabetes and cardiovascular disease. Risk also interacts with physiologic and cognitive reserve, because even at the same chronological age and with the same number of illnesses, older patients vary from having high reserve (ie, biologically younger than their age) to being frail (biologically older than their age). Surveillance for the presence of cognitive impairment is also an important component of long-term survivorship care with older patients. Increasing the workforce of cancer care providers who have geriatrics training or who are working within multidisciplinary teams that have this type of expertise would be one avenue toward integrating assessment of the cognitive effects of cancer systemic therapy into routine clinical practice.
Despite trials of mammography and widespread use, optimal screening policy is controversial.
To evaluate U.S. breast cancer screening strategies.
6 models using common data elements.
National data on ...age-specific incidence, competing mortality, mammography characteristics, and treatment effects.
A contemporary population cohort.
Lifetime.
Societal.
20 screening strategies with varying initiation and cessation ages applied annually or biennially.
Number of mammograms, reduction in deaths from breast cancer or life-years gained (vs. no screening), false-positive results, unnecessary biopsies, and overdiagnosis.
The 6 models produced consistent rankings of screening strategies. Screening biennially maintained an average of 81% (range across strategies and models, 67% to 99%) of the benefit of annual screening with almost half the number of false-positive results. Screening biennially from ages 50 to 69 years achieved a median 16.5% (range, 15% to 23%) reduction in breast cancer deaths versus no screening. Initiating biennial screening at age 40 years (vs. 50 years) reduced mortality by an additional 3% (range, 1% to 6%), consumed more resources, and yielded more false-positive results. Biennial screening after age 69 years yielded some additional mortality reduction in all models, but overdiagnosis increased most substantially at older ages.
Varying test sensitivity or treatment patterns did not change conclusions.
Results do not include morbidity from false-positive results, patient knowledge of earlier diagnosis, or unnecessary treatment.
Biennial screening achieves most of the benefit of annual screening with less harm. Decisions about the best strategy depend on program and individual objectives and the weight placed on benefits, harms, and resource considerations.
National Cancer Institute.
Reply to S. Yang et al Carroll, Judith E; Mandelblatt, Jeanne S; Breen, Elizabeth C
Journal of clinical oncology,
2023-Apr-20, 2023-04-20, 20230420, Letnik:
41, Številka:
12
Journal Article
Background
To determine long‐term quality‐of‐life (QOL) trajectories among breast cancer survivors aged 65+ (older) evaluating the effects of personality and social support.
Methods
Older women ...(N = 1280) newly examined with invasive, nonmetastatic breast cancer completed baseline assessments. Follow‐up data were collected 6 and 12 months later and then annually for up to 7 years (median 4.5 years). Quality of life was assessed using EORTC‐QLQ‐C30 emotional, physical, and cognitive scales. Optimism (Life Orientation Test), Coping (Brief COPE), and social support (Medical Outcomes Study) were assessed at baseline. Group‐based trajectory modeling identified QOL trajectories; multinomial regression evaluated effects of predictors on trajectory groups. Age, education, systemic therapy, comorbidity, and reported precancer function (SF‐12) were considered as controlling variables.
Results
Three trajectories were identified for each QOL domain: “maintained high,” “phase shift” (lower but parallel scores to “maintained high” group), and “accelerated decline” (lowest baseline scores and steepest decline). Accelerated decline in emotional, physical, and cognitive function was seen in 6.9%, 31.8%, and 7.6% of older survivors, respectively. Maladaptive coping and lower social support increased adjusted odds of being in the accelerated decline group for all QOL domains; lower optimism was only related to decline in emotional function. Chemotherapy was related to physical and cognitive but not emotional function trajectories.
Conclusions
Personality and social resources affect the course of long‐term emotional well‐being of older breast cancer survivors; treatment is more important for physical and cognitive than emotional function. Early identification of those vulnerable to deterioration could facilitate clinical and psychological support.
Purpose
Breast cancer patients aged 65+ (“older”) vary in frailty status. We tested whether a deficits accumulation frailty index predicted long-term mortality.
Methods
Older patients (
n
= 1280) ...with non-metastatic, invasive breast cancer were recruited from 78 Alliance sites from 2004 to 2011, with follow-up to 2015. Frailty categories (robust, pre-frail, and frail) were based on 35 baseline illness and function items. Cox proportional hazards and competing risk models were used to calculate all-cause and breast cancer-specific mortality for up to 7 years, respectively. Potential covariates included demographic, psychosocial, and clinical factors, diagnosis year, and care setting.
Results
Patients were 65–91 years old. Most (76.6%) were robust; 18.3% were pre-frail, and 5.1% frail. Robust patients tended to receive more chemotherapy ± hormonal therapy (vs. hormonal) than pre-frail or frail patients (45% vs. 37 and 36%,
p
= 0.06), and had the highest adherence to hormonal therapy. The adjusted hazard ratios for all-cause mortality (
n
= 209 deaths) were 1.7 (95% CI 1.2–2.4) and 2.4 (95% CI 1.5–4.0) for pre-frail and frail versus robust women, respectively, with an absolute mortality difference of 23.5%. The adjusted hazard of breast cancer death (
n
−99) was 3.1 (95% CI 1.6–5.8) times higher for frail versus robust patients (absolute difference of 14%). Treatment differences did not account for the relationships between frailty and mortality.
Conclusions
Most older breast cancer patients are robust and could consider chemotherapy where otherwise indicated. Patients who are frail or pre-frail have elevated long-term all-cause and breast cancer mortality. Frailty indices could be useful for treatment decision-making and care planning with older patients.
Screening mammography guidelines do not explicitly consider racial differences in breast cancer epidemiology, treatment, and survival.
To compare tradeoffs of screening strategies in Black women ...versus White women under current guidelines.
An established model from the Cancer Intervention and Surveillance Modeling Network simulated screening outcomes using race-specific inputs for subtype distribution; breast density; mammography performance; age-, stage-, and subtype-specific treatment effects; and non-breast cancer mortality.
United States.
A 1980 U.S. birth cohort of Black and White women.
Screening strategies until age 74 years with varying initiation ages and intervals.
Outcomes included benefits (life-years gained LYG, breast cancer deaths averted, and mortality reduction), harms (mammographies, false positives, and overdiagnoses), and benefit-harm ratios (tradeoffs) by race. Efficiency (benefits per unit resource), mortality disparity reduction, and equity in tradeoffs were evaluated. Equitable strategies for Black women were defined as those with tradeoffs closest to benchmark values for screening White women biennially from ages 50 to 74 years.
Biennial screening from ages 45 to 74 years was most efficient for Black women, whereas biennial screening from ages 40 to 74 years was most equitable. Initiating screening 10 years earlier in Black versus White women reduced Black-White mortality disparities by 57% with similar LYG per mammogram for both populations. Selection of the most equitable strategy was sensitive to assumptions about disparities in real-world treatment effectiveness: The less effective treatment was for Black women, the more intensively Black women could be screened before tradeoffs fell short of those experienced by White women.
Single model.
Initiating biennial screening in Black women at age 40 years reduces breast cancer mortality disparities and yields benefit-harm ratios that are similar to tradeoffs of White women screened biennially from ages 50 to 74 years.
National Cancer Institute at the National Institutes of Health.
IMPORTANCE: Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular ...subtype could guide future decisions to reduce disease burden. OBJECTIVE: To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu). DESIGN, SETTING, AND PARTICIPANTS: Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated. EXPOSURES: Screening mammography and treatment. MAIN OUTCOMES AND MEASURES: The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment. RESULTS: In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2−, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER−/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER−/ERBB2−, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%). CONCLUSIONS AND RELEVANCE: In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.
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