Lead time in breast cancer detection and implications for periodicity of screening

Mapping the Temporal Landscape of Breast Cancer Using Epigenetic Entropy

Although generally unknown, the age of a newly diagnosed tumor encodes valuable etiologic and prognostic information. Here, we estimate the age of breast cancers, defined as the time from the start of growth to detection, using a measure of epigenetic entropy derived from genome-wide methylation arrays. Based on an ensemble of neutrally fluctuating CpG (fCpG) sites, this stochastic epigenetic clock differs from conventional clocks that measure age-related increases in methylation. We show that younger tumors exhibit hallmarks of aggressiveness, such as increased proliferation and genomic instability, whereas older tumors are characterized by elevated immune infiltration, indicative of enhanced immune surveillance. These findings suggest that the clock captures a tumor's effective growth rate resulting from the evolutionary-ecological competition between intrinsic growth potential and external systemic pressures. Because of the clock's ability to delineate old and stable from young and aggressive tumors, it has potential applications in risk stratification of early-stage breast cancers and guiding early detection efforts.

Breast cancer patients enrolled in the Swiss mammography screening program "donna" demonstrate prolonged survival

STUDY GOAL

We compared the survival rates of women with breast cancer (BC) detected within versus outside the mammography screening program (MSP) "donna".

METHODS

We merged data from the MSP with the data from corresponding cancer registries to categorize BC cases as within MSP (screen-detected and interval carcinomas) and outside the MSP. We analyzed the tumor stage distribution, tumor characteristics and the survival of the women. We further estimated hazard ratios using Cox-regressions to account for different characteristics between groups and corrected the survival rates for lead-time bias.

RESULTS

We identified 1057 invasive (ICD-10: C50) and in-situ (D05) BC cases within the MSP and 1501 outside the MSP between 2010 and 2019 in the Swiss cantons of St. Gallen and Grisons. BC within the MSP had a higher share of stage I carcinoma (46.5% vs. 33.0%; p < 0.01), a smaller (mean) tumor size (19.1 mm vs. 24.9 mm, p < 0.01), and fewer recurrences and metastases in the follow-up period (6.7% vs. 15.6%, p < 0.01). The 10-year survival rates were 91.4% for women within and 72.1% for women outside the MSP (p < 0.05). Survival difference persisted but decreased when women within the same tumor stage were compared. Lead-time corrected hazard ratios for the MSP accounted for age, tumor size and Ki-67 proliferation index were 0.550 (95% CI 0.389, 0.778; p < 0.01) for overall survival and 0.469 (95% CI 0.294, 0.749; p < 0.01) for BC related survival.

CONCLUSION

Women participating in the "donna" MSP had a significantly higher overall and BC related survival rate than women outside the program. Detection of BC at an earlier tumor stage only partially explains the observed differences.

Breast cancer distant recurrence lead time interval by detection method in an institutional cohort

BACKGROUND

Lead time, the interval between screen detection and when a disease would have become clinically evident, has been cited to explain longer survival times in mammography detected breast cancer cases (BC).

METHODS

An institutional retrospective cohort study of BC outcomes related to detection method (mammography (MamD) vs. patient (PtD)). Cases were first primary invasive stage I-III BC, age 40-74 years (n = 6603), 1999-2016. Survival time was divided into 1) distant disease-free interval (DDFI) and 2) distant disease-specific survival (DDSS) as two separate time interval outcomes. We measured statistical association between detection method and diagnostic, treatment and outcome variables using bivariate comparisons, Cox proportional hazards analyses and mean comparisons. Outcomes were distant recurrence (n = 422), DDFI and DDSS.

RESULTS

39% of cases were PtD (n = 2566) and 61% were MamD (n = 4037). MamD cases had a higher percentage of Stage I tumors [MamD 69% stage I vs. PtD 31%, p < .001]. Rate of distant recurrence was 11% among PtD BC cases (n = 289) vs. 3% of MamD (n = 133) (p < .001). Order of factor entry into the distant recurrence time interval (DDFI) model was 1) TNM stage (p < .001), 2) HR/HER2 status (p < .001), 3) histologic grade (p = .005) and 4) detection method (p < .001). Unadjusted PtD DDFI mean time was 4.34 years and MamD 5.52 years (p < .001), however when stratified by stage, the most significant factor relative to distant recurrence, there was no significant difference between PtD and MamD BC. Distant disease specific survival time did not differ by detection method.

CONCLUSION

We observed breast cancer distant disease-free interval to be primarily associated with stage at diagnosis and tumor characteristics with less contribution of detection method to the full model. Patient and mammography detected breast cancer mean lead time to distant recurrence differed significantly by detection method for all stages but not significantly within stage with no difference in time from distant recurrence to death. Lead time difference related to detection method appears to be present but may be less influential than other factors in distant disease-free and disease specific survival.

Sampling-based Markov regression model for multistate disease progression: Applications to population-based cancer screening program

To develop personalized screening and surveillance strategies, the information required to superimpose state-specific covariates into the multi-step progression of disease natural history often relies on the entire population-based screening data, which are costly and infeasible particularly when a new biomarker is proposed. Following Prentice's case-cohort concept, a non-standard case-cohort design from a previous study has been adapted for constructing multistate disease natural history with two-stage sampling. Nonetheless, the use of data only from first screens may invoke length-bias and fail to consider the test sensitivity. Therefore, a new sampling-based Markov regression model and its variants are proposed to accommodate additional subsequent follow-up data on various detection modes to construct state-specific covariate-based multistate disease natural history with accuracy and efficiency. Computer simulation algorithms for determining the required sample size and the sampling fraction of each detection mode were developed either through power function or the capacity of screening program. The former is illustrated with breast cancer screening data from which the effect size and the required sample size regarding the effect of BRCA on multistate outcome of breast cancer were estimated. The latter is applied to population-based colorectal cancer screening data to identify the optimal sampling fraction of each detection mode.

Estimating lead-time bias in lung cancer diagnosis of patients with previous cancers

Surprisingly, survival from a diagnosis of lung cancer has been found to be longer for those who experienced a previous cancer than for those with no previous cancer. A possible explanation is lead-time bias, which, by advancing the time of diagnosis, apparently extends survival among those with a previous cancer even when they enjoy no real clinical advantage. We propose a discrete parametric model to jointly describe survival in a no-previous-cancer group (where, by definition, lead-time bias cannot exist) and in a previous-cancer group (where lead-time bias is possible). We model the lead time with a negative binomial distribution and the post-lead-time survival with a linear spline on the logit hazard scale, which allows for survival to differ between groups even in the absence of bias; we denote our model Logit-Spline/Negative Binomial. We fit Logit-Spline/Negative Binomial to a propensity-score matched subset of the Surveillance, Epidemiology, and End Results-Medicare linked data set, conducting sensitivity analyses to assess the effects of key assumptions. With lung cancer-specific death as the end point, the estimated mean lead time is roughly 11 months for stage I&II patients; with overall survival, it is roughly 3.4 months in stage I&II. For patients with higher-stage lung cancers, the mean lead time is 1 month or less for both outcomes. Accounting for lead-time bias reduces the survival advantage of the previous-cancer group when one exists, but it does not nullify it in all cases.

The impact of the Polish mass breast cancer screening program on prognosis in the Pomeranian Province

INTRODUCTION

Mammographic screening results in diagnosis of less advanced breast cancer (BC). A meta-analysis of randomized clinical trials confirmed that BC screening reduces mortality. In 2007, the National Breast Cancer Screening Program (NBCSP) was established in Poland with the crucial aim of reducing mortality from BC. The purpose of this study was to assess the impact of participation in the NBCSP on prognosis.

MATERIAL AND METHODS

A single institution, non-randomized retrospective study was undertaken. The study population comprised 643 patients with BC treated in the Department of Surgical Oncology (DSO) at the Medical University of Gdansk over a 4-year period, from 01.01.2007 until 31.12.2010. Patients were divided into two groups: group A - patients who participated in the NBCSP (n = 238, 37.0%); and group B - patients who did not participate in the NBCSP (n = 405, 63.0%).

RESULTS

Statistical analysis revealed that group A displayed a less advanced AJCC stage (more patients in AJCC stage I, p = 0.002), lower tumor diameter (more patients with pT1, p = 0.006, and pT < 15 mm, p = 0.008) and a lower incidence of metastases to axillary lymph nodes (more patients with pNO, p = 0.01). From 2009 to 2010 the NBCSP revealed a statistically significant benefit - significantly more patients in stage 0 + I (60.7% vs. 48.8%, p = 0.018) and with tumors pT < 15 mm (48.8% vs. 35.1%, p = 0.011) were observed in group A.

CONCLUSIONS

The study results revealed the beneficial impact of the NBCSP. Superior prognostic factors and favorable staging were observed in women who participated in the NBCSP.

Clarifying the debate on population-based screening for breast cancer with mammography: A systematic review of randomized controlled trials on mammography with Bayesian meta-analysis and causal model

BACKGROUND

The recent controversy about using mammography to screen for breast cancer based on randomized controlled trials over 3 decades in Western countries has not only eclipsed the paradigm of evidence-based medicine, but also puts health decision-makers in countries where breast cancer screening is still being considered in a dilemma to adopt or abandon such a well-established screening modality.

METHODS

We reanalyzed the empirical data from the Health Insurance Plan trial in 1963 to the UK age trial in 1991 and their follow-up data published until 2015. We first performed Bayesian conjugated meta-analyses on the heterogeneity of attendance rate, sensitivity, and over-detection and their impacts on advanced stage breast cancer and death from breast cancer across trials using Bayesian Poisson fixed- and random-effect regression model. Bayesian meta-analysis of causal model was then developed to assess a cascade of causal relationships regarding the impact of both attendance and sensitivity on 2 main outcomes.

RESULTS

The causes of heterogeneity responsible for the disparities across the trials were clearly manifested in 3 components. The attendance rate ranged from 61.3% to 90.4%. The sensitivity estimates show substantial variation from 57.26% to 87.97% but improved with time from 64% in 1963 to 82% in 1980 when Bayesian conjugated meta-analysis was conducted in chronological order. The percentage of over-detection shows a wide range from 0% to 28%, adjusting for long lead-time. The impacts of the attendance rate and sensitivity on the 2 main outcomes were statistically significant. Causal inference made by linking these causal relationships with emphasis on the heterogeneity of the attendance rate and sensitivity accounted for the variation in the reduction of advanced breast cancer (none-30%) and of mortality (none-31%). We estimated a 33% (95% CI: 24-42%) and 13% (95% CI: 6-20%) breast cancer mortality reduction for the best scenario (90% attendance rate and 95% sensitivity) and the poor scenario (30% attendance rate and 55% sensitivity), respectively.

CONCLUSION

Elucidating the scenarios from high to low performance and learning from the experiences of these trials helps screening policy-makers contemplate on how to avoid errors made in ineffective studies and emulate the effective studies to save women lives.

Predicting the benefit of screening for disease

To evaluate the benefits and risks associated with screening for disease, a model is developed to characterize the changes in incidence and survival distributions effected by a screening program. Screening is presumed to increase survival by resulting in diagnosis of disease at earlier stages. All disease states in the model are observable, thus facilitating application to empirical data. An example of such an application using data from a breast cancer detection project is given for the case of one screening for two-stage disease having Weibull-distributed diagnosis times.

Predicting the benefit of screening for disease

To evaluate the benefits and risks associated with screening for disease, a model is developed to characterize the changes in incidence and survival distributions effected by a screening program. Screening is presumed to increase survival by resulting in diagnosis of disease at earlier stages. All disease states in the model are observable, thus facilitating application to empirical data. An example of such an application using data from a breast cancer detection project is given for the case of one screening for two-stage disease having Weibull-distributed diagnosis times.

The theory of periodic screening II: doubly bounded recurrence times and mean lead time and detection probability estimation

Additional theory important in the design and evaluation of a periodic screening program is presented. The distributions of doubly bounded preclinical state forward and backward recurrence times of the stochastic screening model are derived. Properties of these distributions are used to obtain an expression for estimating the mean lead time gained by screening, an alternative theoretical expression for the mean lead time and an equation for calculating an estimate of the probability of detecting preclinical disease.

The theory of periodic screening II: doubly bounded recurrence times and mean lead time and detection probability estimation

Additional theory important in the design and evaluation of a periodic screening program is presented. The distributions of doubly bounded preclinical state forward and backward recurrence times of the stochastic screening model are derived. Properties of these distributions are used to obtain an expression for estimating the mean lead time gained by screening, an alternative theoretical expression for the mean lead time and an equation for calculating an estimate of the probability of detecting preclinical disease.

Quantifying Gains in the War on Cancer Due to Improved Treatment and Earlier Detection

INTRODUCTION

There have been significant improvements in both treatment and screening efforts for many types of cancer over the past decade. However, the effect of these advancements on the survival of cancer patients is unknown, and many question the value of both new treatments and screening efforts.

METHODS

This study uses a retrospective analysis of SEER Registry data to quantify reductions in mortality rates for cancer patients diagnosed between 1997 and 2007. Using variation in trends in mortality rates by stage of diagnosis across cancer types, we use logistic regression to decompose separate survival gains into those attributable to advances in treatment versus advances in detection. We estimate the gains in survival due to gains in both treatment and detection overall and separately for 15 of the most common cancer types.

RESULTS

We estimate that 3-year cancer-related mortality of cancer patients fell 16.7% from 1997 to 2007. Overall, advances in treatment reduced mortality rates by approximately 12.2% while advances in early detection reduced mortality rates by 4.5%. The relative importance of treatment and detection varied across cancer types. Improvements in detection were most important for thyroid, prostate and kidney cancer. Improvements in treatment were most important for non-Hodgkins lymphoma, lung cancer and myeloma.

CONCLUSION

Both improved treatment options and better early detection have led to significant survival gains for cancer patients diagnosed from 1997 to 2007, generating considerable social value over this time period.

Age at diagnosis in relation to survival following breast cancer: a cohort study

Background

Age is an important risk factor for breast cancer, but previous data has been contradictory on whether patient age at diagnosis is also related to breast cancer survival. The present study evaluates age at diagnosis as a prognostic factor for breast cancer on a large cohort of patients at a single institution.

Methods

All 4,453 women diagnosed with breast cancer in Malmö University Hospital, Sweden between 1961 and 1991 were followed up on for 10 years with regards to breast cancer-specific mortality (BCSM) in different age groups. Corresponding relative risks (RR), with 95% confidence intervals, were obtained using Cox’s proportional hazards analysis. All analyses were adjusted for potential confounders and stratified for axillary lymph node involvement (ALNI) and diagnostic period.

Results

As compared to women aged 40 to 49 years, those who were aged under 40 (RR: 1.40; 95% CI: 1.04 to 1.88) and 80 or more years (RR: 1.80; 95% CI: 1.45 to 2.25) had a statistically significant higher 10-year mortality rate. When adjusted for potential confounders, including stage at diagnosis, the associations only remained statistically significant for women aged 80 years or more. In the analyses stratified on ALNI, ALNI-negative women under 40 years had a statistically significant higher five-year mortality rate (RR: 2.65; 95% CI: 1.23 to 5.70). In the analyses stratified on diagnostic period, the positive association between women aged under 40 or aged 80 or more years and high BCSM rate remained, with statistically significant results for women aged 80 years or more in all periods.

Conclusions

Women under 40 years of age had a poor prognosis, and this association was strongest among young women with axillary lymph node negative breast cancer. An age of 80 years or more was a prognostic factor for poor survival, independent of stage at diagnosis and diagnostic period.

Patterns of changing cancer risks with time since diagnosis of a sibling

Family history is a well-known risk factor for many cancers. However, it is important to know if/how the familial risk of cancer changes over time. For each of four major cancers (colorectal, breast, prostate and melanoma), we identified siblings of cancer patients (case siblings) and siblings of matched cancer-free controls sampled from Swedish population-based registers. Effects of age and time since diagnosis on sibling risks were examined using Poisson regression and presented graphically as smoothed hazard ratios (HRs). Screening effects were investigated by comparing hazards before/after the introduction of mammography for breast cancer and prostate-specific antigen (PSA) testing for prostate cancer. Case siblings had higher cancer incidence than control siblings for all cancers at all ages, with overall incidence rate ratios (IRRs) of 2.41 (95% confidence interval 2.14-2.71) for colorectal cancer, 2.37 (2.24-2.52) for breast cancer, 3.69 (3.46-3.93) for prostate cancer and 3.20 (2.72-3.76) for melanoma. Risks were highest in siblings who were young when the first cancer was diagnosed in the family, with siblings aged 30-40 having IRR 9.05 (3.03-27.00) for colorectal cancer and 4.30 (2.87-6.45) for breast cancer. Smoothed HRs remained fairly constant for up to 20 years except for prostate cancer, where the HR decreased steeply during the first few years. After introduction of PSA testing, men had higher incidence of prostate cancer shortly after diagnosis in a brother, but no such screening effect was found for breast cancer. Our findings can help inform the screening and counseling of family members of cancer patients.

Screening for breast cancer with mammography

BACKGROUND

A variety of estimates of the benefits and harms of mammographic screening for breast cancer have been published and national policies vary.

OBJECTIVES

To assess the effect of screening for breast cancer with mammography on mortality and morbidity.

SEARCH METHODS

We searched PubMed (22 November 2012) and the World Health Organization's International Clinical Trials Registry Platform (22 November 2012).

SELECTION CRITERIA

Randomised trials comparing mammographic screening with no mammographic screening.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted data. Study authors were contacted for additional information.

MAIN RESULTS

Eight eligible trials were identified. We excluded a trial because the randomisation had failed to produce comparable groups.The eligible trials included 600,000 women in the analyses in the age range 39 to 74 years. Three trials with adequate randomisation did not show a statistically significant reduction in breast cancer mortality at 13 years (relative risk (RR) 0.90, 95% confidence interval (CI) 0.79 to 1.02); four trials with suboptimal randomisation showed a significant reduction in breast cancer mortality with an RR of 0.75 (95% CI 0.67 to 0.83). The RR for all seven trials combined was 0.81 (95% CI 0.74 to 0.87). We found that breast cancer mortality was an unreliable outcome that was biased in favour of screening, mainly because of differential misclassification of cause of death. The trials with adequate randomisation did not find an effect of screening on total cancer mortality, including breast cancer, after 10 years (RR 1.02, 95% CI 0.95 to 1.10) or on all-cause mortality after 13 years (RR 0.99, 95% CI 0.95 to 1.03).Total numbers of lumpectomies and mastectomies were significantly larger in the screened groups (RR 1.31, 95% CI 1.22 to 1.42), as were number of mastectomies (RR 1.20, 95% CI 1.08 to 1.32). The use of radiotherapy was similarly increased whereas there was no difference in the use of chemotherapy (data available in only two trials).

AUTHORS' CONCLUSIONS

If we assume that screening reduces breast cancer mortality by 15% and that overdiagnosis and overtreatment is at 30%, it means that for every 2000 women invited for screening throughout 10 years, one will avoid dying of breast cancer and 10 healthy women, who would not have been diagnosed if there had not been screening, will be treated unnecessarily. Furthermore, more than 200 women will experience important psychological distress including anxiety and uncertainty for years because of false positive findings. To help ensure that the women are fully informed before they decide whether or not to attend screening, we have written an evidence-based leaflet for lay people that is available in several languages on www.cochrane.dk. Because of substantial advances in treatment and greater breast cancer awareness since the trials were carried out, it is likely that the absolute effect of screening today is smaller than in the trials. Recent observational studies show more overdiagnosis than in the trials and very little or no reduction in the incidence of advanced cancers with screening.

Individually tailored screening of breast cancer with genes, tumour phenotypes, clinical attributes, and conventional risk factors

Background:

We demonstrated how to comprehensively translate the existing and updated scientific evidence on genomic discovery, tumour phenotype, clinical features, and conventional risk factors in association with breast cancer to facilitate individually tailored screening for breast cancer.

Methods:

We proposed an individual-risk-score-based approach that translates state-of-the-art scientific evidence into the initiators and promoters affecting onset and subsequent progression of breast tumour underpinning a novel multi-variable three-state temporal natural history model. We applied such a quantitative approach to a population-based Taiwanese women periodical screening cohort.

Results:

Risk prediction for pre-clinical detectable and clinical-detected breast cancer was made by the two risk scores to stratify the underlying population to assess the optimal age to begin screening and the inter-screening interval for each category and to ascertain which high-risk group requires an alternative image technique. The risk-score-based approach significantly reduced the interval cancer rate as a percentage of the expected rate in the absence of screening by 30% and also reduced 8.2% false positive cases compared with triennial universal screening.

Conclusion:

We developed a novel quantitative approach following the principle of translational research to provide a roadmap with state-of-the-art genomic discovery and clinical parameters to facilitate individually tailored breast cancer screening.

Molecular profiles of screen detected vs. symptomatic breast cancer and their impact on survival: results from a clinical series

BACKGROUND

Stage shift is widely considered a major determinant of the survival benefit conferred by breast cancer screening. However, factors and mechanisms underlying such a prognostic advantage need further clarification. We sought to compare the molecular characteristics of screen detected vs. symptomatic breast cancers and assess whether differences in tumour biology might translate into survival benefit.

METHODS

In a clinical series of 448 women with operable breast cancer, the Kaplan-Meier method and the log-rank test were used to estimate the likelihood of cancer recurrence and death. The Cox proportional hazard model was used for the multivariate analyses including mode of detection, age at diagnosis, tumour size, and lymph node status. These same models were applied to subgroups defined by molecular subtypes.

RESULTS

Screen detected breast cancers tended to show more favourable clinicopathological features and survival outcomes compared to symptomatic cancers. The luminal A subtype was more common in women with mammography detected tumours than in symptomatic patients (68.5 vs. 59.0%, p=0.04). Data analysis across categories of molecular subtypes revealed significantly longer disease free and overall survival for screen detected cancers with a luminal A subtype only (p=0.01 and 0.02, respectively). For women with a luminal A subtype, the independent prognostic role of mode of detection on recurrence was confirmed in Cox proportional hazard models (p=0.03). An independent role of modality of detection on survival was also suggested (p=0.05).

CONCLUSIONS

Molecular subtypes did not substantially explain the differences in survival outcomes between screened and symptomatic patients. However, our results suggest that molecular profiles might play a role in interpreting such differences at least partially.Further studies are warranted to reinterpret the efficacy of screening programmes in the light of tumour biology.

Comparison between screen-detected and symptomatic breast cancers according to molecular subtypes

Breast cancer screening programs make it possible to detect early cancer, thus reducing breast cancer mortality. We studied the clinicopathologic characteristics and prognosis of screen-detected invasive breast cancer compared with symptomatic breast cancer. And we compared the result according to molecular subtypes (luminal A, luminal B, Her2, and triple negative), with the goal of identifying the role of screening in each subtypes. From January 2002 to June 2008, 3,141 patients who underwent surgery for the treatment of invasive ductal carcinoma at Samsung Medical Center were included. Among them, 1,025 patients were screen-detected, and 2,116 patients who were screened over 2 years or never were symptomatic. We retrospectively reviewed the clinical and pathologic data. Screen-detected breast cancer was associated with older age, smaller tumor size, more hormone-receptor positive, less lymph node involvement, earlier stage, and reduced mortality compared with symptomatic breast cancer (P < 0.001). According to the molecular subtype, luminal A was most common (63.6%) and showed the most obvious survival benefit in screen-detected tumors in comparison with symptomatic tumors (5-year OS: 99.7 vs. 96.5%, 5-year DFS: 96.4 vs. 90.7%). Screen detection was independently associated with improved overall and disease-free survival outcomes after adjustment for covariates (HR 0.32, P = 0.035; HR 0.58, P = 0.020, respectively) only in the luminal A subtype. Differences in pathological features such as tumor size, nodal status, grade, and age at diagnosis with different molecular subtype distributions may explain the survival advantage of patients with screen-detected breast cancer. Screening programs seem to have a different efficacy depending on the molecular subtype of the breast cancer, especially in the luminal A subtype, for which screen detection acts as an independent prognostic factor itself.

Independent prognostic value of screen detection in invasive breast cancer

BACKGROUND

Mammographic screening has led to a proportional shift toward earlier-stage breast cancers at presentation. We assessed whether the method of detection provides prognostic information above and beyond standard prognostic factors and investigated the accuracy of predicted overall and breast cancer-specific survival by the computer tool Adjuvant! among patients with screen-detected, interval, and nonscreening-related carcinomas.

METHODS

We studied 2592 patients with invasive breast cancer who were treated at the Netherlands Cancer Institute from January 1, 1990, through December 31, 2000. Overall and breast cancer-specific survival probabilities among patients with mammographically screen-detected (n = 958), interval (n = 417), and nonscreening-related (n = 1217) breast carcinomas were compared. Analyses were adjusted for clinicopathologic characteristics and adjuvant systemic therapy. Because of gradual implementation of population-based screening in the Netherlands, analyses were stratified a priori according to two periods of diagnosis. All statistical tests were two-sided.

RESULTS

Screen detection was associated with reduced mortality (adjusted hazard ratio for all-cause mortality = 0.74, 95% confidence interval = 0.63 to 0.87, P < .001, and adjusted hazard ratio for breast cancer-specific mortality = 0.62, 95% confidence interval = 0.50 to 0.78, P < .001, respectively) compared with nonscreening-related detection. The absolute adjusted reduction in breast cancer-specific mortality was 7% at 10 years. The prognostic value of the method of detection was independent of the period of diagnosis and was similar across tumor size and lymph node status categories, indicating its prognostic value beyond stage migration. Adjuvant! underestimated breast cancer-specific survival in patients with screen-detected (-3.2%) and interval carcinomas (-5.4%).

CONCLUSIONS

Screen detection was found to be independently associated with better prognosis for overall and breast cancer-specific survival and to provide prognostic information beyond stage migration among patients with invasive breast cancer. We propose that the method of detection should be taken into account when estimating individual prognosis.

Screening for breast cancer with mammography

BACKGROUND

A variety of estimates of the benefits and harms of mammographic screening for breast cancer have been published and national policies vary.

OBJECTIVES

To assess the effect of screening for breast cancer with mammography on mortality and morbidity.

SEARCH STRATEGY

We searched PubMed (November 2008).

SELECTION CRITERIA

Randomised trials comparing mammographic screening with no mammographic screening.

DATA COLLECTION AND ANALYSIS

Both authors independently extracted data. Study authors were contacted for additional information.

MAIN RESULTS

Eight eligible trials were identified. We excluded a biased trial and included 600,000 women in the analyses. Three trials with adequate randomisation did not show a significant reduction in breast cancer mortality at 13 years (relative risk (RR) 0.90, 95% confidence interval (CI) 0.79 to 1.02); four trials with suboptimal randomisation showed a significant reduction in breast cancer mortality with an RR of 0.75 (95% CI 0.67 to 0.83). The RR for all seven trials combined was 0.81 (95% CI 0.74 to 0.87). We found that breast cancer mortality was an unreliable outcome that was biased in favour of screening, mainly because of differential misclassification of cause of death. The trials with adequate randomisation did not find an effect of screening on cancer mortality, including breast cancer, after 10 years (RR 1.02, 95% CI 0.95 to 1.10) or on all-cause mortality after 13 years (RR 0.99, 95% CI 0.95 to 1.03).Numbers of lumpectomies and mastectomies were significantly larger in the screened groups (RR 1.31, 95% CI 1.22 to 1.42) for the two adequately randomised trials that measured this outcome; the use of radiotherapy was similarly increased.

AUTHORS' CONCLUSIONS

Screening is likely to reduce breast cancer mortality. As the effect was lowest in the adequately randomised trials, a reasonable estimate is a 15% reduction corresponding to an absolute risk reduction of 0.05%. Screening led to 30% overdiagnosis and overtreatment, or an absolute risk increase of 0.5%. This means that for every 2000 women invited for screening throughout 10 years, one will have her life prolonged and 10 healthy women, who would not have been diagnosed if there had not been screening, will be treated unnecessarily. Furthermore, more than 200 women will experience important psychological distress for many months because of false positive findings. It is thus not clear whether screening does more good than harm. To help ensure that the women are fully informed of both benefits and harms before they decide whether or not to attend screening, we have written an evidence-based leaflet for lay people that is available in several languages on www.cochrane.dk.

Method of detection and breast cancer survival disparities in Hispanic women

BACKGROUND

Hispanic women in New Mexico (NM) are more likely than non-Hispanic women to die of breast cancer-related causes. We determined whether survival differences between Hispanic and non-Hispanic women might be attributable to the method of detection, an independent breast cancer prognostic factor in previous studies.

METHODS

White women diagnosed with invasive breast cancer from 1995 through 2004 were identified from NM Surveillance Epidemiology End Results (SEER) files (n = 5,067) and matched to NM Mammography Project records. Method of cancer detection was categorized as "symptomatic" or "screen-detected." The proportion of Hispanic survival disparity accounted for by included variables was assessed using Cox models.

RESULTS

In the median follow-up of 87 months, 490 breast cancer deaths occurred. Symptomatic versus screen-detection was classifiable for 3,891 women (76.8%), and was independently related to breast cancer-specific survival [hazard ratio (HR), 1.6; 95% confidence interval (95% CI), 1.3-2.0]. Hispanic women had a 1.5-fold increased risk of breast cancer-related death, relative to non-Hispanic women (95% CI, 1.2-1.8). After adjustment for detection method, the Hispanic HR declined from 1.50 to 1.45 (10%), but after inclusion of other prognostic indicators the Hispanic HR equaled 1.23 (95% CI, 1.01-1.48).

CONCLUSIONS

Although the Hispanic HR declined 50% after adjustment, the decrease was largely due to adverse tumor prognostic characteristics.

IMPACT

Reduction of disparate survival in Hispanic women may rely not only on increased detection of tumors when asymptomatic but on the development of greater understanding of biological factors that predispose to poor prognosis tumors.

Screening for breast cancer with mammography

BACKGROUND

A variety of estimates of the benefits and harms of mammographic screening for breast cancer have been published and national policies vary.

OBJECTIVES

To assess the effect of screening for breast cancer with mammography on mortality and morbidity.

SEARCH STRATEGY

We searched PubMed (November 2008).

SELECTION CRITERIA

Randomised trials comparing mammographic screening with no mammographic screening.

DATA COLLECTION AND ANALYSIS

Both authors independently extracted data. Study authors were contacted for additional information.

MAIN RESULTS

Eight eligible trials were identified. We excluded a biased trial and included 600,000 women in the analyses. Three trials with adequate randomisation did not show a significant reduction in breast cancer mortality at 13 years (relative risk (RR) 0.90, 95% confidence interval (CI) 0.79 to 1.02); four trials with suboptimal randomisation showed a significant reduction in breast cancer mortality with an RR of 0.75 (95% CI 0.67 to 0.83). The RR for all seven trials combined was 0.81 (95% CI 0.74 to 0.87). We found that breast cancer mortality was an unreliable outcome that was biased in favour of screening, mainly because of differential misclassification of cause of death. The trials with adequate randomisation did not find an effect of screening on cancer mortality, including breast cancer, after 10 years (RR 1.02, 95% CI 0.95 to 1.10) or on all-cause mortality after 13 years (RR 0.99, 95% CI 0.95 to 1.03).Numbers of lumpectomies and mastectomies were significantly larger in the screened groups (RR 1.31, 95% CI 1.22 to 1.42) for the two adequately randomised trials that measured this outcome; the use of radiotherapy was similarly increased.

AUTHORS' CONCLUSIONS

Screening is likely to reduce breast cancer mortality. As the effect was lowest in the adequately randomised trials, a reasonable estimate is a 15% reduction corresponding to an absolute risk reduction of 0.05%. Screening led to 30% overdiagnosis and overtreatment, or an absolute risk increase of 0.5%. This means that for every 2000 women invited for screening throughout 10 years, one will have her life prolonged and 10 healthy women, who would not have been diagnosed if there had not been screening, will be treated unnecessarily. Furthermore, more than 200 women will experience important psychological distress for many months because of false positive findings. It is thus not clear whether screening does more good than harm. To help ensure that the women are fully informed of both benefits and harms before they decide whether or not to attend screening, we have written an evidence-based leaflet for lay people that is available in several languages on www.cochrane.dk.

Molecular characteristics of screen-detected vs symptomatic breast cancers and their impact on survival

Background:

Several recent studies have shown that screen detection remains an independent prognostic factor after adjusting for disease stage at presentation. This study compares the molecular characteristics of screen-detected with symptomatic breast cancers to identify if differences in tumour biology may explain some of the survival benefit conferred by screen detection.

Methods:

A total of 1379 women (aged 50–70 years) with invasive breast cancer from a large population-based case–control study were included in the analysis. Individual patient data included tumour size, grade, lymph node status, adjuvant therapy, mammographic screening status and mortality. Immunohistochemistry was performed on tumour samples using 11 primary antibodies to define five molecular subtypes. The effect of screen detection compared with symptomatic diagnosis on survival was estimated after adjustment for grade, nodal status, Nottingham Prognostic Index (NPI) and the molecular markers.

Results:

Fifty-six per cent of the survival benefit associated with screen-detected breast cancer was accounted for by a shift in the NPI, a further 3–10% was explained by the biological variables and more than 30% of the effect remained unexplained.

Conclusion:

Currently known biomarkers remain limited in their ability to explain the heterogeneity of breast cancer fully. A more complete understanding of the biological profile of breast tumours will be necessary to assess the true impact of tumour biology on the improvement in survival seen with screen detection.

Prognostic role of detection method and its relationship with tumor biomarkers in breast cancer: the university of Texas M.D. Anderson Cancer Center experience

PURPOSE

To assess the effect of tumor detection method (screening versus symptom-based diagnosis) in predicting breast cancer survival and investigate how biological features of breast cancer are related to the tumor detection method.

PATIENTS AND METHODS

The study population consisted of 5,481 women diagnosed with primary invasive breast cancer between 1997 and 2005 and received their treatment at The University of Texas M. D. Anderson Cancer Center.

RESULTS

Patients with symptom-detected tumors had an increased risk of recurrence or death [relative risk (RR), 1.34; P = 0.006] and breast cancer-specific death (RR, 1.31; P = 0.117) than patients with screen-detected tumors after adjusting for tumor characteristics and treatments received. This relationship was especially evident among estrogen receptor (ER)-negative tumors (RR, 1.60 for breast cancer recurrence for ER-negative tumors; RR, 1.18 for ER-positive tumors). ER status and Ki-67 expression were statistically significantly associated with symptom detection rate after adjusting for patients' age, tumor stage, tumor size, and nuclear grade [odds ratio (OR) of ER negative versus ER positive, 1.35; P < 0.001; OR of Ki-67 10-30% versus <10%, 1.40; P = 0.005; OR of Ki-67 >30% versus <10%, 2.11; P < 0.001].

CONCLUSION

The method of detection was a statistically significant independent predictor of breast cancer recurrence. Information on the method of tumor detection should be collected to improve the prediction of prognosis of breast cancer patients.

Screening for breast cancer with mammography

BACKGROUND

A variety of estimates of the benefits and harms of mammographic screening for breast cancer have been published and national policies vary.

OBJECTIVES

To assess the effect of screening for breast cancer with mammography on mortality and morbidity.

SEARCH STRATEGY

We searched PubMed (June 2005).

SELECTION CRITERIA

Randomised trials comparing mammographic screening with no mammographic screening.

DATA COLLECTION AND ANALYSIS

Both authors independently extracted data. Study authors were contacted for additional information.

MAIN RESULTS

Seven completed and eligible trials involving half a million women were identified. We excluded a biased trial from analysis. Two trials with adequate randomisation did not show a significant reduction in breast cancer mortality, relative risk (RR) 0.93 (95% confidence interval 0.80 to 1.09) at 13 years; four trials with suboptimal randomisation showed a significant reduction in breast cancer mortality, RR 0.75 (0.67 to 0.83) (P = 0.02 for difference between the two estimates). RR for all six trials combined was 0.80 (0.73 to 0.88). The two trials with adequate randomisation did not find an effect of screening on cancer mortality, including breast cancer, RR 1.02 (0.95 to 1.10) after 10 years, or on all-cause mortality, RR 1.00 (0.96 to 1.04) after 13 years. We found that breast cancer mortality was an unreliable outcome that was biased in favour of screening, mainly because of differential misclassification of cause of death. Numbers of lumpectomies and mastectomies were significantly larger in the screened groups, RR 1.31 (1.22 to 1.42) for the two adequately randomised trials; the use of radiotherapy was similarly increased.

AUTHORS' CONCLUSIONS

Screening likely reduces breast cancer mortality. Based on all trials, the reduction is 20%, but as the effect is lower in the highest quality trials, a more reasonable estimate is a 15% relative risk reduction. Based on the risk level of women in these trials, the absolute risk reduction was 0.05%. Screening also leads to overdiagnosis and overtreatment, with an estimated 30% increase, or an absolute risk increase of 0.5%. This means that for every 2000 women invited for screening throughout 10 years, one will have her life prolonged. In addition, 10 healthy women, who would not have been diagnosed if there had not been screening, will be diagnosed as breast cancer patients and will be treated unnecessarily. It is thus not clear whether screening does more good than harm. Women invited to screening should be fully informed of both benefits and harms.

Rate of over-diagnosis of breast cancer 15 years after end of Malmö mammographic screening trial: follow-up study

OBJECTIVE

To evaluate the rate of over-diagnosis of breast cancer 15 years after the end of the Malmö mammographic screening trial.

DESIGN

Follow-up study.

SETTING

Malmö, Sweden.

SUBJECTS

42 283 women aged 45-69 years at randomisation.

INTERVENTIONS

Screening for breast cancer with mammography or not (controls). Screening was offered at the end of the randomisation design to both groups aged 45-54 at randomisation but not to groups aged 55-69 at randomisation.

MAIN OUTCOME MEASURES

Rate of over-diagnosis of breast cancer (in situ and invasive), calculated as incidence in the invited and control groups, during period of randomised design (period 1), during period after randomised design ended (period 2), and at end of follow-up.

RESULTS

In women aged 55-69 years at randomisation the relative rates of over-diagnosis of breast cancer (95% confidence intervals) were 1.32 (1.14 to 1.53) for period 1, 0.92 (0.79 to 1.06) for period 2, and 1.10 (0.99 to 1.22) at the end of follow-up.

CONCLUSION

Conclusions on over-diagnosis of breast cancer in the Malmö mammographic screening trial can be drawn mainly for women aged 55-69 years at randomisation whose control groups were never screened. Fifteen years after the trial ended the rate of over-diagnosis of breast cancer was 10% in this age group.

Role of Detection Method in Predicting Breast Cancer Survival: Analysis of Randomized Screening Trials

BACKGROUND

Screening mammography detects breast cancers earlier than those detected symptomatically, and so mammographically detected breast cancers tend to have better prognoses. The so-called stage shift that results from screen detection is subject to lead-time and length biases, and so earlier detection may not translate into longer survival. We used data from three large breast cancer screening trials--Health Insurance Plan (HIP) of New York and two Canadian National Breast Cancer Screening Studies (CNBSS)--to investigate survival benefits of breast cancer screening beyond stage shift. We also address whether method of detection is an independent prognostic factor in breast cancer.

METHODS

The HIP trial randomly assigned approximately 62,000 women to screening and control groups. The two CNBSS trial cohorts CNBSS-1 and CNBSS-2 included a total of 44,970 women in the screening group and 44,961 in the control group. After adjusting for stage and other tumor characteristics in a Cox proportional hazards model, survival distributions were compared by method of breast cancer detection with both univariate and multivariable analyses. All P values are two-sided.

RESULTS

Breast cancers detected by screening mammography had a shift in stage distribution to earlier stages (for HIP, P < .001; for CNBSS-1, P = .03; and for CNBSS-2, P < .001). After adjusting for tumor size, lymph node status, and disease stage in a Cox proportional hazards model, method of detection was a statistically significant independent predictor of disease-specific survival. Patients with interval cancers had a 53% (95% confidence interval [CI] = 17% to 100%) greater hazard of death from breast cancer than patients with screen-detected cancers, and patients with cancer in the control groups had a 36% (95% CI = 10% to 68%) greater hazard of death than patients with screen-detected cancer.

CONCLUSION

There was an apparent survival benefit beyond stage shift for patients with screen-detected breast cancers compared with patients with breast cancers detected otherwise. Method of detection appears to be an important prognostic factor, even after adjusting for known tumor characteristics. This finding suggests that clinical trialists should routinely collect information about method of detection.

Lung Cancer Screening: Simulations of Effects of Imperfect Detection on Temporal Dynamics

PURPOSE

To use a mathematic model to demonstrate effects of imperfect detection on temporal dynamics of radiologic lung cancer screening.

MATERIALS AND METHODS

Monte Carlo simulations of lung cancer screening programs were performed in subjects at high risk for developing cancer. The effects of detection probabilities, symptomatic presentation of tumors, tumor volume doubling time, and time between screenings were examined. Computed tomography (CT) and chest radiography models were used.

RESULTS

For imperfect detection probabilities, the percentage of subjects with cancers detected with repeated screenings decreased to a steady-state value. The transition period was the period during which screenings were performed and detection rates decreased. At steady-state repeat screening, the proportion of subjects with cancers diagnosed at screening or by means of symptomatic presentation was determined by the annual probability of developing cancer and not by the sensitivity of the screening modality. The sensitivity of the screening technique did affect detected cancer size, number of interval cancers, and total number of cancers observed. CT was used to detect more total cancers over the course of the screening program and cancers with a smaller average size; moreover, fewer interval cancers were observed with CT screening than with chest radiography screening.

CONCLUSION

Lung cancer screening with imperfect detection has a transition period between baseline screening and steady-state behavior of annual screenings. Advantages of CT screening include a decrease in the average cancer size at detection, a decrease in the number of observed interval cancers, and an increase in the total number of cancers observed. Steady-state behavior indicates that long-term trials of screening may not be necessary.

Modeling recurrence in colorectal cancer

OBJECTIVE

To assess the role of recurrence in prognosis of colon cancer, we investigated several methodologic issues, including application of classic survival analysis and Markov model.

STUDY DESIGN AND SETTING

The data were recorded by the Registry of Digestive Tumors of Côte d'Or, France, for 874 patients who had been treated by surgery between 1976 and 1984 and followed for up to 11 years. Survival analyses included the Cox proportional hazards model and its two generalizations that allow recurrence to be taken into account as a time-dependent covariate or as a competing outcome. The Markov model was used to analyze simultaneously recurrence and death.

RESULTS

The competing risks approach is not appropriate because censoring is indisputably informative. The Markov model and the Cox model, with recurrence as a time-dependent covariate, provided similar results, demonstrating the impact of age and gender on recurrence and revealing a reduction in the effect of site and stage on mortality.

CONCLUSION

A Markov multistate model seems to give new insights about the course of digestive cancer progression and into the role of recurrence in this process.

The process of metastasisation for breast cancer

To investigate the process of metastasis, primary clinical data and disease events such as metastases, local recurrence and survival (median follow-up 9.4 years) from the Munich Cancer Registry from 1978 to 1996 were analysed. Since metastases, even from small tumours, may be initiated before the diagnosis of the primary tumour, the growth of the primary tumour and metastasisation may be two autonomous processes. In our data, survival following metastases was almost unrelated to primary tumour size. However, the number of M1 cases and the time to metastasisation depended on the tumour diameter at diagnosis. The time from initiation of metastases to its diagnosis was estimated as 5.8 years. The growth of metastases was almost homogeneous. However, the growth time following metastasisation-depending on the metastases-free time, receptor status and histological grade-only varied by approximately a factor of 2. Local recurrence, above all, was an indicator of metastases. Furthermore, local recurrence may also have the potential to metastasise. Excess mortality due to local recurrence was estimated up to 9.3 years after diagnosis. Our hypothesised metastases model illustrates the importance of early detection, the concept of breast-conserving therapy and additional metastases from local recurrence. It highlights the benefits of optimal local therapy of the primary tumour and the limitations of systemic therapy. It also questions the use of axilla dissection and lymph node irradiation. Its generalisation to solid tumours may help to clarify many of the current controversial debates.

Estimating the influence of rescreening interval on the benefits associated with cancer screening: approaches and limitations

ABSTRACT Randomized controlled trials that seek to measure the ability of a screening test to lower cancer mortality generally do not provide data that bear on the relative efficacy of different screening intervals. Guidance regarding the choice of a screening interval that achieves a high level of case-finding, without being excessively costly, can be obtained from one or more of several study designs that examine the subsequent occurrence of cancer in persons who have had a negative screening test. However, each of these can potentially provide a misleading result, and so their limitations must be considered before using the data they generate to develop a rational rescreening policy.

Testing reminder and motivational telephone calls to increase screening mammography: a randomized study

BACKGROUND

Prospective randomized trials have demonstrated that motivational telephone calls increase adherence to screening mammography. To better understand the effects of motivational calls and to maximize adherence, we conducted a randomized trial among women aged 50-79 years.

METHODS

We created a stratified random sample of 5062 women due for mammograms within the Group Health Cooperative of Puget Sound, including 4099 women with prior mammography and 963 without it. We recruited and surveyed 3743 (74%) of the women before mailing a recommendation. After 2 months, 1765 (47%) of the 3743 women had not scheduled a mammogram and were randomly assigned to one of three intervention groups: a reminder post-card group (n = 590), a reminder telephone call group (n = 585), and a motivational telephone call addressing barriers group (n = 590). The telephone callers could schedule mammography. We used Cox proportional hazards models to estimate the hazard ratio (HR) and 95% confidence interval (CI) for documented mammography use by 1 year.

RESULTS

Women who received reminder calls were more likely to get mammograms (HR = 1.9; 95% CI = 1.6-2.4) than women who were mailed postcards. The motivational and reminder calls (average length, 8.5 and 3.1 minutes, respectively) had equivalent effects (HR = 0.97; 95% CI = 0.8-1.2). After we controlled for the intervention effect, women with prior mammography (n = 1277) were much more likely to get a mammogram (HR = 3.4; 95% CI = 2.7-4.3) than women without prior use (n = 488). Higher income, but not race or more education, was associated with higher adherence.

CONCLUSIONS

Reminding women to schedule an appointment was as efficacious as addressing barriers. Simple intervention groups should be included as comparison groups in randomized trials so that we better understand more complex intervention effects.

Instrumental variables when evaluating screening trials: estimating the benefit of detecting cancer by screening

When evaluating the benefit of detecting cancer by screening we try to answer the question, 'what would a screen detected subject's outcome have been if his/her cancer had progressed to clinical detection'. By 'outcome' we mean survival time, cancer size and stage, lead time effects and more. Because only an unethical study can answer it directly, researchers have attempted to answer the question indirectly using data from randomized cancer screening studies (subjects randomized to study (screened) or control (not screened)). Inferences are made by first selecting the cancer cohort (those subjects who are found to have cancer), then comparing subjects having screen detected cancers to subjects having clinically detected cancers. However, there are two difficulties with this approach: (i) because screening (intends to) detect cancers early, at the trial's end the study group contains more cancer cases than the control group and so the cancer cohort has some unidentified control subjects missing (that is, subjects having cancer during the screening period that have not yet been clinically detected); (ii) because screen detected cancers (may) differ from clinically detected cancers, the comparison group should include only a (non-identified) subset of the cancer cohort's control subjects (that is, only those control subjects having cancers that would have been screen detected). Statistical literature acknowledges these difficulties and attempts to solve them separately, but without success; those methods do not yield meaningful causal inferences and admit substantial bias. Recently, Angrist, Imbens and Rubin and Imbens and Rubin provide a framework for instrumental variable methods that we interpret as allowing us to make causal inferences with incompletely identified comparison groups. We apply their framework to evaluating cancer screening trials and find that we may simultaneously accommodate both difficulties while giving a meaningful answer to the question posed above. Using data from a breast cancer screening trial we demonstrate the general method with a variety of outcome measures and extensions.

A novel form of ascertainment bias in case-control studies of cancer screening

In case-control studies of cancer screening, some have generally admonished investigators against case definitions based on diagnosis dates because of lead-time bias. However, perhaps partly due to vagueness, the admonitions have been frequently ignored. A recurrence-time model simulates case ascertainment when diagnosis must occur within a specific calendar period. The model depends on screening test sensitivity and rate, age-specific preclinical incidence rates, and preclinical duration time and survival time distributions. For one study of sigmoidoscopic screening for colorectal cancer, when the true odds ratio is 1, its estimate is 0.50 to 0.75 under plausible assumptions. This bias can affect any observational study wherein case definition depends on diagnosis times (e.g., health-plan enrollment data). To avoid bias in observational investigations of cancer screening wherein the case definition depends on the diagnosis date, one must ensure that both screening and preclinical incidence do not occur before the case definition period.

Managed care data and public health: the experience of Group Health Cooperative of Puget Sound

Traditional group and staff model HMOs have contributed to public health investigations for decades. HMOs offer several advantages for this type of research because of their defined population and provider groups and the integrated nature of care delivery in these organizations. Traditional HMOs have also made investments in sophisticated data systems to support evidence-based care that is supported by high-quality clinical data available in automated information systems. This paper reviews why traditional HMOs are ideal places to conduct public health research and analyzes how recent market trends may threaten this role for managed care.

Empirical comparison of the results of randomized controlled trials and case-control studies in evaluating the effectiveness of screening mammography

The gold standard for evaluating screening programs is the randomized controlled trial (RCT). Case-control studies are easier to perform but their role in this area is controversial. The purpose of this article is to compare empirically the results of RCTs and case-control studies conducted to evaluate the efficacy and effectiveness of screening mammography and examine possible explanations for differences in their results. We located eight RCTs and five case-control studies of screening mammography. For women aged 40-74 years at screening, comparison of the summary risk estimates of the RCTs (0.76, 95% CI: 0.69-0.83) with that of the case-control studies (0.44, 95%, CI: 0.38-0.50) showed RCTs to have a significantly higher summary risk estimate than case-control studies (ratio = 1.74, 95% CI: 1.48-2.04). It is notable that the RCTs were compromised in most instances by low compliance rates (50-80%) in the treatment groups and by significant use of screening in the control groups (20-30%). Adjustment of the RCT results for these cross-overs yields results that are in reasonable agreement with the summary estimate for the case-control studies. These findings support the use of case-control studies to estimate the efficacy of mammographic screening where RCTs are not feasible. They suggest that the efficacy of mammography in women aged 50 years and above is somewhat greater than the effectiveness measured by the intent-to-treat analysis of RCTs.

Colorectal cancer mass-screening: estimation of faecal occult blood test sensitivity, taking into account cancer mean sojourn time

Mass screening using the faecal occult blood test (FOBT) can reduce mortality from colorectal cancer. Reliable estimation of FOBT sensitivity is crucial in assessing the potential effectiveness of a mass-screening procedure. Available estimates could be inaccurate because they neglect the temporal aspect of screening. The aim of our study was to estimate the sensitivity of the FOBT in mass screening for colorectal cancer, taking into account the duration of the pre-clinical phase of the disease assessed by the mean sojourn time (MST), and to assess whether MST and FOBT sensitivity differ according to cancer subsite. We analysed data taken from the first round of the mass-screening programme of the department of Calvados (France), involving 164,364 subjects of whom 43.4% participated in FOB screening. MST and sensitivity were estimated using a simple empirical approach, a traditional maximum likelihood method and log-linear modelling using the Bayesian technique of Gibbs sampling. MST was estimated as between 4.5 and 5 years for all subsites combined. According to the Gibbs sampling method, MSTs were 3.5, 6.4 and 2.6 years for proximal colon, distal colon and rectal cancer, respectively. Our estimation methods give a low sensitivity for the FOBT (50%), results for different subsites being closer to each other, slightly higher for proximal cancer. Our results strongly suggest that tumour growth rates are very different according to subsite, slowest for distal cancer and speediest for rectal cancer. Consideration of FOBT sensitivity without MST appears unreliable. Our results by subsite suggest that combining FOBT and sigmoidoscopy could be a good strategy for colorectal cancer screening.

Estimation of mean sojourn time in breast cancer screening using a Markov chain model of both entry to and exit from the preclinical detectable phase

The sojourn time, time spent in the preclinical detectable phase (PCDP) for chronic diseases, for example, breast cancer, plays an important role in the design and assessment of screening programmes. Traditional methods to estimate it usually assume a uniform incidence rate of preclinical disease from a randomized control group or historical data. In this paper, a two-parameter Markov chain model is proposed and developed to explicitly estimate the preclinical incidence rate (lambda 1) and the rate of transition from preclinical to clinical state (lambda 2, equivalent to the inverse of mean sojourn time) without using control data. A new estimate of sensitivity is proposed, based on the estimated parameters of the Markov process. When this method is applied to the data from the Swedish two-county study of breast cancer screening in the age group 70-74, the estimate of MST is 2.3 with 95 per cent CI ranging from 2.1 to 2.5, which is close to the result based on the traditional method but the 95 per cent CI is narrower using the Markov model. The reason for the greater precision of the latter is the fuller use of all temporal data, since the continuous exact times to events are used in our method instead of grouping them as in the traditional method. Ongoing and future researches should extend this model to include, for example, the tumour size, nodal status and malignancy grade, along with methods of simultaneously estimating sensitivity and the transition rates in the Markov process.

Design and analysis of cancer screening trials

This article reviews approaches to the design and analysis of cancer screening trials. After summarizing some basic screening concepts and potential pitfalls, we introduce several possible screening trial designs with examples from the literature. We review in detail methods for analyzing screening trial data, including testing for a significant difference in disease-specific mortality between the control and intervention groups, estimating the mortality differential if one exists, and evaluating the programme lead time, the screen sensitivity and the role of stage shifting. We consider Overall mortality analyses, which are based on the experience of the trial population, and Limited mortality analyses, which are based on the experience of comparable groups of cases in the control and intervention groups. We discuss methods for selecting candidate comparable case groups and confirming that they are in fact comparable. We conclude by showing how the principles discussed have been used in the planning and design of a current screening trial for multiple cancers.

A data-analytic approach for estimating lead time and screening benefit based on survival curves in randomized cancer screening trials

Screening tests are used frequently for control of diseases such as cancer. The increased survival time of screen-detected cases over those that are detected clinically may be due in part to 'lead time', or the length of time by which the disease is diagnosed earlier by screening in the presence or absence of any real extension in survival time. A realistic evaluation of screening needs to assess the true benefit of screening; that is, the length of time by which survival has been extended, beyond merely the time of the advanced diagnosis. The comparison of survival measured from time of entry between cases in a screening arm and in a control arm in randomized studies avoids the lead time bias. If the effects of average lead time and average benefit on survival are additive, these effects can be estimated by recognizing that (a) the difference in survival curves since time of diagnosis confounds benefit and lead time, but (b) the difference in survival curves since time of start of study involves benefit only. The method is evaluated on simulated data for its accuracy and may be used on data from randomized studies.

A 50-year experience of male breast cancer: is outcome changing?

During the period 1933-1983, 124 men (median age 62.5 years, range 33-86 years) were treated for breast carcinoma. Median length of follow-up was 6.7 years and was complete for 93% of patients. Presenting complaints were most frequently a mass (95%) or pain (31%) while physical examination revealed the tumour to be central in 95% of patients with nipple or skin retraction in 36% and associated gynaecomastia in 12%. Twenty-seven per cent of the patients had a positive family history of breast cancer, 6% noted previous breast trauma and 7% had prior chest wall irradiation. Mean tumour size was 2.5 cm, and the pathological stage was 0 in 3%, I in 17%, II in 22%, III in 35%, IV in 11%, and unknown in 12%. Ninety-four per cent were ductal carcinoma. Histological grading of tumours was 2% grade 1, 10% grade 2, 33% grade 3 and 48% grade 4. Ninety-two per cent of patients underwent mastectomy (41% radical, 39% modified radical and 12% simple), while adjuvant irradiation was used in 44% and chemotherapy in 9%. Median disease-free patient survival was 5 years (36% of patients developed tumour recurrence). Median overall patient survival was 6.3 years (57% at 5 years and 31% at 10 years). Tumour size (P < 0.05), pathological stage (P < 0.04), and tumour grade (P = 0.007) were adverse factors for recurrence, while pathological stage (P < 0.02), tumour size (P < 0.03), pain (P < 0.05) and age (P < 0.02) were associated with a decreased survival.(ABSTRACT TRUNCATED AT 250 WORDS)

Mammographic assessment of human breast cancer growth and duration

BACKGROUND

Accumulating data from numerous sources have confirmed that breast cancers have highly variable rates of growth. Contemporary thought supports that collectively the gross rates should decelerate with increasing tumor mass.

METHODS

Using composite data derived from mammographically measured growth of breast cancers observed at the Universities of Heidelberg and Louisville, the growth curve providing the best fit to the observed data, and the variance occurring around this curve has been calculated.

RESULTS

A generalized logistic equation provided the best fit, with a natural variance ranging from extremely rapidly growing to slowly growing cancer. These data do not cover the entire range of growth rates because cancers appearing acutely between mammograms were observed only once, and some breast cancers never grew.

CONCLUSIONS

The highly variable decelerating growth rates of breast cancers are better but incompletely defined, and these rates are of value in considering screening strategies and prognosis.

Effects of lead time, length bias, and false-negative assurance on screening for breast cancer

This article presents a model of breast cancer screening programs. The model shows the effects of the screening threshold, screen sensitivity, and false-negative assurance on the cumulative mortality rate in the screened population. It shows that factors of screen design and a penalty associated with false-negative assurance can result in excess mortality rates in screened populations--especially in those age classes in which the incidence of rapidly growing tumors is high. Factors related to the magnitude of this effect are described.