Breast carcinoma growth rate described by mammographic doubling time and S-phase fraction. Correlations to clinical and histopathologic factors in a screened population

The prognostic potential of mammographic growth rate of invasive breast cancer in the Nijmegen breast cancer screening cohort

OBJECTIVES

Insight into the aggressiveness of potential breast cancers found in screening may optimize recall decisions. Specific growth rate (SGR), measured on mammograms, may provide valuable prognostic information. This study addresses the association of SGR with prognostic factors and overall survival in patients with invasive carcinoma of no special type (NST) from a screened population.

METHODS

In this historic cohort study, 293 women with NST were identified from all participants in the Nijmegen screening program (2003-2007). Information on clinicopathological factors was retrieved from patient files and follow-up on vital status through municipalities. On consecutive mammograms, tumor volumes were estimated. After comparing five growth functions, SGR was calculated using the best-fitting function. Regression and multivariable survival analyses described associations between SGR and prognostic factors as well as overall survival.

RESULTS

Each one standard deviation increase in SGR was associated with an increase in the Nottingham prognostic index by 0.34 [95% confidence interval (CI): 0.21-0.46]. Each one standard deviation increase in SGR increased the odds of a tumor with an unfavorable subtype (based on histologic grade and hormone receptors; odds ratio 2.14 [95% CI: 1.45-3.15]) and increased the odds of diagnosis as an interval cancer (versus screen-detected; odds ratio 1.57 [95% CI: 1.20-2.06]). After a median of 12.4 years of follow-up, 78 deaths occurred. SGR was not associated with overall survival (hazard ratio 1.12 [95% CI: 0.87-1.43]).

CONCLUSIONS

SGR may indicate prognostically relevant differences in tumor aggressiveness if serial mammograms are available. A potential association with cause-specific survival could not be determined and is of interest for future research.

Role of myeloid-derived suppressor cells in tumor recurrence

The establishment of primary tumor cells in distant organs, termed metastasis, is the principal cause of cancer mortality and is a crucial therapeutic target in oncology. Thus, it is critical to establish a better understanding of metastatic progression for the future development of improved therapeutic approaches. Indeed, such development requires insight into the timing of tumor cell dissemination and seeding of distant organs resulting in occult lesions. Following dissemination of tumor cells from the primary tumor, they can reside in niches in distant organs for years or decades, following which they can emerge as an overt metastasis. This timeline of metastatic dormancy is regulated by interactions between the tumor, its microenvironment, angiogenesis, and tumor antigen-specific T-cell responses. An improved understanding of the mechanisms and interactions responsible for immune evasion and tumor cell release from dormancy would help identify and aid in the development of novel targeted therapeutics. One such mediator of dormancy is myeloid derived suppressor cells (MDSC), whose number in the peripheral blood (PB) or infiltrating tumors has been associated with cancer stage, grade, patient survival, and metastasis in a broad range of tumor pathologies. Thus, extensive studies have revealed a role for MDSCs in tumor escape from adoptive and innate immune responses, facilitating tumor progression and metastasis; however, few studies have considered their role in dormancy. We have posited that MDSCs may regulate disseminated tumor cells resulting in resurgence of senescent tumor cells. In this review, we discuss clinical studies that address mechanisms of tumor recurrence including from dormancy, the role of MDSCs in their escape from dormancy during recurrence, the development of occult metastases, and the potential for MDSC inhibition as an approach to prolong the survival of patients with advanced malignancies. We stress that assessing the impact of therapies on MDSCs versus other cellular targets is challenging within the multimodality interventions required clinically.

Myeloid derived suppressor cells and the release of micro-metastases from dormancy

Metastasis is the primary cause of cancer mortality and an improved understanding of its pathology is critical to the development of novel therapeutic approaches. Mechanism-based therapeutic strategies require insight into the timing of tumor cell dissemination, seeding of distant organs, formation of occult lesions and critically, their release from dormancy. Due to imaging limitations, primary tumors can only be detected when they reach a relatively large size (e.g. > 1 cm³), which, based on our understanding of tumor evolution, occurs approximately 10 years and about 30 doubling times following tumor initiation. Genomic profiling of paired primary tumors and metastases has suggested that tumor seeding at secondary sites occurs early during tumor progression and frequently, years prior to clinical diagnosis. Following seeding, tumor cells may enter into and remain in a dormant state, and if they survive and are released from dormancy, they can proliferate into an overt lesion. The timeline of tumor initiation and metastatic dormancy is regulated by tumor interactions with its microenvironment, angiogenesis, and tumor-specific cytotoxic T-lymphocyte (CTL) responses. Therefore, a better understanding of the cellular interactions responsible for immune evasion and/or tumor cell release from dormancy would facilitate the development of therapeutics targeted against this critical part of tumor progression. The immunosuppressive mechanisms mediated by myeloid-derived suppressor cells (MDSCs) contribute to tumor progression and, we posit, promote tumor cell escape from CTL-associated dormancy. Thus, while clinical and translational research has demonstrated a role for MDSCs in facilitating tumor progression and metastasis through tumor escape from adoptive and innate immune responses (T-, natural killer and B-cell responses), few studies have considered the role of MDSCs in tumor release from dormancy. In this review, we discuss MDSC expansion, driven by tumor burden associated growth factor secretion and their role in tumor cell escape from dormancy, resulting in manifest metastases. Thus, the therapeutic strategies to inhibit MDSC expansion and function may provide an approach to delay metastatic relapse and prolong the survival of patients with advanced malignancies.

Role of myeloid-derived suppressor cells in metastasis

The spread of primary tumor cells to distant organs, termed metastasis, is the principal cause of cancer mortality and is a critical therapeutic target in oncology. Thus, a better understanding of metastatic progression is critical for improved therapeutic approaches requiring insight into the timing of tumor cell dissemination and seeding of distant organs, which can lead to the formation of occult lesions. However, due to limitations in imaging techniques, primary tumors can only be detected when they reach a relatively large size (e.g., > 1 cm³), which, based on our understanding of tumor evolution, is 10 to 20 years (30 doubling times) following tumor initiation. Recent insights into the timing of metastasis are based on the genomic profiling of paired primary tumors and metastases, suggesting that tumor cell seeding of secondary sites occurs early during tumor progression and years prior to diagnosis. Following seeding, tumor cells may remain in a dormant state as single cells or micrometastases before emerging as overt lesions. This timeline and the role of metastatic dormancy are regulated by interactions between the tumor, its microenvironment, and tumor-specific T cell responses. An improved understanding of the mechanisms and interactions responsible for immune evasion and tumor cell release from dormancy would support the development of novel targeted therapeutics. We posit herein that the immunosuppressive mechanisms mediated by myeloid-derived suppressor cells (MDSCs) are a major contributor to tumor progression, and that these mechanisms promote tumor cell escape from dormancy. Thus, while extensive studies have demonstrated a role for MDSCs in the escape from adoptive and innate immune responses (T-, natural killer (NK)-, and B cell responses), facilitating tumor progression and metastasis, few studies have considered their role in dormancy. In this review, we discuss the role of MDSC expansion, driven by tumor burden, and its role in escape from dormancy, resulting in occult metastases, and the potential for MDSC inhibition as an approach to prolong the survival of patients with advanced malignancies.

A Mathematical Model to Predict Diagnostic Periods for Secondary Distant Metastases in Patients with ER/PR/HER2/Ki-67 Subtypes of Breast Cancer

Previously, a consolidated mathematical model of primary tumor (PT) growth and secondary distant metastasis (sdMTS) growth in breast cancer (BC) (CoMPaS) was presented. The aim was to detect the diagnostic periods for visible sdMTS via CoMPaS in patients with different subtypes ER/PR/HER2/Ki-67 (Estrogen Receptor/Progesterone Receptor/Human Epidermal growth factor Receptor 2/Ki-67 marker) of breast cancer. CoMPaS is based on an exponential growth model and complementing formulas, and the model corresponds to the tumor-node-metastasis (TNM) staging system and BC subtypes (ER/PR/HER2/Ki-67). The CoMPaS model reflects (1) the subtypes of BC, such as ER/PR/HER2/Ki-67, and (2) the growth processes of the PT and sdMTSs in BC patients without or with lymph node metastases (MTSs) in accordance with the eighth edition American Joint Committee on Cancer prognostic staging system for breast cancer. CoMPaS correctly describes the growth of the PT in the ER/PR/HER2/Ki-67 subtypes of BC patients and helps to calculate the different diagnostic periods, depending on the tumor volume doubling time of sdMTS, when sdMTSs might appear. CoMPaS and the corresponding software tool can help (1) to start the early treatment of small sdMTSs in BC patients with different tumor subtypes (ER/PR/HER2/Ki-67), and (2) to consider the patient almost healthy if sdMTSs do not appear during the different diagnostic periods.

Machine learning-based prediction of breast cancer growth rate in vivo

Background

Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.

Methods

A serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.

Results

SM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.

Conclusion

Our Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications.

Timing and Delays in Breast Cancer Evaluation and Treatment

BACKGROUND

Even small delays in the treatment of breast cancer are a frequently expressed concern of patients. Knowledge about this subject is important for clinicians to counsel patients appropriately and realistically, while also optimizing care. Although data and quality measures regarding time to chemotherapy and radiotherapy have been present for some time, data regarding surgical care are more recent and no standard exists. This review was written to discuss our current knowledge about the relationship of treatment times to outcomes.

METHODS

The published medical literature addressing delays and optimal times to treatment was reviewed in the context of our current time-dependent standards for chemotherapy and radiotherapy. The surgical literature and the lack of a time-dependent surgical standard also were discussed, suggesting a possible standard.

RESULTS

Risk factors for delay are numerous, and tumor doubling times are both difficult to determine and unhelpful to assess the impact of longer treatment times on outcomes. Evaluation components also have a time cost and are inextricable from the patient's workup. Although the published literature has lack of uniformity, optimal times to each modality are strongly suggested by emerging data, supporting the current quality measures. Times to surgery, chemotherapy, and radiotherapy all have a measurable impact on outcomes, including disease-free survival, disease-specific survival, and overall survival.

CONCLUSIONS

Delays have less of an impact than often thought but have a measurable impact on outcomes. Optimal times from diagnosis are < 90 days for surgery, < 120 days for chemotherapy, and, where chemotherapy is administered, < 365 days for radiotherapy.

Mammography and Morphobiologic Characteristics of Human Breast Cancer

Aims

A comparative analysis was performed to verify a possible correlation between mammographic features and morphobiologic characteristics of the tumor in a series of 176 invasive primary breast cancer patients.

Methods

Breast cancers were grouped according to mammographic features as follows: tumor mass with spiculated borders; tumor mass with well-circumscribed borders; tumor with density alteration of parenchyma with no clear borders; a cluster of micro-calcifications as the only sign of tumor presence; tumor without mammographic abnormality. The tumor tissue biologic characteristics investigated were: hormone receptor content, tumor proliferative activity, DNA content and cytohlstologic tumor-grade differentiation.

Results

Spiculated tumors showed a significantly higher percentage of estrogen-receptorpositive cases with respect to circumscribed tumors, independently of the patient's menopausal status. Tumors with only microcalcifications were all from premenopausal patients and showed a significantly higher percentage of progesterone-receptor-positive cases (83 %). Tumor proliferative activity did not significantly differ in the 5 mammographic breast cancer groups; aneuploidy was less frequent in tumors with spiculated borders than in mammographic types (39 % vs 57 %; p = 0.05); percentages of G1-G2-G3 tumors did not differ significantly among the mammographic groups considered.

Conclusions

Certain relationships between mammographic features and biologic characteristics could be of potential clinical interest and stimulate more detailed studies on this issue.

The effect of one additional driver mutation on tumor progression

Tumor growth is caused by the acquisition of driver mutations, which enhance the net reproductive rate of cells. Driver mutations may increase cell division, reduce cell death, or allow cells to overcome density-limiting effects. We study the dynamics of tumor growth as one additional driver mutation is acquired. Our models are based on two-type branching processes that terminate in either tumor disappearance or tumor detection. In our first model, both cell types grow exponentially, with a faster rate for cells carrying the additional driver. We find that the additional driver mutation does not affect the survival probability of the lesion, but can substantially reduce the time to reach the detectable size if the lesion is slow growing. In our second model, cells lacking the additional driver cannot exceed a fixed carrying capacity, due to density limitations. In this case, the time to detection depends strongly on this carrying capacity. Our model provides a quantitative framework for studying tumor dynamics during different stages of progression. We observe that early, small lesions need additional drivers, while late stage metastases are only marginally affected by them. These results help to explain why additional driver mutations are typically not detected in fast-growing metastases.

Inhibitors targeting mitosis: tales of how great drugs against a promising target were brought down by a flawed rationale

Although they have been advocated with an understandable enthusiasm, mitosis-specific agents such as inhibitors of mitotic kinases and kinesin spindle protein have not been successful clinically. These drugs were developed as agents that would build on the success of microtubule-targeting agents while avoiding the neurotoxicity that encumbers drugs such as taxanes and vinca alkaloids. The rationale for using mitosis-specific agents was based on the thesis that the clinical efficacy of microtubule-targeting agents could be ascribed to the induction of mitotic arrest. However, the latter concept, which has long been accepted as dogma, is likely important only in cell culture and rapidly growing preclinical models, and irrelevant in patient tumors, where interference with intracellular trafficking on microtubules is likely the principal mechanism of action. Here we review the preclinical and clinical data for a diverse group of inhibitors that target mitosis and identify the reasons why these highly specific, myelosuppressive compounds have failed to deliver on their promise.

Malignant transformation and stromal invasion from normal or hyperplastic tissues: true or false?

Carcinogenesis is believed to be a multi-step process, progressing sequentially from normal to hyperplastic, to in situ, and to invasive stages. A number of studies, however, have detected malignancy-associated alterations in normal or hyperplastic tissues. As the molecular profile and clinical features of these tissues have not been defined, the authors invited several well-recognized pathologist, oncologists, biologist, surgeons, and molecular biologist to offer their opinion on: (1) whether these tissues belong to a previously unrevealed malignant entity or focal alterations with no significant consequence? (2) whether these alterations are linked to early onset of cancer or cancer of unknown primary site, and (3) how to further define these lesions?

AACR centennial series: the biology of cancer metastasis: historical perspective

Metastasis resistant to therapy is the major cause of death from cancer. Despite almost 200 years of study, the process of tumor metastasis remains controversial. Stephen Paget initially identified the role of host-tumor interactions on the basis of a review of autopsy records. His "seed and soil" hypothesis was substantiated a century later with experimental studies, and numerous reports have confirmed these seminal observations. An improved understanding of the metastatic process and the attributes of the cells selected by this process is critical for the treatment of patients with systemic disease. In many patients, metastasis has occurred by the time of diagnosis, so metastasis prevention may not be relevant. Treating systemic disease and identifying patients with early disease should be our goal. Revitalized research in the past three decades has focused on new discoveries in the biology of metastasis. Even though our understanding of molecular events that regulate metastasis has improved, the contributions and timing of molecular lesion(s) involved in metastasis pathogenesis remain unclear. Review of the history of pioneering observations and discussion of current controversies should increase understanding of the complex and multifactorial interactions between the host and selected tumor cells that contribute to fatal metastasis and should lead to the design of successful therapy.

AACR centennial series: the biology of cancer metastasis: historical perspective

Metastasis resistant to therapy is the major cause of death from cancer. Despite almost 200 years of study, the process of tumor metastasis remains controversial. Stephen Paget initially identified the role of host-tumor interactions on the basis of a review of autopsy records. His "seed and soil" hypothesis was substantiated a century later with experimental studies, and numerous reports have confirmed these seminal observations. An improved understanding of the metastatic process and the attributes of the cells selected by this process is critical for the treatment of patients with systemic disease. In many patients, metastasis has occurred by the time of diagnosis, so metastasis prevention may not be relevant. Treating systemic disease and identifying patients with early disease should be our goal. Revitalized research in the past three decades has focused on new discoveries in the biology of metastasis. Even though our understanding of molecular events that regulate metastasis has improved, the contributions and timing of molecular lesion(s) involved in metastasis pathogenesis remain unclear. Review of the history of pioneering observations and discussion of current controversies should increase understanding of the complex and multifactorial interactions between the host and selected tumor cells that contribute to fatal metastasis and should lead to the design of successful therapy.

Hormone replacement therapy (HRT), breast cancer and tumor pathology

Within an average observation period of 5-6 years, several clinical trials reported an increased risk of breast cancer due to hormone replacement therapy (HRT). However, it remains disputable, whether the increased rate of breast cancers detected within the given time frame is indeed due to newly induced tumors and thus constitutes HRT-initiated primary breast cancers. Onco-pathologically speaking it appears more likely that HRT stimulates the growth of already existing small tumor nests which - due to their small size - would otherwise go undiagnosed. The major arguments are: In summary, HRT is hence more likely to be a tumor promoter than a de novo-inducer of breast cancers.

Mitotic activity index in interval breast cancers

AIMS

The Mitotic Activity Index (MAI) is a strong prognostic factor for disease free survival in breast cancer. The MAI is lower in screen detected tumours, correlating with less aggressive biological behaviour in this group. In this study the MAI is compared between screen detected, interval and symptomatic breast cancers.

METHODS

Between 1991 and 1999, the MAI was determined in 581 breast cancers, 160 were detected by screening, 66 were interval carcinomas, and 355 were symptomatic breast cancers. Other prognostic factors were also registered.

RESULTS

The interval group had a significantly higher median MAI (17-18, range 1-134) than the screen detected group (7-8, range 0-94,P <0.0001). There was no difference with the symptomatic group (MAI 15, range 0-149,P =0.92).

CONCLUSIONS

Interval cancers had an intermediate outcome when correlated with other prognostic factors, compared to screen detected and symptomatic cancers.

The effects of major depression and phobia on stage at diagnosis of breast cancer

OBJECTIVE

To examine the longitudinal effects of major depression and phobia on stage at diagnosis of subsequent breast cancer.

METHOD

Data from the New Haven Epidemiologic Catchment Area (ECA) study were linked to the Connecticut Tumor Registry (CTR). The sample comprised of seventy-two women with a first primary breast cancer diagnosed sometime after their baseline ECA study interview. In the ECA study, lifetime psychiatric history was assessed using the Diagnostic Interview Schedule based on DSM-III criteria. Stage at diagnosis of breast cancer was taken from CTR records and dichotomized into early stage (in situ and localized tumors) versus late stage (regional and distant tumors).

RESULTS

A positive history of major depression was associated with an increased likelihood of late-stage diagnosis of breast cancer (odds ratio [OR] = 9.81, p = 0.039), whereas a positive history of phobic disorders was associated with a decreased likelihood of late-stage diagnosis (OR = 0.01, p = 0.021), controlling for sociodemographic characteristics of the sample.

CONCLUSIONS

These analyses revealed a longitudinal association between reported lifetime psychiatric history and stage at diagnosis of subsequent breast cancer. Phobia may motivate women to adhere to breast cancer screening recommendations and to report suspicious symptoms to a physician without delay. Major depression, on the other hand, was identified as an important predictor of late-stage diagnosis; proper recognition and management of depression in the primary care setting may have important implications for breast cancer detection and survival.

Chronological Changes of Microcalcifications of Breast Carcinoma

BACKGROUND: Clustered microcalcifications are important for the detection of breast carcinomas, but few reports have described chronological changes of the microcalcifications. METHODS: The mammographic features of 18 breast cancer cases for which previous survey films were available and in which clustered microcalcifications with no tumor shadows were recognized at diagnosis were studied. Chronological changeswere analyzed by measuring the increase in the length of areas containing calcifications and the diameters of microcalcifications on mammograms using computerized image analysis. RESULTS: Chronological changes in the length of areas of microcalcifications were classified into two types by simple linear regression. Fast increase was common in the comedo type of carcinoma and slow increase was common in the non-comedo type. Three of nine cases that received follow-up examinations on two or more occasions eventually changed from slow type to fast type, and the distributionpattern of diameters of microcalcifications also changed from non-comedo type to comedo type. A follow-up study of 48 cases with a cluster of fewer than five extremely fine calcifications revealed breast carcinoma in 7 patients within 5 years. CONCLUSION: The increase of microcalcifications was generally fast in comedotype and slow in non-comedo type lesions. An increase in the extent of microcalcification was seen occasionally during the last period between follow-up examinations in mixed type tumors, indicating a conversion of the intraductal component to a more malignant grade.

On the growth rates of human malignant tumors: implications for medical decision making

Testicular carcinomas, pediatric tumors, and some mesenchymal tumors are examples of rapidly proliferating cell populations, for which the tumor volume doubling time (TVDT) can be counted in days. Cancers from the breast, prostate, and colon are frequently slow-growing, displaying a TVDT of months or years. Irrespective of their growth rates, most human tumors have been found: to start from one single cell, to have a long subclinical period, to grow at constant rates for long periods of time, to start to metastasize often even before the primary is detected, and to have metastases that often grow at approximately the same rate as the primary tumor. The recognition of basic facts in tumor cell kinetics is essential in the evaluation of important present-day strategies in oncology. Among the facts emphasized in this review are: (1) Screening programs. Most tumors are several years old when detectable by present-day diagnostic methods. This makes the term "early detection" questionable. (2) Legal trials. The importance of so-called doctor's delay is often discussed, but the prognostic value of "early" detection is overestimated. (3) Analyses of clinical trials. Such analysis may be differentiated depending on the growth rates of the type of tumor studied. Furthermore, uncritical analysis of survival data may be misleading if the TVDT is not taken into consideration. (4) Analyses of epidemiological data. If causes of malignant tumors in humans are searched for, the time of exposure must be extended far back in the subject's history. (5) Risk estimations by insurance companies. For the majority of human cancers, the 5-year survival rate is not a valid measurement for cure. Thus, basic knowledge of tumor kinetics may have important implications for political health programs, legal trials, medical science, and insurance policies.

Assessment of lifetime gained as a result of mammographic breast cancer screening using a computer model

A computer model for the simulation of breast cancer screening (MBS) is used to calculate the results of screening in terms of lifetime. To optimize breast cancer screening protocols, risk (lifetime lost due to radiation-induced tumours) versus benefit (lifetime gained due to early detection of breast cancer) analyses are performed for a simulated stable Swedish female population. The present study focuses on the results of different screening strategies employing single view mammography, including starting and finishing ages of screening, time interval between successive screening sessions as well as the influence of high detection screening and differences between different populations, based on lifetime lost or gained. To test the stability of the recommendations with respect to possible changes in the variables used in MBS, calculations are also performed for high risk factors for breast tumour induction using both the additive and multiplicative risk models, fast growing breast tumours, late incidence of breast tumours and age dependent survival. The results of the simulations expressed in terms of lifetime gained suggest that a theoretical benefit can be obtained employing starting and finishing ages of 35 and 75 years, respectively. In terms of number of fatal breast tumours, the favourable screening period is 40-80 years. It is concluded that the recommendations are stable for changes in the input variables of MBS. The benefits of higher detection screening are more marked for younger than for older women. A high screening frequency results in more lifetime gained, especially at relatively young ages, whereas for older ages the effect is only marginal.

Interval carcinomas of the breast: a group with intermediate outcome

BACKGROUND

Interval carcinoma is defined as a carcinoma detected between two mammographic screening rounds after a negative screening. By some authors these carcinomas are considered to be more aggressive than screen-detected carcinomas.

METHODS

In a group of 937 patients referred for breast cancer in the period 1975-1990, 76 interval carcinoma patients were treated. In a retrospective study the outcome was studied of patients with an interval carcinoma in comparison with patients with screen-detected carcinomas and of patients with clinically detected carcinomas outside the screening program.

RESULTS

No significant difference was found in the 5-year and 10-year disease-free survival of patients with interval carcinoma (80%, 68%) and the screen-detected group (89%, 81%) (P = 0.12). The interval group did significantly better than the patients with carcinomas detected outside the screening program (P = 0.03).

CONCLUSION

Interval-detected cancers for patients in the screening program had an outcome intermediate between patients with screen-detected cancers and patients with cancers detected outside the screening program. The difference between interval-detected cancers and cancers detected outside the screening program was significant, whereas the difference between screen-detected and interval cancers was not.

Histopathology and growth rate of interval breast carcinoma. Characterization of different subgroups

BACKGROUND

Interval breast cancers are defined as carcinomas occurring within 2 years after a negative screening Distinction has to made between cancers existent at the time of screening but missed for some reason, and fast-growing incident cancers. This is important because the natural history and the implications for the treatment of the patient might differ.

METHODS

Radiologic and histopathologic characteristics were assembled for 104 interval cancers diagnosed within the DOM project, the Utrecht program for the early detection of breast cancer. At a mammographic review for 27 cases, signs of malignant or benign tumor were found (missed cases). For 77 cases no radiologic signs were present on review. Twenty of these cases had a mitotic rate of > 3 and a high tumor growth rate (mean doubling time: 51 days). This combination seemed implausible, therefore, it was thought hypothesized that these tumors were most likely present, although radiologically invisible (masked), at the time of screening. The remaining cases (n = 57) were classified as true interval cancers and further divided into 14 fast-growing cases (mitotic rate > or = 3/high-power field [HPF]) and 43 cases with an intermediate growth rate (mitotic rate < 3/HPF).

RESULTS

Factors associated with the masking of tumors were the histologic tumor type, absence of microscopic calcifications, and presence of dense breast tissue. Fast-growing tumors were characterized by a young patient age, absence of microscopic calcifications, and a high percentage of regional lymph node positive tumors. The 5-year survival probability was 100% for missed cases, 70% for masked cases, 80% for cases with an intermediate growth rate, and 54% for fast-growing cases.

CONCLUSIONS

It is possible to separate interval breast cancers in true interval cases and cases (most likely) existent at the time of screening. Part of this last group is invisible by mammography (masked).

MBS: a model for risk benefit analysis of breast cancer screening

Breast cancer screening programmes employing mammography are being implemented in various European countries. Different screening protocols are used in demonstration projects and nationwide programmes. To evaluate and improve protocols, a computer model for the evaluation of breast cancer screening has been developed. The availability of such a model can be of great importance in obtaining a better insight into the influence of various parameters. The Monte Carlo computer model is based on random selection from distributions of relevant parameters including tumour onset, tumour growth rate, lifetime expectancy, tumour detection size for screening and spontaneous observation. The radiation risk is calculated for various screening protocols employing multiplicative and additive risk models combined with lifetime expectancy, number of females screened and absorbed dose per screening session. The benefit is calculated on the basis of the reduction in tumour size at detection due to screening compared with spontaneous observation and the survival as a function of tumour diameter. Data from the Swedish two-county study are used to validate the model in terms of prevalence, interval tumour rates and interval tumour diameter distributions. Except for the spontaneous tumour diameter distribution, the model can describe the Swedish two-county study. Specific information is presented on the distributions of relevant parameters.

Computer model challenges breast cancer treatment strategy

The breast cancer treatment failure rate remains unacceptably high. The current breast cancer treatment paradigm, based primarily on Gompertzian kinetics and animal models, advocates short-course, intensive chemotherapy subsequent to tumor debulking, citing drug resistance and host toxicity as the primary reasons for treatment failure. To better understand treatment failure, we have studied breast cancer from the perspective of computer modeling. Our results demonstrate breast cancers grow in an irregular fashion; this differs from the Gompertzian mode of animal models and thus challenges the validity of the current paradigm. Clinical and laboratory data support the concept of irregular growth rather than the common claim that human tumors grow in a Gompertzian fashion. Treatment failure mechanisms for breast cancer appear to differ from those for animal models, and thus treatments optimize on animal models may not be optimal for breast cancer. A failure mechanism consistent with our results involves temporarily dormant tumor cells in anatomical or pharmacological sanctuary, which eventually result in aggressive metastatic disease.