Estimates of Breast Cancer Growth Rate and Sojourn Time from Screening Database Information:

Surveillance for Hepatocellular Carcinoma Also Improves Survival of Incidentally Detected Intrahepatic Cholangiocarcinoma Arisen in Liver Cirrhosis

BACKGROUND

Due to its poor survival, intrahepatic cholangiocarcinoma (ICC) is held to be a much more aggressive cancer than hepatocellular carcinoma (HCC). In most published series, patients were diagnosed when symptomatic. However, ICC is now increasingly being discovered during the surveillance for HCC in cirrhosis. Whether this earlier detection of ICC is associated with an equally dismal prognosis or not is unknown.

METHODS

This is amulticenter retrospective study of consecutive ICC patients. Patients were stratified into subgroups according to the absence/presence of cirrhosis. A propensity score matching was performed to reduce the potential biases. Cirrhotic patients were further stratified according to their surveillance status. The lead-time bias and its potential effects were also estimated.

RESULTS

We gathered 184 patients. Eighty-five patients (46.2%) were cirrhotic. Liver cirrhosis was not related to a worse overall survival (33.0 vs. 32.0 months, p = 0.800) even after the propensity score analysis (43.0 in vs. 44.0 months in 54 pairs of patients, p = 0.878). Among the cirrhotic population, 47 (55.3%) patients had received a diagnosis of ICC during a surveillance programme. The 2 subgroups differed in maximum tumour dimensions (30 vs. 48 mm in surveyed and non-surveyed patients, respectively). Surveyed patients were more likely to receive surgical treatments (59.8 vs. 28.9%, p = 0.003). Overall survival was higher in surveyed patients (51.0 vs. 21.0 months, p < 0.001). These benefits were confirmed after correcting for the lead-time bias.

CONCLUSIONS

Cirrhotic patients have different clinical presentation and outcomes of ICC according to their surveillance status. In our series, ICC in cirrhosis was not associated with worse OS. Cirrhosis itself should not discourage either surgical or non-surgical treatments.

Effects of mutations and immunogenicity on outcomes of anti-cancer therapies for secondary lesions

Cancer development is driven by mutations and selective forces, including the action of the immune system and interspecific competition. When administered to patients, anti-cancer therapies affect the development and dynamics of tumours, possibly with various degrees of resistance due to immunoediting and microenvironment. Tumours are able to express a variety of competing phenotypes with different attributes and thus respond differently to various anti-cancer therapies. In this paper, a mathematical framework incorporating a system of delay differential equations for the immune system activation cycle and an agent-based approach for tumour-immune interaction is presented. The focus is on those metastatic, secondary solid lesions that are still undetected and non-vascularised. By using available experimental data, we analyse the effects of combination therapies on these lesions and investigate the role of mutations on the rates of success of common treatments. Findings show that mutations, growth properties and immunoediting influence therapies' outcomes in nonlinear and complex ways, affecting cancer lesion morphologies, phenotypical compositions and overall proliferation patterns. Cascade effects on final outcomes for secondary lesions are also investigated, showing that actions on primary lesions could sometimes result in unexpected clearances of secondary tumours. This outcome is strongly dependent on the clonal composition of the primary and secondary masses and is shown to allow, in some cases, the control of the disease for years.

Breast Cancer Screening: The Debate that Never Ends

Screening mammography has been shown to decrease breast cancer deaths through randomized controlled trials. However, there remains significant debate surrounding the most appropriate time to commence screening and the optimal screening interval. Several national organizations have recently updated their guidelines by reanalyzing the published data. Interestingly, each organization has come to different conclusions regarding their recommendation for breast cancer screening in the average risk woman. Three of the main organizations that issue guidelines for breast cancer screening in the United States are reviewd in this chapter.

Growth rate of invasive ductal carcinomas from a screened 50-74-year-old population

Objective As breast cancer growth rate is associated with menopause, most screening programmes target mainly women aged 50-74. We studied the association between age at diagnosis and growth rate in this screening-specific age range. Methods We used data from breast cancer patients diagnosed in the screening programme in Nijmegen, the Netherlands. The data were restricted to the screening rounds when analogue mammography was used in both the screening and clinical setting. Growth rate expressed as tumour volume doubling time was based on increasing tumour size in longitudinal series of mammograms. Estimates were based on (a) tumours showing at least two measurable shadows, (b) tumours showing a shadow at detection only (left censored), and (c) tumours showing no growth (right-censored observation). All 293 tumours were consecutively diagnosed invasive ductal breast cancers in participants of the Nijmegen screening programme in the period 2000-2007. Results Depending on the assumptions made on tumour margins and mammographic density, the relation of volume doubling time with age non-significantly varies from a decrease of 3.3% to an increase of 1.4% for each year increase in age at diagnosis (all P-values ≥ 0.18). Applying left censoring on indistinct tumours, the geometric mean volume doubling time was 191 days (95% confidence interval 158-230). Conclusion We found no significant change in growth rate with age in women diagnosed with invasive ductal breast cancer in the screening age range 50-74. This outcome does not support differential screening intervals by age based solely on breast cancer growth rate for this particular group.

Implications of Overdiagnosis: Impact on Screening Mammography Practices

This review article explores the issue of overdiagnosis in screening mammography. Overdiagnosis is the screen detection of a breast cancer, histologically confirmed, that might not otherwise become clinically apparent during the lifetime of the patient. While screening mammography is an imperfect tool, it remains the best tool we have to diagnose breast cancer early, before a patient is symptomatic and at a time when chances of survival and options for treatment are most favorable. In 2015, an estimated 231,840 new cases of breast cancer (excluding ductal carcinoma in situ) will be diagnosed in the United States, and some 40,290 women will die. Despite these data, screening mammography for women ages 40-69 has contributed to a substantial reduction in breast cancer mortality, and organized screening programs have led to a shift from late-stage diagnosis to early-stage detection. Current estimates of overdiagnosis in screening mammography vary widely, from 0% to upwards of 30% of diagnosed cancers. This range reflects the fact that measuring overdiagnosis is not a straightforward calculation, but usually one based on different sets of assumptions and often biased by methodological flaws. The recent development of tomosynthesis, which creates high-resolution, three-dimensional images, has increased breast cancer detection while reducing false recalls. Because the greatest harm of overdiagnosis is overtreatment, the key goal should not be less diagnosis but better treatment decision tools. (Population Health Management 2015;18:S3-S11).

Screening Mammography in a Public Hospital Serving Predominantly African-American Women: A Stage-Survival-Cost Model

BACKGROUND

Ethnic and socioeconomic disparities pervade breast cancer patterns and outcomes. Mammography guidelines reflect the difficulty in optimizing mortality reduction and cost-effectiveness, with controversy still surrounding the 2009 U.S. Preventive Services Task Force (USPSTF) recommendations. This study simulates USPSTF and American Cancer Society (ACS) guidelines' effects on stage, survival, and cost of treatment in an urban public hospital.

METHODS

Charts of 274 women diagnosed with stage I, II, or III breast cancer (2008-2010) were reviewed. Published tumor doubling times were used to predict size at diagnosis under simulated screening guidelines. Stage distributions under ACS and USPSTF guidelines were compared with those observed. Cohort survival for observed and hypothetical scenarios was estimated using national statistics. Treatment costs by stage, calculated from Georgia Medicaid claims data, were similarly applied.

RESULTS

Mean age at diagnosis was 56 years. African Americans predominated (82.5%), with 96% publically insured or uninsured. Simulated stages at diagnosis significantly favored ACS guidelines (43.1% stage 1/38.3% stage 2/9.9% stage 3 vs. USPSTF 23.0%/53.3 %/15.0%), as did 5-year survival and cost of treatment relative to both observed and USPSTF-predicted schema (p<.0001). Following USPSTF guidelines predicted lower survival and additional costs.

CONCLUSIONS

Following ACS guidelines seems to lead to earlier diagnosis for low-income African-American women and increase 5-year survival with lower overall and breast-specific costs. The data suggest that adjusting screening practices for lower socioeconomic status, ethnic minority women may prove essential in addressing cancer disparities.

Estimation of lead-time bias and its impact on the outcome of surveillance for the early diagnosis of hepatocellular carcinoma

BACKGROUND & AIMS

Lead-time is the time by which diagnosis is anticipated by screening/surveillance with respect to the symptomatic detection of a disease. Any screening program, including surveillance for hepatocellular carcinoma (HCC), is subject to lead-time bias. Data regarding lead-time for HCC are lacking. Aims of the present study were to calculate lead-time and to assess its impact on the benefit obtainable from the surveillance of cirrhotic patients.

METHODS

One-thousand three-hundred and eighty Child-Pugh class A/B patients from the ITA.LI.CA database, in whom HCC was detected during semiannual surveillance (n = 850), annual surveillance (n = 234) or when patients came when symptomatic (n = 296), were selected. Lead-time was estimated by means of appropriate formulas and Monte Carlo simulation, including 1000 patients for each arm.

RESULTS

The 5-year overall survival after HCC diagnosis was 32.7% in semiannually surveilled patients, 25.2% in annually surveilled patients, and 12.2% in symptomatic patients (p<0.001). In a 10-year follow-up perspective, the median lead-time calculated for all surveilled patients was 6.5 months (7.2 for semiannual and 4.1 for annual surveillance). Lead-time bias accounted for most of the surveillance benefit until the third year of follow-up after HCC diagnosis. However, even after lead-time adjustment, semiannual surveillance maintained a survival benefit over symptomatic diagnosis (number of patients needed to screen = 13), as did annual surveillance (18 patients).

CONCLUSIONS

Lead-time bias is the main determinant of the short-term benefit provided by surveillance for HCC, but this benefit becomes factual in a long-term perspective, confirming the clinical utility of an anticipated diagnosis of HCC.

Clonal evolution in breast cancer revealed by single nucleus genome sequencing

Sequencing studies of breast tumor cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumors. Here, we developed a whole-genome and exome single cell sequencing approach called Nuc-Seq that utilizes G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumor nuclei from an estrogen-receptor positive breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumor evolution and remained highly stable as the tumor masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Many of the diverse mutations were shown to occur at low frequencies (<10%) in the tumor mass by targeted single-molecule sequencing. Using mathematical modeling we found that the triple-negative tumor cells had an increased mutation rate (13.3X) while the ER+ tumor cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.

Estimating cytomegalovirus growth rates by using only a single point

Calculation of pathogen growth rates is important in understanding the natural history of infection and effects of therapy. However, it is often difficult to estimate pathogen growth because patients are treated immediately upon the detection of infection, leaving only one nonzero untreated reading. Previous approaches have relied on the flawed assumption that pathogen loads just prior to detection are at the assay detection threshold. We have developed a novel method for estimating the pathogen growth rate from a single reading and investigated the initial growth of cytomegalovirus (CMV) in allogeneic hematopoietic stem cell transplant (HSCT) patients. We applied this approach to CMV viral loads measured at least weekly in 122 patients in the 3 months posttransplant. Viral growth rates were estimated by using a modeling approach that accounts for the viral load and the time since the last negative reading. Viral growth rates decreased rapidly within the first week, from 0.72/day (doubling time, 0.96 day) at the point of reactivation to 0.22/day (doubling time, 3.1 days) at 1 week. Results from this method correlated closely with a two-point regression analysis of a subset of 58 patients with detectable subthreshold viral loads immediately prior to overt reactivation. Patients with lymphocyte counts of ≥0.5 × 10(9)/liter had significantly slower viral growth than patients with low lymphocyte counts (0.612/day versus 0.325/day, P < 0.0001). Thus, our novel method of estimating pathogen growth rates reveals a rapid slowing of CMV growth during reactivation in HSCT patients and a significant impact of the lymphocyte count on CMV growth.

Modeling protective anti-tumor immunity via preventative cancer vaccines using a hybrid agent-based and delay differential equation approach

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry.

An innovative approach to treating cancer envisions developing preventative anti-cancer vaccines to train a person's immune cells to eliminate early-stage tumors close to genesis. The design of such a treatment strategy requires an understanding of the tumor and immune interactions leading to a successful anti-cancer immune response. To engage this problem, we formulate a mathematical model of the immune response against incipient tumours consisting of as low as hundreds to thousands of cancer cells, which is far below the clinical detection threshold of over 100,000 cells. The model considers the initial stimulation of the immune response and the resulting immune attack on the tumor mass and is formulated as a hybrid agent-based and delay differential equation model. We apply the model to test dynamics over a wide range of dynamic parameters, including immune and tumor cell growth rates and the size of the initial anti-cancer immune population. Our results show that an anti-cancer memory immune cell population of 3% or less can successfully eradicate an incipient tumor population over a wide range of dynamic parameters, indicating that a vaccination approach is feasible.

Imaging of sound speed using reflection ultrasound tomography

OBJECTIVES

The goal of this work was to obtain and evaluate measurements of tissue sound speed in the breast, particularly dense breasts, using backscatter ultrasound tomography.

METHODS

An automated volumetric breast ultrasound scanner was constructed for imaging the prone patient. A 5- to 7-MHz linear array transducer acquired 17,920 radiofrequency pulse echo A-lines from the breast, and a back-wall reflector rotated over 360° in 25 seconds. Sound speed images used reflector echoes that after preprocessing were uploaded into a graphics processing unit for filtered back-projection reconstruction. A velocimeter also was constructed to measure the sound speed and attenuation for comparison to scanner performance. Measurements were made using the following: (1) deionized water from 22°C to 90°C; (2) various fluids with sound speeds from 1240 to 1904 m/s; (3) acrylamide gel test objects with features from 1 to 15 mm in diameter; and (4) healthy volunteers.

RESULTS

The mean error ± SD between sound speed reference and image data was -0.48% ± 9.1%, and the error between reference and velocimeter measurements was -1.78% ± 6.50%. Sound speed image and velocimeter measurements showed a difference of 0.10% ± 4.04%. Temperature data showed a difference between theory and imaging performance of -0.28% ± 0.22%. Images of polyacrylamide test objects showed detectability of an approximately 1% sound speed difference in a 2.4-mm cylindrical inclusion with a contrast to noise ratio of 7.9 dB.

CONCLUSIONS

An automated breast scanner offers the potential to make consistent automated tomographic images of breast backscatter, sound speed, and attenuation, potentially improving diagnosis, particularly in dense breasts.

Calibration methods used in cancer simulation models and suggested reporting guidelines

Increasingly, computer simulation models are used for economic and policy evaluation in cancer prevention and control. A model's predictions of key outcomes, such as screening effectiveness, depend on the values of unobservable natural history parameters. Calibration is the process of determining the values of unobservable parameters by constraining model output to replicate observed data. Because there are many approaches for model calibration and little consensus on best practices, we surveyed the literature to catalogue the use and reporting of these methods in cancer simulation models. We conducted a MEDLINE search (1980 through 2006) for articles on cancer-screening models and supplemented search results with articles from our personal reference databases. For each article, two authors independently abstracted pre-determined items using a standard form. Data items included cancer site, model type, methods used for determination of unobservable parameter values and description of any calibration protocol. All authors reached consensus on items of disagreement. Reviews and non-cancer models were excluded. Articles describing analytical models, which estimate parameters with statistical approaches (e.g. maximum likelihood) were catalogued separately. Models that included unobservable parameters were analysed and classified by whether calibration methods were reported and if so, the methods used. The review process yielded 154 articles that met our inclusion criteria and, of these, we concluded that 131 may have used calibration methods to determine model parameters. Although the term 'calibration' was not always used, descriptions of calibration or 'model fitting' were found in 50% (n = 66) of the articles, with an additional 16% (n = 21) providing a reference to methods. Calibration target data were identified in nearly all of these articles. Other methodological details, such as the goodness-of-fit metric, were discussed in 54% (n = 47 of 87) of the articles reporting calibration methods, while few details were provided on the algorithms used to search the parameter space. Our review shows that the use of cancer simulation modelling is increasing, although thorough descriptions of calibration procedures are rare in the published literature for these models. Calibration is a key component of model development and is central to the validity and credibility of subsequent analyses and inferences drawn from model predictions. To aid peer-review and facilitate discussion of modelling methods, we propose a standardized Calibration Reporting Checklist for model documentation.

Long-term risk of false-positive screening results and subsequent biopsy as a function of mammography use

PURPOSE

To retrospectively determine the long-term risk of false-positive mammographic assessments and to evaluate the effect of screening regularity on the risk of false-positive events.

MATERIALS AND METHODS

Institutional review board approval was obtained, and informed consent was waived. Retrospective analysis was performed for the occurrence of false-positive assessments among 83,511 women who underwent 314,185 mammographic examinations from January 1, 1985, to February 19, 2002. Data were collected from a database that had been assembled prospectively. Two categories of false-positive events were examined: biopsies that did not reveal cancer and false-positive mammographic assessments. Rates of false-positive events were compared by using a chi2 analysis, and 95% confidence limits were calculated. Because comparisons of multiple pairs were considered, all P values that demonstrated statistical significance exceeded the requirement of the Bonferroni correction.

RESULTS

While the overall rates of biopsies that did not reveal cancer and of false-positive mammographic assessments were similar to those found in other studies, most of the burden of false-positive events was borne by women who underwent intermittent screening. Long-term rates of false-positive events were lower among women who underwent regular screening than among those who underwent intermittent screening. In the 5-year group, 2.9% of women who underwent five mammographic examinations over the next 5 years had biopsy results that did not reveal cancer, whereas 4.6% of women who underwent three mammographic examinations over the next 5 years had biopsy results that did not reveal cancer. For women who underwent regular screening, the risk of undergoing biopsies that did not reveal cancer declined over time to 0.25% per year after several years of screening, a value that is lower than the risk of these events among women who did not undergo screening. The rate of false-positive mammographic assessments was also lower for women who underwent regular screening than for those who underwent intermittent screening.

CONCLUSION

Prompt annual attendance for mammographic screening reduces the occurrence of false-positive mammographic results.

Mathematical modelling of radiotherapy strategies for early breast cancer

Targeted intraoperative radiotherapy (Targit) is a new concept of partial breast irradiation where single fraction radiotherapy is delivered directly to the tumour bed. Apart from logistic advantages, this strategy minimizes the risk of missing the tumour bed and avoids delay between surgery and radiotherapy. It is presently being compared with the standard fractionated external beam radiotherapy (EBRT) in randomized trials. In this paper we present a mathematical model for the growth and invasion of a solid tumour into a domain of tissue (in this case breast tissue), and then a model for surgery and radiation treatment of this tumour. We use the established linear-quadratic (LQ) model to compute the survival probabilities for both tumour cells and irradiated breast tissue and then simulate the effects of conventional EBRT and Targit. True local recurrence of the tumour could arise either from stray tumour cells, or the tumour bed that harbours morphologically normal cells having a predisposition to genetic changes, such as a loss of heterozygosity (LOH) in genes that are crucial for tumourigenesis, e.g. tumour suppressor genes (TSGs). Our mathematical model predicts that the single high dose of radiotherapy delivered by Targit would result in eliminating all these sources of recurrence, whereas the fractionated EBRT would eliminate stray tumour cells, but allow (by virtue of its very schedule) the cells with LOH in TSGs or cell-cycle checkpoint genes to pass on low-dose radiation-induced DNA damage and consequently mutations that may favour the development of a new tumour. The mathematical model presented here is an initial attempt to model a biologically complex phenomenon that has until now received little attention in the literature and provides a 'proof of principle' that it is possible to produce clinically testable hypotheses on the effects of different approaches of radiotherapy for breast cancer.