Anne Michelle Noone

Circulating Tumor Cells: A Useful Predictor of Treatment Efficacy in Metastatic Breast Cancer

PURPOSE Five or more circulating tumor cells (CTCs) per 7.5 mL of blood predicts for poorer progression-free survival (PFS) in patients with metastatic breast cancer (MBC). We conducted a prospective study to demonstrate that CTC results correlate strongly with radiographic disease progression at the time of and in advance of imaging. PATIENTS AND METHODS Serial CTC levels were obtained in patients starting a new treatment regimen for progressive, radiographically measurable MBC. Peripheral blood was collected for CTC enumeration at baseline and at 3- to 4-week intervals. Clinical outcomes were based on radiographic studies performed in 9- to 12-week intervals. RESULTS Sixty-eight patients were evaluable for the CTC-imaging correlations, and 74 patients were evaluable for the PFS analysis. Median follow-up was 13.3 months. A statistically significant correlation was demonstrated between CTC levels and radiographic disease progression in patients receiving chemotherapy or endocrine therapy. This correlation applied to CTC results obtained at the time of imaging (odds ratio [OR], 6.3), 3 to 5 weeks before imaging (OR, 3.1), and 7 to 9 weeks before imaging (OR, 4.9). Results from analyses stratified by type of therapy remained statistically significant. Shorter PFS was observed for patients with five or more CTCs at 3 to 5 weeks and at 7 to 9 weeks after the start of treatment. CONCLUSION We provide, to our knowledge, the first evidence of a strong correlation between CTC results and radiographic disease progression in patients receiving chemotherapy or endocrine therapy for MBC. These findings support the role of CTC enumeration as an adjunct to standard methods of monitoring disease status in MBC.

Breast Cancer Adjuvant Chemotherapy Decisions in Older Women: The Role of Patient Preference and Interactions With Physicians

PURPOSE Breast cancer chemotherapy decisions in patients > or = 65 years old (older) are complex because of comorbidity, toxicity, and limited data on patient preference. We examined relationships between preferences and chemotherapy use. METHODS Older women (n = 934) diagnosed with invasive (> or = 1 cm), nonmetastatic breast cancer from 2004 to 2008 were recruited from 53 cooperative group sites. Data were collected from patient interviews (87% complete), physician survey (93% complete), and charts. Logistic regression and multiple imputation methods were used to assess associations between chemotherapy and independent variables. Chemotherapy use was also evaluated according to the following two groups: indicated (estrogen receptor [ER] negative and/or node positive) and possibly indicated (ER positive and node negative). RESULTS Mean patient age was 73 years (range, 65 to 100 years). Unadjusted chemotherapy rates were 69% in the indicated group and 16% in the possibly indicated group. Women who would choose chemotherapy for an increase in survival of < or = 12 months had 3.9 times (95% CI, 2.4 to 6.3 times; P < .001) higher odds of receiving chemotherapy than women with lower preferences, controlling for covariates. Stronger preferences were seen when chemotherapy could be indicated (odds ratio [OR] = 7.7; 95% CI, 3.8 to 16; P < .001) than when treatment might be possibly indicated (OR = 1.9; 95% CI, 1.0 to 3.8; P = .06). Higher patient rating of provider communication was also related to chemotherapy use in the possibly indicated group (OR = 1.9 per 5-point increase in communication score; 95% CI, 1.4 to 2.8; P < .001) but not in the indicated group (P = .15). CONCLUSION Older womens preferences and communication with providers are important correlates of chemotherapy use, especially when benefits are more equivocal.

Socioeconomic and psychosocial gradients in cardiovascular pathogen burden and immune response: The multi-ethnic study of atherosclerosis

BACKGROUND The biologic mechanisms linking socioeconomic position and psychosocial factors to cardiovascular disease (CVD) are not well understood. Immune response to persistent pathogens may be one of these mechanisms. METHODS We analyzed cross-sectional data from the multi-ethnic study of atherosclerosis (N=999) composed of adults age 45-84. Log-binomial regression and ordinal logistic regression models were used to examine associations of socioeconomic factors and psychosocial factors with pathogen burden and immune response among those infected. Pathogen burden was assessed based on seroprevalence of Helicobacter pylori, cytomegalovirus, herpes simplex virus-1, and Chlamydia pneumoniae and antibody levels were used to characterize high immune response to all four pathogens. RESULTS Low education was a strong and significant independent predictor of higher pathogen burden after adjustment for covariates (adjusted odds ratio (OR) 95% confidence interval (CI) 1.37, 1.19-1.57). Among subjects seropositive for all four pathogens, low education and a higher level of chronic psychosocial stress showed a positive association with higher antibody response, although associations were no longer significant in models with all covariates included (OR=1.64, 95% CI 0.82-3.31 for lowest vs. highest educational category and OR=1.29, 95% CI 0.96-1.73 for a one level increase in chronic stress). CONCLUSION Pathogen burden and heightened immune response may represent a biological pathway by which low socioeconomic position and chronic stress are related to increased rates of cardiovascular disease.

Racial differences in colorectal cancer survival in the Detroit Metropolitan area

African‐American (AA) women have lower survival rates from cervical cancer compared with white women. The objective of this study was to examine the influence of socioeconomic status (SES) and other variables on racial disparities in overall survival among women with invasive cervical cancer.

Racial differences in breast cancer survival in the Detroit Metropolitan area

SummaryAfrican American (AA) women have poorer breast cancer survival compared to Caucasian American (CA) women. The purpose of this analysis was to determine whether socioeconomic status (SES) and treatment differences influence racial differences in breast cancer survival. The study population included 9,321 women (82% CA, 18% AA) diagnosed with local (63%) or regional (37%) stage disease between 1988 and 1992, identified through the Metropolitan Detroit SEER registry. Data on SES were obtained through linkage with the 1990 Census of Population and Housing Summary Tape and cases were geocoded to census block groups. Pathology, treatment and survival data were obtained through SEER. Cox proportional hazards models were used to compare survival for AA versus CA women after adjusting for age, SES, tumor size, number of involved lymph nodes, and treatment. AA␣women were more likely to live in a geographic area classified as working poor than were CA women (p<0.001). AA women were less likely to have lumpectomy and radiation and more likely to have mastectomy with radiation (p<0.001). After multivariable adjusted analysis, there were no significant racial differences in survival among women with local stage disease, although AA women with regional stage disease had persistent but attenuated poorer survival compared to CA women. After adjusting for known clinical and SES predictors of survival, AA and CA women who are diagnosed with local disease demonstrate similar overall and breast cancer-specific survival, while race continues to have an independent effect among women presenting at a later stage of disease.

A Bayesian approach to competing risks analysis with masked cause of death

Cause-specific analyses under a competing risks framework have received considerable attention in the statistical literature. Such analyses are useful for comparing mortality patterns across racial and/or age groups. Earlier work in the statistical literature focused on the situation when the cause of death is known. A challenging twist to the problem arises when the cause of death is not known exactly, but can be narrowed down to a set of potential causes that do not necessarily act independently. This phenomenon, referred to as masking, is often the result of incomplete or partial information on death certificates and/or lack of routine autopsy on every patient. In this article we propose a semiparametric Bayesian approach for analyzing competing risks survival data with masked cause of death. The models proposed do not assume independence among the causes, and are valid for an arbitrary number of causes. Further, the Bayesian approach is flexible in allowing a general pattern of missingness for the cause of death. We illustrate our methodology using breast cancer data from the Detroit Surveillance, Epidemiology, and End Results registry.

Identifying representative trees from ensembles

Tree-based methods have become popular for analyzing complex data structures where the primary goal is risk stratification of patients. Ensemble techniques improve the accuracy in prediction and address the instability in a single tree by growing an ensemble of trees and aggregating. However, in the process, individual trees get lost. In this paper, we propose a methodology for identifying the most representative trees in an ensemble on the basis of several tree distance metrics. Although our focus is on binary outcomes, the methods are applicable to censored data as well. For any two trees, the distance metrics are chosen to (1) measure similarity of the covariates used to split the trees; (2) reflect similar clustering of patients in the terminal nodes of the trees; and (3) measure similarity in predictions from the two trees. Whereas the latter focuses on prediction, the first two metrics focus on the architectural similarity between two trees. The most representative trees in the ensemble are chosen on the basis of the average distance between a tree and all other trees in the ensemble. Out-of-bag estimate of error rate is obtained using neighborhoods of representative trees. Simulations and data examples show gains in predictive accuracy when averaging over such neighborhoods. We illustrate our methods using a dataset of kidney cancer treatment receipt (binary outcome) and a second dataset of breast cancer survival (censored outcome).

4-1BB costimulation of effector T cells for adoptive immunotherapy of cancer: involvement of Bcl gene family members.

We previously reported that in vitro costimulation of murine MCA 205 tumor-draining lymph node (TDLN) cells through a third signal, 4-1BB (CD137), in addition to CD3 and CD28 engagement significantly increases T-cell yield and amplifies antitumor responses in adoptive therapy. The increased T-cell yield seemed to be related to inhibition of activation-induced cell death. In this study, using real time-polymerase chain reaction and intracellular staining, we tested our hypothesis that antiapoptotic Bcl gene members are modulated in 4-1BB ligated TDLN cells. TDLN cells activated through 4-1BB in conjunction with CD3/CD28 demonstrated elevated Bcl-2 and Bcl-xL gene and protein expression compared with CD3/CD28 activation. Furthermore, Bcl-2 and/or Bcl-xL inhibition abrogated 4-1BB–conferred rescue of activation-induced cell death in TDLN cells, and as a result, 4-1BB–enhanced TDLN cell yield was abolished. Congenic mice were used as donors for TDLN cells labeled with CFSE to evaluate proliferation and persistence of activated cells after intravenous adoptive transfer. The effector function of transferred cells was assessed by determining the incidence of interferon-γ–producing cells in response to tumor stimulation in serial blood samples drawn from treated mice using intracellular cytokine staining. CD28 and CD28/4-1BB costimulation significantly enhanced in vivo proliferation and survival of the infused cells compared with CD3 activation. 4-1BB coligation augmented the proliferation and effector function of the infused cells compared with both CD3 and CD3/CD28-activated cells. Characterizing the function of signaling molecules involved in T-cell activation pathways may allow optimization of conditions in the generation of effector T cells for cancer immunotherapy.