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Recent evidence suggests that the breast and ovarian cancer susceptibility gene product BRACA1 is involved in the DNA damage response. However, the precise biochemical function of BRACA1 has remained unknown. Initially, we identified a naturally-occurring allele of BRACA1 which codes for a single amino acid substitution from arginine to tryptophan at residue 1699 (R11699W) and displays temperature-sensitive activity in transcription. The transcription activity of the mutant protein appears to undergo complex regulation, as temperature-sensitive (TS) transcription activation was found to be cell type specific and not dependent on the tissue of origin. We have characterized the behavior of this mutant and isolated several stable cell lines. In addition, through a screen in yeast we identified 11 more unique TS mutants and determined a preferential location for these mutations in the first BRCT domain of BRCA1. We have also generated a series of mutations at residue 1699 and characterized them for transcription activity in different temperatures. Our results provide a framework to engineer conditional mutants of BRCA1 that will aid in the dissection of its in vivo function.

The overall objective of this research proposal is semi-parametric inference of the Cox proportional hazards (PH) regression model for a survival function Pr(X > x I Z = z) = S(x I z) = S 0 (x)ezbeta , where X is a time-to-event variable. which is subject to interval censoring, Z represents the covariates, S0 is a baseline survival function, and beta represents the regression coefficients. The main objective of our research is to develop asymptotic inferences of the generalized maximum likelihood estimators (GMLE) of beta and S(. I z). A critical limitation with GMLE under interval censoring is that it is computationally feasible only for a small data set. We therefore propose to also investigate asymptotic properties of a computationally simpler alternative to GMLE, namely two-stage estimators (TSE) of beta and S(. I z) obtained by a two-stage modified Newton-Raphson algorithm involving data grouping. In the four years of our research, we have implemented a foolproof algorithm for obtaining TSE, proved consistency and established asymptotic normality for both GMLE and TSE under both discrete and continuous distributional assumptions, and proposed new diagnostic method for PH assumption. Also, we have successfully applied our asymptotic Cox regression methodology to the analysis of a large-scale, long-term breast cancer relapse follow-up study. Our results will be useful to data analysis of breast cancer relapse follow-up studies, chemoprevention intervention trials and genetic studies on familial aggregation of breast cancer and related cancers.

BRCA2 mutations leading to premature termination of the protein confer high cancer risk. Currently very few clinical options are possible for women carrying predisposing mutations. So far, the only one to provide a significant reduction in risk is prophylactic mastectomy and oopherectomy. Restoring BRCAl function in these patients might result in a significant decrease in cancer risk. We proposed to restore BRCAl function using antibiotics. In eukaryotic cells, aminoglycosides interact with ribosomal RNA and relaxes codon recognition allowing normal tRNAs to insert an amino acid at a codon specifying a stop. As a result, the ribosome will read through the mutation and produce a full-length protein that can potentially restore the protein's original function. We focused on the following aims: Screen aminoglycosides in yeast to determine if they could suppress a nonsense mutation in BRCAl; Determine the ability of selected antibiotics in human cells to suppress different types of mutations and on the wild type BRCAl. We show that gentamicin suppresses BRCAl nonsense mutations is able to restore some of the wildtype protein levels and may provide a preventive strategy for individuals carrying these mutations. Given the dearth of alternatives for these individuals and the results obtained in our studies the use of antibiotics merits further investigation., The original document contains color images. All DTIC reproductions will be in black and white.

The overall objective of this research proposal is semi-parametric inference of the Cox proportional hazards (PH) regression model for a survival function Pr(X > x/Z=z) = S(x/z) = S.(x) ex beta, where X is a timetoevent variable, which is subject to interval censoring, Z represents the covariates, So is a baseline survival function, and Z represents the regression coefficients. One objective of our research is to develop asymptotic inferences of the generalized maximum likelihood estimators (GMLE) of beta and S(.

The overall objective of our research proposal is nonparametric inference of the joint survival function S(x1, ..., xd) =Pr(X1 > x1, ..., Xd > xd) of d (>= 2) correlated time-to-event variables X1, ..., Xd, each of which is subject to interval censoring. The standard estimator of S is the generalized maximum likelihood estimator (GMLE) S. However, S cannot be expressed in a closed-form expression and its statistical properties have not been studied in the multivariate case. The technical objectives of this pioneer methodological research proposal are to develop asymptotic generalized maximal likelihood (GML) inference of S and to derive efficient computational algorithms for the GML procedure. In our fourth and final year of research, we have implemented a computer software for asymptotic inference of GMLE p of the correlation coefficient p between a pair of the X' variables. When the censoring distribution is continuous, we have numerically established p is not asymptotically normal and we have implemented a bootstrap method for obtaining interval estimator of p. Thus in our four years of research, we have successfully completed the tasks we proposed. The results will be useful to breast cancer researchers pursuing chemoprevention intervention trials involving multiple surrogate endpoint biomarkers, and genetic epidemiologists conducting studies on familial aggregation of breast cancer and related cancers.

Recent evidence suggests that the breast and ovarian cancer susceptibility gene product BRCAl is involved in at least two fundamental cellular processes: transcriptional regulation and DNA repair. The precise mechanism of action of BRCAl in either of these processes is still unknown. We have identified a naturally-occurring allele of BRCAl which codes for a single amino acid substitution from arginine to tryptophan at residue 1699 (R1699W). This mutation occurs in a region at tile N- terminal BRCT domain that is highly conserved among BRCAl homologs. When the C-terminus of the mutant protein (aa 1560-1863) was fused to a heterologous GAL4 DNA-binding domain and expressed in yeast or mammalian cells, it was able to activate transcription of a reporter gene to levels observed for wild type BRCAl at the permissive temperature (30C) but exhibited significantly less transcription activity at the restrictive temperature (37C or 39C). The transcription activity of the mutant protein appears to undergo complex regulation, as temperature-sensitive transcription activation was found to be cell type specific and not dependent on the tissue of origin. Stable cell lines expressing the mutant protein had similar capacity for DNA-damage repair of double strand breaks induced by ionizing radiation at all temperatures examined, suggesting that the activity of the mutant protein in DNA-damage repair is not temperature sensitive. . Our results demonstrate that the transcriptional activity of the R1699W) mutant can be modulated as a function of temperature and provide a novel experimental approach which can be utilized to dissect the molecular mechanism(s) of BRCAl in processes related to transcription., The original document contains color images. All DTIC reproductions will be in black and white.

In our original proposal we presented preliminary evidence suggesting a critical region for the modulation of BRCA1's transactivation activity and proposed the existence of an intramolecular interaction domain that masks the activation domain of BRCA1, thus impairing the recruitment of the machinery involved in transcription initiation. Our hypothesis was that BRCA1 transcriptional function is regulated by an auto inhibitory intramolecular interaction between regions encoded by exon 12 (and possibly part of exon 13) and the C-terminal region comprising the BRCT domains. We suggested that this mechanism might form the basis of the regulation of transcriptional activation by BRCA1. Our expectation was that a region that interacts and masks the activation domain would be identified in detail and would reveal one of the means by which BRCAl activity is regulated. During the past four years the experiments performed seem to refute our original hypothesis. At this point, the experiments conducted here have refuted our initial hypothesis of a regulatory role for an intramolecular interaction in BRCA1. Nevertheless, the experiments revealed that a putative coiled-coil domain spanning exons 12 and 13 is important for transcription regulation.

Inherited mutations in BRCA1 account for the majority of cancer cases in families with hereditary breast and ovarian cancer. Current evidence indicates that BRCA1 is involved in several cellular processes including transcriptional activation, cell cycle regulation, DNA damage repair and maintenance of genomic stability 2 Deleterious alterations in BRCA1 may result in disruption of any or all of these processes and lead to cancer. Missense, nonsense and frameshift mutations that disrupt the function of BRCA1 confer cancer predisposition to individuals carrying the mutation. Most of these mutations are highly penetrant and confer 56-85% lifetime risk for breast cancer, which is significantly higher than the 11% lifetime risk in the general population. Linkage analysis suggests that all mutations leading to premature termination of the protein documented so far will confer high cancer risk.

Interval-censored (IC) data are encountered in three areas of breast cancer research. The most common application is in clinical relapse follow-up studies in which the study endpoint is disease-free survival. When a patient relapses, it is usually known that the relapse takes place between two follow-up visits, and the exact time to relapse is unknown. In statistics, we say relapse time is interval censored. Interval censoring is also encountered in breast cancer registry studies in which information on family history of cancer is updated periodically. The Strang Breast Surveillance Program for women at increased risk for breast cancer, for instance, has enlisted over 800 women with complete pedigree information which is verified and updated continuously. Family history data such as age at diagnosis of a specific cancer, or a benign but risk-conferring condition, are obtained from each registrant at each update. Time to a cancer event, and definitely time to first detection of a benign condition, are at best known to fall in the time interval between the last update and age at diagnosis. A third but increasingly important area of application of interval censoring is in breast cancer chemoprevention experiments or prevention trials, which involve the observation of one or more surrogate endpoint biomarkers (SEB) over time. The scientific question of interest here is the estimation of time for the SEB to reach a target value, and time from cessation of intake of a chemopreventive agent to the loss of its protective effect. Unfortunately, the exact values of both these time variables are known only to lie in between two successive assay inspection times.

Several physiological roles of the breast and ovarian cancer susceptibility gene (BRCA1) have been described which include control of cell cycle, activation of transcription and nodulation of DNA damage response. The mechanism by which BRCA1 mediates these processes remains unclear. We have identified and characterized a naturally-occurring cancer-predisposing allele of BRCA1 with a missense mutation that displays temperature-sensitive activity. When the carboxy-terminus of BRCA1 carrying the mutation was fused to a GAL4 DNA-binding domain and expressed in human embryonic kidney cells, it was able to activate transcription of a CAL4-responsive reporter gene in a temperature-sensitive manner. At the permissive temperature, transcription activity of this mutant was approximately equal to wild-type, while at the non-permissive temperature, its activity was diminished but not abolished. Based on this observation, we designed a yeast-based screen for additional temperature-sensitive mutations of the C-terminus of BRCA1. One of the mutants identified in yeast, H1686Q, was able to activate transcription of a luciferase reporter gene in human cells in a temperature-dependent manner. Unlike the naturally-occurring mutation, the H1686Q was active only at the permissive temperature. Studies using full-length BRCA1 constructs carrying the naturally-occurring mutation indicate that the cellular distribution of this mutated protein was similar to wild-type at both permissive and non-permissive temperatures. We have generated several stable cell lines that express the full-length naturally-occurring cancer-predisposing mutant protein and are presently using these cells to analyze the role of BRCA1 in transcription activation, cell cycle control and DNA damage response.

The overall objective of this research proposal is semi-parametric inference of the Cox regression model for a survival function Pr(X > x/Z=z)=S(x/z)= So(x)ez beta, where X is subject to interval censoring, Z represents the covariates, So is a baseline survival function, and beta represents the regression coefficients. One objective of our research is to develop asymptotic inference of the generalized maximum likelihood estimator (GMLE) of the regression coefficients beta and S(./z).

The long-range goal of the laboratory is to elucidate the role of genes involved in the development of breast and ovarian cancer, with a focus on the function of the tumor suppressor gene BRCAl. The human BRCAl gene codes for a nuclear phosphoprotein that is likely to be multifunctional. Recent genetic and biochemical evidence indicates that BRCAl participates in the cellular DNA damage response. However, it is not known how BRCAl exert its actions. Several lines of evidence suggest that it may function through transcription. Our working model is that impairment of BRCAl-mediated transcription activation predisposes to the development of cancer. By the end of the third year of our project we were able to develop a functional assay system to study the impact of all unclassified missense variants of BRCAl that are located between aa 1366 and 1864 greatly expanding the scope of the transcription assay. In the course of this work we have also identified mutations in exon 13 that affect transcription activation and may define a region important for transcriptional regulation. Our results, taken together, reinforce the notion that sequences coded by exons 12 and 13 are important for the regulation of transcription by BRCAl.

Interval-censored (IC) data are encountered in three areas of breast cancer research. The most common application is in clinical relapse follow-up studies in which the study endpoint is disease-free survival. When a patient relapses, it is usually known that the relapse takes place between two follow-up visits, and the exact time to relapse is unknown. In statistics, we say relapse time is interval censored. Interval censoring is also encountered in breast cancer registry studies in which information on family history of cancer is updated periodically. The Strang Breast Surveillance Program for women at increased risk for breast cancer, for instance, has enlisted over 800 women with complete pedigree information which is verified and updated continuously. Family history data such as age at diagnosis of a specific cancer, or a benign but risk-conferring condition, are obtained from each registrant at each update. Time to a cancer event, and definitely time to first detection of a benign condition, are at best known to fall in the time interval between the last update and age at diagnosis. A third but increasingly important area of application of interval censoring is in breast cancer chemoprevention experiments or prevention trials, which involve the observation of one or more surrogate endpoint biomarkers (SEB) over time. The scientific question of interest here is the estimation of time for the SEB to reach a target value, and time from cessation of intake of a chemopreventive agent to the loss of its protective effect. Unfortunately, the exact values of both these time variables are known only to lie in between two successive assay inspection times. In a breast cancer follow-up study, we will often encounter covariates (for instance, tumor size and nodal status in a relapse study, and baseline SEB value in a chemoprevention trial).

BRCA1 is involved in two fundamental cellular processes: DNA repair and transcriptional regulation. BRCAl C-terminus acts as a transactivation domain and introduction of germ-line mutations, but not benign polymorphisms, abolishes transcriptional activation, suggesting a critical role for this function of BRCAl in cancer development. Our hypothesis is that BRCA1 transactivation function is regulated by an intramolecular interaction. During the past year we focused on three specific aims: 1) map the interaction sites; 2) define the in vivo dominant negative activity of truncations in BRCAl that retain the inhibitory domain but disrupt the transactivation domain; 3) To analyze which mutations abolish transcriptional activation. We performed immunoprecipitations with FLAG-tagged constructs which revealed an in vivo interaction of the C-terminal region with aa 1366-1559, consistent with our hypothesis. We optimized transfection conditions for breast and ovarian cancer cells and are now currently determining if the trans-inhibition is differentially regulated in these cells. In addition, we provided validation for our functional assay, a required step before testing the effect of mutations located in the putative interaction region., Original contains color plates: All DTIC reproductions will be in black and white.

Interval-censored (IC) data are encountered in three areas of breast cancer research. The most common application is in clinical relapse follow-up studies in which the study endpoint is disease-free survival. When a patient relapses, it is usually known that the relapse takes place between two follow-up visits, and the exact time to relapse is unknown. In statistics, we say relapse time is interval censored. Interval censoring is also encountered in breast cancer registry studies in which information on family history of cancer is updated periodically. The Strang Breast Surveillance Program for women at increased risk for breast cancer, for instance, has enlisted over 800 women with complete pedigree information which is verified and updated continuously. Family history data such as age at diagnosis of a specific cancer, or a benign but risk-conferring condition, are obtained from each registrant at each update. Time to a cancer event, and definitely time to first detection of a benign condition, are at best known to fall in the time interval between the last update and age at diagnosis. A third but increasingly important area of application of interval censoring is in breast cancer chemoprevention experiments or prevention trials, which involve the observation of one or more surrogate endpoint biomarkers (SEB) over time. The scientific question of interest here is the estimation of time for the SEB to reach a target value, and time from cessation of intake of a chemopreventive agent to the loss of its protective effect. Unfortunately, the exact values of both these time variables are known only to lie in between two successive assay inspection times.

A randomized controlled trial of a psychoeducational group intervention was conducted. The specific aims were to examine the impact of the intervention on knowledge of breast cancer and risk factors, breast cancer beliefs, breast cancer anxiety, coping skills, quality of life and adherence to screening. The intervention components included social support enhancement, education, cognitive restructuring, and problem solving. Group sessions (5 to 10 women in each group) met for one and half-hours each of six weeks, with six-month and one year booster sessions. Interviews were conducted prior to randomization (Time 1), at the end of the six-week intervention (Time 2), at six months (Time 3) and one year (Time 4). 247 healthy, asymptomatic women at high risk for breast cancer (control condition N=l08); treatment condition N-139) participated in the study. The mean age is 43, primarily white (90%), with 39% having a college education. At baseline, 73% of women overestimated their risk, 17% accurately estimated their risk and 10% underestimated their risk for developing breast cancer. A repeated measures analysis of variance (ANOVA) found a significant reduction in breast cancer specific anxiety within the treatment condition from Time 1 to Time 4 (p<.02), and a decrease in perception of risk (p <.01). Women in the treatment condition significantly improved their knowledge of breast cancer (p <.02) and risk factors for breast cancer at Time 4 (p <.002). ANOVA found that women in the treatment condition used more active coping and less behavioral disengagement than women in the control condition (p <.04). A logistic regression analyses found that women in the treatment condition adhered to age appropriate mammogram recommendations at Time 4 (p <.01) more than women in the control condition. These findings suggest that the intervention helps to decrease anxiety, increase knowledge, improve coping strategies, and improve adherence to mammography.

Progress on determining the function of BRCA1 suggests its involvement in DNA repair and transcriptional regulation. BRCA1 C-terminus acts as a transactivation domain and introduction of germ-line mutations, but not benign polymorphisms, abolishes transcriptional activation, suggesting a critical role for this function of BRCA1 in cancer development. Our hypothesis is that BRCA1 transactivation function is regulated by an intramolecular interaction. During the past year we focused on two specific aims: (1) map the interaction sites; and (2) define the in vive dominant negative activity of truncations in BRCA1 that retain the inhibitory domain but disrupt the transactivation domain. We optimized transfection conditions and selected proper expression vectors for our analysis. In addition, we obtained several constructs containing BRCA1 fragments and confirmed protein expression in mammalian and yeast cells that will serve as important tools. A yeast two-hybrid approach and an interaction assay in mammalian cells were used to identify the interaction sites. However, while results from our interaction assay in mammalian cells are promising, the yeast two-hybrid system is not adequate due to the high background presented by the BRCA1 fragments. We have also investigated a yeast-based assay to screen for the dominant negative activity of various BRCA1 alleles., Original contains color plates: All DTIC reproductions will be in black and white.

Over expression of Wnt proteins has long been know to lead to mammary hyperplasia and neoplasia in the mouse mammary gland. Unregulated Wnt signaling may also contribute to the formation of human breast tumours as over expression of Wnt proteins and nuclear localization of 13-catenin has been reported. The experiments in this proposal are designed to identify the receptor proteins responsible for transduction of oncogenic Wnt signals in mammary cells. Possible candidates are members of the Frizzled, Notch and LRP families of transmembrane proteins as all have been suggested to act as Wnt receptors. A survey of the Frizzled, Notch and LRP proteins expressed in the mature virgin mammary gland of the mouse has been conducted to identify candidate receptors. Currently the ability of these proteins to interact physically with Wnt ligands is being tested in cross- linking and co-immunoprecipitation experiments. Also the ability of these proteins to transduce, and of dominant negative form to attenuate, a Wnt signal is being evaluated in a functional assay for Wnt signaling. Finally, a mammary specific transgene encoding a dominant negative Wnt receptor has been produced. This will be introduced into mice by pronuclear injection and tested for its ability to antagonize extracellular Wnt signals in mice and to prevent the onset of mammary hyperplasia and tumorigenesis caused by the Wnt-1 oncogene.

Interval-censored (IC) data are encountered in three areas of breast cancer research. The most common application is in clinical relapse follow-up studies in which the study endpoint is disease-free survival. When a patient relapses, it is usually known that the relapse takes place between two follow-up visits, and the exact time to relapse is unknown. In statistics, we say relapse time is interval censored. Interval censoring is also encountered in breast cancer registry studies in which information on family history of cancer is updated periodically. The Strang Breast Surveillance Program for women at increased risk for breast cancer, for instance, has enlisted over 800 women with complete pedigree information which is verified and updated continuously. Family history data such as age at diagnosis of a specific cancer, or a benign but risk-conferring condition, are obtained from each registrant at each update. Time to a cancer event, and definitely time to first detection of a benign condition, are at best known to fall in the time interval between the last update and age at diagnosis. A third but increasingly important area of application of interval censoring is in breast cancer chemoprevention experiments or prevention trials, which involve the observation of one or more surrogate endpoint biomarkers (SEB) over time. The scientific question of interest here is the estimation of time for the SEB to reach a target value, and time from cessation of intake of a chemopreventive agent to the loss of its protective effect. Unfortunately, the exact values of both these time variables are known only to lie in between two successive assay inspection times.

The overall aim of the research proposal is the statistical nonparametric inferences of the redistribution-to- the-center estimator (RTCE) and the generalized maximum likelihood estimator (GMLE) for the survival function of a time-to-event variable that is subject to interval censoring. The RTCE, proposed by the Strang Center, has a closed-form expression and is equal to GMLE under a homogeneous condition. The GMLE is the standard estimator in survival analysis. However, it cannot be expressed in a closed-form expression, and asymptotic distribution theory for it has been limited. From the study of the asymptotic properties of RTCE, we have gained important insight into proofs of asymptotic properties of GMLE. Specifically, we have established consistency, asymptotic normality and efficiency of GMLE under different conditions. Also, we have derived an asymptotic nonparametric two-sample distance test for comparing two populations. Under finite distributional assumptions on the survival and censoring distributions, we have established consistency, asymptotic normality for both the regression coefficients and the survival function of the Cox regression model. We point out major computational limitations associated with the Newton-Raphson algorithm for computing the asymptotic estimates of the Cox regression parameters, and suggest a simpler two-step estimation alternative., Collection of journal articles and abstracts.

The goals of this study are to: (1) examine the impact of a psychoeducational intervention on the intermediate outcome variables of knowledge of breast cancer and risk factors, breast cancer beliefs, cancer attitudes, and coping skills in women at increased risk for breast cancer; (2) examine the impact of a psychoeducational intervention on the endpoint variables of quality of life and adherence to screening in women at increased risk for breast cancer; and (3) explore the mechanisms by which the psychological intervention may improve quality of life and increase adherence to breast cancer screening in women at increased risk for breast cancer. The design is a randomized two-group design in which women are assigned to either the experimental or control arm. The intervention (experimental) components include; social support enhancement, education, cognitive restructuring, and problem solving. As of November 1998, 409 women have agreed to participate in the study and 212 have completed Time 1 assessments, 130 have completed Time 2 assessments; 106 women have completed Time 3 assessments, and 86 women have completed Time 4 assessments. Preliminary data indicates that knowledge of breast cancer is increased (p<.OOl), knowledge of risk factors is increased (p<.OOl), overestimation of risk is decreased (p<.02), and breast cancer specific anxiety is decreased (p<.O1) in the women in the experimental arm.

The overall aim of our research proposal is the statistical nonparametric inference of the redistribution-to-the-center estimator (RTCH) and the generalized maximum likelihood estimator (GMLE) for the survival function of a time-to- event variable that is subject to interval censoring. The RTCH, which is proposed by us, has a closed-form expression and is equal to the GMLE under a homogeneous condition. The GMLH is the standard optimal estimator in survival analysis. However, it cannot be expressed in a closed-form expression, and asymptotic distribution theory for it has been limited. From the asymptotic study of the RTCE, we have gained important insight into proofs of asymptotic properties of the GMTE. In the past four years we have established consistency, asymptotic normality and asymptotic efficiency of the GMLE under a variety of conditions. In addition, we have derived an asymptotic nonparametric two-sample distance test procedure for comparing two populations. Finally, we have begun investigating the asymptotic inference of Cox regression model for interval-censored data by establishing consistency and asymptotic normality of the %GMLE of the regression parameters under some finite assumptions. These preliminary results are being applied to a breast cancer prognostic relapse follow-up study.

The overall aim of our research proposal is the statistical inference of nonparametric estimates, the restribution-to-the-inside estimator (RTIE) and the generalized maximum likelihood estimator (GMLE),for the survival function of a time-to-event variable that is subject to interval censoring. The RTIE, which is proposed by us, has a closed-form expression and is equal to the GMLE under a homogeneous condition. The GMLE is the standard optimal procedure in survival analysis. However, no closed-form expression for the GMLE is available, and asymptotic distribution theory for it has been limited. Our research efforts in the third year have focused on the asymptotic inference of the GMLE under conditions more general than the discrete distribution assumption that we previously imposed on the censoring variables. Additionally, we have derived an asymptotic nonparametric the sample test procedure for comparing two populations. Finally, we have begun investigating the asymptotic inference of Cox regression model for interval-censored data by establishing consistency of the GMLE of the model parameters under finite assumptions on both the survival and censoring distributions.

The overall aim of our research proposal is the statistical investigation of a non-parametric estimate which we call redistribution-to-the-inside estimator (RTIE) for the survival function s(t) = Pr(X > t), where the survival time X is subject to interval censoring. Our research efforts in the first year have been focused on two aspects of RTIE for interval censored data satisfying the condition that for any pair f censoring intervals, either they are disjoint, or one is a subset of the other (DI condition). First, we have completed the implementation of a computer program oded in the C language to carry out the RTIE estimation procedure, including a Kaplan-Meier type plotting program for RTIE written in the S+ language. Second, we derive the uniform almost sure limit (strong consistency) of RTIE for any arbitrary S and any arbitrary censoring distribution function C under the DI model.

HE GOALS OF THIS STUDY ARE: (1) TO EXAMINE THE IMPACT OF A PSYCHOEDUCATIONAL INTERVENTION ON THE INTERMEDIATE OUTCOME VARIABLES OF KNOWLEDGE OF BREAST CANCER AND RISK FACTORS, BREAST CANCER BELIEFS, CANCER ATTITUDES, AND COPING SKILLS IN WOMEN AT INCREASED RISK FOR BREAST CANCER; (2) TO EXAMINE THE IMPACT OF A PSYCHOEDUCATIONAL INTERVENTION ON THE ENDPOINT VARIABLES OF QUALITY OF LIFE ADHERENCE TO SCREENING IN WOMEN AT INCREASED RISK FOR BREAST CANCER; AND (3) TO EXPLORE THE MECHANISMS BY WHICH THE PSYCHOLOGICAL INTERVENTION MAY IMPROVE QUALITY OF LIFE AND INCREASE ADHERENCE TO BREAST CANCER SCREENING IN WOMEN AT INCREASED RISK FOR BREAST CANCER. The design is a randomized two group design in which women are assigned to either the experimental or control group. The intervention (experimental) components include; social support enhancement, education, cognitive restructuring, and problem-solving. A total of 360 are expected to participate this study over a four year period of time. To date 101 women have agreed to participate in the study and 83 have completed Time 1 and 2 assessments; 17 women have completed Time 3 assessments. It is too early for any meaningful data analyses.