Abstract PD4-06: A clinical model for assessing the individual breast cancer risk in mammography screening

Background. Mammography screening reduces breast cancer mortality, but is suboptimal for the breast cancers that are not detected by the screening. These women are identified as symptomatic interval cancers with more aggressive tumors and worse pronosis. To efficiently screen for breast cancer the individual breast cancer risk should be determined. We describe a model that is suited for bi-annual screening programs and estimates the 2-year risk of breast cancer. The risk model could be used at most mammography screening units without adding substantial cost.

Methods. The study was based on the population based prospective KARMA cohort including 70,877 participants. Mammograms were collected up to five years following baseline mammogram. A prediction model was developed using mammographic features (density, microcalcifications and masses), use of hormone replacement therapy (HRT), family history of breast cancer, menopausal status, and body mass index. Relative risks were calculated using conditional logistic regression and 2-year absolute risks were calculated

Results. Comparing women at highest and lowest mammographic density yielded a 5-fold higher risk of breast cancer for women at highest density. When adding microcalcifications and masses to the model, high-risk women had a nearly 9-fold higher risk of breast cancer compared to those at lowest risk. In the full model, taking HRT use, family history of breast cancer and menopausal status into consideration, area under the curve (AUC) reached 0.73.

We calculated the absolute 2-year risk of breast cancer based on national incidence and mortality rates. We also stratified women into risk groups using the NICE guidelines adapted to 2-year risks. The 20% women with moderate or high breast cancer risk were 7.6 times more likely to develop breast cancer compared to the general risk. Also 18% of the women showed 4 times reduced risk compared to the average population.

Conclusions. This risk model can improve mammography screening by identifying women that are in need of additional examination procedures. There is also a substantial proportion of women with low breast cancer risk who will have little benefit from screening.

Citation Format: Eriksson M, Czene K, Pawitan Y, Hall P. A clinical model for assessing the individual breast cancer risk in mammography screening [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD4-06.

Abstract P2-06-06: A clinical model for assessment of the individual breast cancer risk

Background. Most mammography screening programs are not individualized. To efficiently screen for breast cancer the individual risk of the disease should be determined. We describe a model that estimate the 2-year risk of breast cancer and could be used at most mammography screening units without adding substantial cost.

Methods. The study was based on the population based prospective Karma cohort including 70,877 participants. Mammograms were collected up to three years following baseline mammogram. A prediction protocol was developed using mammographic features (density, microcalcifications and masses), use of hormone replacement therapy (HRT), family history of breast cancer, menopausal status, age, and body mass index. Relative risks were calculated using conditional logistic regression. Absolute risks were calculated using the iCARE protocol.

Results. Comparing women at highest and lowest mammographic density yielded a 5-fold higher risk of breast cancer for women at highest density. When adding microcalcifications and masses to the model, high-risk women had a nearly 9-fold higher risk of breast cancer compared to those at lowest risk. The difference in microcalcifications and masses between left and right breast was a better predictor of breast cancer than number of microcalcifications and masses in the breasts.

When calculating the absolute 2-year risk of breast cancer we stratified women using the NICE guidelines for 10-year risk divided by 5 (Table 1). The mean absolute 2-year risk of breast cancer in the different risk categories was 0.12%, 0.33%, 0.83% and 1.95% for women at low, moderate, general, and high risk. In most countries with established mammography screening programs approximately 5 women in a 1000 are diagnosed with breast cancer at regular screening. We managed to identify a low risk group of approximately 10% of all women where 1 woman in a 1000 will be diagnosed with breast cancer, contrasting the 2% of all women at highest risk where 20 women out of a 1000 will be diagnosed with breast cancer within 2 years of last negative screen (Table 1).

In the full model, taking HRT use, family history of breast cancer and menopausal status into consideration, area under the curve (AUC) reached 0.71.

Conclusions. Our model includes three mammographic features that could easily be derived from clinically available software. By adding information on some few established risk factors it is possible to improve clinical care by identifying women in need of additional examination procedures. At the same time there is a substantial proportion of women that will have very little benefit from mammography screening due to their low risk of breast cancer.

Table 1. Absolute 2-year risk of breast cancer in women stratified in to risk categories based on the NICE guidelinesAbsolute 2-year risk (risk group)Percent women at riskMean absolute 2-year risk2Stratified 2-year risk0-0.15 (low)10.30.121.0 (reference)0.15-<0.6 (general)64.80.332.750.6-<1.6 (moderate)22.90.826.83≥1.6 (high)2.01.9516.2

Citation Format: Eriksson M, Czene K, Pawitan Y, Leifland K, Darabi H, Hall P. A clinical model for assessment of the individual breast cancer risk [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-06-06.

Bounds on causal interactions for binary outcomes

A common goal of epidemiologic research is to study how two exposures interact in causing a binary outcome. Causal interaction is defined as the presence of subjects for which the causal effect of one exposure depends on the level of the other exposure. For binary exposures, it has previously been shown that the presence of causal interaction is testable through additive statistical interaction. However, it has also been shown that the magnitude of causal interaction, defined as the proportion of subjects for which there is causal interaction, is generally not identifiable. In this article, we derive bounds on causal interactions, which are applicable to binary outcomes and categorical exposures with arbitrarily many levels. These bounds can be used to assess the magnitude of causal interaction, and serve as an important complement to the statistical test that is frequently employed. The bounds are derived both without and with an assumption about monotone exposure effects. We present an application of the bounds to a study of gene-gene interaction in rheumatoid arthritis.

A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease

The study of de novo point mutations (new germline mutations arising from the gametes of the parents) remained largely static until the arrival of next-generation sequencing technologies, which made both whole-exome sequencing (WES) and whole-genome sequencing (WGS) feasible in practical terms. Single nucleotide polymorphism genotyping arrays have been used to identify de novo copy-number variants in a number of common neurodevelopmental conditions such as schizophrenia and autism. By contrast, as point mutations and microlesions occurring de novo are refractory to analysis by these microarray-based methods, little was known about either their frequency or impact upon neurodevelopmental disease, until the advent of WES. De novo point mutations have recently been implicated in schizophrenia, autism and mental retardation through the WES of case-parent trios. Taken together, these findings strengthen the hypothesis that the occurrence of de novo mutations could account for the high prevalence of such diseases that are associated with a marked reduction in fecundity. De novo point mutations are also known to be responsible for many sporadic cases of rare dominant mendelian disorders such as Kabuki syndrome, Schinzel-Giedion syndrome and Bohring-Opitz syndrome. These disorders share a common feature in that they are all characterized by intellectual disability. In summary, recent WES studies of neurodevelopmental and neuropsychiatric disease have provided new insights into the role of de novo mutations in these disorders. Our knowledge of de novo mutations is likely to be further accelerated by WGS. However, the collection of case-parent trios will be a prerequisite for such studies. This review aims to discuss recent developments in the study of de novo mutations made possible by technological advances in DNA sequencing.

Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer

Epithelial-mesenchymal transition (EMT) is an initiating event in tumor cell invasion and metastasis. It has been shown to occur in resistance to a range of cancer therapies, including tamoxifen. MicroRNAs (miRNAs) have been associated with EMT as well as resistance to standard therapies. To investigate the role of miRNAs in the development of resistance to tamoxifen as well as accompanying EMT-like properties, we established a tamoxifen-resistant (TamR) model by continually exposing MCF-7 breast cancer cells to tamoxifen. In addition to the molecular changes known to be involved in acquired tamoxifen resistance, TamR cells displayed mesenchymal features and had increased invasiveness. Genome-wide miRNA microarray analysis revealed that miRNA-375 was among the top downregulated miRNAs in resistant cells. Re-expression of miR-375 was sufficient to sensitize TamR cells to tamoxifen and partly reversed EMT. A combination of mRNA profiling, bioinformatics analysis and experimental validation identified metadherin (MTDH) as a direct target of miR-375. Knockdown of MTDH partially phenocopied the effects of miR-375 on the sensitivity to tamoxifen and the reversal of EMT. We observed an inverse correlation between the expression of miR-375 and its target MTDH in primary breast cancer samples, implying the pathological relevance of targeting. Finally, tamoxifen-treated patients with higher expression of MTDH had a shorter disease-free survival and higher risk of relapse. As most cancer-related deaths occur because of resistance to standard therapies and metastasis, re-expression of miR-375 or targeting MTDH might serve as potential therapeutic approaches for the treatment of TamR breast cancer.

Time trends in risk and risk determinants of non-Hodgkin lymphoma in solid organ transplant recipients

Organ transplantation increases risk of non-Hodgkin lymphoma (NHL), but long-term risk and time trends have seldom been evaluated. Immunosuppressive drug load is an important risk determinant, but the details are unclear. We studied NHL risk in a nationwide Swedish cohort of 11 081 graft recipients transplanted 1970-2008. Relative risks (RRs) were estimated within the cohort and versus the general population by age, sex, follow-up time and calendar period. NHL risk was also assessed by cumulative and average doses of immunosuppressive treatments in a nested case-control design throughout 1997 using conditional logistic regression. We observed 153 NHL cases during 97 853 years of follow-up. Compared with the general population, NHL risk was eightfold increased (RR 7.9; 95% confidence interval [CI] 6.6-9.4), and increased risks persisted after ≥15 years of follow-up among kidney (6.1; 95% CI 3.5-10) and nonkidney recipients (44; 14-103). Among nonkidney recipients, NHL risk was lower in the 2000s compared with the 1990s (0.5; 95% CI 0.3-1.0; p = 0.04). A high average dose of antithymocyte immunoglobulin (ATG) conferred an eightfold increased risk of NHL (OR 8.5; 95% CI 1.9-38). To conclude, posttransplant NHL risk decreased during the last decade among nonkidney recipients, possibly because of a more careful use of ATG, the introduction of new drugs, or both.

Estimating the number of true discoveries in genome-wide association studies

Recent genome-wide association studies have reported the discoveries of genetic variants of small to moderate effects. However, most studies of complex diseases face a great challenge because the number of significant variants is less than what is required to explain the disease heritability. A new approach is needed to recognize all potential discoveries in the data. In this paper, we present a practical model-free procedure to estimate the number of true discoveries as a function of the number of top-ranking SNPs together with the confidence bounds. This approach allows a practical methodology of general utility and produces relevant statistical quantities with simple interpretation.

TMPRSS2:ERG gene fusion associated with lethal prostate cancer in a watchful waiting cohort

The identification of the TMPRSS2:ERG fusion in prostate cancer suggests that distinct molecular subtypes may define risk for disease progression. In surgical series, TMPRSS2:ERG fusion was identified in 50% of the tumors. Here, we report on a population-based cohort of men with localized prostate cancers followed by expectant (watchful waiting) therapy with 15% (17/111) TMPRSS2:ERG fusion. We identified a statistically significant association between TMPRSS2:ERG fusion and prostate cancer specific death (cumulative incidence ratio=2.7, P<0.01, 95% confidence interval=1.3-5.8). Quantitative reverse-transcription-polymerase chain reaction demonstrated high ets-related [corrected] gene (ERG) expression to be associated with TMPRSS2:ERG fusion (P<0.005). These data suggest that TMPRSS2:ERG fusion prostate cancers may have a more aggressive phenotype, possibly mediated through increased ERG expression.

Estimation of genetic and environmental factors for melanoma onset using population-based family data

Estimation of genetic and environmental contributions to cancers falls in the framework of generalized linear mixed modelling with several random effect components. Computational challenges remain, however, in dealing with binary or survival phenotypes. In this paper, we consider the analysis of melanoma onset in a population of 2.6 million nuclear families in Sweden, for which none of the current survival-based methodologies is feasible. We treat the disease outcome as a binary phenotype, so that the standard proportional hazard model leads to a generalized linear model with the complementary-log link function. For rare diseases this link is very close to the probit link, and thus allows the use of marginal likelihood for the estimation of the variance components. We correct for the survival length bias by censoring the parent generation within each family at the time they attain the same cumulative hazard as the child generation, thus improving the validity of the estimates. Our finding that childhood shared environment in addition to genetic factors had a considerable effect on the development of melanoma is consistent with epidemiological studies.

Multicomponent variance estimation for binary traits in family-based studies

In biometrical genetic analyses of binary traits, the use of family data overcomes some limitations of twin studies, particularly in terms of sample size and types of genetic or environmental factors that can be estimated. However, because of computational problems, recent methods in the application of generalized linear mixed models for family data structure have limited the ability to handle large data sets with general covariates. In this paper, we investigate the use of the hierarchical likelihood approach to the analysis of binary traits from family data. In a simulation study, the method is shown to be highly accurate for the estimation of both the variance components and fixed regression parameters, even for small family sizes. For illustration, we analyze a real data set of familial aggregation of preeclampsia, a pregnancy-induced hypertension. When possible, the analysis is compared with the exact maximum likelihood approach.

Children and adults with acute lymphoblastic leukaemia have similar gene expression profiles

OBJECTIVES

To compare the gene expression pattern in children and adults with acute lymphoblastic leukaemia (ALL) in order to improve our understanding of the difference in disease biology and prognosis.

METHODS

The gene expression profiles in diagnostic samples from 29 children and 15 adults with ALL were analysed using the oligonucleotide chip Hu95ver2a, produced by Affymetrix.

RESULTS

Unsupervised hierarchical cluster analysis revealed that, in spite of differences in outcome, patients clustered irrespective of age, first by T-cell or B-precursor immunophenotype, and second by cytogenetic changes within the B-precursor group. The expression pattern analysis allowed the reclassification of some samples into the proper cytogenetic group. We also showed that separate clustering of samples with the BCR/ABL translocation could be explained by different breakpoint regions in the BCR. No significant difference in gene expression was observed between samples with and without CDKN2A deletion within the B-precursor group. Analysis of different age groups revealed a similarity in expression profiles when infants with the MLL translocation and adults over 40 yr of age were compared irrespective of karyotype.

CONCLUSIONS

In spite of the difference in clinical outcome, the gene expression pattern in children and adults with ALL is very similar and is primarily dependent on immunophenotype and cytogenetic aberrations. However, when age groups are compared, the expression patterns of infants and adults over 40 show a remarkable similarity.

Non-Gaussian smoothing of low-count transmission scans for PET whole-body studies

A non-Gaussian smoothing (NGS) technique is developed for filtering low count transmission (TR) data to be used for attenuation correction (AC) of positron emission tomography (PET) studies. The method is based on a statistical technique known as the generalized linear mixed model that allows an inverse link function that avoids the inversion of the observed transmission data. The NGS technique has been implemented in the sinogram domain in one-dimensional mode as angle-by-angle computation. To make it adaptive as a function of the TR count statistics we also develop and validate an objective procedure to choose an optimal smoothing parameter. The technique is assessed using experimental phantoms, simulating PET whole-body studies, and applied to real patient data. Different experimental conditions, in terms of TR scan time (from 1 h to 1 min), covering a wide range of TR counting statistic are considered. The method is evaluated, in terms of mean squared error (MSE), by comparing pixel by pixel the distribution for high counts statistics TR scan (1 h) with the corresponding counts distribution for low count statistics TR scans (e.g., 1 min). The smoothing parameter selection is shown to have high efficiency, meaning that it tends to choose values close to the unknown best value. Furthermore, the counts distribution of emission (EM) images, reconstructed with AC generated using low count TR data (1 min), are within 5% of the corresponding EM images reconstructed with AC generated using the high count statistics TR data (1 h). An application to a real patient whole-body PET study shows the promise of the technique for routine use.

Gene expression profiling for prognosis using Cox regression

Given the promise of rich biological information in microarray data we will expect an increasing demand for a robust, practical and well-tested methodology to provide patient prognosis based on gene expression data. In standard settings, with few clinical predictors, such a methodology has been provided by the Cox proportional hazard model, but no corresponding methodology is available to deal with the full set of genes in microarray data. Furthermore, we want the procedure to be able to deal with the general survival data that include censored information. Conceptually such a procedure can be constructed quite easily, but its implementation will never be straightforward due to computational problems. We have developed an approach that relies on an extension of the Cox proportional likelihood that allows random effects parameters. In this approach, we use the full set of genes in the analysis and deal with survival data in the most general way. We describe the development of the model and the steps in the implementation, including a fast computational formula based on a subsampling of the risk set and the singular value decomposition. Finally, we illustrate the methodology using a data set obtained from a cohort of breast cancer patients.

Estimation of genetic and environmental factors for binary traits using family data

While the family-based analysis of genetic and environmental contributions to continuous or Gaussian traits is now straightforward using the linear mixed models approach, the corresponding analysis of complex binary traits is still rather limited. In the latter we usually rely on twin studies or pairs of relatives, but these studies often have limited sample size or have difficulties in dealing with the dependence between the pairs. Direct analysis of extended family data can potentially overcome these limitations. In this paper, we will describe various genetic models that can be analysed using an extended family structure. We use the generalized linear mixed model to deal with the family structure and likelihood-based methodology for parameter inference. The method is completely general, accommodating arbitrary family structures and incomplete data. We illustrate the methodology in great detail using the Swedish birth registry data on pre-eclampsia, a hypertensive condition induced by pregnancy. The statistical challenges include the specification of sensible models that contain a relatively large number of variance components compared to standard mixed models. In our illustration the models will account for maternal or foetal genetic effects, environmental effects, or a combination of these and we show how these effects can be readily estimated using family data.

Association between ease of suppression of ventricular arrhythmia and survival

BACKGROUND

We tested the hypothesis that patients whose ventricular arrhythmias are easy to suppress have a lower rate of arrhythmic death, defined as arrhythmic death and nonfatal cardiac arrest, the primary end point in the Cardiac Arrhythmia Suppression Trials (CAST-I and CAST-II), than patients whose ventricular arrhythmias are hard to suppress. In addition, we evaluated the association between ease of suppression of ventricular arrhythmias and mortality of all causes.

METHODS AND RESULTS

CAST-I investigated the effect on arrhythmic death of ventricular premature depolarization (VPD) suppression achieved by three drugs, encainide, flecainide, and moricizine, at two different dose levels; CAST-II investigated the same effect, using moricizine alone at three dose levels. If suppression was achieved, patients were randomized to the effective active drug or corresponding placebo. To examine the independence of easily suppressed ventricular arrhythmias as a predictor of arrhythmic death, we adjusted statistically for other variables that were related both to ease of suppression and arrhythmic death. Patients with ventricular arrhythmias (n = 1778) that were easy to suppress had fewer arrhythmic deaths during follow-up than those with ventricular arrhythmias that were hard to suppress (n = 1173) (relative risk, .59; P = .003). Patients whose VPDs were easily suppressed were older and had a lower frequency of prior history of heart failure and myocardial infarction. They also had a higher incidence of anterior myocardial infarction, VPD frequency, and average ejection fraction. After adjusting for these variables, we found that easily suppressed ventricular arrhythmias were still significant predictors of arrhythmic death (relative risk, .66; P = .013).

CONCLUSIONS

This study shows that the ease of VPD suppression identifies a subgroup of postmyocardial infarction patients who have low risk of arrhythmic death.

Identification of a secondary peak in myocardial infarction onset 11 to 12 hours after awakening: the Cardiac Arrhythmia Suppression Trial (CAST) experience

OBJECTIVES

The purpose of this study was to assess the relation between the time of awakening and the time of onset of acute myocardial infarction.

BACKGROUND

Previous investigation has shown the onset of symptoms of acute myocardial infarction to have a primary peak 1 to 2 h after awakening. In studies not corrected for time of awakening, there appears to be a late afternoon/early evening peak, but data correlating the onset of symptoms with awakening have been limited by small numbers of patients, perhaps precluding identification of a secondary peak.

METHODS

In the Cardiac Arrhythmia Suppression Trial (CAST), 3,549 patients had a documented myocardial infarction and entered antiarrhythmic drug titration. Of these, 3,309 had data on the onset of symptoms relative to the time of awakening and form the basis of this report.

RESULTS

A total of 870 patients (26.3%) were awakened by symptoms. Of the remaining 2,439 patients who were not awakened by symptoms, 798 (32.7%) experienced the onset of symptoms in the 1st 4 h after awakening (with the highest number in the 1st h), after which the incidence of symptom onset decreased in a linear fashion, with a secondary peak 11 to 12 h after awakening. Both peaks are statistically significant. A similar pattern was seen in most of the subgroups examined (based on age, gender and various other demographic characteristics).

CONCLUSIONS

Analysis of the very large CAST data base confirms the relation between awakening and onset of symptoms of myocardial infarction, suggesting involvement of the morning catecholamine surge. A secondary peak in symptom onset, occurring 11 to 12 h after awakening, is a new observation and may relate to ingestion of the evening meal or other trigger factors concentrated in those hours.

Psychosocial predictors of mortality in the Cardiac Arrhythmia Suppression Trial-1 (CAST-1)

Psychosocial variables predict the recurrence of clinical events in symptomatic patients, controlling for measures of disease severity. The Cardiac Arrhythmia Suppression Trial-1, a pharmacologic test of the arrhythmia suppression and mortality hypothesis among postmyocardial infarction patients, allowed a prospective test of the relationship of distress, perceived support, social interaction, life stress, and other variables, to mortality, adjusting statistically for ejection fraction, arrhythmia rates, and other known risk factors for coronary heart disease. Results indicated that the treatment medications, encainide and flecainide, were powerful predictors of mortality. Although the psychosocial variables were significant as univariate predictors, these variables were not significant as predictors in a multivariate model that included drug treatment. When the data analysis was restricted to patients randomized to placebo, thereby eliminating the antiarrhythmic drug effect, the level of perceived social support was a significant multivariate predictor of mortality, adjusting for measures of disease severity. The adjusted hazards ratio for a 1-point decrease in the perceived support score is equal to 1.46, based on the multivariate model.

Data-dependent bandwidth selection for emission computed tomography reconstruction

At present, the choice of bandwidth in emission computed tomography (ECT) reconstruction is done by subjective means. The authors develop an automated objective selection technique for linear reconstruction algorithms such as filtered backprojection. The approach is based on the method of unbiased risk estimation. A set of 2-D validation studies using computer simulated and physical phantom data from the Hoffman et al. (1990) brain phantom are carried out. These 2-D studies incorporate measured corrections for object attenuation and lack of uniformity in detector sensitivity. It is found that the unbiased risk approach works very well. Over a range of count rates and brain slice source distributions, the root mean square (RMS) error of the fully automated reconstruction, with the data-dependent choice of bandwidth, is around 5% greater than the RMS error for the reconstruction with an ideal choice of the bandwidth.

Reducing negativity artifacts in emission tomography: post-processing filtered backprojection solutions

The problem of negative artifacts in emission tomography reconstructions computed by filtered backprojection (FBP) is of practical concern particularly in low count studies. Statistical reconstruction methods based on maximum likelihood (ML) are automatically constrained to be non-negative but their excessive computational overhead (orders of magnitude greater than FBP) has limited their use in operational settings. Motivated by the statistical character of the negativity artifact, the authors develop a simple post-processing technique that iteratively adjusts negative values by cancellation with positive values in a surrounding local neighborhood. The compute time of this approach is roughly equivalent to 2 applications of FBP. The approach was evaluated by numerical simulation in 1- and 2-dimensional (2D) settings. In 2D, the source distributions included the Hoffman, the Shepp and Vardi, and a digitized version of the Jaszczak cold spheres phantoms. The authors' studies compared smoothed versions of FBP, the post-processed FBP, and ML implemented by the expectation-maximization algorithm. The root mean square (RMS) error between the true and estimated source distribution was used to evaluate performance; in 2D, additional region-of-interest-based measures of reconstruction accuracy were also employed. In making comparisons between the different methods, the amount of smoothing applied to each reconstruction method was adapted to minimize the RMS error-this was found to be critical.

Effects of advancing age on the efficacy and side effects of antiarrhythmic drugs in post-myocardial infarction patients with ventricular arrhythmias. The CAST Investigators

OBJECTIVE

To determine the effect of age on the response to anti-arrhythmic drugs.

DESIGN

Randomized controlled trial comparing particular drugs.

SETTING

Multi-institutional (The Cardiac Arrhythmia Suppression Trial, CAST).

PARTICIPANTS

2,371 patients, age less than 80, with ventricular arrhythmias after a recent myocardial infarction. Subjects classified by age as less than or equal to 55, 56-65, and 66-79 years.

INTERVENTION

Upwardly titrated doses of encainide, flecainide or moricizine. After identification of a tolerated and effective dose of one of the drugs, participants were randomized to that drug and dose versus its placebo for up to 10 months.

MAIN OUTCOME MEASURES

Efficacy of drug (suppression of ventricular premature depolarizations and/or non-sustained ventricular tachycardia), side effects and mortality.

RESULTS

Older patients had more previous MIs, congestive heart failure (CHF), hypertension, NSVT, repolarization abnormalities, digitalis use, and diuretic use. They had less pathologic Q-waves or electrocardiographic injury pattern, and their left ventricular ejection fraction (LVEF) was lower. First dose VPD suppression with the first drug averaged 53% and is not associated with age (P = 0.29). Adverse events including death are more frequent in older patients taking study drugs (P less than 0.001). This trend is consistent in all three study drugs and at varying LVEFs. History of prior MI, low LVEF, VPD (in log scale), and digitalis therapy also correlates with adverse events (all P less than 0.05). Following adjustment for these factors, older age is an independent predictor of adverse events (relative risk 1.30 per decade of age, P less than 0.001).

CONCLUSIONS

Older age increases the susceptibility to adverse cardiac events from a class of relatively toxic antiarrhythmic agents.

Methods for assessing quality of life in the cardiac arrhythmia suppression trial (CAST)

The CAST was a randomized, double-blind placebo-controlled multicentre trial of antiarrhythmic medications designed to suppress ventricular arrhythmias in patients after an acute myocardial infarction (MI). A collection of 21 items derived from established scales was used to assess aspects of quality of life in CAST. The questions focused on symptoms, mental health, physical functioning, social functioning, life satisfaction, and life expectancy. Additional aspects included exposure to major stressful life events, and perceived social support and social integration. Work status was also recorded. Using the baseline values of 1465 (98%) out of 1498 patients enrolled in the CAST main study between 15 June 1987 and 19 April 1989, the reliability and validity of the scales used in CAST were computed. High internal consistency reliability (> or = 0.70) was found for Symptoms, Mental Health, and Physical Functioning. The discriminative validity, in particular for Symptoms, Mental Health, Physical and Social Functioning, showed that patients with heart failure and previous MI, as well as those suffering from angina and dyspnea, had a worse quality of life than those patients who were not experiencing these symptoms. It was concluded that the scales selected to form the CAST quality of life questionnaire were both reliable and clinically valid for this patient population and therefore could be used to detect disease progression and treatment effects.

Increased risk of death and cardiac arrest from encainide and flecainide in patients after non-Q-wave acute myocardial infarction in the Cardiac Arrhythmia Suppression Trial. CAST Investigators

This report examines whether in the Cardiac Arrhythmia Suppression Trial death and cardiac arrest from encainide, flecainide and moricizine during the titration phase and from encainide and flecainide during the follow-up phase were related to presence (Q-wave acute myocardial infarction [Q-AMI]) or absence (non-Q-AMI) of pathologic Q waves. In all, 2,371 patients (70% with Q-AMI, 26% with non-Q-AMI, and 4% unknown) entered the titration phase, starting 117 +/- 163 days after index AMI and lasting for an average of 21 days. For the titration phase, no significant differences existed between Q-AMI and non-Q-AMI patients for death and cardiac arrest rate, ventricular premature complex suppression rate, and nonrandomization rate. A total of 1,498 patients entered the follow-up phase of an average of 10 months (starting 129 +/- 158 days after the index AMI), and were randomized to encainide or flecainide, or their matching placebos. In the placebo group, non-Q-AMI patients had a significantly lower rate of death and cardiac arrest than Q-AMI patients (1.0 and 4.6%, respectively; p = 0.04). Encainide and flecainide significantly elevated death and cardiac arrest rate in both non-Q-AMI patients (8.7%, p less than 0.01) and Q-AMI patients (7.8%, p = 0.04). The relative risk for encainide or flecainide over placebo in the non-Q-AMI patients was 8.7, which was significantly higher than 1.7 observed for the Q-AMI patients (p = 0.03). None of the baseline characteristics had any significant interaction with encainide or flecainide.(ABSTRACT TRUNCATED AT 250 WORDS)

Events in the cardiac arrhythmia suppression trial: baseline predictors of mortality in placebo-treated patients

Patients randomized to placebo in the encainide and flecainide arms of the Cardiac Arrhythmia Suppression Trial (CAST) have been found to have a relatively low 1-year mortality rate of 3.9% in comparison with previous studies of patients in the postmyocardial infarction period. To determine the comparability of CAST with previous studies, baseline variables were examined in the 743 patients randomized to placebo in the flecainide and encainide arms of CAST. Twenty-three baseline characteristics were correlated with major outcome events: arrhythmic death (16 events), total mortality (26 events) and congestive heart failure (51 events). On multivariate analysis the risk of new or worsening congestive heart failure was significantly associated with diuretic use, diabetes, high New York Heart Association functional class, age, prolonged QRS duration and low ejection fraction. The risk of arrhythmic death or resuscitated cardiac arrest was significantly associated with an index Q wave myocardial infarction, history of heart failure, use of digitalis, diabetes and prolonged QRS duration. Total mortality or resuscitated cardiac arrest was significantly associated with an index Q wave myocardial infarction, diabetes, ST segment depression, high functional class, prolonged QRS duration and low ejection fraction. The variables at baseline associated with mortality from all causes or arrhythmic death or resuscitated cardiac arrest and heart failure in the CAST placebo-treated patients are similar to those identified in previous postmyocardial infarction studies. Thus, the observation of increased mortality in CAST associated with the administration of encainide and flecainide for suppression of ventricular premature depolarizations is probably applicable to any comparably defined group of patients in the postmyocardial infarction period.

Prevalence, characteristics and significance of ventricular premature complexes and ventricular tachycardia detected by 24-hour continuous electrocardiographic recording in the Cardiac Arrhythmia Suppression Trial. CAST Investigators

The prevalence, characteristics and significance of ventricular arrhythmias detected by ambulatory electrocardiography were evaluated in 1,498 patients who were randomized to encainide, flecainide or placebo in the Cardiac Arrhythmia Suppression Trial. The mean ventricular premature complex (VPC) frequency at baseline was 133 +/- 257 VPCs/hour. Nonsustained ventricular tachycardia (VT) (rate greater than or equal to 120 beats/min) was present in 22% of patients. Accelerated idioventricular rhythm (rate less than 120 beats/min) occurred in 22% of subjects. There were 63 deaths/resuscitated cardiac arrests in the active treatment (encainide/flecainide) group and 26 in the placebo group. In the treatment group mortality increased with increasing VPC frequency, (p = 0.006), whereas in the placebo group such a relation was not present. Mortality/resuscitated cardiac arrest increased in patients with greater than or equal to 2 VT episodes than in those with less than or equal to 1 episode in the active treatment group (p = 0.04). There was no significant association between VT and mortality/resuscitated cardiac arrest in the placebo group. The presence of accelerated idioventricular rhythm was not associated with increased mortality/resuscitated cardiac arrest in either the active treatment or placebo groups. However, mortality was lower in patients with accelerated idioventricular rhythm rates less than 100 beats/min than in those with rates greater than or equal to 100 beats/min (p = 0.05). Thus, in the Cardiac Arrhythmia Suppression Trial the previously described association between mortality/resuscitated cardiac arrest and ventricular arrhythmias (VPC and VT) were only observed in the active treatment group. In addition, based on the results obtained in this highly selected population, it is suggested that the definition of accelerated idioventricular rhythm should be a rate less than 100 beats/min, and at a rate greater than or equal to 100 beats/min it should be categorized as VT.

Congestive heart failure symptoms in patients with preserved left ventricular systolic function: analysis of the CASS registry

The clinical characteristics and long-term survival of 284 patients from the Coronary Artery Surgery Study (CASS) registry data base who had moderate to severe congestive heart failure symptoms and a left ventricular ejection fraction greater than or equal to 0.45 were studied. A control group consisting of registry patients with an ejection fraction greater than or equal to 0.45 who did not have heart failure was used for comparison. Patients who had heart failure were older and more likely to be female and to have a higher incidence of hypertension, diabetes and chronic lung disease than registry patients who did not have heart failure. As a group, patients with heart failure had more severe angina and were more likely to have had a prior myocardial infarction than were registry patients without heart failure. At 6 year follow-up, 82% of patients in the heart failure group survived compared with 91% of patients in the control group (p less than 0.0001). Multivariate analysis using the Cox proportional hazards model identified the following independent predictors of mortality: regional ventricular systolic dysfunction, number of diseased coronary arteries, advanced age, hypertension, lung disease, diabetes, increased left ventricular end-diastolic pressure and heart failure symptoms. Among patients with heart failure, the 6-year survival rate of those who had three-vessel coronary artery disease was 68% compared with 92% for the group without coronary artery disease. However, the 6-year survival rate for patients with heart failure who underwent surgical revascularization of diseased coronary arteries was not significantly improved compared with that of patients treated medically.(ABSTRACT TRUNCATED AT 250 WORDS)

Statistical interim monitoring of the Cardiac Arrhythmia Suppression Trial

The Cardiac Arrythmia Suppression Trial was stopped much earlier than planned. Statistical considerations played a very important role in the decision. Flexible group sequential testing was developed for the trial by implementing a Lan and DeMets procedure with use of the permutation test. We compute P-values from the joint permutation distribution of the test statistics, so we do not need to estimate the sampling distribution which in general is rather difficult to do without strict assumptions. The method also gives an exact test for small samples and allows us to use more complicated or non-Gaussian statistics. We also utilized stochastic curtailment ideas to evaluate various scenarios that might occur during the course of the trial, which assisted the Data and Safety Monitoring Board in making appropriate decisions.